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Figura 2. Emissão anual de dióxido de carbono equivalente (CO2-eq.) proveniente de diferentes setores produtivos [START_REF] Gerber | Tackling climate change through livestock -A global assessment of emissions and mitigation opportunities[END_REF]. ............................................ 6 Figura 3. Emissões de gases geradas pela cadeia suinícola oriundas da alimentação (tons de verde), alojamento (tons de azul) e manejo de efluentes (tons de laranja) [START_REF] Gerber | Tackling climate change through livestock -A global assessment of emissions and mitigation opportunities[END_REF] Figura 5. Consumo, utilização e perdas de nitrogênio por suínos aos 152 kg, consumindo dieta com 12% de proteína bruta e 13,32 MJ/kg de energia metabolizável (elaborado a partir de Galassi et al., 2010). ............................... 12 Figura 6. Visão global do metabolismo proteico (adaptado de Nelson & Cox, 2014) Figura 8. Relação entre os elementos de uma análise do ciclo de vida (ISO, 2006). ..... 21 Figura 9. Análise do ciclo de vida de diferentes sistemas de produção de suínos (em porcentagem do sistema convencional): A, dados analisados por hectare de terra utilizada; B, dados analisados por kg de peso vivo. PAG, potencial de aquecimento global, EU, potencial de eutrofização; AC, potencial de acidificação; DAE, demanda acumulada de energia; OT, ocupação de terra [START_REF] Dourmad | The optimum dietary amino acid pattern for growing pigs: 2. Requirements for maintenance and for tissue protein accretion[END_REF] Figura 10. Análise do ciclo de vida da produção de suínos: A, impacto de cada etapa produtiva, em porcentagem do impacto ambiental total da produção; B, impacto do sistema de manejo de dejetos, em porcentagem do manejo de dejetos líquidos. PAG, potencial de aquecimento global, EU, potencial de eutrofização; AC, potencial de acidificação; DAE, demanda acumulada de energia; OT, ocupação de terra (Cherubini et al., 2015). ................................. 26 Figura 11. Análise do ciclo de vida da produção de dietas (A) sem a inclusão de aminoácidos industriais (Sem AA), com aminoácidos industriais (Com AA) e com aminoácidos e redução do nível de proteína bruta (Baixa PB), e da produção de suínos (B). Impactos são expressos em porcentagem da dieta 'Sem AA'. PAG, potencial de aquecimento global, EU, potencial de eutrofização; AC, potencial de acidificação; DAE, demanda acumulada de energia; OT, ocupação de terra (Monteiro et al., 2016) (19,24; 18,24; 17,24 e 16,24%), sendo atendidas as exigências de aminoácidos digestíveis por meio da adição de L-lisina, DL-metionina, Ltreonina, L-triptofano, L-valina e L-isoleucina. A partir dos dados obtidos nos

Experimentos I e II, determinou-se o impacto ambiental da produção de suínos na fase inicial, através da ACV, para as categorias potencial de aquecimento global (PAG), potencial de acidificação (AC), potencial de eutrofização (EU), demanda acumulada de energia (DAE), ecotoxicidade terrestre (ECO) e ocupação de terra (OT). Houve redução linear na ingestão de nitrogênio e fósforo, bem como na excreção de nitrogênio, com a redução dos níveis de PB da dieta. A excreção total de nitrogênio reduziu 0,238 g/d para cada 1 g de redução no consumo diário de nitrogênio. The nitrogen excretion was reduced with industrial amino acids incorporation.

However, an increase in GWP was observed, in which the lowest impact was obtained for noAA diets (2.38 kg CO2-eq.). Similar effects were observed for CED and TE, with an increase of 9 and 8%, respectively, moving from noAA to lowCP diet. Conversely, AC and EU were reduced by 11 and 13%, respectively, at the lowCP scenario. In the same way, LO was reduced about 7%, when industrial amino acids incorporation was increased in diets. In conclusion, the dietary CP reduction was efficient to reduce nitrogen excretion, both in experimental and computer simulation data. However, for environmental impact categories modelled through LCA, this reduction brings benefits for LO (observed experimental data). For estimated data, the dietary CP reduction decreased the impact under nitrogen-dependent variables, as AC and EU, being those estimated data similar to observed data for CED, TE and LO.

Keywords: carbon emission, environment, modelling, nitrogen.

I -INTRODUÇÃO

O agronegócio brasileiro possui grande participação na economia do país, cuja Além do impacto local decorrente da excreção de nutrientes via dejetos, a suinocultura é responsável pela emissão de 668 milhões de toneladas de CO2-eq. por ano [START_REF] Gerber | Tackling climate change through livestock -A global assessment of emissions and mitigation opportunities[END_REF], o que representa um impacto em nível global. O potencial poluidor desta atividade vem aumentando a busca por tecnologias limpas de produção, uma vez que certificações de sustentabilidade estão se tornando cada vez mais um diferencial positivo para a exportação de produtos (FGV, 2016).

Neste sentido, o Governo Brasileiro, por meio do Ministério da Agricultura, Pecuária e Abastecimento, propôs em 2010 o Plano ABC (Agricultura de Baixa Emissão de Carbono), com a finalidade de planejar ações para a adoção de tecnologias de produção agrícola e animal sustentáveis [START_REF] Brasil | Plano setorial de mitigação e de adaptação às mudanças climáticas para a consolidação de uma economia de baixa emissão de carbono na agricultura: Plano ABC (Agricultura de Baixa Emissão de Carbono)[END_REF]. Em 2015, este plano tornou a produção de suínos uma prioridade, por meio da criação do programa "Suinocultura de Baixa Emissão de Carbono" (Brasil, 2015), com o intuito de difundir mecanismos de desenvolvimento limpo para a produção de suínos, rumo a uma economia de baixa emissão de carbono.

A redução do conteúdo de proteína bruta (PB) na dieta de suínos, com a consequente inclusão de aminoácidos industriais (AAI), pode reduzir a excreção de N (Hernandez et al., 2011;Gallo et al., 2013;[START_REF] Ball | The Effect of Level of Crude Protein and Available Lysine on Finishing Pig Performance, Nitrogen Balance and Nutrient Digestibility[END_REF]Toledo et al., 2014;Pomar et al., 2014;[START_REF] Andretta | Feeding behavior of growing-finishing pigs reared under precision feeding strategies[END_REF] e, consequentemente, mitigar o impacto ambiental da produção de suínos.

Nos últimos anos, a análise do ciclo de vida (ACV) vem sendo bastante difundida na produção animal (Mosnier et al., 2011;[START_REF] Doreau | Enteric methane production and greenhouse gases balance of diets differing in concentrate in the fattening phase of a beef production system[END_REF]Prudêncio da Silva et al., 2014) e, devido às preocupações ambientais associadas à suinocultura, vem sendo também utilizada na produção de suínos [START_REF] Dourmad | The optimum dietary amino acid pattern for growing pigs: 2. Requirements for maintenance and for tissue protein accretion[END_REF]Cherubini et al., 2015;Mackenziet et al., 2015Mackenziet et al., , 2016;;Monteiro et al., 2016). A grande vantagem desta metodologia é a possibilidade de avaliar o impacto como um todo, incluindo os recursos e emissões associados à toda cadeia produtiva. Entretanto, são escassos os estudos envolvendo a ACV na produção de suínos no Brasil, o que justifica a realização de pesquisas com esse propósito.

Como alimentar uma população crescente em tempos de mudança climática?

As projeções da Food and Agricultural Organization (FAO) para 2050 são de que a população mundial chegará a 9,1 bilhões de habitantes (Alexandratos & Bruinsma, 2012), 20,8% a mais que hoje. A urbanização vai continuar em ritmo acelerado, com cerca de 70% da população mundial apresentando nível de renda muitas vezes superior ao atual (FAO, 2009). Para alimentar essa população mais urbana e mais rica, a produção anual de cereais deverá ser de aproximadamente 3 bilhões de toneladas e a produção anual de carne de aproximadamente 470 milhões de toneladas [START_REF] Brasil | Plano setorial de mitigação e de adaptação às mudanças climáticas para a consolidação de uma economia de baixa emissão de carbono na agricultura: Plano ABC (Agricultura de Baixa Emissão de Carbono)[END_REF]. Em 2015, este plano tornou a produção de suínos uma prioridade, através da criação do programa "Suinocultura de Baixa Emissão de Carbono" (Brasil, 2015). Este programa tem como objetivo a difusão de tecnologias limpas para a produção de suínos, o estímulo ao tratamento de dejetos e seu uso como combustíveis e fertilizantes, além de linhas de crédito para que os suinocultores tenham acesso a tecnologias de baixa emissão de carbono.

Mais recentemente, no ano de 2015, a Conferência das Partes de Mudanças Climáticas (COP), que vem sendo realizada periodicamente pela Organização das Nações Unidas, chegou ao primeiro acordo climático global. Este acordo começa a valer a partir de 2020 e dispõe que, até esta data, todos os países do mundo deverão, por lei, reduzir suas emissões de gases poluentes (United Nations, 2015). Isso implicará em mudanças profundas nos modelos de desenvolvimento econômico e social de cada nação, rumo a uma economia de baixo carbono.

Estas ações, tanto em nível mundial quanto nacional, visam a redução das emissões relacionadas com a agropecuária, uma vez que 14,5% das emissões de gases de efeito estufa são consequência deste setor produtivo [START_REF] Gerber | Tackling climate change through livestock -A global assessment of emissions and mitigation opportunities[END_REF], tendo a suinocultura como terceiro maior emissor (Figura 2).

Setor de produção animal Figura 2. Emissão anual de dióxido de carbono equivalente (CO2-eq.) proveniente de diferentes setores produtivos [START_REF] Gerber | Tackling climate change through livestock -A global assessment of emissions and mitigation opportunities[END_REF].

Produção de suínos e o meio ambiente

A suinocultura é considerada uma atividade contribuinte da contaminação do ar, água e solo (Basset-Mens & van Der Werf, 2005), já que o sistema intensivo de criação demanda significativos níveis de energia, água e utiliza alimentos com altas concentrações de proteína. Essas entradas na cadeia suinícola são responsáveis pela produção de metano (CH4), amônia (NH3) e outras emissões no ar, assim como riscos de contaminação do solo e da água devido a práticas ineficientes de manejo de dejetos (McAuliffe et al., 2016). Globalmente, estima-se que a produção de suínos produza 668 milhões de toneladas de CO2-eq por ano, oriundos da alimentação, alojamento e manejo dos efluentes (Figura 3). Desse total, a etapa de alimentação contribui com 53% das emissões. -eq./ano Figura 3. Emissões de gases geradas pela cadeia suinícola oriundas da alimentação (tons de verde), alojamento (tons de azul) e manejo de efluentes (tons de laranja) (Gerber et al., 2013).

Outro ponto da produção de suínos refere-se ao elevado número de contaminantes gerados pelos dejetos, cuja ação individual ou combinada pode representar importante fonte de degradação dos recursos naturais. O acúmulo de Cu e Zn no solo, por exemplo, pode impor, em médio ou em longo prazo, risco de toxicidade sobre as plantas e os microrganismos (Dourmad & Jondreville, 2007). Além disso, o fósforo excretado nos dejetos vem sendo apontado como um dos elementos responsáveis pelo processo de eutrofização das águas, que pode proporcionar grandes impactos ao ecossistema aquático de superfície [START_REF] Merten | Qualidade da água em bacias hidrográficas rurais: um desafio atual para a sobrevivência futura[END_REF]. Da mesma forma, o N excretado é considerado um elemento de grande impacto ao meio ambiente.

Por ser facilmente lixiviado, o N oferece maior risco de contaminação das águas subterrâneas [START_REF] Merten | Qualidade da água em bacias hidrográficas rurais: um desafio atual para a sobrevivência futura[END_REF] Dejetos aplicados e armazenados, N2O

Ciclo do nitrogênio e seu impacto no ecossistema

É fato que grande parte da população mundial foi beneficiada pelo uso dos fertilizantes nitrogenados [START_REF] Ham | The world's nitrogen cycle and human impacts[END_REF], um dos pilares da Revolução Verde na agricultura que evitou uma fome global no século XX [START_REF] Pinpali | Green Revolution: Impacts, limits, and the path ahead[END_REF]. O ar atmosférico é constituído por uma mistura de gases, predominantemente N, que constitui 78% do total [START_REF] Brimblecombe | Air Composition and Chemistry[END_REF] [START_REF] Galloway | Nitrogen Cycles: Past, Present, and Future[END_REF][START_REF] Galloway | Transformation of the nitrogen cycle: recent trends, questions, and potentials solutions[END_REF][START_REF] Galloway | Transformation of the nitrogen cycle: recent trends, questions, and potentials solutions[END_REF][START_REF] Ham | The world's nitrogen cycle and human impacts[END_REF].

A preocupação se foca no chamado "nitrogênio reativo" (Nr), que é causa da maior parte dos problemas ambientais em escala local e global, uma vez que o excesso de N altera o processo biogeoquímico e as funções do ecossistema [START_REF] Ham | The world's nitrogen cycle and human impacts[END_REF][START_REF] Powers | Measurement and mitigation of reactive nitrogen species from swine and poultry production facilities In Joint Annual Meeting[END_REF]. Estima-se que no ano de 1860, 34 Tg (milhões de toneladas) de Nr foram emitidas na forma de óxidos de nitrogênio e NH3; Já em 1995, este valor aumentou para 100 Tg de Nr emitido, com projeções de que em 2050 este valor chegue a 200 Tg de Nr [START_REF] Galloway | Nitrogen Cycles: Past, Present, and Future[END_REF]. As emissões antropogênicas de Nr possuem efeito nas mudanças climáticas, na química da atmosfera, na composição e função do ecossistema aquático e terrestre (Vitousek et al., 1997). Além disso, como o N é facilmente transportado na água ou ar, os impactos do uso do N na agricultura nem sempre são observados somente no local onde o N foi inicialmente utilizado [START_REF] Ham | The world's nitrogen cycle and human impacts[END_REF].

Espécies de Nr incluem óxidos de nitrogênio (óxido nítrico, dióxido de nitrogênio, óxido nitroso), ânions (nitrato e nitrito) e derivados de amina (NH3, sais de amônia e ureia) [START_REF] Powers | Measurement and mitigation of reactive nitrogen species from swine and poultry production facilities In Joint Annual Meeting[END_REF]. Destas diferentes espécies, emissões no ar a partir do alojamento de suínos e aves são compostas predominantemente pelo NH3 seguido pelo óxido nitroso, enquanto que as emissões a partir dos dejetos são NH3, íons de amônio e ureia, com quantidades traços de nitrato e nitrito [START_REF] Powers | Measurement and mitigation of reactive nitrogen species from swine and poultry production facilities In Joint Annual Meeting[END_REF].

Vários trabalhos projetaram cenários futuros para as emissões de Nr (FAO, 2000;[START_REF] Tilman | Forecasting agriculturally driven global environmental change[END_REF][START_REF] Tubiello | Reducing climate change impacts on agriculture: Global and regional effects of mitigation, 2000-2080[END_REF][START_REF] Galloway | Transformation of the nitrogen cycle: recent trends, questions, and potentials solutions[END_REF] et al., 2008;[START_REF] Galloway | Transformation of the nitrogen cycle: recent trends, questions, and potentials solutions[END_REF].

Especificamente com relação à produção animal, que é responsável por aproximadamente 50% de todas as emissões de NH3 [START_REF] Ham | The world's nitrogen cycle and human impacts[END_REF] água durante alojamento, manejo dos dejetos ou aplicação de dejetos na agricultura [START_REF] Powers | Measurement and mitigation of reactive nitrogen species from swine and poultry production facilities In Joint Annual Meeting[END_REF]. É neste último ponto crítico que o nutricionista de animais pode interferir em maior grau. Neste sentido, um dos focos das pesquisas em nutrição de suínos é buscar alternativas para minimizar o impacto ambiental causado pela excreção de N nos dejetos, principalmente por meio de estratégias nutricionais e alimentares.

Alimentação de suínos como chave para a produção sustentável de carne

Pesquisas demonstram que a redução do conteúdo de PB na dieta de suínos é um dos fatores que mais contribuem para a redução do impacto ambiental, principalmente para as variáveis acidificação, eutrofização e ocupação de terra (Garcia-Launay et al., 2014;Kebreab et al., 2016). Essa premissa parte do princípio de que o conteúdo de N dos dejetos e as emissões de gases nitrogenados durante a armazenagem, tratamento e aplicação destes nas lavouras estão positivamente relacionadas com o consumo de N e, consequentemente, excreção deste elemento nas fezes e urina (Figura 5).

De acordo com Dourmad et al. (1999), a eficiência de retenção de N varia conforme a categoria animal, sendo menor em porcas (20-30% do ingerido), intermediária em animais em crescimento (30-40%) e alta em leitões desmamados (45-55%). Estas diferenças estão relacionadas à idade do animal, pois em animais mais velhos, ocorre redução da eficiência de tradução do RNAm em proteína [START_REF] Davis | Developmental changes in the feeding-induced stimulation of translation initiation in muscle of neonatal pigs[END_REF] e redução da sensibilidade dos tecidos alvo ao sinal de hormônios e AA (D 'Mello, 2003) O metabolismo envolvido na utilização do N por suínos pode ser resumido na Figura 6. A proteína ingerida é hidrolisada no trato gastrointestinal em AA, constituídos de grupamentos amino (-NH2) e carboxílico (-COOH). Estes são transportados para dentro das células epiteliais do intestino delgado, para então entrarem nos capilares sanguíneos e serem direcionados ao fígado (Nelson & Cox, 2014). Neste órgão, pode ocorrer a remoção dos grupos α-amino e os α-ceto ácidos resultantes desta desaminação são metabolizados para que os esqueletos de carbono consigam entrar nas vias metabólicas, ou como precursores de glicose, ou como intermediários do ciclo do ácido cítrico (Nelson & Cox, 2014).

Os AA também podem ser utilizados para formação da proteína corporal, assim, em situações em que o organismo precisa sintetizar glicose a partir de precursores nãocarboidratos, esta pode ser novamente convertida em AA durante o processo de gliconeogênese no fígado (Weiner et al., 2014). Já os AA não digeridos no trato gastrointestinal são excretados nas fezes e os absorvidos, mas que não são necessários para uma função específica, são metabolizados no fígado e os resíduos nitrogenados são excretados na urina (NRC, 2012).

As perdas endógenas de N no trato gastrointestinal compreendem proteínas, peptídeos, AA e outras substâncias contendo N. A excreção fecal de N corresponde à fração de proteínas indigestíveis e às perdas endógenas. Devido à alta atividade microbiana, este N fecal pode ser rapidamente degradado em compostos nitrogenados, formando ácidos graxos voláteis e NH3. Estima-se que, a cada 1% de redução da PB em dietas para suínos, é possível diminuir a excreção de N em 8% e reduzir em mais de 8% a emissão de NH3 (NRC, 2012), devido à redução da desaminação do excesso de AA e síntese e excreção de ureia pela urina [START_REF] Dourmad | The optimum dietary amino acid pattern for growing pigs: 2. Requirements for maintenance and for tissue protein accretion[END_REF].

Na produção animal, a principal fonte de NH3 é a rápida hidrólise de ureia da urina pela enzima urease fecal, em uma reação conhecida como ureólise (dependente de temperatura e concentração de ureia), levando à formação do íon amônio (NH4 + ) em meio aquoso [START_REF] Cortus | A dynamic model of ammonia emission from urine puddles[END_REF]. A próxima etapa é a dissociação do NH4 + (ionizado) em NH3 (não ionizado). O equilíbrio desta fase é influenciado pela temperatura e pH [START_REF] Philippe | Ammonia emissions from pig houses: Influencing factors and mitigation techniques[END_REF]. Para que ocorra a volatilização, o NH3 produzido na forma líquida é convertido a NH3 gasoso, reação dependente da temperatura, velocidade do ar e área de superfície [START_REF] Monteny | Ammonia emission from dairy cow buildings: a review of measurement techniques, influencing factors and possibilities for reduction[END_REF].

Outra fonte de NH3 é a degradação de proteínas não digestíveis, um processo lento e, portanto, de importância secundária [START_REF] Zeeman | Soy Moratorium: Mapping and monitoring of soybean production in Amazon biome and 9th year = Moratória da Soja: Mapeamento e monitoramento do plantio de soja no bioma Amazônia e 9° Ano[END_REF]. As transformações do N que ocorrem nos efluentes de suínos incluem a mineralização do N orgânico em NH3, a assimilação do N em matéria orgânica, a nitrificação em nitrito (NO2 -) e, posteriormente, em nitrato (NO3 -), e por fim, desnitrificação em gás nitrogênio (N2), tendo o óxido nitroso (N2O) como um potencial coproduto [START_REF] Philippe | Ammonia emissions from pig houses: Influencing factors and mitigation techniques[END_REF]. Figura 7. Efeito da mudança do conteúdo de proteína bruta da dieta sobre a excreção de nitrogênio por suínos.

Nos 16 estudos a partir de dados da literatura (Figura 7), a excreção diária de N variou de 8 para 48 g/d, com valores mais elevados para animais em terminação, quando comparados à animais jovens. Em média, estes experimentos demonstraram 11% de redução na excreção de N para cada ponto percentual de redução no conteúdo de PB da dieta.

Entretanto, dietas formuladas com baixos níveis de PB podem proporcionar maior deposição de gordura na carcaça de suínos (Alonso et al., 2010). Isso ocorre porque dietas com baixo teor de PB proporcionarão ao animal menor gasto de energia para a desaminação dos AA em excesso, menor excreção de ureia na urina e menor produção de calor dos animais (Noblet et al., 2001), resultando em maior energia líquida disponível, que pode ser depositada na carcaça como gordura, principalmente em animais em crescimento e terminação. Portanto, ao se avaliar dietas com diferentes níveis de PB, é importante utilizar o sistema de energia líquida [START_REF] Noblet | Prediction of net energy value of feeds for growing pigs[END_REF], para que o nível de energia dos tratamentos não influencie o desempenho e os parâmetros de carcaça [START_REF] Tous | Effect of reducing dietary protein and lysine on growth performance, carcass characteristics, intramuscular fat, and fatty acid profile of finishing barrows[END_REF].

Neste contexto, a otimização da eficiência de utilização do N, em dietas para suínos, pode ser uma forma eficiente de promover a sustentabilidade do sistema produtivo, relacionada à redução da excreção de N e, consequentemente, redução da produção de Nr a partir dos dejetos. Estas premissas têm aumentado o interesse pelo desenvolvimento de métodos para melhor compreender e mensurar os impactos ambientais, principalmente considerando o cenário atual, no qual a tendência é buscar ações rumo a uma economia de baixa emissão e baixo impacto.

Análise do ciclo de vida como ferramenta na avaliação do impacto ambiental

Uma ferramenta para a modelagem ambiental de sistemas, processos ou produtos é a análise do ciclo de vida (ACV). A ACV quantifica e avalia os recursos consumidos e as emissões ao ambiente em todas as fases do ciclo de vida de um produto, desde a extração de recursos, por meio da produção de materiais, componentes

de produtos e o produto em si, até sua utilização, reutilização, reciclagem ou disposição final (Guinée et al., 2002). Esta análise vem sendo amplamente aplicada na produção animal (Mosnier et al., 2011;[START_REF] Doreau | Enteric methane production and greenhouse gases balance of diets differing in concentrate in the fattening phase of a beef production system[END_REF]Prudêncio da Silva et al., 2014) e, devido às preocupações ambientais associadas à suinocultura, vem sendo também utilizada na produção de suínos [START_REF] Dourmad | The optimum dietary amino acid pattern for growing pigs: 2. Requirements for maintenance and for tissue protein accretion[END_REF]Cherubini et al., 2015;[START_REF] Mackenzie | Accounting for uncertainty in the quantification of the environmental impacts of Canadian pig farming systems[END_REF]Mackenzie et al., , 2016)).

A ACV é uma técnica que se iniciou no final dos anos 60 e início dos anos 70, cujo foco eram questões como a eficiência energética, o consumo de matérias-primas e a eliminação de resíduos. Exemplo disto foi o estudo financiado pela Coca Cola Company em 1969, para comparar o consumo de recursos e as emissões associadas às embalagens da bebida [START_REF] Jensen | Life-cycle assessment (LCA)a guide to approaches, experiences and information sources[END_REF]. Apesar do estudo nunca ter sido publicado, devido ao seu conteúdo confidencial, serviu como embasamento para muitas decisões relacionadas às embalagens, representando um indicativo para a empresa substituir as embalagens de vidro por embalagens de plástico, pois, anteriormente, a embalagem plástica era vista como uma vilã ao meio ambiente. Em 1972, no Reino Unido, Ian

Boustead utilizou esta análise no cálculo da energia total usada na produção de vários tipos de recipientes de bebidas, incluindo vidro, aço, plástico e alumínio [START_REF] Boustead | Plastics and the environment: Review Report[END_REF]. Nos anos seguintes, Boustead consolidou sua metodologia e a tornou aplicável para vários materiais [START_REF] Boustead | Handbook of industrial Energy Analysis[END_REF].

Por isso, Guinée et al. (2002) afirmam que a ACV é mais que apenas um estudo, pois seus resultados podem ser utilizados para a tomada de decisões pela indústria, organizações governamentais e não governamentais. Assim, é mais apropriado considerar um projeto de ACV como um processo organizacional, que pode ser realizado de diversas maneiras e aplicado em diversos cenários. O método de trabalho para a ACV está estruturado em torno de um quadro que se tornou objeto de consenso mundial, e que constitui a base de uma série de normas da International Organization for Standardization (ISO). A ISO 14044 (ISO, 2006), por exemplo, divide a ACV em quatro principais componentes: definição do objetivo e escopo do estudo, análise do inventário de ciclo de vida, avaliação de impacto do ciclo de vida e interpretação.

Definição do objetivo e escopo do estudo

O objetivo refere-se à informação e justificativa do objetivo do estudo de ACV e a especificação de como os resultados serão utilizados, ou seja, a aplicação, além de quem serão os usuários dos resultados deste estudo (Guinée et al., 2002). Na etapa de definição do escopo, as principais características pretendidas com o estudo devem ser descritas de forma a abranger questões temporais, geográficas e tecnológicas, o modo de análise empregado e o nível de sofisticação do estudo (Guinée et al., 2002). De acordo com a ISO 14044 (ISO, 2006), ainda nesta etapa, deve ser feita a delimitação da unidade funcional e o fluxo de referência para que a comparação entre os sistemas seja feita com base na mesma função e quantificada pela mesma unidade funcional. Para isso, é necessária a delimitação das fronteiras do sistema para que se conheçam quais os processos que serão incluídos na análise (ISO, 2006).

Análise do inventário de ciclo de vida

A análise de inventário de ciclo de vida (ICV) é a fase na qual são definidos os sistemas envolvidos na obtenção do produto. A definição inclui o desenho dos diagramas de fluxo com processos unitários, coletando dados de cada um desses processos, execução das etapas de alocação para os processos multifuncionais (que compreendem mais de um produto final) e completar os cálculos finais (Guinée et al., 2002). Os dados qualitativos e quantitativos serão então incluídos no inventário, devendo ser coletados para cada processo unitário e incluídos dentro dos limites do sistema. Os dados podem ser medidos, calculados ou estimados e serão utilizados para quantificar as entradas e saídas do processo unitário (ISO, 2006). Estas etapas resultam em uma tabela de inventário, listando e quantificando as entradas e saídas no ambiente associadas à unidade funcional, em termos de kg de dióxido de carbono, mg de fenol, kg de minério de ferro, metros cúbicos de gás natural, entre outros (Guinée et al., 2002).

Alocação

A alocação consiste na divisão adequada dos aspectos ambientais entre a

unidade funcional e os subprodutos do sistema (ISO, 2006). A sua utilização se faz necessária quando não se consegue separar os impactos gerados pelo produto em estudo daqueles impactos gerados simultaneamente pelo sistema produtivo (Ramírez, 2009).

Um exemplo clássico de alocação é o fracionamento do petróleo. Não se pode atribuir o impacto ambiental do processo do fracionamento a um único produto, uma vez que são gerados vários outros neste processo (Wang et al., 2004). Portanto, é necessário separar a quantidade de emissões e os consumos de recursos atribuídos a cada fração (Ramírez, 2009).

Existem diversos procedimentos de alocação que podem ser baseados em propriedades físicas, químicas e econômicas (Ramírez, 2009). Este mesmo autor cita que, para o cálculo da alocação, é necessário (i) encontrar uma relação entre os coprodutos gerados no sistema e os dados de entrada, (ii) determinar o valor do fator de alocação para cada coproduto do sistema e (iii) multiplicar todos os dados de emissão e/ou consumo de recursos pelo fator de emissão. Como exemplo, pode-se citar a alocação econômica, que consiste no fracionamento do impacto ambiental do sistema de acordo com o valor econômico de cada produto gerado. Na Tabela 1, pode-se observar o caso do fracionamento do petróleo. Conhecendo-se as quantidades de cada produto geradas neste processo, e o preço de cada fração, pode-se calcular os valores para o processo (quantidade * preço, para cada fração). A partir da divisão do valor do processo de cada fração pelo valor do processo total, obtém-se o fator de alocação e, dessa forma, conhece-se a contribuição de cada produto no impacto ambiental do sistema. No caso do óleo combustível, sua obtenção contribui com 25% das emissões e recursos utilizados em todo processo de fracionamento do petróleo.

Tabela 1. Alocação econômica do processo de fracionamento do petróleo (Guinée et al., 2002). Apesar da alocação ser necessária, a norma ISO 14044 (ISO, 2006) aconselha que este processo seja evitado sempre que possível. Isto se justifica, pois ao se adicionar mais cálculos ao estudo de ACV, mais incertezas também são atribuídas à pesquisa (Ramírez, 2009).

Produto

Avaliação do impacto do ciclo de vida

A avaliação do impacto do ciclo de vida (AICV) é a fase em que se faz a seleção das categorias de impacto, dos indicadores da categoria e a caracterização dos modelos (ISO, 2006). As etapas obrigatórias da AICV são (i) a seleção das categorias de impacto, indicadores das categorias e modelos de caracterização, (ii) ligação dos resultados do ICV às categorias de impacto selecionadas (classificação) e (iii) cálculo dos resultados dos indicadores das categorias (caracterização; ISO, 2006). As etapas opcionais são (i) normalização, que se refere ao cálculo da magnitude do indicador de categoria em relação às informações utilizadas como referência, (ii) grupamento, que é a ordenação e classificação das categorias de impacto, (iii) ponderação, onde é feita a conversão e agregação dos resultados dos indicadores das categorias de impacto, usando fatores numéricos baseados em valores escolhidos, e (iv) análise da qualidade dos dados, cuja função é a melhor compreensão da confiabilidade do conjunto de resultados, podendo ser feita a partir de uma análise de incertezas ou análise sensitiva (ISO, 2006).

Nesta etapa é que os resultados dos indicadores de categoria podem ser agrupados e ponderados (Guinée et al., 2002).

Existem dois tipos de métodos para a avaliação do impacto do ciclo de vida, os métodos clássicos ou orientados aos problemas ambientais e os métodos orientados ao dano. Os métodos clássicos restringem-se à modelagem quantitativa, pois compilam os resultados do impacto do ciclo de vida em categorias de pontos médios, como ecotoxicidade, eutrofização e acidificação, sendo denominados como midpoint; já os métodos orientados ao dano buscam modelar toda a cadeia de causa-efeito até os pontos finais, ou seja, danos causados à saúde humana e qualidade do ecossistema, como substâncias carcinogênicas, efeitos respiratórios e mudanças climáticas, sendo conhecidos como endpoints [START_REF] Jolliet | IMPACT 2002+: A new life cycle impact assessment methodology[END_REF]. Os endpoints apresentam maiores incertezas que os midpoints, devido à abrangência da modelagem deste grupo (Alvarenga, 2010).

Escolha das categorias de impacto

O United States Environmental Protection Agency -EPA ( 2006) cita que, na AICV, os impactos são definidos como as consequências causadas pelas entradas e saídas de um sistema à saúde humana, às plantas, aos animais ou à disponibilidade futura de recursos naturais. A partir disso, os impactos são agrupados em categorias focadas em três pontos: (i) saúde humana, (ii) a saúde ecológica e (iii) depleção de recursos (Tabela 2). A seleção das categorias de impacto deve traduzir o resultado da análise do inventário, demonstrando a contribuição do cenário criado para cada uma das categorias, condizentes ao objetivo do estudo (Guinée et al., 2002). Essa escolha deve ser feita de acordo com a abordagem utilizada, que pode ser orientada para os problemas ambientais (midpoints) ou para os danos (endpoints). 

Interpretação do ciclo de vida

A última etapa é a interpretação do ciclo de vida, em que os resultados da análise, e todas as escolhas e as premissas feitas no decorrer da análise, são avaliadas em termos de solidez e robustez, e são tiradas as conclusões gerais (Guinée et al., 2002).

Os principais elementos da fase de interpretação são a avaliação e a análise dos resultados, onde o autor deve apresentar os resultados de forma clara e compreensível, consistentes com o objetivo e o escopo definidos; e a formulação das conclusões e recomendações do estudo, em que se deve buscar identificar as limitações da análise e fazer recomendações para o público-alvo da ACV (ISO, 2006). A relação entre os elementos da ACV estão esquematizadas na Figura 8. 

Limitações do método

A metodologia de ACV para avaliação ambiental, por ser um modelo extremamente compreensivo, necessita de uma grande quantidade de dados para se fazer a análise. Isso faz com que várias incertezas estejam atreladas aos dados.

Entretanto, é uma das metodologias mais úteis para este tipo de avaliação, por possibilitar uma visão integrada dos problemas ambientais associados a um produto, ou a um sistema (Alvarenga, 2010).

Os dados de entradas e saídas de uma ACV, geralmente são valores médios. Por este motivo, devem-se avaliar as incertezas dos dados ao final da ACV, que pode ser feita por meio da análise de sensibilidade do resultado final, a partir da incerteza existente nos dados (Alvarenga, 2010). No caso de um sistema agropecuário, existem ainda mais incertezas relacionadas aos parâmetros técnicos e dados de inventário de uma ACV, devido à grande diversidade do sistema de produção e à ampla variedade de práticas agrícolas (Basset-Mens & van der Werf, 2005). Esse é um dos principais problemas para a aplicação da ACV em sistemas agrícolas, pela falta de referências sobre a diversidade dos sistemas existentes e a complexidade das interações entre as variáveis (Prudêncio da Silva, 2011).

5.6.

Utilização da análise do ciclo de vida na produção de suínos 2010). Os ingredientes utilizados nas dietas de suínos possuem diferentes valores de impacto ambiental, diferindo tanto pela forma de obtenção, como reservas minerais para o fosfato, quanto pela região produtora, como o caso de ingredientes associados com o processo de desmatamento (Tabela 3).

A
Tabela 3. Impacto ambiental dos principais ingredientes utilizados na dieta de suínos de acordo com a análise do ciclo de vida (dados por kg de alimento).

Ingredientes PAG (kg CO2-eq.) EU (g PO4-eq.) AC (g SO2-eq.) ECO (g 1.4-DBC-eq.) Para o cálculo do impacto do ciclo de vida de ingredientes utilizados como matérias-primas nas rações de suínos, vários fatores precisam ser considerados.

Tomando a produção de milho como exemplo (Alvarenga, 2010), para o cálculo do impacto do ciclo de vida de 1 kg de grão, é necessário o levantamento do sistema de plantio (direto ou convencional), caracterização da região produtora (área desmatada ou não), entradas utilizadas para o preparo do solo (maquinário, combustível), tipo de fertilização (química ou orgânica, bem como as fontes de N, fosfato, potássio, calcário) e formas de controle de pragas (substância ativa presente nos pesticidas, fungicidas, herbicidas). Após o levantamento do inventário para a produção do grão, é necessário calcular os impactos decorrentes da colheita, transporte até a etapa de secagem e posterior transporte até a fábrica de rações.

Geralmente, a etapa de produção de ração é a que mais contribui com o impacto em uma ACV, principalmente sobre a ecotoxicidade terrestre, demanda acumulada de energia e ocupação de terra (Basset-Mens & van Der Werf, 2005;Garcia-Launay et al., 2014).

Alojamento

A etapa de alojamento abrange todas as emissões decorrentes do manejo dos animais e dos dejetos antes de sua disposição final, sendo as emissões variáveis de acordo com as instalações, como animais confinados em piso ripado ou compacto, ou animais criados no sistema de cama sobreposta (Reckmann et al., 2012;Garcia-Launay et al., 2014).

Com relação aos compostos nitrogenados, fatores de emissão devem ser aplicados sobre a quantidade de N excretada para estimativa das emissões de NH3 (como exemplo o fator 0,24 kg de N-NH3/kg N excretado, proposto por Rigolot et al., 2010b), N2O (IPCC, 2006), NOX (Dämmgen & Hutchings, 2008). As emissões entéricas de metano podem ser calculadas em função da fibra digestível ingerida, como proposto por Rigolot et al. (2010a).

No que se refere ao sistema de produção de suínos, em uma avaliação do impacto do sistema convencional, convencional adaptado, tradicional e orgânico na Europa, [START_REF] Dourmad | The optimum dietary amino acid pattern for growing pigs: 2. Requirements for maintenance and for tissue protein accretion[END_REF], ao expressarem o potencial de impacto ambiental por kg de peso vivo dos suínos (Figura 9), notaram que o sistema tradicional obteve o maior impacto na categoria de aquecimento global (3,47 kg de CO2-eq), superando o sistema convencional (2,25 kg de CO2-eq). Porém, remeteram este dado ao fato de que este sistema possui uma menor eficiência alimentar, devido à utilização de raças mais rústicas. O sistema convencional adaptado também apresentou maior impacto na categoria aquecimento global (2,57 kg de CO2-eq) que o sistema convencional, principalmente devido ao baixo desempenho animal e utilização mais frequente de cama sobreposta.

Com relação à ocupação da terra, o sistema tradicional apresentou o maior impacto (10,6 m 2 ), seguido pelo sistema orgânico (9,14 m 2 ) e o convencional (4,13 m 2 ) (Figura 9-B). Para o sistema tradicional, a alta ocupação da terra é devido a terminação de suínos ser ao ar livre, fato que contribui com mais de 50% da ocupação da terra/kg de peso vivo. Para o sistema orgânico, a alta ocupação da terra deve-se ao baixo rendimento das culturas utilizadas neste sistema. Entretanto, quando os impactos são expressos por hectare de terra utilizada, os sistemas assumem classificação inversa, com o orgânico como o menos impactante, seguido pelo tradicional, convencional adaptado e convencional (Figura 9-A).

Figura 9. Análise do ciclo de vida de diferentes sistemas de produção de suínos (em porcentagem do sistema convencional): A, dados analisados por hectare de terra utilizada; B, dados analisados por kg de peso vivo. PAG, potencial de aquecimento global, EU, potencial de eutrofização; AC, potencial de acidificação; DAE, demanda acumulada de energia; OT, ocupação de terra [START_REF] Dourmad | The optimum dietary amino acid pattern for growing pigs: 2. Requirements for maintenance and for tissue protein accretion[END_REF].

Manejo de dejetos

As emissões que ocorrem em sequência à etapa de alojamento, incluem emissões durante a armazenagem de dejetos e sua posterior aplicação no campo. Para tanto, as emissões de compostos nitrogenados, da mesma forma como na etapa de alojamento, são calculadas aplicando coeficientes de emissão à quantidade de N restante após as emissões durante a etapa de alojamento. Dessa forma, é possível obter as quantidades emitidas durante a armazenagem e aplicação dos dejetos de NH3 (Rigolot et al., 2010be Andersen et al. 2001, respectivamente), N2O (IPCC, 2006 para ambas as etapas), NOx (Dämmgen & Hutchings, 2008e Nemecek & Kägi, 2007, respectivamente). As emissões de metano durante a armazenagem dos dejetos podem ser calculadas em função da matéria orgânica excretada, levando em conta a temperatura ambiental da região produtora, como proposto por Rigolot et al. (2010b).

A etapa de manejo de dejetos tem grande influência sobre o impacto ambiental da produção de suínos, e também pode variar em função do tipo de tratamento. Neste sentido, Cherubini et al. (2015) avaliaram quatro sistemas de manejo de dejetos suínos: dejetos líquidos armazenados em tanques, biodigestor para queima, biodigestor para melhor desempenho ambiental para a maioria das categorias de impacto, principalmente devido à captura do biogás e pelo potencial de economia de energia.

Figura 10. Análise do ciclo de vida da produção de suínos: A, impacto de cada etapa produtiva, em porcentagem do impacto ambiental total da produção; B, impacto do sistema de manejo de dejetos, em porcentagem do manejo de dejetos líquidos. PAG, potencial de aquecimento global, EU, potencial de eutrofização; AC, potencial de acidificação; DAE, demanda acumulada de energia; OT, ocupação de terra (Cherubini et al., 2015). PV, peso vivo; GP, ganho de peso; Soja, dietas baseadas em farelo de soja; Grãos, dietas baseadas em farelo de soja e grãos de cereais; sem AA, dietas sem inclusão de aminoácidos industriais; com AA, dietas com inclusão de aminoácidos industriais e nível mínimo de proteína bruta; Baixa PB, dieta com inclusão de aminoácidos industriais e nível reduzido de proteína bruta.

As implicações ambientais da incorporação de L-lisina, L-treonina e fontes de Entretanto, nem sempre a redução do conteúdo de PB na dieta de suínos é acompanhada pela redução do impacto ambiental. Em um estudo que avaliou o uso de coprodutos nas dietas de suínos, foi reportado que a utilização de farinha de carne na dieta aumentou o conteúdo de PB quando comparada às dietas baseadas em milho e farelo de soja (147 versus 133 g de PB/kg, respectivamente; Mackenzie et al., 2016).

Entretanto, o potencial de aquecimento global para cada kg de carcaça suína foi 2%

inferior quando os animais foram alimentados com dietas baseadas em farinha de carne, considerando um sistema canadense de produção de suínos.

Os benefícios do uso de co-produtos em dietas para suínos para a sustentabilidade do sistema produtivo são claros, uma vez que os coprodutos possuem seu impacto alocado a partir do produto principal. No estudo desenvolvido no Canadá, a farinha de carne foi alocada a partir da produção de carne para o consumo humano; uma vez que a alocação é baseada no valor econômico de ambos os produtos (produto principal: carne para o consumo humano e seu coproduto: farinha de carne e ossos), como coprodutos apresentam menor preço, é esperado que os impactos ambientais sejam reduzidos por meio do uso destes ingredientes.

Outro estudo, avaliando o impacto ambiental da produção de suínos no Brasil, demonstrou que à medida que o conteúdo de PB na dieta de suínos foi reduzido pela incorporação de AAI, o impacto do ciclo de vida das dietas aumentou para as categorias aquecimento global, acidificação e demanda de energia (Figura 11-A; Monteiro et al., 2016). Entretanto, quando o impacto é avaliado para toda a produção, a utilização de AAI na dieta pode ser interessante para reduzir impactos associados com a excreção de N, como acidificação e eutrofização (Figura 11-B). Neste estudo, a substituição do farelo de soja por AAI aumentou o potencial de aquecimento global da produção de suínos, pois a produção de cada kg de AAI emite mais CO2-eq. que a produção de grãos utilizados como fontes proteicas, quando estes não são associados ao processo de desmatamento. Além disso, a menor excreção de N em suínos alimentados com dietas de baixa PB compensou o maior impacto da dieta sobre a categoria acidificação. Impactos são expressos em porcentagem da dieta 'Sem AA'. PAG, potencial de aquecimento global, EU, potencial de eutrofização; AC, potencial de acidificação; DAE, demanda acumulada de energia; OT, ocupação de terra (Monteiro et al., 2016).

Perspectivas

De maneira geral, muitos estudos utilizaram a metodologia de ACV para estimar o impacto ambiental da produção de suínos. No Brasil, entretanto, as pesquisas ainda 

II -OBJETIVOS OBJETIVO GERAL

 Avaliar o impacto ambiental da redução dos níveis de proteína bruta na dieta de suínos, por meio da análise do ciclo de vida.

OBJETIVOS ESPECÍFICOS

 Quantificar à excreção de nitrogênio e fósforo dos suínos na fase inicial (15 aos 30 kg de peso vivo), bem como o desempenho dos animais nesta fase, recebendo dietas com níveis decrescentes de proteína bruta, e utilizar estes dados nos cálculos da análise do ciclo de vida da produção de suínos dos 15 aos 30 kg;

 Utilizar os dados de desempenho e excreção, estimados por meio do software InraPorc®, nos cálculos da análise do ciclo de vida da produção de suínos, dos 15 aos 30 kg de peso vivo, e confrotar estes dados com os obtidos experimentalmente por meio da abordagem bayesiana;

 Utilizar o software InraPorc® para obter dados de excreção e desempenho de suínos nas fases de crescimento e terminação (dos 30 aos 115 kg de peso vivo), e utilizar estes dados como entradas para a análise do ciclo de vida da produção de suínos;

 Identificar as principais oportunidades de cada cenário de proteína bruta, e mostrar como estas informações podem ser usadas para melhorar o desempenho ambiental da suinocultura brasileira.

III -Dietary crude protein reduction for starter pigs lessens the land occupation impact 1

ABSTRACT: The objective was to evaluate, through life cycle assessment and with experimental data, the impact of producing piglets fed diets with different crude protein for each 1 g of reduction on daily nitrogen intake. However, there was no statistical difference (P>0.05) among experimental treatments for the impact categories. For LO, there was a reduction (P=0.078) of impact with CP reduction, which was 8% lower in the diet with

Introduction

The increasing international demand for high quality meat products, as well as greater awareness of climate change, has put pressure on the livestock industry, including pig production, to deliver high quality products while reducing its environmental impact. A wide range of past and current research has been addressed

indicating that the reduction in dietary crude protein (CP), through the use of industrial amino acids (IAA), could reduce nitrogen excretion by pigs and, consequently, mitigate the environmental burdens of pig production, as reviewed by Dourmad and Jondreville (2007). However, the pig supply chain involves a very complex system, which requires the production of fertilizers and pesticides for crop production, land transformation for crop production, a large net of transportation to and from farms, water use for animal intake and farmyard washing, energy for light and heat and waste management (McAuliffe et al., 2016).

To fill this gap, life cycle assessment (LCA) evaluates the environmental impact as a whole and this method has been widely used in recent years in the swine production chain (McAuliffe et al., 2016). However, most LCA studies use average input data, adding some uncertainties on the results, due to the diversity of productions systems and farming practices (Basset-Mens and van der Werf, 2005). Besides, using technical performance indicators based on the agroindustry to evaluate the effect of feeding strategies must be done carefully in a LCA study. The effects of between-animal variability on pig performance and requirements have been demonstrated in different studies [START_REF] Brossard | Modelling the variation in performance of a population of growing pig as affected by lysine supply and feeding strategy[END_REF], Brossard et al., 2014) and could affect both performance and excretion.

This raises the question of whether this average data can be considered a faithful representation of the nutrient excretion by pigs, due to the dynamic phenomenon of dietary nutrient utilization, which changes over the fattening period (van Milgen et al., 2008). In addition to this, although several studies have been conducted in pork supply chains, to our knowledge there have been few studies on the LCA evaluation of nutritional approaches in Brazil (Cherubini et al., 2015, Monteiro et al., 2016). The aim of this study was to evaluate the environmental impact of raising pigs fed different levels of dietary CP, based on LCA methodology with observed individual data of performance and excretion.

Material and methods

Goal and scope definition

The definition of system and subsystem boundaries was derived from Nguyen et al. (2010) and is described in Figure 1. The LCA considered the activity of piglet production, from 15 to 30 kg body weight, in four different scenarios of feed formulation, including crop production, grain drying and processing, production and transport of feed ingredients, feed production at the feed factory, transport of the feed to the farm, starting pig production, and manure storage, transport and spreading (Figure 1). Impacts were calculated at the farm gate and the functional unit considered was one kg of body weight gain (BWG) over the starting period. The starting pig production system considered was a conventional nursery farm with indoor rearing of castrated males on partially slated floor and the collection and storage of manure as liquid slurry.

production (FIESC, 2014). We hypothesized that the grains came from the main producing areas in South Brazil. For transport inventory, we used the methodology described by Prudêncio da Silva et al. (2010). Products imported were assumed to be mainly transported by sea followed by road (Mosnier et al., 2011).

Feed specifications

The total amino acid composition of maize and soybean meal used in the diet formulation were obtained through near-infrared spectroscopy -NIRS, by Evonik Industries, and the standardized digestibility coefficients of amino acids proposed by Rostagno et al. (2011) were applied in these total contents, for each ingredient.

Four experimental feeds were evaluated (Table 1), with different levels of CP content (19.24, 18.24, 17.24 and 16.24%), meeting the requirements of digestible amino acids proposed by Rostagno et al. (2011) with inclusion of L-lysine HCl, DLmethionine, L-threonine, L-tryptophan, L-valine and L-isoleucine. Diets were formulated to have the same net energy content and, at least, 3230 kcal kg -1 of ME (Rostagno et al., 2011). Sodium bicarbonate was used to keep the same electrolyte balance among the experimental diets.

The feed production process at the feed factory was included in the inventory, considering that it would be held in the pig production region (Garcia-Launay et al.,

2014).

Pig production

All procedures were performed in accordance with Brazilian guidelines reviewed and approved by the Ethics Committee of the Universidade Estadual de Maringá (protocol No. 7470031215). The Brazilian guidelines are based on Federal Law N°.

11794 of October 8, 2008.

Trial I (performance). Twenty eight crossbred barrow piglets (LW x LD), with an initial average weight of 15.3 ± 1.15 kg and final weight of 31.6 ± 2.31 kg were used. Pigs were housed in a nursery masonry shed with suspended floor, covered with fiber cement tiles. The stalls measured 1.32 m 2 , with cement floors and feeders in the front and partially slatted plastic floor with a nipple-type drinker in the back. Diets and water were provided ad libitum throughout the experimental period. The average daily minimum and maximum temperatures recorded in the trial period were 18.9 ± 1.95 ºC and 33.7 ± 2.03 ºC, respectively. The average relative air humidity of the experimental period was 68.9 ± 10.3 %.

The animals were divided up in a randomized block design with four treatments, seven replications in time and one animal per experimental unit. The piglets were weighed at the beginning and at the end of the trial, as well as feed supplies and refusals. These data were used to calculate feed conversion ratio (FCR), average daily gain (ADG) and average daily feed intake (ADFI).

At the end of the trial, backfat thickness and loin muscle depth (longissimus thoracis) were measured from images between the 7 th and 8 th thoracic vertebra, using ultrasound equipment (Aloka model, SSD 500V, coupled with a linear probe USF-5011U-3.5; Aloka, USA) and by using the Biosoft Toolbox II software for swine (Biotronics Inc, USA).

Trial II (nitrogen and phosphorus balance). Twenty crossbred barrow piglets (LW x LD) with average weight of 21.4 ± 1.62 kg were housed in metabolic cages, in a room with partially controlled environment. The average minimum and maximum temperatures recorded in the trial period were 23.2 ± 1.13 ºC and 27.1 ± 0.941ºC, respectively. The average relative air humidity of the experimental period was 57.7 ± 21.1 %. The experimental design was set in a randomized block, replicated in time, totaling four treatments and five replications, and the experimental unit consisted of a piglet.

The piglets received two daily meals, provided at 07h30 and 15h30. The total daily amount was determined according to the intake in the adaptation phase, based on metabolic weight (BW 0.75 ). To avoid waste and facilitate handling, the diets were moistened with 30 % water, and after each meal, water was supplied at the feeder at the rate of 3 mL g -1 of feed, calculated for each experimental unit, in order to avoid excess of water intake.

To calculate the nitrogen and phosphorus balance, total feces collection was performed for which 2 g ferric oxide (Fe2O3) was added to the diets to mark the beginning and end of feces collection. The total amount of feces produced was collected daily and stored in plastic bags and then kept in a freezer at -18 ºC. Urine was totally collected daily in plastic buckets containing 20 mL of HCl 1:1. A 20 % sample was collected daily and frozen at -18 ºC.

Analytical procedures

Representative samples of the feeds were analyzed according to Association of Official Analytical Chemists (AOAC, 1990) for dry matter (method 950.05), ash (method 942.05), crude fiber (method 962.09) and total nitrogen (method 984.13). The phosphorus, copper, zinc and potassium concentrations in feed samples were obtained by using UV-Vis spectrophotometry (model Cary 50®, Varian Inc.). Urine and feces samples were analyzed for total nitrogen and, for feces, for total phosphorus, dry matter, ash and crude fiber.

SO2-eq.), terrestrial ecotoxicity (TE, g 1,4-DCB-eq.), cumulative energy demand (CED, MJ), and land occupation (LO, m 2 .year). The GWP was calculated according to the 100year global warming potential factors in kg CO2-eq.

Calculations and statistical analyses

We calculated for each diet the average nitrogen and phosphorus retention coefficient from the balance data in Trial II (Table 2). These coefficients were then used to determine nitrogen and phosphorus excretion in Trial I, according to the actual nutrient intake of each pig (Table 3). The LCA calculations were performed for each pig according to its individual performance and excretion from 15 to 30 kg BW on average.

These calculations were performed using a calculation model developed with SAS software (Statistical Analysis System, version 9.2).

Performance responses and environmental impacts were subjected to variance analysis using the GLM procedure (Statistical Analysis System, version 9.2). The statistical model included effects of CP level and block. When the dietary effect was significant, we subjected the variable to regression analysis. The degrees of freedom from the CP level parameter were divided into polynomials. The initial body weight of the piglets was used as a covariate for the statistical analysis of ADFI, ADG, FCR, backfat thickness and loin depth. The feed intake during the trial was used as a covariate for the LCA variables. All analyses were performed using SAS (Statistical Analysis System, version 9.2).

The ß error of LCA parameters was used in order to help explaining P-values from 5 to 10% of significance. This procedure was performed by using the power anova test of R package.

environmental impact per kg of feed; LO was the only impact that was reduced when dietary CP decreased (Table 1).

Global warming potential and cumulative energy demand

No differences were found for GWP (P=0.831) and CED (P=0.164) among dietary treatments. The average values ranged between the experimental treatments from 1.76 to 1.77 kg CO2-eq. per kg BWG for GWP and from 17.8 to 19.6 MJ-eq. per kg BWG for CED (Table 4).

Main processes contributing to impacts were feed production (production and transport of feed ingredients, feed processing at the feed factory and transport to the farm), animal housing, and manure management (storage, transport and spreading;

Figure 2). Manure management had the highest contribution to GWP (50 %), followed by feed production (42 %), while for CED, feed production was the main contributor (54 %) followed by animal housing (48 %).

Potentials of acidification and eutrophication

The average values ranged from 30.0 to 33.2 g SO2-eq. per kg BWG for AP and from 10.3 to 11.3 g PO4-eq. per kg BWG for EP (Table 4). Despite these variations, no differences were observed between the experimental feeds for AP (P=0.180) and EP (P=0.111).

For both categories, feed production had the highest contribution to impact (65 and 77 % for AP and EP, respectively), followed by animal housing (24 and 15 % for AP and EP, respectively).

Terrestrial ecotoxicity and land occupation

Dietary CP reduction did not affect TE impact (P=0.470) whereas, according to the power of statistical test (ß = 64 %), reduced LO (P=0.078), with values ranging from 4.68 to 5.17 g 1,4-DBC-eq. per kg BWG for TE and from 1.89 to 2.06 m 2 •year per kg BWG for LO (Table 4).

For both categories, feed production was the main contributor (91 and 100 % for TE and LO, respectively); TE was also related to manure management (9 %), but with a rather low contribution (Figure 2).

Discussion

Performance, nitrogen and phosphorus balance

Like the findings of this study, Toledo et al. (2014) did not observe any differences in performance-related variables of piglets weighing 6 to 15 kg, by decreasing dietary CP levels. The amino acid imbalance may negatively influence the feed intake [START_REF] Park | Amino Acid Imbalance-Biochemical Mechanism and Nutritional Aspects[END_REF] and, consequently, the performance. As this did not occur in our experiment, it can be inferred that the IAA addition was effective in keeping the protein quality and in maintaining performance.

Low dietary CP diets could provide the animals with less energy spent on amino acid deamination, less urea excretion in urine and lower heat production (Noblet et al., 2001), resulting in more net energy available to be deposited in carcass as fat, mainly in the growing-finishing phase. However, in our study, pigs fed with low CP diets did not show increased backfat thickness, as diets were formulated to provide the same amount of net energy, exempting the effects mentioned above.

The linear reduction in nitrogen intake and excretion, with the CP reduction, corroborate previous research in weaning piglets [START_REF] Gloaguen | The use of free amino acids allows formulating very low crude protein diets for piglets[END_REF], Toledo et al., 2014) and in growing pigs (Andretta et al., 2014, Pomar et al., 2014). The National Research Council (NRC, 2012) suggested that for each percentage unit of dietary CP reduction, nitrogen excretion can be expected to decrease by 8 %, due to the lower amino acid deamination and, consequently, lower urea excretion in urine. The same reduction was found in our study, in which each percentage point of CP reduction, reduced on average total nitrogen excretion by 10 %.

According to the regression equations adjusted for nitrogen intake (Table 3), the nitrogen excretion in urine increased by 0.127 g d -1 for every 1 g increase in the daily nitrogen intake. For total nitrogen excretion, an increase of 0.226 g d -1 was estimated for every 1 g increase in the daily nitrogen intake. Therefore, the higher the nitrogen intake, the higher the nitrogen excretion will be.

Life cycle impacts

The hypothesis for reducing the environmental impacts of piglet production through CP reduction was not validated by our results, as there was no statistical difference among experimental treatment for the LCA categories. These results could be due to the lack of difference in animal performance (Table 2), since environmental impacts are highly dependent on feed intake and final values are expressed per kg of BWG.

Global warming potential and cumulative energy demand

The increase in GWP impact per kg of feed when dietary CP is reduced (Table 1), is related to the higher IAA addition and the replacement of soybean meal by maize.

Global warming potential associated with IAA production are higher per kg of product than for grain or soybean meal production (Ogino et al., 2013).

The benefits of the IAA addition related to the reduction of nitrogen excretion during housing and, consequently, lower nitrogen gaseous emissions, might compensate for the higher impact of low CP diet (i.e., 16.24% of CP). However, this was not observed in our study, since no significant difference was observed for GWP among dietary treatments (Table 4). This could be related to the hypothesis for the origin of soybean. In this study it was assumed that the soybean was produced in South Brazil in an area without recent deforestation. Indeed as shown by Prudêncio da Silva et al.

(2010) considering the CO2-eq. emissions due to the effect of land use change as a consequence of rainforest conversion in crop areas, increases GWP of soybean meal. In this situation replacing soybean meal by cereals and IAA appears an interesting strategy to reduce GWP impact, as clearly shown by Kebreab et al. (2016) and Monteiro et al. (2016).

However, Brazilian government and industry have made efforts to identify soybean produced in deforested areas from Amazon Biome, as through the Soy Moratorium (ABIOVE, 2016). As a consequence, soybean produced in these areas has been reduced in recent years (Gibbs et al., 2015), which justifies the use of soybean from non-deforested areas, in current and future evaluations of Brazilian scenarios.

Manure management was the process with the greatest contribution for GWP impact (Figure 2), due to the direct effect of ambient temperature on the amount of methane emitted during manure storage (Rigolot et al., 2010); gas with a GWP 25 times that of CO2 (IPCC, 2007).

Experimental feeds with high IAA addition showed higher CED, per kg of feed (Table 1). This was expected, because according to Kebreab et al. (2016), the production of IAA and phytase demands high amounts of non-renewable energy.

Despite this high contribution of feed production to CED impact (almost 54 %; Figure 2), the IAA addition did not significantly affect the CED per kg BWG.

Garcia-Launay et al. ( 2014) observed a reduction of CED impact of fattening pig production in France when dietary CP content was reduced. However, they took into account that 100 % of soybean was imported from Brazil (mainly from Center-West) with a high energy demand at the transport step.

Considering 100 % of soybean production in South Brazil, the same region of pig production, Monteiro et al. (2016) also observed an increase in CED impact per kg BWG when dietary CP was reduced. The difference in CED impact between high and low CP diets found by these authors was about 8.7 %, a value close to the difference observed in our study (9.2 %; Table 4). However the difference was significant in their study probably because they used simulated data from 2000 pigs.

Our results are in agreement with Kebreab et al. (2016), who also did not observe differences on CED between diets with different CP and total phosphorus levels. They concluded that the high non-renewable energy used during IAA production, could be an area where the industry could take action to reduce impacts.

Potentials of acidification and eutrophication

The reduction of dietary CP content, led to a slight increase in AP and EP impacts, per kg of feed (Table 1). This result was also observed in previous studies (Mosnier et al., 2011, Garcia-Launay et al., 2014, Mackenzie et al., 2016, Monteiro et al., 2016).

Feed production showed the highest contribution for AP and EP impacts (Figure 2) which is consistent with the results reported by other authors (Basset-Mens and van der Werf, 2005, Garcia-Launay et al., 2014). Although low CP diets showed higher AP and EP impacts, per kg of feed, several authors reported that these diets could modify several steps of pig chain, reducing the amounts of nitrogen excreted and, consequently, reducing the nitrogen gas emissions during housing and manure management (Garcia-Launay et al., 2014, Monteiro et al., 2016), as well as nitrate losses during manure application.

Indeed, nitrogen and phosphorus contribute to the eutrophication process, and nitrogen contributes to the acidification process by ammonia emissions (Guinée et al., 2002). For this reason, most research evaluating the effect on dietary CP reduction for pigs, reported a reduction on AP and EP with low CP diets (Ogino et al., 2013;Garcia-Launay et al., 2014;Mackenzie et al., 2016;Kebreab et al., 2016). In the abovementioned research, data were not evaluated statistically, and the effect of betweenanimal variability was also not taken into account. Similar trends are observed in the present study with about 9 % reduction of AP and EP impacts; however, these differences are not significant.

Terrestrial ecotoxicity and land occupation

The high TE per kg of feed (Table 1) in low CP diets was related to the higher IAA addition. Copper and zinc, the elements that most contribute to the TE impact (Guinée et al., 2002), are found in small amounts in fertilizer and herbicides used during grain production, compared to their amount during IAA manufacturing. Garcia-Launay et al. ( 2014) calculated that TE impact for L-lysine manufacturing was 82 % higher than for soybean meal production. For the other IAA (L-tryptophan, DLmethionine and L-valine), authors estimated an impact 91 % higher than soybean meal.

In this context, due to the fact that feed production contributed to more than 90 % of total TE impact (Figure 2), the diet with 16.24 % of CP, with the highest IAA addition, presented a 9 % higher TE impact per kg BWG, compared to 19.24 % of CP diet, although the differences between treatments were not significant. These results are in agreement with the results observed in previous studies by Garcia-Launay et al. (2014) and Monteiro et al (2016) who observed a 4-11% increase of TE impact of fattening pig production with low CP feeding strategies.

Regarding LO, the increase in IAA addition reduced the impact per kg of feed (Table 1), once low CP diets resulted in lower soybean inclusion and higher maize and IAA inclusion. Considering the grain production in Brazil, Prudêncio da Silva et al.

(2014) reported a LO impact for soybean meal more than twice as high as for maize.

Due to the high contribution of feed production to LO impact (Figure 2), which is almost 100%, reducing the impact per kg of feed, consequently reduced the LO impact of piglet production (Table 4). The reduction in LO through IAA addition in pig diets has already been demonstrated in fattening pigs or over the whole pig production system (Mosnier et al., 2011, Garcia-Launay et al., 2014, Monteiro et al., 2016).

Potential for reducing environmental impacts through crude protein reduction

As mentioned earlier, the huge challenge for livestock production will be to meet the growing demand for food in the next decades, without compromising environmental integrity. The reduction of dietary CP through the IAA addition, has been considered as an efficient strategy to reduce the environmental impact of pig production (Dourmad and Jondreville, 2007), because it reduces nitrogen excretion. Recently, with LCA application in livestock production, this strategy continued to be considered effective for reducing the impact under some categories, such as acidification and/or eutrophication [START_REF] Eriksson | Environmental systems analysis of pig productionthe impact of feed choice[END_REF], Ogino et al., 2013, Garcia-Launay et al., 2014, Kebreab et al., 2016, Mackenzie et al., 2016, Monteiro et al., 2016).

For GWP impact, reducing dietary CP has also been found to be efficient in many studies [START_REF] Eriksson | Environmental systems analysis of pig productionthe impact of feed choice[END_REF], Ogino et al., 2013, Garcia-Launay et al., 2014, Cherubini et al., 2015, Mackenzie et al., 2016). However, more recent researches showed that this strategy is mainly effective when protein-rich ingredients with high impact are used, for instance soybean meal associated with deforestation or transported at long distances, whatever the pig production context considered in the LCA (Kebreab et al., 2016, Monteiro et al., 2016).

Almost all these results have been obtained on fattening pigs. The results in the present study obtained on post-weaning piglets are overall in line with the results found on fattening pigs. The results of reducing dietary CP on GWP and CED are limited with even a tendency to have increased impact in low CP diets. Differences are more marked for EP, AP ad LO, with about 9 % reduction with low CP diets. However due to the between animal variability most of these differences are not statistically significant.

Another point observed in our study is the lack of national IAA production, which contributes to increasing the impact under CED of Brazilian pig production, once IAA must be imported, except L-lysine. From the moment that IAA is produced nationally, low CP diets could present an environment benefit in pig production, concerning the CED and TE reduction.

Conclusions

Our results indicated that the dietary CP reduction for piglets from 15 to 30 kg of BW, through the IAA supplementation, reduced the environmental impact under LO, considering a Brazilian context of pig production. 1 Lean percentage = 60.69798 -0.89211 * backfat + 0.10560 * Muscle depth [START_REF] Vítek | Improvement of accuracy in the estimation of lean meat content in pig carcasses[END_REF]. 

Introduction

Livestock production has been identified as an activity with a high pollution potential (Basset-Mens and van der Werf, 2005), due to contamination risks in high pig density regions, as the Southern Brazil (FIESP, 2014). As consequence, strategies to mitigate enviromental impact of swine production has been addressed and the dietary crude protein (CP) reduction, through industrial amino acid (IAA) inclusion, was established as a technique which can change nitrogen excretion (Toledo et al., 2014;Andretta et al., 2014), showing a potential to reduce the environmental impact.

In recent years, life cycle assessment (LCA) has been widely used in swine production (McAuliffe et al., 2016) to evaluate the environmental impact as a whole.

Previous studies have been shown that feed production is the step with highest contribution to LCA impact (Basset-Mens e van der Werf, 2005; Mosnier et al., 2011;Garcia-Launay et al., 2014), indicating that feed strategies could directly interfere in the impact generation.

However, LCA approach is very comprehensive, using a concept based on input/output accounting throughout the product life cycle. As a result, many uncertainties are associated to technical parameters, mainly in a livestock system, due to the diversity of production systems and the wide range of agricultural practices (Basset-Mens & van der Werf, 2005). This is the main problem to LCA application in those systems, because of the lack of references on the diversity of systems and the complexity of interactions between variables (Prudêncio da Silva, 2011).

Besides that, predicted data could be obtained through models and/or software, which couldn't be overall adequate for the diversity in production systems, corroborating the need to establish an environmental impact assessment of LCA using predicted and observed data. The aim of this study was to validate the environmental impact of raising pigs from 15 to 30 kg, fed with dietary CP reduction, based on LCA methodology with predicted performance and excretion data.

Material and methods

The environmental impacts were evaluated following the suggestions of Guinée et al. (2002), according to the steps: goal and scope definition, life cycle inventory and life cycle impact assessment.

Goal and scope definition

The definition of system and subsystem boundaries was derived from Nguyen et al. ( 2010) and is described in Figure 1. The LCA considered the activity of piglet production, from 15 to 30 kg of body weight, in four different scenarios of feed formulation, including crop production, grain drying and processing, production and transport of feed ingredients, feed production at the feed factory, transport of the feed to the farm, starting pig production, and manure storage, transport and spreading (Figure 1). Impacts were calculated at the farm gate and the functional unit considered was one kg of body weight gain (BWG) over the starting period. The starting pig production system considered was a conventional nursery farm with indoor rearing of barrows on partially slated floor and the collection and storage of manure as liquid slurry.

Life cycle inventory (LCI)

Resource use and emissions associated with the production and delivery of inputs for crop production (fertilizers, pesticides, tractor fuel and agricultural machinery) came described by Prudêncio da Silva et al. (2010). Products imported were assumed to be mainly transported by sea followed by road (Mosnier et al., 2011).

Feed specifications

The amino acid composition of maize and soybean meal used in the diet formulation were obtained through near-infrared spectroscopy -NIRS, by Evonik Industries, and the standardized digestibility of amino acids from these ingredients was determined as in Rostagno et al. (2011).

Four experimental feeds were evaluated (Table 1), with different levels of CP content (19.24, 18.24, 17.24 and 16.24%), meeting the requirements of digestible amino acids proposed by Rostagno et al. (2011) with inclusion of L-lysine HCl, DLmethionine, L-threonine, L-tryptophan, L-valine and L-isoleucine. Diets were formulated to have the same net energy content and, at least, 3230 kcal kg -1 of ME (Rostagno et al., 2011). Sodium bicarbonate was used to keep the same electrolyte balance among the experimental diets.

The feed production process at the feed factory was included in the inventory, considering that it would be held in the pig production region (Garcia-Launay et al., 2014).

Pig production

Predicted data. Performance data from Rostagno et al. (2011), with weekly feed intake and body weight data (high performance), were used to adjust average animal profile parameters for growth and feed intake using InraPorc® software (INRA, Saint-Gilles, France), for barrows. Thus, ad libitum net energy intake was modeled as a gamma function of BW expressing daily net energy intake in multiples of net energy intake above maintenance, with two parameters 'a' (4,8779) and 'b' (0,0219) and c a fixed parameter representing the maintenance energy requirement (0.75 MJ kg -1 BW 0.60 , van Milgen et al., 2015). Protein deposition (PD) was modeled by a Gompertz function described using mean PD (278 g d -1 ) and precocity (0,016) (van Milgen et al., 2008).

From this animal profile, simulations were performed for each dietary CP content scenario, in order to determine animal performance, nutrient balance and excretion, from 15 to 30 kg of body weight (BW), according to InraPorc®.

Observed data. Performance and nutrient excretion data came from two trials presented in Chapter III of this thesis, in which the productive phase and experimental feeds used were the same in relation to the predicted data.

Manure management

The environmental consequences of manure utilization were evaluated using system expansion as described by Nguyen et al. (2010). Thus, manure produced was assumed to substitute a certain amount of mineral fertilizers, by using a mineral fertilizer equivalency (MFE, %). We assumed that the MFE was 75 % of total nitrogen in manure (Nguyen et al., 2010), with 5 % extra loss as nitrates compared to mineral fertilizers (Garcia-Launay et al., 2014), and MFE was 100 % for phosphorus (Sommer et al., 2008).

Life cycle impact assessment

Emissions from animal production

Emissions to air during swine production were estimated step-by-step for NH3, N2O, NOx and CH4, as described by Monteiro et al. (2016). The NH3 emissions from the building and during manure storage were calculated according to emission factors proposed by Rigolot et al. (2010), considering the effect of ambient temperature in Southern Brazil (mean of 22°C). The amounts of nitrogen, P, Cu, Zn, K and organic matter excreted by the pigs were obtained from InraPorc® simulations. These data, and data from essays, were used to calculate the amount of each element available at field application.

Characterization factors

We kg CO2-eq.), eutrophication potential (EP, g PO4-eq.), acidification potential (AP, g SO2-eq.), terrestrial ecotoxicity (TE, g 1,4-DCB-eq.), cumulative energy demand (CED, MJ), and land occupation (LO, m 2 .year). The GWP was calculated according to the 100year global warming potential factors in kg CO2-eq.

Validation by using predicted and observed data

Performance, excretion and environmental impact data for each CP level, from essays (observed) and from InraPorc® simulations (predicted), were compared by using a Bayesian approach. Results differences for each pair of samples were described as Dif = y2-y1, providing a difference sample, normally distributed such that:

Difi ~ N (μ, τ)

where i = 1, 2, ..., n, considering for μ (mean) and τ (precision), noninformative a priori distribution, such that, μ ~ N (0,10 -6 ) and τ ~ Gamma (10 -3 ,10 -3 ) with variance  2 =1/ τ, according to OpenBUGS parameterization, software which simulate parameters chains through MCMC process (Monte Carlo Markov Chain).

A posteriori distributions were obtained through the Brugs package program R (R Development Core Team, version 3.2.5). One hundred thousand values were generated through the MCMC method, with a discharge of 10,000 initial values in jumps of size 1. The convergence of the chains was tested by the coda package R program according to the criteria of [START_REF] Heidelberger | Simulating run length control in the presence of an initial transient[END_REF].

The average a posteriori estimates were used for each parameter, and a credibility interval (CIr) was calculated for the average difference, where significance was observed in the parameters in which the value zero did not belong to the range of 95% of credibility (0∉CIr).

Results

Animal performance, nitrogen and phosphorus balance

The reduction in dietary CP provided a variation of 0.75 % in average daily gain, comparing the diet with 19.24 % of CP (0.668 kg d -1 ) in relation to 16.24 % of CP (0.673 kg d -1 ; Table 2). There was a reduction of 0.55 % in feed conversion ratio for pigs fed lower CP level. Backfat thickness and lean percentage were the same between experimental feeds (Table 2).

There was a reduction on nitrogen intake and excreted, with dietary CP reduction. The amounts of phosphorus intake were reduced as dietary CP was decreased, as well as phosphorus excreted (Table 2).

Life cycle impacts

Global warming potential, cumulative energy demand and terrestrial ecotoxicity

The average values for GWP ranged between the experimental treatments from 1.53 to 1.55 kg CO2-eq. kg -1 BWG, from 17.5 to 19.4 MJ-eq. kg -1 BWG for CED and from 4.78 to 5.15 g of 1,4-DBC-eq. kg -1 BWG (Table 3). For these categories, the impact was increased as the dietary CP was reduced.

Potentials of acidification and eutrophication and land occupation

The average values ranged from 34.0 to 35.6 g SO2-eq. kg -1 BWG for AP, from 10.8 to 11.3 g PO4-eq. kg -1 BWG for EP and from 1.88 to 2.09 m 2 •year kg -1 BWG (Table 3). These categories, however, showed an impact reduction with the decreasing in dietary CP content.

Validation by using predicted and observed data

Differences were observed (0∉CIr) between predicted (InraPorc®) and observed (essays) data for the parameters average daily gain and nitrogen excreted, as well as for the impacts categories GWP, AP and EP (Table 4). However, predicted feed intake, phosphorus excreted, CED, TE and LO did not differ (0∈CIr) from the observed data (Table 4).

Discussion

Performance, nitrogen and phosphorus balance

The feed conversion ratio showed a little reduction as the dietary CP was decreased (Table 2). Conversely, Toledo et al. (2014) did not observe any differences (P>0.05) in feed conversion ratio of piglets weighing 6 to 15 kg, by decreasing dietary CP levels.

Low CP diets could provide the animals with less energy spent on amino acid deamination, less urea excretion in urine and lower heat production (Noblet et al., 2001), resulting in more net energy available to be deposited in carcass as fat. However, when the net energy system is used, it does not occur. For this reason, backfat thickness and lean percentage data, in our study, did not vary between experimental feeds (Table 2). This could be due to the software which considered that fat deposition was not affected by dietary CP reduction, once all diets showed the same net energy content.

However, it's worth pointing out that we did not use population version of this software, so our data did not took into account the effect between-animal variability, which affect both performance and excretion data (Brossard et al., 2014).

The reduction on intake and excretion, as the dietary CP was reduced, corroborate previous studies (Andretta et al., 2014;Pomar et al., 2014;Toledo et al., 2014). The National Research Council (NRC, 2012) suggested that for each percentage unit of dietary CP reduction, nitrogen excretion can be expected to decrease by 8 %, due to the lower amino acid deamination and, consequently, lower urea excretion in urine.

Similarly, Andretta et al. (2014) reported that nitrogen excretion was reduced by 8 % for each percentage unit of dietary CP reduction, for precision feeding in comparison with 3-phase feeding. By using predicted nitrogen balance data, we observed that total nitrogen excretion was reduced by 5 % for each percentage unit of dietary CP reduction (Table 2).

Life cycle impacts

The hypothesis for reducing the environmental impacts of piglet production (from 15 to 30 kg) through CP reduction was confirmed by our results for the categories AP, EP and LO, however this strategy increase the impact for GWP, CED and TE (Table 3).

Global warming potential, cumulative energy demand and terrestrial ecotoxicity

The increase in GWP impact due to the dietary CP reduction generally is observed in studies which LCI did not take into account the grain production from deforested areas. In a study considering different soybean production systems, Prudêncio da Silva et al. ( 2010) observed that CO2-eq. emissions were increased by about 47 % when protein sources came from recent deforested areas. Therefore, considering CO2-eq. emissions due to the effect of land use change as a consequence of rainforest conversion in crop areas (Prudêncio da Silva et al., 2010), IAA utilization could be an interesting strategy for reducing the environmental impact under this category (Kebreab et al., 2016;Monteiro et al., 2016).

However, it should also be considered that deforestation for soy production has reduced in the Amazon Biome in 2014 (Gibbs et al., 2015), moreover, several Brazilian

States produced soybean in non-deforested areas (Prudêncio da Silva et al., 2010).

Though, new legislations are needed to further reduce the deforestation for soy production, both in Amazon and Cerrado Biome. This justifies the use of soybean from non-deforested areas, in current and future evaluations of Brazilian scenarios.

As the dietary CP was reduced, an increase in CED was observed (Table 3).

According to Kebreab et al. (2016) the production of IAA and phytase demands high amounts of non-renewable energy. These authors also considered that the high non-Silva et al. ( 2014) reported a LO impact for soybean meal more than twice as high as for maize.

Validation by using predicted and observed data

The bayesian t-paired test indicated that InraPorc® utilization was efficient to predict feed intake and phosphorus excretion data, and to predict the impacts under CED, TE and LO, since predicted and observed data did not differed (0∈CIr; Table 4).

Regarding feed intake, the validation could be due to the software uses mathematical models that consider the animal growth as a dynamic phenomenon, which varies according to the nutritional supply (van Milgen et al., 2008).

For this variable, we have chosen modeling the ad libitum net energy intake as a gamma function of BW. However, different equations types (linear, power and exponential) are available for the user and ad libitum feed intake can be expressed on amount (kg) or energy basis (digestible, metabolizable or net), being the equation and the choice whether ad libitum intake is controlled, with important impact on model predictions (van Milgen et al., 2008;2015). If intake is assumed to be controlled by quantity, feeding a high-fat diet would result in a greater energy intake, and performance would then be higher for the high-fat diet (van Milguen et al., 2008).

Phosphorus excretion in InraPorc® software is estimated as the difference between intake and retained. The retention is estimated considering a fixed amount of phosphorus retained, for each kg of BWG [START_REF] Dourmad | Mathematical modelling of manure production by pig farms. Effect of feeding and housing conditions[END_REF], since retained amounts of phosphorus presented close values between studies [START_REF] Rymarz | Content and retention of calcium, phosphorus, potassium and sodium in the bodies of growing gilts[END_REF][START_REF] Rymarz | Chemical body composition of growing pigs. Ca, P, K, Na and Mg contents in the body[END_REF][START_REF] Jongbloed | Phosphorus in the feeding of pigs, effect of diet on the absorption and retention of phosphorus by growing pigs[END_REF][START_REF] Hendriks | Whole-body mineral composition of entire male and female pigs depositing protein at maximal rates[END_REF][START_REF] Mahan | Effect of initial breeding weight on macro-and micromineral composition over three-parity period using a high-producing genotype[END_REF][START_REF] Mahan | Macro-and micromineral composition of pigs from birth to 145 kilograms of body weight[END_REF]. Although predicted data were modeled as function of phosphorus retained, and observed data were obtained by fecal analysis, both values were statically similar (Table 4).

The validation between predicted and observed data for CED, TE and LO categories (Table 4), but not for GWP, AP and EP categories, could be due to the high contribution of feed production for the impact under these categories, and low contribution of animal housing and manure management. For CED, TE and LO, the impact reduction was almost exclusively associated with feed production, accounting for 70 % to 100 % of these impacts (Basset-Mens and van der Werf, 2005;[START_REF] Eriksson | Environmental systems analysis of pig productionthe impact of feed choice[END_REF]Garcia-Launay et al., 2014).

The GWP and EP impact categories, although they have not been validated, showed the same behavior between predicted and observed, which followed the same tendency as the dietary CP was reduced (Figure 2).

The validation of feed intake, but not of weight gain, could be related to the modelling approach used in these estimative. As before mentioned, net energy intake was modeled as a function of BW. The weight gain, however, was modeled from protein deposition (PD) potential. Potential PD is defined by a Gompertz function, parameterized by the initial body protein, mean PD and precocity [START_REF] Emmans | Models of pig growth: problems and proposed solutions[END_REF]van Milguen et al., 2008). This leads that predicted weight gain, from a constant net energy intake (variation from 1.20 to 1.21 kg of feed d -1 , which corresponds a net energy intake from 2941 to 2966 kcal d -1 ), did not differ between dietary CP levels, fact that did not occur with observed data (Figure 2).

Conclusions

Our predicted results indicated that the dietary CP reduction for piglets from 15 to 30 kg of BW, through the IAA supplementation, reduced the environmental impact under AP, EP and LO, considering a Brazilian context of pig production.

Predicted data for modelling the life cycle impact of piglet production from 15 to 30 kg did not reliably represent the categories GWP, AP and EP, in relation to the dietary CP reduction. However, they were statistically representative of the impact under CED, TE and LO. subjected to variance analysis using SAS. For global warming potential, the IAA addition did not appear to be an efficient strategy since the lowest impact (2.38 kg CO2eq. kg BWG -1 ) was obtained for noAA diet and the higher (2.51 kg CO2-eq. kg BWG -1 ) for lowCP diet. Similar effects were observed for cumulative energy demand and terrestrial ecotoxicity, which also increased by 9 and 8 %, respectively, with IAA addition. Conversely, acidification and eutrophication impacts were significantly (P<0.05) reduced by IAA addition, with values 11 and 13% lower than noAA for lowCP. Similarly, land occupation was reduced by 7 % moving from noAA to lowCP.

From the results it appears that global warming potential, energy demand and ecotoxicity depend mainly on the impacts of the feed ingredients, whereas acidification and eutrophication are highly dependent on nitrogen excretion.

Keywords: amino acids, excretion, nitrogen, swine

Introduction

The environmental impacts of pig production have come under increased debate in recent years, resulting in greater focus on identifying and mitigating the environmental degradation they may cause. The Conference of Parties (COP21) is a recent example of the global concern about environment, when stakeholders from many countries pledged to prepare strategies, plans and actions for mitigating greenhouse gas emissions (United Nations, 2015). Nationally, programs have been created aiming a low carbon economy, as Agricultura de Baixa Emissão de Carbono [START_REF] Brasil | Plano setorial de mitigação e de adaptação às mudanças climáticas para a consolidação de uma economia de baixa emissão de carbono na agricultura: Plano ABC (Agricultura de Baixa Emissão de Carbono)[END_REF].

For livestock, a strategic sector for several countries, the reduction of environmental impacts has been widely discussed. Among the main strategies, the better adjustment of nutrient supply to meet the requirements of animals may be a key factor in improving efficiency of nutrient retention, reducing excretion and consequently increasing the sustainability of pig production system (Dourmad and Jondreville, 2007).

In this sense, dietary crude protein (CP) reduction through industrial amino acids (IAA) addition could reduce nitrogen excretion by growing-finishing pigs (Andretta et al., 2014;Pomar et al., 2014) and seems to be an efficient strategy to reduce environmental impacts.

In recent years, life cycle assessment (LCA) has been widely used in agriculture (Guinée et al., 2002) and several studies of swine production chains have been conducted as reviewed by McAuliffe et al. (2016). This method has the advantage of evaluate the impact of pig production during its whole life-cycle, from the feedstuffs impacts to manure management impacts (McAuliffe et al., 2016). The aim of this study was to evaluate the environmental impact of pig fattening, based on LCA methodology, comparing different levels of IAA inclusions.

Material and Methods

Goal and scope definition

The definition of system and subsystem boundaries was derived from Nguyen et al. (2010), and is described in Figure 1. The LCA considered the activity of pig fattening in South Brazil, including crop production, grain drying and processing, production and transport of feed ingredients, feed production at the feed factory, transport of the feed to the farm, growing to finishing pig production, and manure storage, transport and spreading (Figure 1). Impacts were calculated at the farm gate and the functional unit considered was one kg of body weight gain (BWG) over the fattening period. The pig production system considered was a conventional growingfinishing pig farms with indoor raising of animals on slated floor and collection and storage of manure as liquid slurry. Animals were gilts and barrows (50/50) supposed to be fed separately.

Life cycle inventory (LCI)

Resource use and emissions associated with the production and delivery of inputs for crop production (fertilizers, pesticides, tractor fuel and agricultural machinery) came from the Ecoinvent database version 3 (SimaPro LCA software 8.0, PRé Consultants). Energy use in the building for light, heating and ventilation was considered, but not the emissions and resources used for the construction of buildings, neither the land occupied by the buildings. Veterinary medicines and hygiene products were also not included, as proposed by Garcia-Launay et al. (2014). The assessment considered the growing-finishing pig production system, in a four phases feeding 

Crop production

We assumed that soybean was produced in Southern Brazil, and that 54% of the wheat bran came from Argentina (MDIC, 2015), the other part being produced in the country. The LCI came from Alvarenga et al. (2012) for maize, and from Prudêncio da Silva et al. ( 2010) for soybean. To perform the LCI of wheat, we used data from government agencies and cooperatives to determine the mean input and output values for each production system in Brazil and Argentina. For the grain-drying and storage stage, we used data from Marques (2006). For the feed ingredients that are co-products, i.e. soybean meal, soybean oil and wheat bran, the resource use and emissions were economically allocated, following the suggestion of Ramirez (2009).

Non-plant feed components

Data for phytase, salt, phosphate, sodium bicarbonate and limestone used in the diet came from [START_REF] Wilfart | LCIA results of feedstuffs for French livestock[END_REF]. The premix was assumed to contain mainly limestone and to have the same impacts (Garcia-Launay et al., 2014). Impacts associated with the production of IAA were based on Mosnier et al. (2011). Meat and bone meal was assumed to come from poultry slaughter process. Impacts associated energy, standardized ileal digestible (SID) amino acids and digestible phosphorus.

Feeds A and B differed in their amino acid and phosphorus concentrations, with feed A being formulated with a high nutrient density to meet 110 % of the mean estimated nutrient requirements at the beginning of the growing period, and feed B formulated with a low nutrient density to meet the mean estimated nutrient requirements at the end of the finishing period (Table 2). Feeds A and B were blended in a four-phases feeding program and taking into account the changes in SID-lysine requirement along the pig's growth. The feed production process at the feed factory was included in the inventory, considering that it would be held in the pig production region, according to Garcia-

Launay et al. (2014).

Pig production

For pig production, because variability between animals is known to affect the response of pig populations [START_REF] Pomar | Modeling stochasticity: Dealing with populations rather than individual pigs[END_REF]Brossard et al., 2014), we decided to use the population version of InraPorc® [START_REF] Vautier | Accounting for variability among individual pigs in deterministic growth models[END_REF] to evaluate the animals' response to the feeding strategies. Parameters for growth and feed intake profiles were thus defined for a population of 1000 barrows and 1000 gilts, according to the method developed by [START_REF] Vautier | Accounting for variability among individual pigs in deterministic growth models[END_REF] using a variance-covariance matrix. Simulations for 2000 pigs (50 % females, 50 % castrated males) were performed for each IAA scenario, in order to determine animal performance, nutrient balance and excretion according to InraPorc®.

Manure management

The environmental consequences of manure utilization were evaluated using system expansion as described by Nguyen et al. (2010). This approach is often used to provide credit for avoided emissions, as explained by [START_REF] Macleod | Greenhouse gas emissions from pig and chicken supply chains[END_REF]. Thus, manure produced was assumed to substitute a certain amount of mineral fertilizers, by using a mineral fertilizer equivalency (MFE, %). We assumed that the MFE was 75 % of total nitrogen in manure (Nguyen et al., 2010), with 5 % extra loss as nitrates compared to mineral fertilizers (Garcia-Launay et al., 2014), and MFE was 100 % for phosphorus (Sommer et al., 2008).

Life cycle impact assessment

Emissions from pig production

Emissions to air during swine production were estimated step-by-step for NH3, N2O, NOx and CH4. The CH4 emissions from enteric fermentations were calculated according to feed digestible fiber content using equations from Rigolot et al. (2010a).

The CH4 emissions from manure storage were calculated according to IPCC (2006) and Rigolot et al. (2010b) considering the average annual ambient temperature (22°C as the mean for South Brazil). The NH3 emissions from the building and during manure storage were calculated according to emission factors proposed by Rigolot et al. (2010b), considering the effect of temperature. The N2O and NOx emissions from slurry storage were calculated according to IPCC (2006) and Dämmgen and Hutchings (2008), respectively.

The amounts of nitrogen, P, Cu, Zn, K and organic matter excreted by the pigs were obtained from InraPorc® simulations. These data were used to calculate the amount of each element available at field application. During field application, NH3 emissions were based on [START_REF] Andersen | Ammoniakemission fra landbruget siden midten af 80'erne. Faglig rapport fra DMU[END_REF]), N2O emissions on IPCC (2006) and NOx emissions on Nemecek and Kägi (2007). The potential of NO3 and PO4 leaching came from [START_REF] Nguyen | Environmental assessment of Danish pork[END_REF].

(12.8. kg -1 BWG; Table 4). Main processes contributing to CED impacts (Figure 2)

were feed production (94 %) and animal housing (13 %).

Acidification potential and eutrophication potential

The highest AP impacts among the AA inclusion scenarios were observed for noAA (64.3 g SO2-eq. kg -1 BWG), and the lowest impact (57.0 g SO2-eq. kg -1 BWG)

for lowCP (Table 4). Feed production had the highest contribution (Figure 2) to AP (53 %), followed by animal housing (31 %).

For EP, the highest (P<0.05) impacts among IAA inclusion scenarios were observed for noAA scenario (19.1 g PO4-eq. kg -1 BWG), and the lowest for lowCP scenario (16.6 g PO4-eq. kg -1 BWG; Table 4). Feed production had the highest contribution to EP (64 %), followed by animal housing (23 %; Figure 2).

Terrestrial ecotoxicity and land occupation

The highest (P<0.05) TE impacts among the IAA inclusion scenarios were observed for lowCP (9.53 g 1,4-DCB-eq. kg -1 BWG) and the lowest for noAA (8.77 g 1,4-DCB-eq. kg -1 BWG; Table 4). Feed production had the highest contribution to TE (70 %), followed by manure management (30 %), while animal housing did not contribute to TE (Figure 2).

Conversely, the highest (P<0.05) LO impact among the AA inclusion scenarios were observed for the noAA inclusion scenario (2.60 m 2 •year kg -1 BWG) and the lowest for lowCP (2.42 m 2 •year kg -1 BWG; Table 4). Taking into account that the LCI did not consider the land used by the buildings, feed production was almost the only contributor process to land occupation (Figure 2). levels of use of chemical and organic fertilizers, pesticides and machinery, distances for transportation of inputs and yield levels, as well as different levels of land occupation and land transformation. They found that CO2-eq. emissions increased by about 47 % when the protein sources came from deforested areas.

The CED tended to increase with the incorporation of IAA (Table 4). One reason for this result was the shorter distance of soybean transport when it came from South, while the IAA (except L-lysine) had to be imported and had a high CED impact.

Another reason was the high energy demand for IAA production. Garcia-Launay et al.

(2014) estimated that the CED impact for soybean production and transport from Brazil

to France was about 12 MJ, while for L-lysine and L-tryptophan the CED were 119 and 237 MJ, respectively. In agreement, Kebreab et al. (2016) reported that the higher CED impact in IAA supplemented diets in pig production systems was due to greater nonrenewable energy use in the production of IAA.

Acidification and eutrophication potential impacts

Since both nitrogen and phosphorus contribute to eutrophication, and nitrogen contributes to acidification by ammonia emissions (Guinée et al., 2002), the AP and EP impacts were often reduced by the incorporation of IAA (Table 4). This was not surprising because this strategy reduced nitrogen and phosphorus excretion (Table 3) and, consequently, also reduced the NH3 emissions from animal housing and manure management, and field application. These results were consistent with those reported by Garcia-Launay et al. (2014), who found that the reduction of dietary protein content decreased the AP impact by about 5 % and the EP impact by about 3 %, for each percentage unit of CP content, and by Ogino et al. (2013), who reported that AP and EP were reduced by about 2 and 9 %, respectively, for each percentage unit of CP content reduction.

Terrestrial ecotoxicity and land occupation

The incorporation of IAA increased TE impact. This was due to the lower TE impact of protein sources, which we hypothesized that came from no deforested areas.

According to Prudêncio da Silva et al. ( 2014), protein sources from recent deforested areas showed TE impact 36 % higher. For this reason, Garcia-Launay et al. (2014) found a TE reduction of about 20 % when moving the formulation scenarios from noAA to lowCP, due to the authors considered that 70 % of protein rich ingredient was originated from recently deforested areas.

The improvement of LO through IAA inclusion was a result of lower soybean inclusion in the diets, since this crop occupies the land for longer periods. Thus, formulations with IAA allowed more maize inclusion, with lower LO impact than soybean meal. Indeed, Prudêncio da Silva et al. ( 2014) reported a LO of soybean meal more than twice than maize in a Brazilian grain production.

Conclusions

The results of this study indicate that global warming potential, energy demand and ecotoxicity impacts depend mainly on the impacts of the feed ingredients, as consequence of production, manufacturing and transport of feedstuffs, whereas acidification and eutrophication are highly dependent on nitrogen and phosphorus excretion, being largely reduced by IAA addition. Furthermore, LCA is a promising subject to be explored in Brazilians conditions. De maneira geral, quando as fontes proteicas não são associadas ao processo de desmatamento, a redução da proteína bruta da dieta, por meio da utilização de aminoácidos industriais, reduziu o impacto sobre a acidificação, eutrofização e ocupação de terra, o que demonstra que o desempenho ambiental da suinocultura, para estas categorias, pode ser melhorado por meio da redução da proteína bruta da dieta. Entretanto, a utilização de dados experimentais demonstrou que nem sempre esta redução do impacto é significativa, devido ao efeito da variabilidade entre os animais, que foi levada em conta neste estudo.

Com relação à representatividade de dados de desempenho e excreção estimados com os observados experimentalmente, foi validada a sua utilização para as categorias demanda acumulada de energia, ecotoxicidade e ocupação de terra. No entanto, o crescimento animal é um fenômeno complexo, dirigido pela regulação combinada da ingestão de alimentos e da utilização de nutrientes, portanto, a maioria dos modelos que descrevem o crescimento de suínos não tem a habilidade de predizer o desempenho em um sentido absoluto.

Como perspectivas, a avaliação de estratégias nutricionais e de alimentação como forma de reduzir o impacto do ciclo de vida da produção de suínos apresenta tendência de aplicação em diferentes contextos produtivos, ou seja, avaliar o comportamento destas estratégias em diferentes regiões/países produtores(as).

Tabela 1 .

 1 Figura 1. Dinâmica de expansão do consumo mundial de carnes e do consumo mundial

  Figura 4. Diferentes cenários de produção de nitrogênio reativo (A) e o impacto de cada

  Figura 6. Visão global do metabolismo proteico (adaptado deNelson & Cox, 2014). .. 13 

  . ..................................................................................... 25

  Figura 1. System boundaries of starting pig production in South Brazil, from 15 to 30 kg, with main processes for the production of crop inputs, crop production, production of feed ingredients and feeds, and pig production .........................71 Figura 2. Relative contribution of the different processes (%) to impacts on global warming potential (GWP), acidification potential (AP), eutrophication potential (EP), cumulative energy demand (CED), terrestrial ecotoxicity (TE) and land occupation (LO). ................................................................................72

Figura 5 .

 5 Figura 5. Consumo, utilização e perdas de nitrogênio por suínos aos 152 kg, consumindo dieta com 12% de proteína bruta e 13,32 MJ/kg de energia metabolizável (elaborado a partirde Galassi et al., 2010).

Figura 6 .

 6 Figura 6. Visão global do metabolismo proteico (adaptado de Nelson & Cox, 2014).

  De acordo comDourmad et al. (1999), as emissões de NH3 variam de acordo com o estágio fisiológico dos suínos, com maiores valores para porcas em lactação (27,3 g NH3/dia), seguido de porcas gestantes (15,9 g NH3/dia), suínos em terminação (11,4 g NH3/dia) e leitões desmamados (4,26 g NH3/dia). De maneira geral, muitos estudos antigos e atuais confirmaram que dietas com baixos níveis de PB, balanceadas quanto ao seu conteúdo de AA essenciais para suínos, resultam na redução da excreção de N (Figura 7) sem influenciar o consumo de ração, ganho médio diário e conversão alimentar(Dourmad & Jondreville, 2007). -■-Monteiro et al. (2016) -□-Andretta et al. (2016) --■--Monteiro et al. (2015) --□--Andretta et al. (2014) -•-Pomar et al. (2014) -○-Nørgaard et al. (2014) --•--Bunger et al. (2014) --○--Toledo et al. (2014) -▲-Ball et al. (2013) -∆-Gallo et al. (2013) --▲--Galassi et al. (2010) --∆--Hernandez et al. (2011) -♦-Portejoie et al. (2004) -◊-Shriver et al. (2003) --♦--Oliveira et al. (2005) --◊--Figueroa et al. (2000)

Figura 8 .

 8 Figura 8. Relação entre os elementos de uma análise do ciclo de vida(ISO, 2006).

  de energia e compostagem. De acordo com cada etapa produtiva, os autores observaram que a produção de ração contribui com 17,6 a 99,5% de todas as categorias de impacto ambiental, enquanto que a etapa de abate assume, comparativamente, proporções quase insignificantes (Figura 10-A).O impacto sobre o potencial de aquecimento global foi maior para a compostagem (3552 kg CO2-eq) seguida do manejo de dejetos líquidos armazenados em tanques (3503 kg CO2-eq), conforme apresentado na Figura 10-B. Para acidificação, o menor valor ficou para o manejo de dejetos líquidos armazenados em tanques (76,1 kg SO2-eq). Com relação à demanda cumulativa de energia, o menor valor foi obtido com o biodigestor para fins de geração de energia (20,0 MJ). Comparativamente, a ACV indicou que a utilização do biodigestor para fins de geração de energia apresentou o

  do ciclo de vida e proteína bruta na dietaComo a produção de rações é a etapa que mais contribui com o impacto do ciclo de vida da produção de suínos (van derWerf et al., 2005), vários trabalhos avaliaram diferentes estratégias de alimentação sobre o impacto deste setor produtivo. Entretanto, a redução do conteúdo de proteína bruta na dieta de suínos é um dos temas mais abordados (Tabela 4).

Tabela 4 .

 4 Impacto de diferentes estratégias de alimentação e nutrição sobre o pontecial de aquecimento global (PAG), potencial de eutrofização (EU) e potencial de acidificação (AC) decorrentes de diferentes sistemas de produção de suínos.

  metionina em dietas para aves e suínos, utilizando a ACV, foram avaliadas porMosnier et al. (2011). Foram avaliadas dietas para as fases de crescimento e terminação (70 aos 180 dias) nos seguintes cenários: (i) única fase sem incorporação dos três AAI; (ii) duas fases sem incorporação de AAI; (iii) duas fases contendo 16,5% e 15,0% de PB, respectivamente, e incorporação de AAI; (iv) duas fases sem restrição do nível de PB e incorporação dos três AAI. Outras duas formulações adicionais foram elaboradas para maximizar a incorporação dos três AAI e minimizar a emissão de gases de efeito estufa.Os autores supracitados observaram que nas dietas baseadas em cereais associados ao desmatamento, a incorporação de AAI reduziu o impacto na categoria aquecimento global. Entretanto, este efeito não foi observado quando se utilizou grãos que não eram associados a este processo. De maneira geral, independentemente dos ingredientes bases utilizados na dieta, a incorporação de AAI reduziu o impacto das dietas nas categorias potencial de eutrofização, ecotoxicidade terrestre e demanda cumulativa de energia. As dietas formuladas para mínima emissão de gases de efeito estufa tiveram os menores valores para aquecimento global e demanda cumulativa de energia, porém, o mesmo não foi observado para as outras categorias de impacto.Resultado similar foi observado porGarcia-Launay et al. (2014), que avaliaram o impacto de diferentes modalidades de incorporação de AAI em dietas para suínos por meio da ACV. Os autores avaliaram duas modalidades de manejo de dejetos (líquido e sólido), duas hipóteses de fontes de proteína (apenas farelo de soja versus farelo de soja, ervilha e farelo de canola) e fontes proteicas associadas ou não ao processo de desmatamento. Para os animais em crescimento e terminação, três programas nutricionais foram considerados: uma fase, duas fases e multi fases. Os cenários de formulação foram os seguintes: formulação sem inclusão de AAI, formulação com adição de AAI e conteúdo de PB fixo, adição de AAI e redução do conteúdo de PB.Para as dietas baseadas apenas em farelo de soja, os menores impactos com relação ao aquecimento global, potencial de acidificação e potencial de eutrofização foram para o programa alimentar multi fases com dietas com redução do nível de PB.

Figura 11 .

 11 Figura 11. Análise do ciclo de vida da produção de dietas (A) sem a inclusão de aminoácidos industriais (Sem AA), com aminoácidos industriais (Com AA) e com aminoácidos e redução do nível de proteína bruta (Baixa PB), e da produção de suínos (B).

(

  CP) levels. In Trial I (performance), 28 crossbred barrow piglets, with an initial average weight of 15.3 ± 1.15 kg were divided up in a randomized block design with four treatments, seven replications and one animal per experimental unit. In Trial II (nitrogen and phosphorus balance), 20 crossbred barrow piglets with an average weight of 21.4 ± 1.62 kg were divided up in a randomized block design with four treatments, five replications and one animal per experimental unit. Four experimental feeds were evaluated: 19.24, 18.24, 17.24 and 16.24% of CP, meeting the requirements of SID amino acids through industrial amino acid (IAA) addition. From Trial I and II data, the environmental impact was calculated for global warming potential, acidification potential, eutrophication potential, cumulative energy demand, terrestrial ecotoxicity and land occupation (LO). Total nitrogen excretion decreased by 0.238 g d -1

Figure 1 -

 1 Figure 1 -System boundaries of starting pig production in South Brazil, from 15 to 30

Figure 2 -

 2 Figure 2 -Relative contribution of the different processes (%) to impacts on global warming potential (GWP), acidification potential (AP), eutrophication potential (EP), cumulative energy demand (CED), terrestrial ecotoxicity (TE) and land occupation (LO).

Figure 1 -

 1 Figure 1 -System boundaries of starting pig production in South Brazil, from 15 to 30

Figure 2 -

 2 Figure 2 -Predicted (continuous line with triangle) and observed (continuous line with circles) data for the average daily gain (predicted = 0.7009 + 0.0017*CP; observed = 0.7675 -0.0021*CP), nitrogen excreted (predicted = -8.1188 + 1.12*CP; observed = 0.1549 + 0.7426*CP), global warming potential (predicted = 1.6755 -0.0077*CP; observed = 1.836 -0.004*CP) and eutrophication potential (predicted = 7.7614 + 0.1843*CP; observed = 5.1256 + 0.31*CP). Trend line: dotted line.

Figure 1 -

 1 Figure 1 -System boundaries of growing-finishing pig production in South Brazil, from 30 to 115 kg, with main processes for the production of crop inputs, crop production, production of feed ingredients and feeds, and pig production.

Figure 2 -

 2 Figure 2 -Relative contribution of the different processes (%) to impacts on global warming potential (GWP), acidification potential (AP), eutrophication potential (EP), cumulative energy demand (CED), terrestrial ecotoxicity (TE) and land occupation (LO)

  

  

  , que foi 8% inferior na dieta com 16,24% de PB, comparada à dieta com 19,24% de PB. No segundo trabalho, a ACV foi calculada a partir de dados de desempenho e excreção de nutrientes estimados a partir do software InraPorc®. Os tratamentos consistiram-se das mesmas dietas experimentais utilizadas no primeiro trabalho. O desempenho e a excreção dos suínos, dos 15 aos 30 kg, foi simulada em cada um dos níveis de PB, utilizando-se o modelo InraPorc®. Os dados estimados e observados foram comparados de forma pareada, por meio da análise bayesiana. Houve redução na excreção de nitrogênio e fósforo em 15% e 21%, respectivamente, ao passar da dieta com maior nível de PB, comparada com a de menor nível. Da mesma forma, observou-se redução de 4% no impacto sobre AC e EU, e de 8% sobre a OT, using paired t-test through Bayesian analysis. The nitrogen and phosphorus excretion were reduced by 15 and 21%, respectively, moving from high CP level diet to low CP diet. In the same way, AC and EU were reduced by 4% and LO by 8%, comparing 19.24% CP diet with 16.24% CP diet. However, the impact under GWP,

	CED and TE increased with the dietary CP reduction. Bayesian analysis showed
	similiratity (0∉CIr) between estimated and observed data for feed intake, phosphorus
	excreted, and the categories CED, TE and LO. In the thirdy study, the LCA
	methodology was applied to growing-finishing pigs. A virtual population of 1000 gilts
	and 1000 barrows was created, from growing and feed intake parameters obtained in
	previous trials. Three feed formulations were evaluated: without industrial amino acids
	cujo impacto aumentou 9 e 8%, respectivamente, ao passar de uma dieta SemAA para 05) for
	uma dieta BaixaPB. Contrariamente, os valores de AC e EU foram significativamente GWP, AC, EP, CED and TE. For LO category, a reduction (P=0.078) was observed in
	reduzidos em 11 e 13%, respectivamente, no cenário BaixaPB. Da mesma forma, o reducing the impact through dietary CP reduction, which was 8% lower in 16.24% CP
	impacto sobre OT foi reduzido em quase 7% quando se aumentou a incorporação de diet, in relation to 19.24% CP diet. In the second study, the LCA was performed from
	aminoácidos na dieta. Conclui-se que a redução dos níveis proteicos da dieta foi

Entretanto, não se observou diferenças (P>0,05) para as variáveis PAG, AC, EU, DAE e ECO. Para a categoria OT, observou-se uma redução (P=0,078) do impacto com a diminuição do conteúdo de PB xviii da dietacomparando a dieta de 19,24 com a de 16,24% de PB. Entretanto o impacto sobre as variáveis PAG, DAE e ECO aumentou à medida que o conteúdo de PB foi reduzido. A análise bayesiana indicou similaridade (0∉ICr) entre observado e estimado para os dados de consumo de ração, fósforo excretado, e as categorias de impacto DAE, ECO e OT. No terceiro trabalho, a metodologia de ACV foi aplicada para animais nas fases de crescimento e terminação. Foi criada uma população virtual de 1000 fêmeas e 1000 machos castrados, a partir de parâmetros de crescimento e consumo de ração obtidos em experimentos previamente realizados. Três formulações foram avaliadas: dieta sem aminoácidos industriais (SemAA); com utilização de aminoácidos e nível mínimo de PB (ComAA); e com inclusão de aminoácidos e sem nível mínimo de PB (Baixa PB). O desempenho e a excreção dos suínos, dos 30 aos 115 kg, foi simulada em cada um dos cenários de utilização de aminoácidos, utilizando-se o modelo InraPorc® população, levando-se em conta a variabilidade entre os animais. Houve redução na excreção de nitrogênio à medida que foram incorporados aminoácidos às dietas. Entretanto, houve aumento do impacto sobre a categoria PAG, cujo menor valor foi observado para dietas SemAA (2,38 kg CO2-eq.). O mesmo foi observado para as categorias DAE e ECO, eficiente para diminuir a excreção total de nitrogênio, tanto experimentalmente, quanto por meio de simulação computacional. Entretanto, para variáveis de impacto ambiental modeladas por meio da ACV, esta redução trouxe benefícios ambientais para a OT xix (dados observados experimentalmente). Para os dados estimados, a redução da PB da dieta reduz o impacto sobre as variáveis dependentes da excreção de nitrogênio, como AC e EU, e estes dados estimados são similares ao observado para as categorias de impacto DAE, ECO e OT.

Palavras-chave: emissão de carbono, meio ambiente, modelagem, nitrogênio.

ABSTRACT

The objective of this study was to calculate the environmental impact of pig production, fed different dietary crude protein (CP) levels, through life cycle assessment (LCA), and confront estimated data and observed data, used as inputs and outputs of LCA, through Bayesian approach. In the first study, two trials were conducted. In the Trial I (growth performance from 15 to 30 kg), 28 barrows piglets with 15.3±1.5 kg were distributed in a randomized block design with four treatments, seven replicates and one animal per experimental unit. In the Trial II (nitrogen and phosphorus balance from 15 to 30 kg), 20 barrows piglets with 21.4±1.6 kg were distributed in a randomized block design with four treatments, five replicates and one animal per experimental unit. The treatments consisted of four diets, in which the CP content was increasingly reduced in one percentual point

(19.24; 18.24; 17

.24 e 16.24%), being the digestible amino acid requirements met by adding L-lysine, DL-methionine, L-threonine, L-tryptophan, Lvaline and L-isoleucine. From Trials I and II data, the LCA of piglet production was calculated for global warming potential (GWP), acidification potential (AC), eutrophication potential (EU), cumulative energy demand (CED), terrestrial ecotocicity (TE) and land occupation (LO). The nitrogen and phosphorus excretion were reduced by dietary CP reduction. Total nitrogen excreted was reduced by 0.238 g/d for each 1g of reduction in daily nitrogen intake. However, no effect was observed (P>0.performance and nutrient excretion data estimated by InraPorc® software. Treatments were the same as first study. Growth performance and nutrient excretion, from 15 to 30 kg, were simulated for each CP level, by using InraPorc®. Estimated and observed data xxi were compared by (noAA) diet, with industrial amino acids and minimum crude protein (CP) content (withAA), and with industrial amino acids without CP constraint (lowCP). Performance and excretion of pigs, from 30 to 115 kg, were simulated for each amino acid utilization scenario, using InraPorc® population model, considering between-animal variability.

  técnicos para iniciar esta atividade, como tratamento dos efluentes antes da aplicação no solo (estabilização) como adubo, sendo que a dose aplicada deve ser calculada com base nos teores de nutrientes presentes nestes resíduos, além das necessidades das culturas(FEPAM, 2007). Já a Fundação do Meio Ambiente

	do Estado de Santa Catarina (FATMA) estabelece a quantidade máxima de dejetos para
	a utilização em lavouras de 5 L/m 2 /ano e, ainda, que a aplicação siga as recomendações
	de adubação indicadas por laudo com base na análise do solo (FATMA, 2000).
	Para o Instituto Ambiental do Paraná (IAP), o interessado em iniciar a atividade
	suinícola deve possuir área agrícola disponível e com aptidão para disposição dos
	dejetos no solo. É necessário calcular a taxa de aplicação destes resíduos em função das

contribuição atingiu 23% do Produto Interno Bruto (PIB) nacional em 2015, ante 21,4% em 2014

[START_REF] Cna | Confederação da Agricultura e Pecuária do Brasil. Balanço 2016 e perspectivas[END_REF]

. Além disso, enquanto o PIB total nacional retraiu 3,8% em 2015, o do agronegócio cresceu 1,8%, em relação a 2014

(IBGE, 2016)

. De acordo com o IBGE (2016), esse crescimento se deve ao desempenho da agricultura, com destaque para as lavouras de soja (crescimento de 11,9%) e milho (7,3%). Na pecuária, destacouse o abate de aves (crescimento de 3,8%) e suínos (5,3%).

Com relação à contribuição da suinocultura, a produção de carne suína no Brasil foi de 3.643 mil toneladas em 2015, mantendo o país no posto de quarto maior produtor mundial

(ABPA, 2016)

. Nos últimos anos, a atividade vem se expandido em regiões do centro-oeste, entretanto, o maior polo produtor ainda é a região sul do país, cuja contribuição ultrapassa 50% do montante nacional

(FIESP, 2014)

.

A carne suína representa mais de 36% do consumo mundial de carnes

(FAO, 2014)

, mas estima-se um aumento para até 143 milhões de toneladas em 2050

(Alexandratos & Bruinsma, 2012)

. A importância econômica da suinocultura, bem como a pressão de órgãos ambientais e da sociedade para que ocorra redução da concentração de nutrientes excretada, têm estimulado a busca por tecnologias de desenvolvimento limpo, principalmente devido ao modelo de produção atual, que concentra grande número de suínos em áreas reduzidas, o que aumenta ainda mais os riscos de contaminação ambiental.

A região Sul do Brasil abriga a maior concentração de suínos do país, o que preocupa as autoridades ambientais com relação às exigências para o licenciamento de novos empreendimentos destinados à suinocultura. No caso do Estado do Rio Grande do Sul, a Fundação Estadual de Proteção Ambiental (FEPAM) exige que sejam seguidos alguns critérios características do dejeto, da análise de fertilidade e granulométrica do solo e da recomendação de adubação para as culturas utilizadas. A Instrução Normativa do IAP considera como elementos limitantes para o uso agrícola dos dejetos o teor de nitrogênio (N) e de fósforo, e estabelece valores máximos de metais pesados nos dejetos para aplicação, que são de 2.500 e 1.000 mg por kg de matéria seca de dejeto para o zinco (Zn) e cobre (Cu), respectivamente

(IAP, 2009)

.

  Tabela 2. Principais categorias de impacto usadas na análise de ciclo de vida

	Categoria de impacto	Escala	Exemplos de impactos de ciclo de vida (ICV)	Descrição do fator de caracterização
	Aquecimento	Global	Emissões de gases de efeito estufa	Converte os dados de ICV em
	global		no ar, como dióxido de carbono	dióxido de carbono equivalente (kg
			(CO2), dióxido de nitrogênio	de CO2-eq.). O potencial de
			(NO2),	metano	(CH4),	aquecimento global pode ser
			clorofluorcarbono	(CFC),	expresso em um horizonte de 50,
			hidroclorofluorcarbono (HCFC) e	100 ou 500 anos
			metil bromide (CH3Br)	
	Depleção da	Global	Emissões	de	origem	Converte os dados de ICV em
	camada de ozônio		antropogênica,			como	triclorofluorometano equivalentes
			clorofluorcarbono	(CFC),	(kg de CFC-11-eq.)
			hidroclorofluorcarbono (HCFC) e
			metil bromide (CH3Br)	
	Acidificação	Regional	Emissão	de	substâncias	Converte os dados de ICV em
		Local	acidificantes ao ar, como óxido de	dióxido de enxofre equivalente
			enxofre	(SOx),	óxido	de	(SO2-eq.)
			nitrogênio (NOx), ácido clorídrico
			(HCl), ácido fluorídrico (HF) e
			amônia (NH4)		
	Eutrofização	Local	Emissão de macronutrientes,	Converte os dados de ICV em
			principalmente	fósforo		e	fosfato equivalentes (PO4-eq.)
			nitrogênio, no ar, água e solo,
			como fosfato (PO4), óxido de
			nitrogênio (NO), dióxido de
			nitrogênio (NO2), nitratos e
			amônia (NH4)		
	Ecotoxicidade	Local	Emissão de substâncias tóxicas ao	Converte os dados de ICV em
	terrestre		ecossistema terrestre como cobre,	diclorobenzeno equivalentes (kg
			zinco e selênio			1,4-diclorobenzeno-eq.)
	Ecotoxicidade	Local	Emissão de substâncias tóxicas ao	Converte os dados de ICV em
	aquática		ecossistema aquático		diclorobenzeno equivalentes (kg
							1,4-diclorobenzeno-eq.)
	Depleção de	Global	Extração de minerais e utilização	Converte os dados de ICV em um
	recursos	Regional	de combustíveis fósseis		índice que quantifica os recursos
		Local					usados versus a quantidade de
							recuros restantes em reservas.
							Expressa os dados em antimônio
							equivalente (kg de antimônio-eq.)
	Uso da terra	Global	Todas as modificações geradas	Converte a massa de resíduos
		Regional	pelo uso da terra			sólidos em volume usando uma
		Local					estimativa da densidade. Expressa
							os valores em m 2 (m 2 /ano)
	Uso da água	Regional	Todo o consumo e utilização de	Converte os dados de ICV em um
		Local	água				índice que quantifica a água
							utilizada versus a quantidade de
							recursos restantes em reservas
	(EPA, 2006; Guinée et al., 2002)				

  suinocultura é um setor altamente complexo, que envolve a produção de fertilizantes e pesticidas para a produção de grãos, transformação da terra, transporte de

matérias-primas e do produto final, energia e calor, água para o consumo animal, limpeza das instalações e abate e manejo dos resíduos e dejetos

(McAuliffe et al., 2016)

.

Vários estudos utilizaram a metodologia de ACV para estimar o impacto ambiental da produção de suínos na Europa

(Basset-Mens and van der Werf, 2005;[START_REF] De Vries | Life Cycle Assessment of Segregating Fattening Pig Urine and Feces Compared to Conventional Liquid Manure Management[END_REF][START_REF] Dourmad | The optimum dietary amino acid pattern for growing pigs: 2. Requirements for maintenance and for tissue protein accretion[END_REF] Garcia-Launay et al., 2014)

, Ásia

(Ogino et al., 2013) 

e América do Norte

[START_REF] Pelletier | Life cycle assessment of highand low-profitability commodity and deep-bedded niche swine production systems in the Upper Midwestern United States[END_REF][START_REF] Mackenzie | Accounting for uncertainty in the quantification of the environmental impacts of Canadian pig farming systems[END_REF] Mackenzie et al., , 2016))

. No Brasil, a utilização da ACV ainda é recente e são poucos os trabalhos encontrados. Essa metodologia foi utilizada na avaliação da produção de soja em diferentes cenários de produção e transporte (Prudêncio da Silva et al., 2010), na produção de frangos de corte

(Alvarenga et al., 2012; Prudêncio da Silva et al., 2014) 

e na produção de suínos em diferentes métodos de manejo de dejetos

(Cherubini et al., 2015)

. Porém, o impacto da nutrição de suínos sobre a ACV ainda é pouco abordado

(Monteiro et al., 2016)

.

Entre as principais etapas produtivas que influenciam o impacto ambiental da produção de suínos, pode-se citar (i) a produção de rações, (ii) o alojamento, (iii) o manejo de dejetos e (iv) o abate. Entretanto, quando a pesquisa refere-se ao impacto da nutrição ou alimentação, a etapa de abate geralmente é descartada

(Garcia-Launay et al., 2014; Monteiro et al., 2016)

, devido o baixo impacto que representa dentro do sistema produtivo

(Cherubini et al., 2015)

.

5.6.1. Produção de rações

Na produção intensiva de suínos, os animais são geralmente alimentados com dietas ricas em proteína e energia, que contribui significativamente com o impacto ambiental da cadeia suinícola

(Basset-Mens & van Der Werf, 2005; de Vries & de Boer, 

  Produção em áreas desmatadas nos últimos 100 anos (DE) e em áreas desmatadas há mais de 100 anos (ND). Dados adaptados de Prudêncio da Silva et al. (2014).

						OT	DAE
						(m²•ano)	(MJ)
	Milho -DE	0.81	4.8	11.5	2.0	0.8	4.20
	Milho -ND	0.39	5.1	14.5	2.1	0.8	3.53
	Soja -DE	1.70	5.5	4.2	3.9	1.6	9.40
	Soja -ND	0.39	5.6	2.4	2.5	1.8	5.86
	Óleo de soja -DE	3.69	12.1	9.2	8.5	3.6	19.57
	Óleo de soja -ND	0.79	12.4	5.2	5.3	3.9	11.70
	Fosfato bicálcico	1.25	13.2	25.2	6.3	0.3	14.58
	Sal	0.20	0.2	2.1	0.0	0.0	2.93
	Premix	0.64	4.4	2.6	2.3	1.0	9.05
	Calcário	0.04	0.0	0.2	0.1	0.0	0.76
	Bicarbonato de Na	1.09	3.3	4.3	7.3	0.0	20.03

PAG, potencial de aquecimento global; EU, potencial de eutrofização; AC, potencial de acidificação; ECO, ecotoxicidade terrestre; OT, ocupação de terra; DAE, demanda acumulada de energia.

  são recentes, demonstrando ser uma linha com grande potencial para ser explorada nas condições nacionais, principalmente levando-se em consideração que o país é o quarto maior produtor de carne suína, com 3.643 mil toneladas produzidas em 2015(ABPA, 2016), e que o governo brasileiro tem investido em programas de desenvolvimento limpo na suinocultura.Outro ponto referente a estes trabalhos é que, até o momento, apenas uma publicação levou em conta a variabilidade existente entre os animais(Monteiro et al., 2016). A variabilidade pode afetar tanto o desempenho, como as exigências nutricionais(Brossard et al., 2014), influenciando, consequentemente, a excreção de nutrientes e a emissão de gases. Além disso, geralmente os dados de entradas e saídas de uma ACV são valores médios obtidos a partir de dados da agroindústria. Isso faz com que várias incertezas estejam atreladas aos dados, principalmente na produção animal, devido à grande diversidade de práticas agrícolas e de manejo (Basset-Mens & van der Werf,

		Evaluating environmental impacts of contrasting pig farming systems with life
		cycle assessment. Animal 8: 2027-2037.		
	Dourmad, J.-Y.; Sève, B.; Latimier, P.; Boisen, S.; Fernández, J.; van der Peet-
		Schwering, C.; Jongbloed, A.W. 1999. Nitrogen consumption, utilisation and
		losses in pig production in France, The Netherlands and Denmark. Livestock
		Production Science 58: 261-264.		
	LITERATURA CITADA EPA 2006. Life cycle assessment: Principles and practice. In (Ed. EPA R)
		Environmental Protection Agency, Cincinnati.	
	Erisman, J.W.; Sutton, M.A.; Galloway, J.; Klimont, Z.; Winiwarter, W. 2008. How a
	ABIOVE, 2016. Moratória da Soja: Mapeamento e monitoramento do plantio de soja no century of ammonia synthesis changed the world. Nature Geosci 1: 636-639.
	bioma FAO 2000. Fertilizer Requirements in 2015 and 2030. In Food and Agriculture Amazônia e 9° Ano. Available from:
		http://www.abiove.org.br/site/_FILES/Portugues/09112016-141009-Organization of the United Nations, Rome.
	relatorio_da_moratoria_da_soja_2015-16_gts.pdf. FAO 2003. World agriculture: Towards 2015/2030. An FAO perspective. . In Food and
	ABPA	110% 2016. Agriculture Organization of the United Nations Earthscan Publications Ltda, PAG 115% Annual Report 2016. Available from: http://abpa-PAG br.com.br/storage/files/versao_final_para_envio_digital_1925a_final_abpa_relat Londres.
	100% orio_anual_2016_portugues_web1.pdf. FAO 2006. Livestock's long shadow-environmental issues and options. FAO, Rome, 105%
	OT Italy.	90%	AC	OT	95%	AC
	80% FAO 2009. How to feed the world in 2050. In High-Level Expert Forum Food and 85% produtiva.
		United Agriculture Organization of the United Nations, Rome. Nations, p. 154.	Disponível	em:
	http://www.fao.org/docrep/009/a0607e/a0607e00.HTM. FAO 2014. Sources of Meat. In Food and Agriculture Organization of the United
		DAE Nations.	EU	DAE		EU
	FATMA 2009. Instrução Normativa nº 11, 2009. Dispõe sobre Suinocultura. SC, 2009.
		8 p.	A				B
	FEPAM 2007. Critérios técnicos para o licenciamento ambiental de novos
	Alvarenga, R.A.F.; Prudêncio da Silva, V.P.; Soares, S.R. 2012. Comparison of the empreendimentos destinados à suinocultura. [Porto Alegre]: [s.n.], 2007. 10 p.
	ecological footprint and a life cycle impact assessment method for a case study FGV 2016. Sustentabilidade dá vantagens a empresas que querem exportar. Fundação
		on Brazilian broiler feed production. Journal of Cleaner Production 28: 25-32. Getúlio Vargas. Available from: http://gvces.com.br/sustentabilidade-da-
	Andersen, J.M.; Poulsen, H.D.; Børsting, C.F.; Rom, H.B.; Sommer, S.G.; Hutchings, vantagens-a-empresas-que-querem-exportar?locale=pt-br.
	FIESP	N.J. 2001. Ammoniakemission fra landbruget siden midten af 80'erne. Faglig 2014. Santa Catarina em dados. Available from:
		rapport fra DMU No. 353. Danmarks Miljøundersøgelser, Roskilde. http://fiesc.com.br/sites/default/files/medias/25_set_sc_dados_2014_em_baixa_
		para_site.pdf.			

2005), e à complexidade das interações entre as variáveis avaliadas (Prudêncio da Silva, 2011). Neste contexto, há uma lacuna para ser preenchida nestas pesquisas, que se refere à validação dos resultados de ACV obtidos a partir de dados estimados com dados observados experimentalmente, em condições inerentes a cada país e/ou região Alexandratos, N.; Bruinsma, J. 2012. World agriculture towards 2030/2050: the 2012 revision. In: Division, A.D.E. (Ed.). Food and Agriculture Organization of the Alonso, V.; Campo, M.D.M.; Provincial, L.; Roncalés, P.; Beltrán, J.A. 2010. Effect of protein level in commercial diets on pork meat quality. Meat Science 85: 7-14. Alvarenga, R.A.F. 2010. Avaliação de métodos de AICV: um estudo de caso de quatro cenários de ração para frangos de corte. Universidade Federal de Santa Catarina. Andretta, I.; Pomar, C.; Kipper, M.; Hauschild, L.; Rivest, J. 2016. Feeding behavior of growing-finishing pigs reared under precision feeding strategies. Journal of Animal Science 94: 3042-3050. Figueroa, J.L.; Lewis, A.J.; Miller, P.S. 2000. Nitrogen balance and growth trials with pigs fed low-crude protein, amino acid-supplemented diets. Nebraska Swine Report 110: 26-28.

Table 1 -

 1 Ingredients, chemical composition and environmental impacts of diets with reduction on crude protein level

			Crude protein content, %	
		19.24	18.24	17.24	16.24
	Ingredients, %				
	Maize	64.94	67.95	71.02	74.13
	Soybean meal	29.89	26.97	23.95	20.87
	Soybean oil	1.445	1.093	0.711	0.315
	Dicalcium phosphate	1.977	2.035	2.095	2.157
	Limestone	0.455	0.439	0.422	0.405
	Premix 1	0.400	0.400	0.400	0.400
	Salt	0.456	0.348	0.233	0.116
	Sodium bicarbonate	-	0.158	0.327	0.499
	L-Lysine HCl 78%	0.258	0.350	0.446	0.543
	DL-Methionine 99%	0.070	0.095	0.121	0.148
	L-Threonine 98.5%	0.076	0.118	0.161	0.205
	L-Tryptophan 98%	-	0.011	0.028	0.044
	L-Valine 100%	-	0.004	0.057	0.111
	L-Isoleucine 100%	-	-	-	0.003
	Antioxidant -BHT	0.010	0.010	0.010	0.010
	Leucomag® 2	0.020	0.020	0.020	0.020
	Calculated composition, %				
	Metabolizable energy (kcal kg -1 )	3279	3263	3246	3230
	Net energy (kcal kg -1 )	2451	2451	2451	2451
	SID lysine	1.093	1.093	1.093	1093
	SID methionine	0.333	0.346	0.359	0.372
	SID met+cys	0.612	0.612	0.612	0.612
	SID threonine	0.689	0.689	0.689	0.689
	SID tryptophan	0.201	0.197	0.197	0.197
	SID valine	0.799	0.754	0.754	0.754
	SID isoleucine	0.725	0.675	0.623	0.601
	Calcium	0.768	0.768	0.768	0.768
	Digestible phosphorus	0.368	0.368	0.368	0.368
	Electrolytic balance (mEq kg -1 )	190.9	190.4	190.4	190.4

Table 1 -

 1 Ingredients, chemical composition and environmental impacts of diets with reduction on crude protein level (continuation)

	Crude protein content, %

Table 2 -

 2 Performance, backfat thickness and muscle depth (longissimus thoracis) of piglets fed diets with different contents in crude protein and amino acid

	supplementation						
			Crude protein content, %			
						RMSE	P-value
		19.24	18.24	17.24	16.24		
	Number of pigs	7	7	7	7		
	Initial BW, kg	15.0	15.1	15.5	15.7	1.128	0.461
	Final BW, kg	30.6	32.6	31.0	32.1	1.35	0.701
	Backfat thickness, mm	5.17	5.84	5.98	5.28	0.114	0.621
	Muscle depth, mm	25.3	28.3	25.9	26.3	0.248	0.703
	Lean % 1	60.5	60.5	60.4	60.5	0.103	0.614
	ADG, kg	0.717	0.754	0.712	0.738	0.062	0.665
	FCR, kg kg -1	1.77	1.79	1.79	1.80	0.166	0.991
	ADFI, kg	1.27	1.35	1.28	1.32	0.109	0.794

BW = body weight; ADG = average daily gain; FCR = feed conversion ratio; ADFI = average daily feed intake; BWG= BW gain.

Table 3 -

 3 Nitrogen and phosphorus balance of piglets fed diets with different contents in crude protein and amino acid supplementation

			Crude protein content, %			
						RMSE P-value
		19.24	18.24	17.24	16.24		
	Number of pigs	5	5	5	5		
	Nitrogen balance (g d -1 )						
	Intake	23.1	21.9	20.6	18.1	1.01	0.001
	Excreted	8.22	6.64	6.28	5.84	0.639	0.001
	Feces	2.58	2.36	2.38	2.21	0.413	0.832
	Urine	5.64	4.28	3.90	3.63	0.599	0.004
	Retention (% of N intake) 1	63.4	69.5	69.5	67.7	4.18	0.104
	Phosphorus balance (g d -1 )						
	Intake	4.23	4.25	3.48	3.15	0.199	0.001
	Excreted	2.15	2.22	1.93	1.86	0.453	0.686
	Retention (% of P intake) 1	49.2	47.8	44.5	41.0	12.1	0.826
	Regression equations						R 2
	As function of CP contente						
	Nitrogen intake (g d -1 )		-2.74945 + 1.38183 * CP%		0.96
	N excreted in urine (g d -1 )		-4.90280 + 0.54024 * CP%		0.86
	Total N excreted (g d -1 )		-4.08593 + 0.63160 * CP%		0.87
	Phosphorus intake (g d -1 )		-2.08301 + 0.34180 * CP%		0.75
	As function of N intake						
	N excreted in urine (g d -1 )		1.71057 + 0.12654 N intake g d -1		0.21
	Total N excreted (g d -1 )		2.02026 + 0.22555 N intake g d -1		0.47

Table 4 -

 4 Potential environmental impacts, per kg of body weight gain, of piglets from 15 to 30 kg, fed diets with different contents in crude protein and amino acid

	supplementation							
			Crude protein content, %				
						RMSE	P-value	1-ß 1 , %
		19.24	18.24	17.24	16.24			
	Number of pigs	7	7	7	7			
	GWP, kg CO2-eq.	1.76	1.76	1.77	1.77	0.138	0.831	5.15
	AP, g SO2-eq.	33.2	30.0	30.4	30.8	3.44	0.180	28.5
	EP, g PO4-eq.	11.3	10.5	10.4	10.3	1.04	0.111	31.6
	CED, MJ-eq.	17.8	17.6	19.3	19.6	1.49	0.164	67.6
	TE, g 1,4-DCB-eq.	4.68	4.82	4.95	5.17	0.417	0.470	39.6
	LO, m 2 •year	2.06	2.00	1.96	1.89	0.150	0.078	36.0

GWP = global warming potential; AP = acidification potential; EP = eutrophication potential; CED = cumulative energy demand; TE = terrestrial ecotoxicity; LO, land occupation.

Table 1 -

 1 Ingredients, chemical composition and environmental impacts of diets with reduction on crude protein level

			Crude protein content, %	
		19.24	18.24	17.24	16.24
	Ingredients, %				
	Maize	64.94	67.95	71.02	74.13
	Soybean meal	29.89	26.97	23.95	20.87
	Soybean oil	1.445	1.093	0.711	0.315
	Dicalcium phosphate	1.977	2.035	2.095	2.157
	Limestone	0.455	0.439	0.422	0.405
	Premix 1	0.400	0.400	0.400	0.400
	Salt	0.456	0.348	0.233	0.116
	Sodium bicarbonate	-	0.158	0.327	0.499
	L-Lysine HCl 78%	0.258	0.350	0.446	0.543
	DL-Methionine 99%	0.070	0.095	0.121	0.148
	L-Threonine 98.5%	0.076	0.118	0.161	0.205
	L-Tryptophan 98%	-	0.011	0.028	0.044
	L-Valine 100%	-	0.004	0.057	0.111
	L-Isoleucine 100%	-	-	-	0.003
	Antioxidant -BHT	0.010	0.010	0.010	0.010
	Leucomag® 2	0.020	0.020	0.020	0.020
	Chemical composition, %				
	Metabolizable energy (kcal kg -1 )	3279	3263	3246	3230
	Net energy (kcal kg -1 )	2451	2451	2451	2451
	SID lysine	1.093	1.093	1.093	1093
	SID methionine	0.333	0.346	0.359	0.372
	SID met+cys	0.612	0.612	0.612	0.612
	SID threonine	0.689	0.689	0.689	0.689
	SID tryptophan	0.201	0.197	0.197	0.197
	SID valine	0.799	0.754	0.754	0.754
	SID isoleucine	0.725	0.675	0.623	0.601
	Calcium	0.768	0.768	0.768	0.768
	Digestible phosphorus	0.368	0.368	0.368	0.368
	Electrolytic balance (mEq kg -1 )	190.9	190.4	190.4	190.4
	1 Premix should provide at least the following nutrient amounts per kg of feed: vitamin A, 6 000 IU; vitamin D3, 1
	800 IU; vitamin E, 30 IU; vitamin K3, 6 mg; vitamin B1, 1 mg; vitamin B2, 5.2 mg; vitamin B6, 1.5 mg; vitamin
	B12, 20 mg; niacin, 30 mg; pantothenic acid, 18 mg; folic acid, 0.6 mg; biotin, 0.09 mg; choline chloride, 0.32 mg;
	methionine, 0.1 g; lysine, 0.28 g; copper, 21 mg; iodine, 1.4 mg; iron, 0.05 g; manganese, 35 mg; selenium, 0.3 mg;
	zinc, 0.12 g; phytase.				

Table 2 -

 2 Performance, backfat thickness, muscle depth (longissimus thoracis) and nitrogen and phosphorus balance of piglets fed diets with different contents in crude protein and amino acid supplementation

			Crude protein content, %	
		19.24	18.24	17.24	16.24
	Performance				
	Final BW, kg	31.0	31.1	31.1	31.2
	Backfat thickness, mm	8.60	8.60	8.60	8.60
	Lean %	63.6	63.4	63.3	63.2
	ADG, kg	0.668	0.670	0.672	0.673
	FCR, kg kg -1	1.80	1.80	1.79	1.79
	ADFI, kg	1.203	1.204	1.205	1.205
	Nutrient balance				
	Nitrogen (g d -1 )				
	Intake	37.0	35.1	33.2	31.3
	Excreted	14.4	13.7	13.0	12.2
	Phosphorus (g d -1 )				
	Intake	8.97	8.85	7.27	6.96
	Excreted	5.02	4.96	4.07	3.89
	BW = body weight; ADG = average daily gain; FCR = feed conversion ratio; ADFI = average daily feed
	intake; BWG= BW gain.				

Table 3 -

 3 Potential environmental impacts, per kg of body weight gain, of piglets from 15 to 30 kg, fed diets with different contents in crude protein and amino acid

	supplementation				
			Crude protein content, %	
		19.24	18.24	17.24	16.24
	GWP, kg CO2-eq.	1.53	1.53	1.54	1.55
	AP, g SO2-eq.	35.6	35.0	34.5	34.0
	EP, g PO4-eq.	11.3	11.1	10.9	10.8
	CED, MJ-eq.	17.5	17.8	18.6	19.4
	TE, g 1,4-DCB-eq.	4.78	4.83	4.88	5.15
	LO, m 2 •year	2.09	2.01	1.96	1.88

GWP = global warming potential; AP = acidification potential; EP = eutrophication potential; CED = cumulative energy demand; TE = terrestrial ecotoxicity; LO, land occupation.

Table 4 -

 4 A posteriori Bayesian estimates of difference between predicted (InraPorc®) and observed (essays) for performance, excretion and life cycle impact data

	Parameter				CIr 1 95%
		Mean	SD	Median		
					2.50%	97.5%
	Feed intake, kg d -1	-0.454	0.139	-0.043	-0.305	0.206
	BW gain, kg d -1	0.059	0.028	0.059	0.009	0.121
	Nitrogen excreted, g d -1	-1.69	0.619	-1.734	-2.74	-0.456
	Phosphorus excreted, g d -1	0.239	0.260	0.244	-0.260	0.712
	Global warming, kg CO2-eq.	0.228	0.022	0.228	0.187	0.268
	Acidification, g SO2-eq.	-3.67	0.907	-3.66	-5.34	-2.00
	Eutrophication, g PO4-eq.	-0.458	0.186	-0.479	-0.764	-0.063
	Energy demand, MJ-eq.	0.250	0.287	0.250	-0.283	0.785
	Ecotoxicity, g 1,4-DCB-eq.	-0.0004	0.062	0.610	-0.118	0.109
	Land occupation, m 2 •year	-0.003	0.026	-0.007	-0.056	0.059

Table 2 -

 2 Minimum limits of nutritional parameters for feed formulation

	997				
			Gilts		Barrows
		Body weight, kg	30	115	30	115
		Net energy, kcal kg -1	2460	2460	2460	2460
		Crude protein, %	17.50	14.70	16.75	11.75
		SID AA 1 , %			
		Lysine	0.835	0.581	0.840	0.522
		Threonine	0.524	0.364	0.527	0.327
		Methionine	0.253	0.175	0.255	0.158
		Met + cys	0.495	0.344	0.498	0.310
		Tryptophan	0.144	0.099	0.144	0.089
		Isoleucine	0.501	0.348	0.504	0.313
		Valine	0.570	0.397	0.572	0.357
		Leucine	0.835	0.581	0.840	0.522
		Phenylalanine	0.418	0.290	0.420	0.261
		Phe + tyr	0.794	0.552	0.798	0.496
		Histidine	0.267	0.186	0.269	0.167
		Arginine	0.351	0.244	0.353	0.219
		Minerals, %			
		Digestible P	0.279	0.199	0.281	0.186
		Ca	0.580	0.413	0.584	0.387
	998	1 SID = standardized ileal digestible.		

Table 1 -

 1 Performance and nitrogen and phosphorus balance of growing-finishing pigs fed without amino acid addition (noAA), with amino acid addition and minimal crude protein constraints (withAA) and with amino acid without any crude protein constraint

	(lowCP)					
		Amino acids inclusion	P-value 1	RMSE
	Variables 2	noAA	withAA	lowCP		
	N° of pigs	2000	2000	2000		
	CP, %	16.0 a	14.9 b	12.7 c	<0.001	8.88
	ADG, kg	0.847 a	0.847 a	0.843 b	<0.001	22.5
	ADFI, kg	2.28 c	2.29 b	2.31 a	<0.001	22.5
	FCR, kg kg -1	2.73 c	2.74 b	2.75 a	<0.001	0.264
	Nitrogen balance, kg					
	Intake	5.89 a	5.52 b	4.70 c	<0.001	540
	Excreted	3.87 a	3.50 b	2.69 c	<0.001	608
	Phosphorus balance, kg					
	Intake	1.12 a	1.09 b	1.02 c	<0.001	117
	Excreted	0.696 a	0.670 b	0.602 c	<0.001	116

1 Means followed by same or no letter do not differ (P > 0.05) according to Tukey's test.

2 CP = average crude protein; ADG = average daily gain; FCR = feed conversion ratio. 123

Table 2 -

 2 Potential environmental impacts at the farm gate, per kg of body weight gain, of growing-finishing pigs fed without amino acid addition (noAA), with amino acid addition and minimal crude protein constraints (withAA) and with amino acid without any crude protein constraint (lowCP)

		Amino acids inclusion	P-value 1	RMSE
		noAA	withAA	lowCP		
	Impact category					
	Global warming, kg CO2-eq.	2.38c	2.44b	2.51a	<0.001	0.242
	Acidification, g SO2-eq.	64.3a	59.7b	57.0c	<0.001	7.82
	Eutrophication, g PO4-eq.	19.1a	17.5b	16.6c	<0.001	2.15
	Energy demand, MJ	12.8c	13.4b	14.0a	<0.001	1.02
	Ecotoxicity, g 1,4-DCB-eq.	8.77c	9.18b	9.53a	<0.001	0.959
	Land occupation, m 2 .ano	2.60a	2.47b	2.42c	<0.001	0.256

Artigo formatado de acordo com as normas da revista Scientia Agricola. ISSN: 0103-9016 (Print).

Premix should provide at least the following nutrient amounts per kg of feed: vitamin A, 6 000 IU; vitamin D3, 1 800 IU; vitamin E, 30 IU; vitamin K3, 6 mg; vitamin B1, 1 mg; vitamin B2, 5.2 mg; vitamin B6, 1.5 mg; vitamin B12,

mg; niacin, 30 mg; pantothenic acid, 18 mg; folic acid, 0.6 mg; biotin, 0.09 mg; choline chloride, 0.32 mg; methionine, 0.1 g; lysine, 0.28 g; copper,

mg; iodine, 1.4 mg; iron, 0.05 g; manganese, 35 mg; selenium, 0.3 mg; zinc, 0.12 g; phytase.2 Leucomag: leucomycin at 30%.

Retention coefficient used to estimate nitrogen (N) and phosphorus (P) excretion in Essay I

Power of statistical test considering alpha = 5%.

Artigo formatado de acordo com as normas da revista Scientia Agricola. ISSN: 0103-9016 (Print).

Leucomag: leucomycin at

30%.

CIr: credibility interval (P<0.05).

Parte do artigo publicado no Journal of Animal Science. doi:10.2527/jas2016-0529.

Means followed by same or no letter do not differ (P > 0.05) according to Tukey's test.

Acknowledgements

This project was conducted within a sandwich PhD thesis program supported by CAPES Foundation, Brazil.

Acknowledgements

This project was conducted within a sandwich PhD thesis program supported by CAPES Foundation, Brazil.

Life cycle inventory (LCI)

Resource use and emissions associated with the production and delivery of inputs for crop production (fertilizers, pesticides, tractor fuel and agricultural machinery) came from the Ecoinvent database version 3 (SimaPro LCA software 8.0, PRé Consultants).

Energy use in the building for light and ventilation was considered, but not the emissions and resources used for the construction of buildings, nor the land occupied by the buildings. Veterinary medicines and hygiene products were also not included, as proposed by Garcia-Launay et al. (2014).

Crop production and non-plant feed components

We assumed that soybean was produced in South Brazil, the second largest producer in the country (CONAB, 2016). Life cycle inventory for maize and soybean came from Alvarenga et al. (2012) and Prudêncio da Silva et al. (2010), respectively.

For the grain-drying and storage stage, we used data from Marques (2006). For soybean meal and soybean oil, the resource use and emissions were economically allocated, following the suggestion of Ramírez (2009).

Data for salt, phosphate, sodium bicarbonate, premix and limestone production, used in the diet, came from Wilfart et al. (2016). The antioxidant and growth promoter were assumed to have the same impacts as the premix. L-lysine HCl, DL-methionine and L-threonine inventory data came from Mosnier et al. (2011). Production of Ltryptophan, L-valine and L-isoleucine were assumed to require twice the amount of resources and energy as the production of L-lysine HCl (Garcia-Launay et al., 2014).

Transport specifications

The pig production system considered was located in South Brazil, as described by Cherubini et al. (2015); this region contributes to more than 50% of the national pig

Manure management

The environmental consequences of manure utilization were evaluated using system expansion as described by Nguyen et al. (2010). Thus, manure produced was assumed to substitute a certain amount of mineral fertilizers, by using a mineral fertilizer equivalency (MFE, %). We assumed that the MFE was 75 % of total nitrogen in manure (Nguyen et al., 2010), with 5 % extra loss as nitrates compared to mineral fertilizers (Garcia-Launay et al., 2014), and MFE was 100 % for phosphorus (Sommer et al., 2008).

Life cycle impact assessment

Emissions from animal production

Emissions to air during swine production were estimated step-by-step for NH3, N2O, NOx and CH4, as described by Monteiro et al. (2016). The NH3 emissions from the building and during manure storage were calculated according to emission factors proposed by Rigolot et al. (2010), considering the effect of ambient temperature. The amounts of nitrogen, phosphorus and organic matter excreted by each pig were obtained from laboratory analysis.

Characterization factors

We based our analysis on the CML 2001 (baseline) method V3.02 as implemented in Simapro software, version 8.05 (PRé Consultant, 2014) and added the following categories: land occupation from CML 2001 (all categories) version 2.04 and total cumulative energy demand version 1.8 (non-renewable fossil + nuclear). Thus, we considered the potential impacts of pig production on global warming potential (GWP, kg CO2-eq.), eutrophication potential (EP, g PO4-eq.), acidification potential (AP, g

Results

Animal performance, nitrogen and phosphorus balance

The reduction in dietary CP did not significantly affect (P>0.05) the performance of piglets, and the variation in ADFI and ADG was less than 7 % between the experimental feeds (Table 2). Backfat thickness and loin depth were also not affected by dietary CP reduction (P>0.05) and the estimated lean percentage was around 60 %.

Nitrogen intake (P=0.001), nitrogen excreted in urine (P=0.001) and total nitrogen excreted (P=0.001), as well as phosphorus intake (P=0.001), declined linearly with the decrease in dietary CP content (Table 3). Despite the lower ingestion and excretion, retention coefficients were not significantly affected (P>0.05) by dietary CP reduction. Nitrogen excreted in feces and phosphorus excreted were not affected (P>0.05) by dietary CP reduction (Table 3).

The estimated nitrogen excreted in urine, as nitrogen intake function (in g d -1 ), could be represented for the equation Nurine = 1.71057 + 0.12654 N intake g d -1 , and the total nitrogen excreted for the equation Nexcreted = 2.02026 + 0.22555 N intake g d -1 (Table 3).

Life cycle impacts

The dietary CP reduction was achieved by replacing soybean meal with maize and IAA. At the same time, the total phosphorus content was also reduced (Table 1).

For the impact categories, GWP, AP, EP, CED and TE, the CP reduction increased the Brossard, L.;Dourmad, J.-Y.;Rivest, J.;[START_REF] Brossard | Modelling the variation in performance of a population of growing pig as affected by lysine supply and feeding strategy[END_REF]. Modelling the variation in performance of a population of growing pig as affected by lysine supply and feeding strategy. Animal 3: 1114-1123. Brossard, L.;Vautier, B.;van Milgen, J.;Salaun, Y.;Quiniou, N. 2014 Energy use in the building for light, heating and ventilation was considered, but not the emissions and resources used for the construction of buildings, nor the land occupied by the buildings. Veterinary medicines and hygiene products were also not included, as proposed by Garcia-Launay et al. (2014).

Crop production and non-plant feed components

We assumed that soybean was produced in South Brazil, the second largest producer in the country (CONAB, 2016). Life cycle inventory for maize and soybean came from Alvarenga et al. (2012) and Prudêncio da Silva et al. ( 2010), respectively.

For the grain-drying and storage stage, we used data from Marques (2006). For soybean meal and soybean oil, the resource use and emissions were economically allocated, following the suggestion of Ramírez (2009).

Data for salt, phosphate, sodium bicarbonate, premix and limestone used in the diet came from Wilfart et al. (2016). The antioxidant and growth promoter were assumed to have the same impacts as the premix. L-lysine HCl, DL-methionine and Lthreonine inventory data came from Mosnier et al. (2011). Production of L-tryptophan, L-valine and L-isoleucine were assumed to require twice the amount of resources and energy as the production of L-lysine HCl (Garcia-Launay et al., 2014).

Transport specifications

The pig production system considered was located in South Brazil, as described by Cherubini et al. (2015); this region contributes to more than 50% of the national pig production (FIESC, 2014). We hypothesized that the grains came from the main producing areas in South Brazil. For transport inventory, we used the methodology renewable energy used during IAA production could be an area where the industry could take action to reduce impacts.

Conversely, Garcia-Launay et al. ( 2014) observed a reduction in CED moving from no IAA diet and high CP to low CP diet. However, this study considered that 100 % of soybean was imported from Brazil (mainly from Center-West) with a high energy demand at the transport step.

The high TE impact in low CP diets (Table 3) was due to low CP diets allowed more IAA inclusion. According to Garcia-Launay et al. ( 2014), TE impact for L-lysine manufacturing was 82 % higher than for soybean meal production. For the other IAA (L-tryptophan, DL-methionine and L-valine), authors estimated an impact 91 % higher than soybean meal. This seems to indicate that the use of maize-soy-based diets, with minimum IAA supplementation, could provide reduction in TE impact, considering Brazilian pig production context, without soybean from deforested areas.

Potentials of acidification and eutrophication and land occupation

There is a high contribution of nitrogen and phosphorus to the eutrophication process, and nitrogen contribution to the acidification process by ammonia emissions (Guinée et al., 2002). For this reason, a reduction on AP and EP was observed in our study, as the dietary CP was reduced. This result is in line of previous researches (Ogino et al., 2013;Garcia-Launay et al., 2014;Mackenzie et al., 2016;Kebreab et al., 2016).

Similarly, for LO impact category there was a reduction of impact by the IAA use, which was already shown in other studies (Mosnier et al., 2011;Garcia-Launay et al., 2014;Monteiro et al., 2016). This could be due to the reduction of soybean inclusion, which occupies the land for longer periods than IAA. Besides, low CP diets allow higher maize inclusion. Considering the grain production in Brazil, Prudêncio da with broiler production were based on Prudêncio da Silva et al. ( 2014) and those associated with processing were based on [START_REF] Wilfart | LCIA results of feedstuffs for French livestock[END_REF]. The environmental impacts between products and co-products were then allocated on an economic basis.

Transport specifications

The pig production system considered was located in South Brazil as described by Cherubini et al. (2015), because this region contributes to more than 69% of the national pig production (ABPA, 2016). We hypothesized that the grains came from the main producing areas in South Brazil. For transport inventory, we used the methodology described by Prudêncio da Silva et al. ( 2010), considering the distances described by [START_REF] Spies | The sustainability of the pig and poultry industries in Santa Catarina, Brazil: a framework for change[END_REF]. Products imported were assumed to be mainly transported by sea followed by road (Mosnier et al., 2011).

Nutrient requirement

Performance data from experimental studies in Brazil [START_REF] Monteiro | Avaliação de programas nutricionais com redução do nível de proteína bruta e fósforo total da dieta para suínos nas fases de crescimento e terminação[END_REF], with weekly recording of feed intake and body weight, were used to adjust average animal profile parameters for growth and feed intake using InraPorc® software (INRA, Saint-Gilles, France), for each gender (Table 1). These profiles were used to calculate, according to InraPorc®, the average nutritional requirement curves for each sex (gilts and barrows), these requirements being used for diet formulation. To take account of the variability, the nutrient requirement of the population was calculated as 110 % of the mean requirement as generally recommended [START_REF] Pomar | Modeling stochasticity: Dealing with populations rather than individual pigs[END_REF][START_REF] Brossard | Modelling the variation in performance of a population of growing pig as affected by lysine supply and feeding strategy[END_REF].

Feed specifications

The feedstuff composition was obtained from Rostagno et al. (2011). Feeds were formulated according to the methodology described by Pomar et al. (2014a). Two experimental feeds (named A and B) were independently formulated on the basis of net

Characterization factors

We based our analysis on the CML 2001 (baseline) method V3.02 as implemented in Simapro software, version 8.05 (PRé Consultant, 2014) and added the following categories: land occupation from CML 2001 (all categories) version 2.04 and total cumulative energy demand version 1.8 (non-renewable fossil + nuclear). This method was chosen because it has been used in most of the pig LCA studies in the literature. Moreover, according to Alvarenga et al. (2012), this method has the advantage of being more robust, because a larger number of environmental impacts categories are analyzed, giving rise to a higher number of hotspots. Thus, we considered the potential impacts of pig production on global warming potential (GWP, kg CO2eq.), eutrophication potential (EP, g PO4-eq.), acidification potential (AP, g SO2-eq.),

terrestrial ecotoxicity (TE, g 1,4-DCB-eq.), cumulative energy demand (CED, MJ), and land occupation (LO, m 2 •year). The GWP was calculated according to the 100-year global warming potential factors in kg CO2-eq.

Calculations and statistical analyzes

The LCA calculations were performed for each pig according to its individual performance and excretion from 70 days (with 30 kg BW on average) to an average BW of 115 kg at slaughter. These calculations were performed using SAS software (Statistical Analysis System, version 9.2). Performance responses and environmental impacts were subjected to variance analysis using the GLM procedure. The statistical model included effects of amino acid inclusion. Differences were considered significant if P<0.05. Means were compared using the Tukey test.

Results

Animal performance and nitrogen and phosphorus balance

Simulated performance of pigs and results of nitrogen and P excretion are presented in Table 3. Average dietary CP content was significantly (P<0.05) affected by IAA inclusion. According to the scenarios of IAA inclusion, the average CP content of the feed was highest for the noAA scenarios, with value about 21 % higher than for lowCP scenarios in comparison with lowCP.

Differences in ADG between noAA and withAA scenarios were not significant (P>0.05). However, pigs fed lowCP showed the lower performance, the worst FCR as a result of lower ADG and higher ADFI. Increasing the level of IAA inclusion reduced nitrogen excretion by 30 %, and P excretion by 14 %.

Potential environmental impacts

Global warming potential and cumulative energy demand

The highest (P<0.05) impacts among the IAA inclusion scenarios were observed for lowCP (2.51 kg CO2-eq. kg -1 BWG), which was 5% higher than noAA (2.38 kg CO2-eq. kg -1 BWG). Main processes contributing to GWP impacts were feed production (production and transport of feed ingredients, feed processing at the feed factory and transport to the farm), animal housing, and manure management (storage, transport and spreading; Figure 2). Manure management had the highest contribution to GWP (50 %), followed by feed production (44 %).

On average, the highest (P<0.05) CED impacts among the IAA inclusion scenarios were observed for lowCP (14 MJ-eq. kg -1 BWG), and the lowest for noAA

Discussion

Performance and nitrogen and phosphorus balance

In agreement with Mosnier et al. (2011) andGarcia-Launay et al. (2014), average dietary CP concentration over the growing-finishing period was reduced with the IAA inclusion, with the lowest level achieved for the lowCP scenario. This was expected, since dietary nutrient utilization is a dynamic phenomenon resulting in a reduction of amino acid requirement, relatively to energy, over the fattening period (van Milgen et al., 2008).

The reduction in nitrogen and P excretion obtained with IAA inclusion was attributable to the reduction in nutrient supply and the better adjustment of AA level to pig's requirements, as already shown by Andretta et al. (2014), who reported that nitrogen excretion was reduced by 8 % for each percentage unit of dietary CP for precision feeding in comparison with 3-phase feeding. In the present study, each percentage unit of dietary CP reduction due to IAA inclusion led to a decrease in nitrogen excretion of around 9 %.

However, increasing the incorporation of IAA tended to reduce performance compared to noAA. Since diets without AA showed more nutrients per kg of feed, to met the essential AA requirements, pigs receiving noAA diets rarely would present low performance, while those fed lowCP, with nutritional levels adjusted to meet 110 % of the mean nutrient requirements of herd, would reduce ADG. [START_REF] Brossard | Modelling the variation in performance of a population of growing pig as affected by lysine supply and feeding strategy[END_REF] indicated that depending on the variability of the population, more than 110 % of the mean AA requirement had to be fed to achieve maximal growing performance. Pomar et al. (2014a) measured similar performance for feeding strategies with different numbers of feeding phases, but in their study the highest AA supply was calculated to meet the requirements of the most demanding pigs. This seems to indicate that feeding 110% of average pig SID-lysine requirement might not be high enough according to the heterogeneity of the population.

Potential for reducing environmental impacts through feeding practices

The hypothesis of reducing environmental impacts of pig production through the inclusion of IAA was validated by our results for some impact categories, considering the production of protein rich ingredients with no deforestation.

Global warming potential and cumulative energy demand

The GWP impact increased with the increasing in IAA inclusion (Table 4). This represented almost 2 % of accretion in the GWP for each percentage unit of dietary CP reduction. In this study, this result was due to the GWP from IAA manufacturing were higher than those from the production of the main feed ingredients, i.e., maize and soybean meal, increasing the GWP impact due to the use of IAA. However, if protein rich ingredients came from deforested areas, this result could be different. Garcia-Launay et al. (2014) found that reducing the dietary CP supply, by increasing the incorporation of IAA, reduced GWP impact by about 3 % for each percentage unit of CP content reduction. However, in this study it was considered that 70 % of the soybean meal was originated from recently deforested areas.

Indeed, the deforestation process contributes substantially to increase the absolute values of CO2-eq. emissions, due to the effect of land-use change (LUC) on carbon release as a consequence of the conversion of forest to cropland (PAS2050, 2011).