By Viacheslav I. Adamchuk, Richard B. Ferguson, Gary W. Hergert (auth.), Erich-Christian Oerke, Roland Gerhards, Gunter Menz, Richard A. Sikora (eds.)
Precision farming is an agricultural administration method utilizing international navigation satellite tv for pc structures, geographic details structures, distant sensing, and knowledge administration platforms for optimizing using foodstuff, water, seed, insecticides and effort in heterogeneous box occasions. This publication, generated through scientists from a wide diversity of medical disciplines, presents huge info at the state of the art of analysis on precision crop defense and up to date advancements in site-specific software applied sciences for the administration of weeds, arthropod pests, pathogens and nematodes. It provides the reader an updated and in-depth evaluate of either simple and utilized study advancements. The chapters talk about I) biology and epidemiology of pests, II) new sensor applied sciences, III) functions of multi-scale sensor platforms, IV) sensor detection of pests in becoming plants, V) spatial and non-spatial information administration, VI) impression of pest heterogeneity and VII) distinctive mechanical and chemical pest keep watch over. Examples for using applied sciences are given for the administration of pests which permit growers to alter program timing and dosage, and to optimize pesticide combos or depth of mechanical weeding in keeping with the spatial and temporal variability of pests.
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Additional info for Precision Crop Protection - the Challenge and Use of Heterogeneity
2004, Girma et al. 2005, Malthus and Madeira 1993, Sullivan and Holbrook 2007, Zhao et al. 2005), this paradigm has met with less than satisfactory results. Most such investigations have used types of correlation analyses to look for unique pathogen-specific spectral signatures, and incorporated the most promising spectral indices/ratios with discriminant analyses (Girma et al. 2005). 4 Use of Satellite Imagery to Detect and Quantify Healthy Green Leaf Area Gradients (1-y) Versus Disease Gradients (y) Disease gradients are the result of two biological processes: pathogen dissemination and pathogen infection (Fig.
1-y (Nutter 1990). We believe that the NIR band is detecting HGLA, and not disease, because there are always very strong (positive), linear relationships between percentage reflectance (or image intensity) in the near infrared band with both yield and green leaf area index (Chong et al. 2001, Guan and Nutter 2002a, Guan and Nutter 2002b, Lathrop and Pennypacker 1980, Nutter 1989, Nutter et al. 2010). ) are actually measuring 1-y, not disease (y) (Guan and Nutter 2002a, Nutter 1989, 2006, Pethybridge 2007b, Pethybridge et al.
2003) depends on spatial, spectral, radiometric and temporal resolution. Spatial resolution (pixel size) depends on the instrumentation and altitude of the measurement platform. I. Adamchuk et al. depends on the type of instrument and may be related to imagery that is panchromatic (having light reflectance integrated over the entire visual part of spectrum), multispectral (typically blue, green, red and near-infrared), or hyperspectral (typically more than 200 narrow spectral bands). Panchromatic and multispectral data suffice to visualize the overall spatial variability of soil reflectance.