Given an abstract from a research paper, your task is to identify and label relationships between chemical compounds and genes mentioned in the abstract.

The relationship type must be one of ['DOWNREGULATOR', 'SUBSTRATE', 'INDIRECT-REGULATOR', 'PART-OF', 'MODULATOR-ACTIVATOR', 'REGULATOR', 'INHIBITOR', 'COFACTOR', 'UPREGULATOR', 'ACTIVATOR', 'ANTAGONIST', 'NOT', 'INDIRECT-DOWNREGULATOR', 'SUBSTRATE_PRODUCT-OF', 'INDIRECT-UPREGULATOR', 'AGONIST', 'PRODUCT-OF', 'MODULATOR', 'DIRECT-REGULATOR', 'UNDEFINED', 'AGONIST-INHIBITOR', 'AGONIST-ACTIVATOR', 'MODULATOR-INHIBITOR'].

Please format your output as a JSON array. Each entry in the array should express a single relation, formatted as ["<Entity_A>", "<RELATION_A_B>", "<Entity_B>"]. If no relations can be found, please output an empty JSON array [].

Abstract:

An improved mass spectrometric method for identification and quantification of phenolic compounds in apple fruits. Thirty-nine phenolic compounds were analysed using ultra high performance liquid chromatography (UHPLC) coupled with diode array and accurate mass spectrometry detection using electrospray ionisation (DAD/ESI-am-MS). Instrumental parameters such as scan speed, resolution, and mass accuracy were optimised to establish accurate mass measurements. The method was fully validated in terms of model deviation (r (2) >0.9990), range (typically 10-3500 ngg (-1)), intra/inter-day precision (< 6% and < 8%, respectively) and accuracy (typically 100 ± 10%). The mass accuracy of each selected phenolic compound was below 1.5 ppm. The results confirmed that the UHPLC-DAD/ESI-am-MS method developed here was convenient and reliable for the determination of phenolic compounds in apple extracts.
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