Abstract
There is an increasing interest in the use of automation in plant production settings. Here, we employed a robotic platform to induce controlled mechanical stimuli (CMS) aiming to improve basil quality. Semi-targeted UHPLC-qToF-MS analysis of organic acids, amino acids, phenolic acids, and phenylpropanoids revealed changes in basil secondary metabolism under CMS, which appear to be associated with changes in taste, as revealed by different means of sensory evaluation (overall liking, check-all-that-apply, and just-about-right analysis). Further network analysis combining metabolomics and sensory data revealed novel links between plant metabolism and sensory quality. Amino acids and organic acids including maleic acid were negatively associated with basil quality, while increased levels of secondary metabolites, particularly linalool glucoside, were associated with improved basil taste. In summary, by combining metabolomics and sensory analysis we reveal the potential of automated CMS on crop production, while also providing new associations between plant metabolism and sensory quality.
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