Abstract
To tackle the urgency of smarter crop management, the complex nature of agricultural ecosystems needs to be better understood, employing and combining different techniques and technologies. In this study, untargeted metabolomics and agro-meteorological survey were coupled to study the variation of Sorghum bicolor (L.) Moench metabolome during crop development, in response to environmental and anthropic factors. Twelve crop fields in the Emilia-Romagna region, Italy, were monitored and sampled at different stages, seedling (Ss), advanced vegetative (Sv), and ripening (Sr), and subjected to 1H NMR-based metabolomics. The analytical method developed resulted to be successful to quickly analyze different sorghum organs. Dhurrin, a cyanogenic glucoside, resulted to be a biomarker of crop quality and development, and several insights into its turnover and functions were obtained. In particular, p-glucosyloxy-2-hydroxyphenylacetic acid was identified, for the first time, as the main metabolite accumulated in sorghum at Sr, after gradual dhurrin neutralization. During plant life, fertilization and biotic and abiotic stress reflected peculiar metabolomic profiles. Water supply and soil features (i.e., clay content) were correlated to metabolomic variations, affecting dhurrin (and related metabolites), amino acids, organic acids, and carbohydrate content. Increase in chlorogenic acid was registered in consequence of predator attacks. Moreover, grain from three fields presented traces of dhurrin and the lowest antioxidant potential, which resulted in poor grain quality. Metabolomics turned out to be a promising tool in view of smart agriculture for monitoring plant growth status and applying appropriate agricultural practices since the early stage of crop development.
Highlights
Population growth, climate change, and the urgent demand for safe, nutritious, and sufficient food worldwide challenge agriculture to intensify production, while concurrently lowering the food environmental footprint.[1]To tackle this demand, it is increasingly important to deeply understand the complexity of agricultural ecosystems
Advanced and accurate information on weather variables and their quantitative relations to crop processes need to be implemented.[4]. In this framework, untargeted metabolomics coupled with agroclimatic studies could represent a valuable tool to obtain information on the variation of crop metabolome in response to environmental and anthropic factors
Metabolomics, which often relies on untargeted analysis protocols, whose data are handled with multivariate techniques, has already been applied successfully in several areas of research, ranging from human diagnostics and epidemiology to plant sciences.[5]
Summary
Population growth, climate change, and the urgent demand for safe, nutritious, and sufficient food worldwide challenge agriculture to intensify production, while concurrently lowering the food environmental footprint.[1]. To tackle this demand, it is increasingly important to deeply understand the complexity of agricultural ecosystems. Advanced and accurate information on weather variables and their quantitative relations to crop processes need to be implemented.[4] In this framework, untargeted metabolomics coupled with agroclimatic studies could represent a valuable tool to obtain information on the variation of crop metabolome in response to environmental and anthropic factors. This approach resulted to be helpful in facilitating the identification of active principles in medicinal plants[6−8] and for food and botanical quality control, in terms of both nutraceutical/biological properties and fraud detection.[9,10]
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