AI Article Synopsis

  • Traditional studies of fruit ripening focused on genetics and a few key metabolites like sugars and organic acids.
  • The use of metabolomics has expanded our knowledge of the numerous metabolic components that affect fruit quality and nutrition.
  • The review highlights the advancements from studying natural variations and genetically modified fruits, and suggests that comparative analyses and machine learning will enhance our understanding of fruit metabolites in the future.

Article Abstract

Classically fruit ripening and development was studied using genetic approaches, with understanding of metabolic changes that occurred in concert largely focused on a handful of metabolites including sugars, organic acids, cell wall components, and phytohormones. The advent and widespread application of metabolomics has, however, led to far greater understanding of metabolic components that play a crucial role not only in this process but also in influencing the organoleptic and nutritive properties of the fruits. Here we review how the study of natural variation, mutants, transgenics, and gene-edited fruits has led to a considerable increase in our understanding of these aspects. We focus on fleshy fruits such as tomato but also review berries, receptacle fruits, and stone-bearing fruits. Finally, we offer a perspective as to how comparative analyses and machine learning will likely further improve our comprehension of the functional importance of various metabolites in the future.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10938048PMC
http://dx.doi.org/10.1093/jxb/erad384DOI Listing

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