ArticleProceedings of the National Academy of Sciences of the United States of America2022
Metabolomic selection for enhanced fruit flavor.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers.
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74 citing papers in PubMed, 198 citations in OpenAlex.
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- Integration of volatilomics, non-targeted metabolomics, and electronic sensory technologies reveals the flavor evolution mechanism in 'Queen Nina' table grapes during ripening.Food chemistry: X · 2026Article
- Integrating Machine Learning and Expert Sensory Evaluation to Identify Key Drivers of Tomato Fruit Quality: A Multi-Model and Age-Stratified Analysis.Foods (Basel, Switzerland) · 2026Article
- Machine learning for food flavor prediction and regulation: models, data integration, and future perspectives.Journal of advanced research · 2026Review
- Mutation of STAY-GREEN 1 in tomato increases volatile organic compounds during fruit ripening.Plant & cell physiology · 2026Article
- Study on domestication characteristics of Xinjiang apricot germplasm based on HPLC sugar-acid identification and machine learning.Food chemistry: X · 2026Article
- Interpretable machine learning for the grade prediction of strong flavorFood chemistry: X · 2026Article
- Salt-stress-induced tomato sweetening involves an SlSnRK2.6-SlZHD8 sugar accumulation cascade triggered by root-derived abscisic acid.The EMBO journal · 2026Article
- Regulation of apocarotenoids for quality improvement and biofortification of horticultural crops.Journal of advanced research · 2026Review
- Metabolomics and machine learning integrated analysis of flavor quality in 'Legacy' and a mutant blueberry.Current research in food science · 2026Article
- Synthetic microbial communities for sustainable hydroponic tomato production.NPJ sustainable agriculture · 2026Article
- Metabolomic phenotyping reveals the GxExS blind spot in berry fruit quality breeding.Frontiers in plant science · 2026Review
- Metabolomics for plant breeding: knowledge without adoption.Frontiers in plant science · 2026Article
- Comprehensive Profiling of Free Amino Acids in Litchi (Foods (Basel, Switzerland) · 2025Article
- Integrated multi-omics reveals the molecular basis of protein storage in developing oat grains.BMC plant biology · 2025Article
- Genetic basis of flavor complexity in sweet corn.Nature genetics · 2025Article
- Breeding perspectives on tackling trait genome-to-phenome (G2P) dimensionality using ensemble-based genomic prediction.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025Review
- The aldehyde (ALD) locus controls C6-aldehyde production in kiwifruit and affects consumer perception of fruit aroma.Plant physiology · 2025Article
- Comprehensive morphological and biochemical characterization of garlic (Allium sativum L.) genotypes using multivariate analysis.BMC plant biology · 2025Article
- SlPLT6 controls ripening initiation and quality traits through modulation of histone acetylation and methylation in tomato.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
14 more citing papers are in PubMed but not listed here.
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although they are staple foods in cuisines globally, many commercial fruit varieties have become progressively less flavorful over time. Due to the cost and difficulty associated with flavor phenotyping, breeding programs have long been challenged in selecting for this complex trait. To address this issue, we leveraged targeted metabolomics of diverse tomato and blueberry accessions and their corresponding consumer panel ratings to create statistical and machine learning models that can predict sensory perceptions of fruit flavor. Using these models, a breeding program can assess flavor ratings for a large number of genotypes, previously limited by the low throughput of consumer sensory panels. The ability to predict consumer ratings of liking, sweet, sour, umami, and flavor intensity was evaluated by a 10-fold cross-validation, and the accuracies of 18 different models were assessed. The prediction accuracies were high for most attributes and ranged from 0.87 for sourness intensity in blueberry using XGBoost to 0.46 for overall liking in tomato using linear regression. Further, the best-performing models were used to infer the flavor compounds (sugars, acids, and volatiles) that contribute most to each flavor attribute. We found that the variance decomposition of overall liking score estimates that 42% and 56% of the variance was explained by volatile organic compounds in tomato and blueberry, respectively. We expect that these models will enable an earlier incorporation of flavor as breeding targets and encourage selection and release of more flavorful fruit varieties.
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