Unrevealing the Halyomorpha halys Damage Fingerprint on Hazelnut Metabolome by Multiomic Platforms and AI-Aided Strategies DOI
Simone Squara, Silvia T. Moraglio, Andrea Caratti

et al.

Journal of Agricultural and Food Chemistry, Journal Year: 2024, Volume and Issue: 72(43), P. 24109 - 24129

Published: Oct. 16, 2024

The brown marmorated stink bug (Halyomorpha halys) poses a significant threat to hazelnut crops by affecting kernel development and causing quality defects, reducing the market value. While previous studies have identified bitter-tasting compounds in affected kernels, impact of feeding on metabolome, particularly concerning aroma precursors, remains underexplored. This study aims map nonvolatile metabolome volatilome samples obtained caging H. halys different cultivars two locations identify markers for diagnosing damage. Using multiomic approach involving headspace solid-phase microextraction (HS-SPME), comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOF MS), liquid chromatography-high-resolution (LC-HRMS), both raw roasted hazelnuts are analyzed, with artificial intelligence (AI) machine learning tools employed explore data correlations. finds that exhibit high chemical complexity classes such as aldehydes, ketones, alcohols, terpenes hazelnuts. Multivariate analysis indicates orchard location significantly impacts followed damage type, cultivar differences being less pronounced. Partial least-squares discriminant (PLS-DA) models achieve predictive accuracy (99%) type (≈80%), showing highest accuracy. Correlation matrices reveal relationships between metabolites samples, suggesting potential could guide assessment mitigation strategies. Data fusion techniques further enhance classification performance, predicting underscoring integrating multiple sets assessment.

Language: Английский

Precision or Personalized Nutrition: A Bibliometric Analysis DOI Open Access
Daniel Hinojosa-Nogueira, Alba Subiri-Verdugo, Cristina Diaz-Perdigones

et al.

Nutrients, Journal Year: 2024, Volume and Issue: 16(17), P. 2922 - 2922

Published: Sept. 1, 2024

Food systems face the challenge of maintaining adequate nutrition for all populations. Inter-individual responses to same diet have made precision or personalized (PN) an emerging and relevant topic. The aim this study is analyze evolution PN field, identifying principal actors topics, providing a comprehensive overview. Therefore, bibliometric analysis scientific research available through Web Science (WOS) database was performed, revealing 2148 papers up June 2024. VOSviewer WOS platform were employed processing analysis, included evaluation diverse data such as country, author most frequent keywords, among others. revealed period exponential growth from 2015 2023, with USA, Spain, England top contributors. field “Nutrition Dietetics” particularly significant, comprising nearly 33% total publications. highly cited institutions are universities Tufts, College Dublin, Navarra. relationship between nutrition, genetics, omics sciences, along dietary intervention studies, has been defining factor in PN. In conclusion, represents promising significant potential further advancement growth.

Language: Английский

Citations

2

Translating 2D-Chromatographic Fingerprinting to Quantitative Volatilomics: Unrevealing Compositional Changes in Maize Silage Volatilome for Robust Marker Discovery DOI
Andrea Caratti, Francesco Ferrero, Ernesto Tabacco

et al.

Journal of Agricultural and Food Chemistry, Journal Year: 2024, Volume and Issue: 72(42), P. 23616 - 23630

Published: Oct. 11, 2024

This study examines the complex volatilome of maize silage, both with and without commercial heterolactic strain inoculation, conserved for 100 days, using quantitative volatilomics. Chemical classes linked to microbial metabolism were analyzed across a concentration range from 10 μg g

Language: Английский

Citations

1

Artificial Intelligence Tools and Concepts Give Access to Authenticity and Quality Information in Brazilian Olive Oil Volatilome DOI
Nathália S. Brilhante, H. R. Bizzo, Andrea Caratti

et al.

Published: Jan. 1, 2024

Download This Paper Open PDF in Browser Add to My Library Share: Permalink Using these links will ensure access this page indefinitely Copy URL DOI

Language: Английский

Citations

0

Two-Dimensional Liquid Chromatography Advancing Metabolomics Research DOI

Yatendra Singh,

Sixue Chen

IntechOpen eBooks, Journal Year: 2024, Volume and Issue: unknown

Published: Oct. 2, 2024

Multidimensional separation systems offer several advantages over traditional one-dimensional systems, particularly their ability to separate molecules from complex mixtures. Two-dimensional liquid chromatography (2D-LC) significantly enhances the analyze mixtures by providing greater power, sensitivity, and flexibility, making it an invaluable tool for metabolomics research. The 2D-LC is exciting mode when pursuing untargeted analysis, as allows high-resolution subsequent identification quantification of more analytes. This chapter summarizes current applications in setups different modes that are being employed, presenting most suitable combinations chromatographic methods targeted applications.

Language: Английский

Citations

0

Artificial Intelligence tools and concepts give access to authenticity and quality information in Brazilian olive oil volatilome DOI
Nathália S. Brilhante, H. R. Bizzo, Andrea Caratti

et al.

Journal of Food Composition and Analysis, Journal Year: 2024, Volume and Issue: 136, P. 106826 - 106826

Published: Oct. 9, 2024

Language: Английский

Citations

0

Unrevealing the Halyomorpha halys Damage Fingerprint on Hazelnut Metabolome by Multiomic Platforms and AI-Aided Strategies DOI
Simone Squara, Silvia T. Moraglio, Andrea Caratti

et al.

Journal of Agricultural and Food Chemistry, Journal Year: 2024, Volume and Issue: 72(43), P. 24109 - 24129

Published: Oct. 16, 2024

The brown marmorated stink bug (Halyomorpha halys) poses a significant threat to hazelnut crops by affecting kernel development and causing quality defects, reducing the market value. While previous studies have identified bitter-tasting compounds in affected kernels, impact of feeding on metabolome, particularly concerning aroma precursors, remains underexplored. This study aims map nonvolatile metabolome volatilome samples obtained caging H. halys different cultivars two locations identify markers for diagnosing damage. Using multiomic approach involving headspace solid-phase microextraction (HS-SPME), comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOF MS), liquid chromatography-high-resolution (LC-HRMS), both raw roasted hazelnuts are analyzed, with artificial intelligence (AI) machine learning tools employed explore data correlations. finds that exhibit high chemical complexity classes such as aldehydes, ketones, alcohols, terpenes hazelnuts. Multivariate analysis indicates orchard location significantly impacts followed damage type, cultivar differences being less pronounced. Partial least-squares discriminant (PLS-DA) models achieve predictive accuracy (99%) type (≈80%), showing highest accuracy. Correlation matrices reveal relationships between metabolites samples, suggesting potential could guide assessment mitigation strategies. Data fusion techniques further enhance classification performance, predicting underscoring integrating multiple sets assessment.

Language: Английский

Citations

0