Fruits and vegetables are highly vulnerable to postharvest spoilage caused by fungal infections, resulting in substantial economic losses and health risks due to mycotoxin contamination. Volatile organic compounds (VOCs), produced by both fungal pathogens and infected hosts, are increasingly recognized as valuable noninvasive biomarkers for the early detection of spoilage and toxigenic risks. This review provides a comprehensive overview of VOCs emitted by major postharvest fungal pathogens and infected fruits and vegetables, highlighting characteristic compounds with diagnostic potential. It further deliberates recent advances in VOC-based detection technologies based on gas chromatography-mass spectrometry (GC-MS), electronic noses (E-nose), and biosensors, emphasizing their performance, practical applicability, and technological limitations. The integration of artificial intelligence (AI) approaches, such as machine learning (ML) and deep learning (DL), is also discussed for effectively forecasting VOC biomarkers and diagnosing postharvest diseases. Finally, future research directions are proposed to guide the development of intelligent, rapid, and cost-effective VOC-based monitoring frameworks for improved postharvest disease management.
Volatile biomarkers of fungal infection and mycotoxin contamination in fruits and vegetables: emerging targets for monitoring and early warning / Zhu, Yatong; Chen, Yong; Xing, Mengyang; Romanazzi, Gianfranco; Tian, Shiping; Li, Boqiang. - In: CRITICAL REVIEWS IN FOOD SCIENCE AND NUTRITION. - ISSN 1040-8398. - 66:10(2025), pp. 2060-2073. [10.1080/10408398.2025.2562369]
Volatile biomarkers of fungal infection and mycotoxin contamination in fruits and vegetables: emerging targets for monitoring and early warning
Romanazzi, Gianfranco;
2025-01-01
Abstract
Fruits and vegetables are highly vulnerable to postharvest spoilage caused by fungal infections, resulting in substantial economic losses and health risks due to mycotoxin contamination. Volatile organic compounds (VOCs), produced by both fungal pathogens and infected hosts, are increasingly recognized as valuable noninvasive biomarkers for the early detection of spoilage and toxigenic risks. This review provides a comprehensive overview of VOCs emitted by major postharvest fungal pathogens and infected fruits and vegetables, highlighting characteristic compounds with diagnostic potential. It further deliberates recent advances in VOC-based detection technologies based on gas chromatography-mass spectrometry (GC-MS), electronic noses (E-nose), and biosensors, emphasizing their performance, practical applicability, and technological limitations. The integration of artificial intelligence (AI) approaches, such as machine learning (ML) and deep learning (DL), is also discussed for effectively forecasting VOC biomarkers and diagnosing postharvest diseases. Finally, future research directions are proposed to guide the development of intelligent, rapid, and cost-effective VOC-based monitoring frameworks for improved postharvest disease management.| File | Dimensione | Formato | |
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