Exploring aroma descriptions of different cherry juice and the mechanism of aroma formation in Lapins using volatilomics and machine learning.

Volatileomics and machine learning characterized cherry juice volatile organic compounds (VOCs) to compare flavor differences and identify processing-suitable varieties, with in-depth analysis of aroma formation in Lapins. Aldehydes and esters were primary differential volatile compounds (DVCs) in cherry juice. Through orthogonal partial least squares discriminant analysis (OPLS-DA), neural network modeling and odor activity value (OAV) analysis, 6-methyl-5-hepten-2-one, butyl propanoate, butanoic acid and rose oxide were identified as key DVCs, with highest OAVs in Lapins. Based on the DVCs and OAV results of different varieties of cherry juice, it was determined that Lapins had the most prominent aroma. The mechanism of aroma formation was analyzed, which involved the metabolism of pyruvic acid, amino acids, fatty acids and carotenoids. This study established a framework for DVC characterization and multimodal aroma analysis, enabling data-driven processing optimization and variety selection. These will advance cherry valorization pathways, enhancing resource efficiency and agricultural circularity.