Application of multivariate machine learning methods to investigate organic compound content of different pepper spices  

作　　者：Yusuf Durmus Ahmet Ferit Atasoy 

机构地区：[1]Department of Gastronomy and Culinary Arts,School of Applied Sciences,ArtvinÇoruh University,Artvin,Turkiye [2]Faculty of Engineering,Department of Food Engineering,Harran University,63010,Sanlıurfa,Turkiye [3]Pepper and Isot Research and Application Center,Harran University,63010,Sanlıurfa,Turkiye

出　　处：《Food Bioscience》2023年第1期199-209,共11页食品生物科学（英文）

基　　金：Project Regional Development Administration,Republic of Turkiye Ministry of Development(Project:GAP-ISOT).

摘　　要：The aim of this study was to uncover all aspects and extract comprehensive and valuable information from thedata obtained from different pepper varieties using machine learning (ML) methods. The red pepper (RP),fabricated isot (FI), and customary isot (CI) spices were stored for 12 months and the variations in the organiccompound content were monitored every 3 months. The data set has been subjected to a supervised ML methodRandom Forest (RF), unsupervised ML methods principal component analysis (PCA), t-Distributed stochasticneighbor embedding (t-SNE), and hierarchical cluster analysis (HCA). The classification accuracy yielded by theRF model was 100%. RF model showed that terpenoids, acids, and alkanes were ineffective in identifying thedifferences between pepper spices, but glucose, succinic acid, citric acid, and fructose were primarily responsiblefor the variations between pepper spices. FI peppers differed significantly from other pepper spices in terms oftheir chemical compositions. Although most organic compounds exhibited positive correlations;furan-fructose,furan-glucose, furan-citric acid, and glucose-malic acid showed negative correlations. RP peppers were mostlystable for the first 6 months of storage, but after this month, due to changes in malic acid, aldehyde, glucose, andfructose, they displayed similar properties as CI. The organic compound content of CI peppers rapidly changed inthe first 3 months of storage and stayed almost stable for the remaining 9 months. Various ML methods wereeffectively employed in this study to examine the changes that different pepper spices exhibited in associationwith storage.Practical applications: Peppers, which are often used in food products for the purpose of bitterness, flavor, andcolor are mostly consumed after drying. The dried pepper is stored for a long time before consuming. Duringstorage, there are significant changes in the organic compound composition and pepper quality. In this study,revealing the changes in organic compound content in detail with mac

关 键 词：Pepper spices Machine learning PCA t-SNE Hierarchical clustering 

分 类 号：TS255[轻工技术与工程—农产品加工及贮藏工程]