Open AccessNutritive quality prediction of peaches during storage
Author(s) -
Zhong Yuming,
Bao Yao,
Chen Yumin,
Zhai Dequan,
Liu Jianliang,
Liu Huifan
Publication year - 2021
Publication title -
food science and nutrition
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.614
H-Index - 27
ISSN - 2048-7177
DOI - 10.1002/fsn3.2287
Subject(s) - sugar , nutrient , fiber , food science , free sugar , reducing sugar , partial least squares regression , high protein , neutral detergent fiber , chemistry , horticulture , biology , mathematics , statistics , organic chemistry
Peaches ( Prunus persica L. Batsch) are commonly consumed fruits with high nutritional value. We evaluated the nutritive qualities of peach fruit during storage. Heatmap analysis showed that protein, ash, and crude fiber contents clustered together, whereas fat and reducing sugars clustered separately. We then classified the nutrients into two clusters; cluster 1 showed low fat and reducing sugar levels and high protein, crude fiber, and ash levels, whereas cluster 2 showed high fat and reducing sugar levels and low protein, cruder fiber, and ash levels. Partial least squares regression and random forest analyses showed accuracies of 67% and 61%, respectively. Spectra at 1,439 and 1,440 nm indicated reducing sugars, and the spectrum at 2,172 nm indicated protein. Thus, Fourier transform‐near infrared spectroscopy could predict the two clusters based on five nutritive qualities. Our findings may help to establish guidelines for promoting the acceptability of peach fruits among consumers.