食品科学2026，Vol.47Issue(19)：312-321,10.DOI:10.7506/spkx1002-6630-20260326-201
高光谱与深度学习融合的黄瓜果实品质无损检测
Non-destructive Quality Detection of Cucumber Fruits Based on the Fusion of Hyperspectral Imaging and Deep Learning
摘要
Abstract
To address the limitations of current methods for determining the physicochemical properties of cucumber fruits,which require sample destruction and are time-consuming,labor-intensive,and unsuitable for large-scale testing.This study included cucumber fruits grown under five irrigation gradients.By combining hyperspectral imaging(HSI)technology with chemometric methods,this study developed predictive models for the soluble solids content,soluble sugar content,and firmness of cucumber fruits.The results indicated that the optimal prediction models for soluble solids,soluble sugars,and firmness in cucumber fruits were established using a convolutional neural network(CNN).The coefficients of determination for the prediction set(Rp2)of the models were 0.861 0,0.894 0,and 0.832 0,respectively,and the root mean square errors of prediction(RMSEP)were 0.145 0 °Brix,0.001 0%,and 3.415 0 N,respectively.Furthermore,the models enabled the visualization of the spatial distribution of these indicators,revealing the spatial heterogeneity of cucumber quality under different irrigation treatments and verifying the excellent predictive capability and high reliability of the models.In conclusion,hyperspectral imaging combined with chemometrics can achieve rapid,non-destructive detection of cucumber fruit quality.This method is systematic and highly accurate,providing a technical basis for the precision irrigation management and quality improvement of vegetables.关键词
黄瓜/高光谱成像技术/无损检测/品质/卷积神经网络/深度学习Key words
cucumber/hyperspectral imaging technology/non-destructive testing/quality/convolutional neural network/deep learning分类
农业科技引用本文复制引用
杨阳,王继涛,吴龙国,马骅,马小龙,寇尔丰,张恬,格桑曲珍,曹云娥..高光谱与深度学习融合的黄瓜果实品质无损检测[J].食品科学,2026,47(19):312-321,10.基金项目
国家自然科学基金地区科学基金项目(32260798) （32260798）
宁夏回族自治区国(境)外智力引进计划项目(宁科外专发[2023]2号) （境）
2025年自治区科技领军人才培养项目(2025GKLRLX22) （2025GKLRLX22）
