食品与发酵工业2026，Vol.52Issue(6)：222-230,中插16-中插17,11.DOI:10.13995/j.cnki.11-1802/ts.043703
基于人工神经网络的鲜腐竹天然保鲜剂复配优化与品质调控
Artificial neural network-based formulation optimization of natural preservative and quality regulation for fresh yuba
摘要
Abstract
To explore the natural preservatives(chitosan hydrochloride,ε-polylysine hydrochloride,and Nisin)on fresh yuba,to determine the optimal combination concentration of preservatives.Single factor and compound experiments were used to detect the sensory quality,pH,total volatile basic nitrogen(TVB-N),thiobarbituric acid(TBA),and the total number of colonies of fresh yuba during stor-age.BP-ANN model based on the quality of fresh yuba during storage was established to explore the preservation effect of different preserv-atives on fresh yuba.The results showed that three kinds of preservatives had certain preservation effects on fresh yuba,and the best com-bination of three types of preservatives was chitosan hydrochloride 1.5％,ε-polylysine hydrochloride 0.04％,Nisin 1％which could sig-nificantly prolong the storage life of fresh yuba,4 days longer than that of blank group at 25 ℃.BP-ANN model RMSE=0.108 for the test set and RMSE=0.066 49 for the training set.The prediction accuracy is good and fitting effect is excellent.It provides a scientific basis for the development of fresh yuba preservation technology and the extension of shelf life.关键词
鲜腐竹/天然保鲜剂/贮藏期/反向传播-人工神经网络Key words
fresh yuba/natural preservatives/storage period/back propagation-artificial neural network(BP-ANN)model引用本文复制引用
程可玉,白卫东,魏先领,龙泳霖,谢子祺,杨欣琛,肖斯立,朱传明,朱开玄,钱敏,董浩..基于人工神经网络的鲜腐竹天然保鲜剂复配优化与品质调控[J].食品与发酵工业,2026,52(6):222-230,中插16-中插17,11.基金项目
广东省"百千万工程"农村科技特派员项目(KTP20240162,KTP20240152) （KTP20240162,KTP20240152）
广东省岭南特色食品科学与技术重点实验室开放基金项目(2025省001-2) （2025省001-2）
河源市2024年度农村科技特派员专题项目(2025004) （2025004）
广东和平腐竹科技小院项目(KA25YY16750) （KA25YY16750）
