Lu Li , Xuejin Li , Ge Gao , Yiming Yan , Xiaodong Wang , Yao Tang , Yuqian Jiang , Xihong Li
{"title":"A kinetic model for predicting shelf-life of fresh extruded rice-shaped kernels (FER)","authors":"Lu Li , Xuejin Li , Ge Gao , Yiming Yan , Xiaodong Wang , Yao Tang , Yuqian Jiang , Xihong Li","doi":"10.1016/j.gaost.2022.09.001","DOIUrl":null,"url":null,"abstract":"<div><p>Fresh extruded rice-shaped kernels (FER) are remoulded rice products from cereals or seed flours, which have the advantages of safety, nutrition, health and time saving. However, the finished products are easy to react with oxygen, so it is necessary to develop a fast, simple and reliable approach to monitor and predict the shelf-life of FER. A comprehensive mathematical model of FER shelf-life prediction was developed using a dynamic modelling approach based on real supply chain conditions. This predictive model was developed to determine four key indexes including acid value, iodine blue value, water uptake ratio and peroxide value. The results showed that when the peroxide value was 1.6849, the FER lost its edible value, nutritional value and commodity value. Moreover, the acid value and peroxide value of FER were used to establish a first-order kinetic model, and the iodine blue value of FER was suited for a zero-order kinetic model. The validation experiment of predicted and measured shelf life showed that the relative error was 3.12%, which was less than 5%. Therefore, this kinetic model could be used to predict the shelf-life of FER quickly and conveniently. The kinetic-based shelf-life prediction model proposed in this study is rapid and practical, providing theoretical basis and guidance for the establishment of quality monitoring and quality evaluation systems of FER during the production, storage, transport and marketing.</p></div>","PeriodicalId":33614,"journal":{"name":"Grain Oil Science and Technology","volume":"5 4","pages":"Pages 187-193"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2590259822000346/pdfft?md5=5cf0a94b55c4b4ac33b2dd77d10bc38f&pid=1-s2.0-S2590259822000346-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Grain Oil Science and Technology","FirstCategoryId":"1087","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2590259822000346","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 0
Abstract
Fresh extruded rice-shaped kernels (FER) are remoulded rice products from cereals or seed flours, which have the advantages of safety, nutrition, health and time saving. However, the finished products are easy to react with oxygen, so it is necessary to develop a fast, simple and reliable approach to monitor and predict the shelf-life of FER. A comprehensive mathematical model of FER shelf-life prediction was developed using a dynamic modelling approach based on real supply chain conditions. This predictive model was developed to determine four key indexes including acid value, iodine blue value, water uptake ratio and peroxide value. The results showed that when the peroxide value was 1.6849, the FER lost its edible value, nutritional value and commodity value. Moreover, the acid value and peroxide value of FER were used to establish a first-order kinetic model, and the iodine blue value of FER was suited for a zero-order kinetic model. The validation experiment of predicted and measured shelf life showed that the relative error was 3.12%, which was less than 5%. Therefore, this kinetic model could be used to predict the shelf-life of FER quickly and conveniently. The kinetic-based shelf-life prediction model proposed in this study is rapid and practical, providing theoretical basis and guidance for the establishment of quality monitoring and quality evaluation systems of FER during the production, storage, transport and marketing.