{"title":"DrYFiT:描述食品薄层干燥的 Excel 免费工具","authors":"Hasan Basri Öksüz, Sencer Buzrul","doi":"10.1111/jfpe.14748","DOIUrl":null,"url":null,"abstract":"<div>\n \n <p>We introduced DrYFiT (drying data fitting tool), a Microsoft Excel freeware tool to be used for modeling thin-layer drying of foods, which is available at https://drive.google.com/drive/folders/1ouompmNkmdmw1KMTJUnY0t8dJqSJ9iKv?usp=drive_link. There are 12 models in the tool and it can be used without any modeling and programming skills. Time and moisture ratio data can be entered and one of models available (one at a time) can be selected to describe the drying data. Parameter values, standard error of the parameters, <i>p</i> value and a statement that indicates whether the parameter is statistically significant or not (<i>α</i> = 0.05) are reported. Moreover, <i>R</i><sup>2</sup>, adjusted <i>R</i><sup>2</sup> and root mean square error values are calculated for each model. Users can instantaneously observe the experimental data and the model fit on the same graph. Residual plot is given next to this graph. It is possible for the users to have the results of all models applied to drying data within a couple of minutes. The results of DrYFiT were compared with some popular software programs used for nonlinear regression and identical values (parameters, standard errors, <i>p</i> values, goodness-of-fit statistics) were obtained for 40 datasets.</p>\n </div>","PeriodicalId":15932,"journal":{"name":"Journal of Food Process Engineering","volume":null,"pages":null},"PeriodicalIF":2.7000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"DrYFiT: An Excel Freeware Tool to Describe Thin Layer Drying of Foods\",\"authors\":\"Hasan Basri Öksüz, Sencer Buzrul\",\"doi\":\"10.1111/jfpe.14748\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n <p>We introduced DrYFiT (drying data fitting tool), a Microsoft Excel freeware tool to be used for modeling thin-layer drying of foods, which is available at https://drive.google.com/drive/folders/1ouompmNkmdmw1KMTJUnY0t8dJqSJ9iKv?usp=drive_link. There are 12 models in the tool and it can be used without any modeling and programming skills. Time and moisture ratio data can be entered and one of models available (one at a time) can be selected to describe the drying data. Parameter values, standard error of the parameters, <i>p</i> value and a statement that indicates whether the parameter is statistically significant or not (<i>α</i> = 0.05) are reported. Moreover, <i>R</i><sup>2</sup>, adjusted <i>R</i><sup>2</sup> and root mean square error values are calculated for each model. Users can instantaneously observe the experimental data and the model fit on the same graph. Residual plot is given next to this graph. It is possible for the users to have the results of all models applied to drying data within a couple of minutes. The results of DrYFiT were compared with some popular software programs used for nonlinear regression and identical values (parameters, standard errors, <i>p</i> values, goodness-of-fit statistics) were obtained for 40 datasets.</p>\\n </div>\",\"PeriodicalId\":15932,\"journal\":{\"name\":\"Journal of Food Process Engineering\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.7000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Food Process Engineering\",\"FirstCategoryId\":\"97\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1111/jfpe.14748\",\"RegionNum\":3,\"RegionCategory\":\"农林科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Food Process Engineering","FirstCategoryId":"97","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1111/jfpe.14748","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
DrYFiT: An Excel Freeware Tool to Describe Thin Layer Drying of Foods
We introduced DrYFiT (drying data fitting tool), a Microsoft Excel freeware tool to be used for modeling thin-layer drying of foods, which is available at https://drive.google.com/drive/folders/1ouompmNkmdmw1KMTJUnY0t8dJqSJ9iKv?usp=drive_link. There are 12 models in the tool and it can be used without any modeling and programming skills. Time and moisture ratio data can be entered and one of models available (one at a time) can be selected to describe the drying data. Parameter values, standard error of the parameters, p value and a statement that indicates whether the parameter is statistically significant or not (α = 0.05) are reported. Moreover, R2, adjusted R2 and root mean square error values are calculated for each model. Users can instantaneously observe the experimental data and the model fit on the same graph. Residual plot is given next to this graph. It is possible for the users to have the results of all models applied to drying data within a couple of minutes. The results of DrYFiT were compared with some popular software programs used for nonlinear regression and identical values (parameters, standard errors, p values, goodness-of-fit statistics) were obtained for 40 datasets.
期刊介绍:
This international research journal focuses on the engineering aspects of post-production handling, storage, processing, packaging, and distribution of food. Read by researchers, food and chemical engineers, and industry experts, this is the only international journal specifically devoted to the engineering aspects of food processing. Co-Editors M. Elena Castell-Perez and Rosana Moreira, both of Texas A&M University, welcome papers covering the best original research on applications of engineering principles and concepts to food and food processes.