文献类型：期刊文献

英文题名：Nondestructive determination of soluble solids content and pH in red bayberry (Myrica rubra) based on color space

作者：Feng, Jie[1,2];Jiang, Lingling[3];Zhang, Jialei[1,2];Zheng, Hong[3];Sun, Yanfang[1,2];Chen, Shaoning[1,2];Yu, Meilan[1,2];Hu, Wei[1,2];Shi, Defa[4];Sun, Xiaohong[5];Lu, Hongfei[1,2]

机构：[1]Zhejiang Sci Tech Univ, Coll Life Sci & Med, Hangzhou 310018, Peoples R China;[2]Zhejiang Prov Key Lab Plant Secondary Metab & Reg, Hangzhou 310018, Peoples R China;[3]Wenzhou Med Univ, Sch Pharmaceut Sci, Wenzhou 325035, Peoples R China;[4]Zhejiang Univ Sci & Technol, Sch Civil Engn & Architecture, Hangzhou 310023, Peoples R China;[5]Shaoxing Univ, Yuanpei Coll, Shaoxing 312000, Peoples R China

年份：2020

卷号：57

期号：12

起止页码：4541

外文期刊名：JOURNAL OF FOOD SCIENCE AND TECHNOLOGY-MYSORE

收录：SCI-EXPANDED(收录号：WOS:000558882600001)、、EI(收录号：20202208760012)、Scopus(收录号：2-s2.0-85085375605)、WOS

基金：This study was funded by Zhejiang Provincial Top Key Discipline of Biology, Zhejiang Provincial Universities Key Discipline of Botany and the Natural Science Foundation of Zhejiang Province (LQ19C160003).

语种：英文

外文关键词：Red bayberry; pH value; Soluble solids content; PLSR; LS-SVM

外文摘要：Color has strong relationship with food quality. In this paper, partial least square regression (PLSR) and least square-support vector machine (LS-SVM) models combined with six different color spaces (NRGB, CIELAB, CMY, HSI, I1I2I3, and YCbCr) were developed and compared to predict pH value and soluble solids content (SSC) in red bayberry. The results showed that PLSR and LS-SVM models coupled with color space could predict pH value in red bayberry (r = 0.93-0.96, RMSE = 0.09-0.12, MAE = 0.07-0.09, and MRE = 0.04-0.06). In addition, the minimum errors (RMSE = 0.09, MAE = 0.07, and MRE = 0.04) and maximum correlation coefficient value (r = 0.96) were found with the PLSR based on CMY, I1I2I3, and YCbCr color spaces. For predicting SSC, PLSR models based on CIELAB color space (r = 0.90, RMSE = 0.91, MAE = 0.69 and MRE = 0.12) and HSI color space (r = 0.89, RMSE = 0.95, MAE = 0.73 and MRE = 0.13) were recommended. The results indicated that color space combined with chemometric is suitable to non-destructively detect pH value and SSC of red bayberry.