文献类型：期刊文献

英文题名：Hyperspectral imaging for predicting and visualizing the acrylamide levels in roasted coffee

作者：Xie, Chuanqi[1];Tang, Wensheng[2];Wang, Changyan[3];Zhang, Yanchao[4];Zhao, Mengyao[3]

机构：[1]Zhejiang Acad Agr Sci, Inst Anim Husb & Vet Sci, State Key Lab Managing Biot & Chem Threats Qual &, Hangzhou 310021, Peoples R China;[2]Huangyan Bur Agr & Rural Affairs, Inst Anim Husb & Vet Sci, Taizhou 318020, Peoples R China;[3]East China Univ Sci & Technol, Sch Biotechnol, State Key Lab Bioreactor Engn, Shanghai 200237, Peoples R China;[4]Zhejiang Sci Tech Univ, Sch Informat Sci & Engn, Hangzhou 310018, Peoples R China

年份：2024

卷号：202

外文期刊名：MICROCHEMICAL JOURNAL

收录：;WOS:【SCI-EXPANDED(收录号:WOS:001243035600001)】；

基金：This work was supported by Zhejiang Provincial Natural Science Foundation of China (ZCLTGN24C1301) and the National Natural Sci- ence Foundation for Young Scientists of China (31801668) .

语种：英文

外文关键词：Hyperspectral imaging; Acrylamide content; Roasted coffee; Prediction; Visualization

摘要：Since it is carcinogenic to humans, the acrylamide content in heat-processed foods should be detected and controlled. This study investigated the spatial distribution and visualization of the acrylamide content in roasted coffee. First, hyperspectral images were collected, from which the spectral-pixel features were extracted. Besides partial least square (PLS), five wavelengths (888, 1123, 1456, 1636, and 1734 nm) based on the successive projections algorithm (SPA) were used to establish prediction models (multiple linear regression (MLR), CatBoost, and XgBoost). SPA-MLR presented the optimal outcome, with a prediction coefficient of determination (Rp2) and a root mean square error of prediction (RMSEP) of 0.81 and 35.90 mu g/kg, respectively. The acrylamide content values for all pixels in the hyperspectral images were subsequently calculated using the prediction equation, thereby producing the spatial distribution and visualization images. The results demonstrated that hyperspectral imaging can effectively predict and visualize the acrylamide levels in roasted coffee.