Machine learning model interpretability using SHAP values: Applied to the task of classifying and predicting the nutritional content of different cuts of mutton
文献类型: 外文期刊
作者: Wang, Li 1 ; Sun, Xuchun 4 ; Liang, Jing 5 ; Ma, Zhiyuan 1 ; Li, Fei 1 ; Hao, Shengyan 6 ; Liu, Baocang 7 ; Guo, Long 1 ; Weng, Xiuxiu 1 ;
作者机构: 1.Lanzhou Univ, State Key Lab Herbage Improvement & Grassland Agro, Lanzhou 730020, Peoples R China
2.Lanzhou Univ, Minist Agr & Rural Affairs, Key Lab Grassland Livestock Ind Innovat, Lanzhou 730020, Peoples R China
3.Lanzhou Univ, Coll Pastoral Agr Sci & Technol, Lanzhou 730020, Peoples R China
4.Linxia Hui Autonomous Prefecture Anim Husb Technol, Linxia 731100, Peoples R China
5.Gansu Agr Univ, Lanzhou 730070, Peoples R China
6.Gansu Acad Agr Sci, Inst Anim Husb Pasture & Green Agr, Lanzhou 730070, Peoples R China
7.Xinjiang Aksu Taikun Feed Co Ltd, Aksu 842008, Peoples R China
关键词: Vis-NIR; Mutton; SHAP; SVM; Fatty acid
期刊名称:FOOD CHEMISTRY-X ( 影响因子:8.2; 五年影响因子:8.2 )
ISSN: 2590-1575
年卷期: 2025 年 29 卷
页码:
收录情况: SCI
摘要: The rapid identification and prediction of nutritional components in fresh meat products pose a significant challenge. This study aims to classify different cuts of fresh mutton and predict their nutritional components using SVM and PLS model, focusing on the differences in fatty acid composition among the longissimus lumborum, hindshank, and foreshank. An SVM-SHAP model predicted crude fat, protein, and fatty acids, while interpreting feature contributions. PUFA were significantly higher in the hindshank than in the longissimus lumborum and foreshank. The SVM model achieved a classification accuracy of 92.5 % and successfully predicted key nutritional parameters such as EE, CP, MUFA and PUFA with RPD values exceeding 2.7 in the test set. SHAP value analysis revealed that lipid-related variables and wavelengths in the 2300-2500 nm region were major contributors to the model. Vis-NIR-based SVM modeling technology is a fast, non-destructive, and accurate tool for evaluating fresh mutton.
- 相关文献
作者其他论文 更多>>
-
Aerial parts of Angelica sinensis supplementation for improved broiler growth and intestinal health
作者:Zhao, Xiangmin;Zhang, Jiawei;Yao, Yali;Li, Lulu;Sun, Likun;Qin, Shizhen;Tang, Defu;Hao, Shengyan;Nian, Fang
关键词:aerial parts of Angelica sinensis; broiler growth performance; intestinal barrier; intestinal homeostasis
-
Deep learning based on the Vis-NIR two-dimensional spectroscopy for adulteration identification of beef and mutton
作者:Wang, Li;Li, Fei;Guo, Tao;Shi, Yanli;Li, Fadi;Liang, Jing;Xu, Hui;Hao, Shengyan;Xu, Hui
关键词:2DCOS; Vis-NIR; Adulterated beef and mutton; Deep learning
-
Genetic diversity of Venturia inaequalis isolates from the scabs in apple trees in Gansu Province, China, using AFLP markers
作者:Lu, Zhaolong;Wang, Senshan;Li, Jiping;Lu, Zhaolong;Hui, Nana;Wang, Li;Zheng, Guo;Li, Jiping
关键词:Keywords Genetic diversity; V; inaequalis; AFLP molecular markers
-
Effect of additives and filling methods on whole plant corn silage quality, fermentation characteristics and in situ digestibility
作者:Jiao, Ting;Lei, Zhaomin;Wu, Jianping;Li, Fei;Wang, Jianfu;Jiao, Jianxin;Wu, Jianping;Casper, David P.
关键词:Corn Silage; Filling Times; Silage Additives; Silage Quality
-
Measurements of Chemical Compositions in Corn Stover and Wheat Straw by Near-Infrared Reflectance Spectroscopy
作者:Guo, Tao;Dai, Luming;Yan, Baipeng;Lan, Guisheng;Li, Fadi;Li, Fei;Pan, Faming;Wang, Fangbin
关键词:near-infrared reflectance spectroscopy; modified partial least squares; corn stover; wheat straw; nutritional value
-
Improving salt tolerance in potato through overexpression of AtHKT1 gene
作者:Wang, Li;Liu, Yuhui;Zhang, Junlian;Wang, Di;Wang, Li;Yang, Jiangwei;Zhang, Junlian;Feng, Shoujiang;Wang, Di;Zhang, Jingjing;Li, Dan;Gan, Yantai
关键词:AtHKT1 gene; Solanum tuberosum; K+; Na+ ratio; Photosynthetic rate; Stomatal conductance; Transpiration rate
-
AtHKT1 gene regulating K+ state in whole plant improves salt tolerance in transgenic tobacco plants
作者:Wang, Li;Liu, Yuhui;Zhang, Junlian;Wang, Di;Wang, Li;Zhang, Junlian;Feng, Shoujiang;Liu, Yuhui;Zhang, Jinwen;Wang, Di;Wang, Zhuoyu;Gan, Yantai
关键词:



