期刊论文

Hu, ZG

英文

Journal of Food Composition and Analysis

0889-1575

2024

126

105871

10.1016/j.jfca.2023.105871

This work was supported by the Hubei Province Technology Innovation special fund [grant number 2019ABA085], Key-Area Research and Development Program of Hubei Province [grant number 2023BBB042]. Author statement Qinyu Zhang: Conceptualization, Methodology, Software, Investigation, Formal analysis, Data curation, Writing – original draft, Writing – review & editing. Zhigang Hu: Conceptualization, Methodology, Project administration, Resources, Writing – review & editing, acquisition. Zijian Xu: Investigation, Writing – review & editing. Peilin Zhang: Investigation, Validation, Writing – review & editing. Yajun Jiang: Resources, Supervision, Writing – review & editing. Dandan Fu: Resources, CRediT authorship contribution statement Hu Zhigang: Conceptualization, acquisition, Methodology, Project administration, Resources, Writing – review & editing. Zhang Peilin: Investigation, Validation, Writing – review & editing. Xu Zijian: Investigation, Writing – review & editing. Zhang Qinyu: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Software, Writing – original draft, Writing – review & editing. Fu Dandan: acquisition, Resources, Supervision, Writing – review & editing. Jiang

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This research aims to accurately forecast the freshness indicators (TVB-N) of skinned and skinless grass carp fillets by integrating near-infrared spectroscopy (NIR) with machine learning algorithms. By comparing the predictive accuracy of machine learning models for the two types of grass carp fillets, the most effective modeling method is identified. Methodologically, the study first applies orthogonal signal correction (OSC) and the first derivative among other algorithms for spectral pre-processing. Subsequently, competitive adaptive reweighted sampling (CARS), moving window partial least ...