Predicting the Freshness of Starch-Coated Snakehead Fish Fillets During Storage Using Hyperspectral Imaging Combined with Transfer Learning.

Mingyuan Sha, Zemao Chen, Jingxiao Yu, Qingyi Wei

Abstract read

In one paragraph

Article in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 authors.

Mingyuan ShaJinan University-University of Birmingham Joint Institute, Jinan University, Guangzhou 511443, China.

Zemao ChenSchool of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China.

Jingxiao YuSchool of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China.ORCID 0009-0008-0697-2632

Qingyi WeiSchool of Food Science and Engineering, South China University of Technology, Guangzhou 510641, China.

Funding

South China University of Technology 2025B03J0124

6 · The paper itself

Abstract

Freshness prediction of starch-coated snakehead fish fillets across different storage times remains challenging due to complex quality deterioration and spectral distribution shifts. In the current research, hyperspectral imaging (HSI) combined with transfer learning (TL) was developed to predict the freshness of starch-coated snakehead fish fillets during short-term refrigerated and long-term frozen storage. The results showed that storage led to texture deterioration, pH increase, TVB-N accumulation, and lipid oxidation, while starch coating effectively delayed quality degradation. Compared with models based only on short-term or long-term data, the domain transfer convolutional neural network (DT-CNN) model improved the robustness of freshness prediction across storage stages. The DT-CNN model based on VIS spectra achieved the best performance for TBA prediction in the starch coating treatment group, with an

Indexed as

freshness predictionhyperspectral imagingstarch-coated snakehead fish fillettransfer learning

Identifiers

PMID42354159

DOI10.3390/foods15122191

PMCPMC13298243

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.