Nondestructive detection of Clonorchis sinensis infection of raw Pseudorasbora parva fish by near-infrared hyperspectral imaging

文献类型： 外文期刊

第一作者： Xu, Sai

作者： Xu, Sai;Lu, Huazhong;Liang, Xin;He, Zhenhui;Lu, Huazhong;Xu, Sai;Lu, Huazhong

作者机构：

关键词： Pseudorasbora parva; Clonorchis sinensis; Hyperspectral imaging; Nondestructive detection; Modeling

期刊名称：LWT-FOOD SCIENCE AND TECHNOLOGY （ 影响因子：6.0； 五年影响因子：6.0 ）

ISSN： 0023-6438

年卷期： 2024 年 203 卷

页码：

收录情况： SCI

摘要： Fish parasites adversely affect aquaculture and can be transmitted to humans via the food chain, necessitatingrapid, non-destructive detection methods. This research investigated the use of visible/near-infrared (VIS/NIR) hyperspectral imaging for the nondestructive identification of Clonorchis sinensis infected Pseudorasbora parva fish, with a 31.82% infection rate in the wild in China. Our analysis of various preprocessing, feature extraction, and modeling algorithm combinations revealed that using standard normal variate preprocessing, competitive adaptive reweighted sampling for feature selection, and partial least squares discriminant analysis significantly enhanced detection efficacy. Detection accuracies reached 99.24% and 93.93% for calibration and validation sets, respectively, based on the spectrum of whole fish. Detection accuracy varied among different fish parts, with the highest in the stomach, followed by the head, caudal fin, and back. Specifically, Stomach spectra achieved 99.24% and 93.93% accuracy for calibration and validation sets, respectively. Notably, a single local spectrum from a 15 x 15 pixel-sized area of the stomach detected parasites with 99.99% and 90.90% accuracy for calibration and validation sets, respectively, significantly increasing detection speed. This study provides a comprehensive methodology for the rapid, nondestructive detection of fish parasites via VIS/NIR hyperspectral imaging technology, demonstrating significant potential for application.

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