https://scholars.lib.ntu.edu.tw/handle/123456789/573133
標題: | Intelligent assessment of the histamine level in mackerel (Scomber australasicus) using near-infrared spectroscopy coupled with a hybrid variable selection strategy | 作者: | Pauline O Chang H.-T Tsai I.-L Lin C.-H SUMING CHEN Chuang Y.-K. |
關鍵字: | Calibration; Fish; Infrared devices; Mean square error; Near infrared spectroscopy; Radial basis function networks; Backward interval partial least square; Flower pollination algorithm; Histamines; Hybrid variables; Infrared: spectroscopy; Near Infrared; Near-infrared; Neural-networks; Partial least-squares; Selectivity ratio; Least squares approximations | 公開日期: | 2021 | 卷: | 145 | 來源出版物: | LWT | 摘要: | Determination of the histamine level in fish is essential not only because it is an indicator of fish freshness but also because this prevents the risk of histamine intoxication in consumers. This study used the strategy of near-infrared (NIR) spectroscopy coupled with a hybrid variable selection for rapid and nondestructive assessment of the histamine level in mackerel. To effectively identify the highly informative spectral variables, a three-step hybrid strategy, combining backward interval partial least squares, selectivity ratio and flower pollination algorithm, was developed. The optimized variables were fitted to the multivariate calibration models of partial least squares model (PLS), radial basis function neural network (RBFNN), and wavelet neural network (WNN). The best model was obtained by the optimized WNN model using the hybrid variable selection method, with R-squared (RP2) value and root mean squared error for prediction were, 0.79 and 70 mg/kg for flesh side dataset, and 0.76 and 75 mg/kg for skin side dataset. The obtained results for the skin side dataset significantly outperformed the PLS(RP2=0.58) and RBFNN (RP2=0.47) calibration models. ? 2021 Elsevier Ltd |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85104795828&doi=10.1016%2fj.lwt.2021.111524&partnerID=40&md5=127f9a3059728782601ef58c055147fb https://scholars.lib.ntu.edu.tw/handle/123456789/573133 |
ISSN: | 236438 | DOI: | 10.1016/j.lwt.2021.111524 |
顯示於: | 生物機電工程學系 |
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