高光谱成像
肉鸡
主成分分析
偏最小二乘回归
线性判别分析
近红外光谱
像素
数学
模式识别(心理学)
材料科学
生物
人工智能
计算机科学
食品科学
统计
神经科学
作者
Hongzhe Jiang,Seung-Chul Yoon,Hong Zhuang,Wei Wang,Yufeng Li,Chengjun Lu,Ning Li
标识
DOI:10.1016/j.infrared.2018.06.025
摘要
In poultry industry, the consensus is the final quality of chicken meat should be assessed at 24 h postmortem (PM). Visible and near-infrared (Vis/NIR, 400–1000 nm) hyperspectral imaging (HSI) was adopted to non-destructively assess final color (color24) and pH (pH24) of broiler breast fillets (pectoralis major). 25 fillets of the collected 75 broiler carcasses were deboned at each of three PM times (2, 4 or 24 h). To obtain representative spectra, regions of interest (ROIs) were extracted from hyperspectral images based on pixels selected from the 2-D scatter pixel plots of the first two principal component (PC) score images. Linear discriminant analysis (LDA) showed that color24 was affected by deboning time. Predictive models built with partial least squares regressions (PLSR) performed well for either a∗24 or b∗24 (Rp ≥ 0.87; RPD ≥ 2.02; RER ≥ 7.91), moderately for L∗24 (Rp = 0.75; RPD = 1.45; RER = 5.74), but unsatisfactorily for pH24 which was mainly due to its narrow value range (0.52). Simplified models based on optimal wavelengths selected by regression coefficients (RC) presented better predictive performances for a∗24 and b∗24 while slightly worse results for L∗24 and pH24. Distribution maps were created by pixels prediction in images, and color24 and pH24 within each broiler breast fillet were readily discernible. Overall, Vis/NIR HSI has a good potential to assess color24 and pH24 of chicken meat, but additional sample sizes should be further included to further enhance the prediction capability.
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