Prediction of chicken quality attributes by near infrared spectroscopy
Prediction of chicken quality attributes by near infrared spectroscopy
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DOI：
10.1016/j.foodchem.2014.07.101
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发表时间：
2015-02-01
期刊：
影响因子：
8.8
通讯作者：
Hirooka, Elisa Yoko
中科院分区：
文献类型：
--
作者：
Barbin, Douglas Fernandes;Kaminishikawahara, Cintia Midori;Hirooka, Elisa Yoko
在本研究中，近红外（NIR）反射率测试作为一种潜在的技术预测鸡胸肉（胸大肌）质量属性。利用主成分分析（PCA）分析了400 ~ 2500 nm波长的光谱，利用偏最小二乘回归（PISR）预测了质量属性。对近红外数据集进行主成分分析，揭示了肌肉反射率（L*）对光谱的影响。PCA不能完全区分苍白、柔软和渗出性肌肉（PSE）和纯苍白肌肉。L*和pH模型分别预测得到高质量的PLSR （R-CV(2)分别为0.91和0.81，SECV分别为1.99和0.07）。持水能力是最难确定的属性（R-CV(2)为0.70，SECV为2.40%）。为了最大化模型的预测性能，样品混合和不同的光谱预处理是不必要的。结果表明，近红外光谱技术可作为鸡肉质量评价的有效工具。(C) 2014 Elsevier Ltd.版权所有。
In the present study, near-infrared (NIR) reflectance was tested as a potential technique to predict quality attributes of chicken breast (Pectoralis major). Spectra in the wavelengths between 400 and 2500 nm were analysed using principal component analysis (PCA) and quality attributes were predicted using partial least-squares regression (PISR). PCA performed on NIR dataset revealed the influence of muscle reflectance (L*) influencing the spectra. PCA was not successful to completely discriminate between pale, soft and exudative (PSE) and pale-only muscles. High-quality PLSR were obtained for L* and pH models predicted individually (R-CV(2) of 0.91 and 0.81, and SECV of 1.99 and 0.07, respectively). Water-holding capacity was the most challenging attribute to determine (R-CV(2) of 0.70 and SECV of 2.40%). Sample mincing and different spectra pre-treatments were not necessary to maximise the predictive performance of models. Results suggest that NIR spectroscopy can become useful tool for quality assessment of chicken meat. (C) 2014 Elsevier Ltd. All rights reserved.