Quality Assessment of Intact Chicken Breast Fillets Using Factor Analysis with Vis/NIR Spectroscopy
Quality Assessment of Intact Chicken Breast Fillets Using Factor Analysis with Vis/NIR Spectroscopy
复制标题
DOI：
10.1007/s12161-017-1102-0
复制
发表时间：
2018-05-01
影响因子：
2.9
通讯作者：
Li, Chunyang
中科院分区：
文献类型：
--
作者：
Yang, Yi;Zhuang, Hong;Li, Chunyang
采用400 ~ 2500nm波长范围的可见/近红外（Vis/NIR）光谱对鸡胸片质量进行了因子分析（FA）评价。根据内在相关性，从测得的8个品质性状（L*、a*、b*、pH、水分、滴漏损失、可表达液和盐致水增益）中提取3个因子。提取的“等级因子”（F(1)）、“颜色因子”（F(2)）和“水分因子”（F(3)）可以分别代表相应品质性状的特征和变化趋势，定义为3个新的品质评价指标。建立了偏最小二乘回归（PLSR）模型，定量分析了光谱信息与8个品质性状和3个因子之间的关系。结果表明，各因子的预测模型优于单个品质性状的预测模型。然后选择各品质性状的关键波长，并取相应的光谱建立新的PLSR预测模型。所选择的关键波长具有明显的实际意义，新模型的预测性能与基于全光谱的模型相当，其中F(1)和F(2)的新模型具有可接受且稳健的预测能力(R(2)p = 0.73, RPD = 1.91；R(2)p = 0.74, RPD = 1.97)。我们的研究结果表明，FA和Vis/NIR光谱是评估鸡胸片质量的有效方法。
Factor analysis (FA) method was tested to assess quality of chicken breast fillets with the visible/near-infrared (Vis/NIR) spectroscopy with wavelength range between 400 and 2500 nm. According to inherent correlation, three factors were extracted from the measured eight quality traits (L*, a*, b*, pH, moisture, drip loss, expressible fluid, and salt-induced water gain). The extracted "grade factor" (F (1)), "color factor" (F (2)), and "moisture factor" (F (3)) could respectively represent the characteristics and the variation tendency of the corresponding quality traits and were defined as three new quality assessment indexes. Furthermore, partial least squares regression (PLSR) models were established to quantitatively relate spectral information to eight individual quality traits and three factors. The results indicated that the models for predicting each factor performed better than those for individual quality traits. Key wavelengths of each quality trait were then selected, and the corresponding spectra were taken to build new PLSR prediction models. The selected key wavelengths showed obvious practical significance, and the new models had comparable predictive performance to those models developed based on the full spectra, among which the new models of F (1) and F (2) had acceptable and robust predictive abilities (R(2)p = 0.73, RPD = 1.91; R(2)p = 0.74, RPD = 1.97). Our results in the present study demonstrate the potential for FA and Vis/NIR spectroscopy as a useful method to assess the quality of chicken breast fillets.