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Assessing the value of a portable near infrared spectroscopy sensor for predicting pork meat quality traits of 'Asturcelta autochthonous swine breed'.

机译:评估便携式近红外光谱传感器在预测“阿斯旺氏猪本地猪品种”猪肉品质性状中的价值。

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Sixty-one intact meat samples from Asturcelta autochthonous swine breed were scanned in the slaughterhouse in reflectance mode. A handheld microelectromechanical system digital transform (Phazir1624, Polychromix Inc.), with a window sampling area of 0.8 x 1 cm and wavelengths ranging from 1,600 to 2,400 nm, was used. With the spectra database recorded were developed different chemometrical models assaying first and second derivatives as math treatment and standard normal variate (SNV) and multiplicative scatter correction for minimizing scattering effect. The greatest predictive capacity was achieved after applying SNV and first derivative for moisture, intramuscular fat (IMF) content, and pH parameters and second derivative for CIE L*, a*, b* colorimetric values, and the Warner-Bratzler force (instrumental texture). The coefficients of determination for calibration ranged from 0.63 to 0.89. The ratio between the standard error of the laboratory and the standard error of calibration ranged from 0.8 to 2.5 for all parameters (1.7 on average) with the exception of b and pH with ratios of 3.5 and 4.1, respectively. The statistical values obtained for the models developed to estimate IMF, CIE L*, a*, b*, moisture, and pH, displayed acceptable predictive capacity. For instrumental texture, the model could be able to discriminate among tender, medium, and hard meat in carcasses for characterization slaughter purposes. copyright Springer Science+Business Media New York 2013.
机译:在屠宰场以反射模式扫描了来自阿斯图尔克塔猪本地品种的61个完整肉样品。使用手持微机电系统数字转换(Phazir1624,Polychromix Inc.),其窗口采样面积为0.8 x 1 cm,波长范围为1600至2,400 nm。利用记录的光谱数据库,开发了不同的化学计量学模型,可将一阶和二阶导数作为数学处理和标准正态变量(SNV)以及乘法散射校正来最小化散射效应。在对水分,肌内脂肪(IMF)含量和pH参数应用SNV和一阶导数以及对CIE L *,a *,b *比色值和Warner-Bratzler力(仪器质地)应用SNV和一阶导数后,获得了最大的预测能力)。校准的确定系数范围为0.63至0.89。对于所有参数,实验室的标准误差与校准的标准误差之间的比率范围为0.8至2.5(平均为1.7),但b和pH的比率分别为3.5和4.1。为估计IMF,CIEL *,a *,b *,水分和pH而开发的模型获得的统计值显示出可接受的预测能力。对于工具质地,该模型可以区分屠体中的嫩肉,中肉和硬肉,以表征屠宰目的。版权所有Springer Science + Business Media纽约,2013年。

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