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Ability of near infrared spectroscopy to predict pork technological traits

机译:近红外光谱预测猪肉技术性状的能力

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The predictive ability of near infrared spectroscopy was studied for some fresh meat quality traits: pH{sub}24, colour parameters (L{sup}*, a{sup}* and b{sup}*) and drip loss (measured after 24 and 48 hours). The material used in this study involved 296 pig longissimus dorsi muscle samples originating from various hybrids of different carcass weight, two abattoirs and five series of slaughter. Samples were scanned both intact and minced over the wavelength range 400-2500 nm using an NIRSystems model 6500 spectrophotometer. Modified partial least squares (PLS) was used to develop models and to obtain calibration statistics: coefficient of determination of calibration and cross-validation ((R{sup}2){sub}(CV)) and standard error of calibration and cross-validation (SECV). The predictive ability of near infrared (NIR) spectroscopy was additionally tested on an independent set of samples and prediction statistics calculated. Best calibrations were obtained on intact meat samples using the spectral range 400-1100 nm. For these models, the (R{sup}2){sub}(CV) values were in the range of 0.54-0.79 and SECV values were 0.10 for pH{sub}24, 2.4 for L{sup}*, 0.8 for a{sup}*, 0.9 for b{sup}*, 1.6% for drip24 and 2.1% for drip48. Within-sample standard deviation (repeatability) of reference measurements was 0.05 for pH{sub}24, 3.1 for L{sup}*, 1.0 for a{sup}*, 0.9 for b{sup}*, 1.1% for drip24 and 1.3% for drip48, indicating limitations in NIR spectroscopy's predictive ability due to the precision of reference methods used for calibration. Prediction errors obtained on the validation set (0.08 for pH{sub}24,2.0 for L{sup}*, 0.8 for a{sup}*, 0.7 for b{sup}*, 1.4% for drip24 and 1.7% for drip48) were in agreement with cross-validation results. Similar model performance was found for driploss prediction (PLS regression) based on spectral information or on a combination of pH{sub}24, L{sup}*, a{sup}*, b{sup}*.
机译:研究了近红外光谱对某些鲜肉品质性状的预测能力:pH {sub} 24,颜色参数(L {sup} *,a {sup} *和b {sup} *)和滴水损失(24后测量)和48小时)。本研究中使用的材料涉及296头猪背最长肌肌肉样品,这些样品来自不同car体重量,两个屠宰场和五个屠宰场的各种杂种。使用NIRSystems 6500型分光光度计在400-2500 nm的波长范围内完整和切碎地扫描样品。修改后的偏最小二乘(PLS)用于开发模型并获得校准统计数据:校准和交叉验证的确定系数((R {sup} 2){sub}(CV))以及校准和交叉验证的标准误差验证(SECV)。另外在一组独立的样本上测试了近红外(NIR)光谱的预测能力,并计算了预测统计量。使用400-1100 nm的光谱范围对完整的肉样品进行最佳校准。对于这些模型,(R {sup} 2){sub}(CV)值在0.54-0.79范围内,pH {sub} 24的SECV值为0.10,L {sup} *的SECV值为2.4,a {sup} *的SECV值为0.8。 {sup} *,b {sup} *为0.9,drip24为1.6%,drip48为2.1%。 pH {sub} 24的参考测量的样品内标准偏差(重复性)为0.05,L {sup} *的为3.1,a {sup} *的为1.0,b {sup} *的为0.9,drip24和1.1的为1.1%滴48%,表明由于用于校准的参考方法的精度,近红外光谱学的预测能力受到限制。在验证集上获得的预测误差(pH {sub} 24为0.08,L {sup} *为2.0,a {sup} *为0.8,b {sup} *为0.7,滴灌24为1.4%,滴灌为1.7%48)与交叉验证结果一致。在基于光谱信息或pH {sub} 24,L {sup} *,a {sup} *,b {sup} *的组合的滴漏预测(PLS回归)中发现了相似的模型性能。

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