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Effect of sample presentation and animal muscle species on the analysis of meat by near infrared reflectance spectroscopy

机译:样品呈现和动物肌肉种类对肉的近红外反射光谱分析的影响

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The useful wavelengths in both the visible and the near infrared region as well as two sample presentations (intact and minced) were evaluated to assess moisture (M), crude protein (CP) and intra muscular fat (IMF) in lamb (n = 300), beef (n = 100) and chicken (n = 48) muscle samples. Samples were scanned in reflectance in a NIRSystems 6500 (NIRSystems, Silver Spring, MD, USA). Predictive equations were performed using modified partial least squares (MPLS) with internal cross-validation. The coefficient of determination in calibration (R{sub}(CAL){sup}2) and the standard error in cross-validation (SECV) were calculated for each chemical parameter. For moisture, crude protein and fat (each expressed as g kg{sup}(-1), R{sub}(CAL){sup}2 and SECV for beef muscle were 0.98, 0.81 and 0.96, respectively, and SECV was 33.1, 21.8 and 44.8 for beef muscle; for chicken muscle the comparable statistics were 0.99, 0.97 and 0.95 and SECV was 6.9,2.4 and 33.1; while for lamb muscle R{sub}(CAL){sup}2 was 0.76, 0.83 and 0.73 and SECV 10.3, 5.5 and 4.7. It was concluded that the minced presentation is the best way to analyse muscle samples. On the other hand, intact presentation could have a great potential for use in the meat industry, although more research will be needed in order to determine quality attributes on meat samples.
机译:评价了可见光和近红外区域中的有用波长以及两个样品表现形式(完整和切碎),以评估羊羔中的水分(M),粗蛋白(CP)和肌肉内脂肪(IMF)(n = 300) ),牛肉(n = 100)和鸡肉(n = 48)肌肉样本。在NIRSystems 6500(NIRSystems,银泉,马里兰州,美国)中以反射率扫描样品。使用带有内部交叉验证的改进的偏最小二乘(MPLS)来执行预测方程。计算每个化学参数的校准测定系数(R {sub}(CAL){sup} 2)和交叉验证标准误差(SECV)。对于水分,粗蛋白和脂肪(分别表示为g kg {sup}(-1),R {sub}(CAL){sup} 2和牛肉的SECV分别为0.98、0.81和0.96,而SECV为33.1) ,牛肉的21.8和44.8;鸡肉的可比较统计数据分别为0.99、0.97和0.95,SECV为6.9、2.4和33.1;而羔羊的R {sub}(CAL){sup} 2为0.76、0.83和0.73以及SECV 10.3、5.5和4.7得出的结论是,切碎的呈现是分析肌肉样本的最佳方法;另一方面,完整的呈现可能在肉类行业中具有巨大的潜力,尽管在肉类行业仍需要更多的研究。为了确定肉样品的质量属性。

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