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利用近红外反射光谱法测定家禽胴体和胸肌样本中的粗蛋白和脂肪含量。

Determination of crude protein and fat in carcass and breast muscle samples of poultry by near infrared reflectance spectroscopy.

作者信息

Valdes E V, Summers J D

出版信息

Poult Sci. 1986 Mar;65(3):485-90. doi: 10.3382/ps.0650485.

DOI:10.3382/ps.0650485
PMID:3703793
Abstract

Near infrared reflectance spectroscopy (NIR) equipment used consisted of an InfraAlyzer 400+ fitted with 19 discrete filters and an HP-85 microcomputer. Calibrations were developed with chicken broiler carcass samples. Samples were divided into two sets: a calibration (CAL) from which equations were developed and a prediction (PRE) set used to validate the equations. The CAL and PRE sets in the carcass calibration consisted of 45 and 54 samples, respectively. Two equations were developed for the prediction of fat in carcass samples (FAT1 and FAT2). Calibration for breast muscle samples included 30 and 27 samples for CAL and PRE sets, respectively. The accuracy of the calibrations was measured by the coefficient of determination (r2), standard error of the estimate (SEE), coefficient of variation (CV), and the mean difference between NIR and chemical values (d). Repeatabilities of chemical and NIR procedures were determined by the F-ratio of the variance of the differences between replicates. The result of the regression analysis between chemical and NIR values indicated good predictions for crude protein (CP) and fat in carcass samples. The r2 and SEE for CP, FAT1, and FAT2 were .98, .94; .91, 2.48; and .91, 2.51 in CAL set; and .91, 1.03; .68, 2.32; and .69, 2.30 in PRE set samples, respectively. No differences were found between FAT1 and FAT2 equations. The carcass calibration equations were tested with samples from laying hens. Higher SEE were found for CP (1.78), but SEE for fat were similar to broiler carcasses. The calibration for breast samples showed higher SEE for CP and fat when compared with carcass samples.(ABSTRACT TRUNCATED AT 250 WORDS)

摘要

所使用的近红外反射光谱(NIR)设备包括一台配备19个离散滤光片的InfraAlyzer 400+和一台惠普85微型计算机。校准是用肉鸡胴体样本进行的。样本被分为两组:一组用于建立方程的校准(CAL)组和一组用于验证方程的预测(PRE)组。胴体校准中的CAL组和PRE组分别包含45个和54个样本。建立了两个用于预测胴体样本中脂肪的方程(FAT1和FAT2)。胸肌样本的校准中,CAL组和PRE组分别包含30个和27个样本。校准的准确性通过决定系数(r2)、估计标准误差(SEE)、变异系数(CV)以及NIR值与化学值之间的平均差异(d)来衡量。化学分析和NIR分析程序的重复性通过重复测量之间差异的方差的F比率来确定。化学值与NIR值之间的回归分析结果表明,对胴体样本中的粗蛋白(CP)和脂肪有良好的预测。CAL组中CP、FAT1和FAT2的r2和SEE分别为0.98、0.94;0.91、2.48;0.91、2.51;PRE组样本中分别为0.91、1.03;0.68、2.32;0.69、2.30。FAT1和FAT2方程之间未发现差异。用蛋鸡的样本对胴体校准方程进行了测试。发现CP的SEE较高(1.78),但脂肪的SEE与肉鸡胴体相似。与胴体样本相比,胸肌样本的校准显示CP和脂肪的SEE更高。(摘要截短于250字)

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