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利用近红外反射光谱法对饲料中的脂肪酸进行定量分析。

Quantification of fatty acids in forages by near-infrared reflectance spectroscopy.

作者信息

Foster Joyce G, Clapham William M, Fedders James M

机构信息

Appalachian Farming Systems Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beaver, West Virginia 25813-9423, USA.

出版信息

J Agric Food Chem. 2006 May 3;54(9):3186-92. doi: 10.1021/jf052398u.

Abstract

Near-infrared reflectance spectroscopy (NIRS) was evaluated as a possible alternative to gas chromatography (GC) for the quantitative analysis of fatty acids in forages. Herbage samples from 11 greenhouse-grown forage species (grasses, legumes, and forbs) were collected at three stages of growth. Samples were freeze-dried, ground, and analyzed by GC and NIRS techniques. Half of the 195 samples were used to develop an NIRS calibration file for each of eight fatty acids, with the remaining half used as a validation data set. Spectral data, collected over a wavelength range of 1100-2498 nm, were regressed against GC data to develop calibration equations for lauric (C12:0), myristic (C14:0), palmitic (C16:0), stearic (C18:0), palmitoleic (C16:1), oleic (C18:1), linoleic (C18:2), and alpha-linolenic (C18:3) acids. Calibration equations had high coefficients of determination for calibration (0.93-0.99) and cross-validation (0.89-0.98), and standard errors of calibration and cross-validation were < 20% of the respective means. Simple linear regressions of NIRS results against GC data for the validation data set had r2 values ranging from 0.86 to 0.97. Regression slopes for C12:0, C14:0, C16:0, C18:0, C16:1, C18:2, and C18:3 were not significantly different (P = 0.05) from 1.0. The regression slope for C18:1 was 1.1. The ratio of standard error of prediction to standard deviation was > 3.0 for all fatty acids except C12:0 (2.6) and C14:0 (2.9). Validation statistics indicate that NIRS has high prediction ability for fatty acids in forages. Calibration equations developed using data for all plant materials accurately predicted concentrations of C16:0, C18:2, and C18:3 in individual plant species. Accuracy of prediction was less, but acceptable, for fatty acids (C12:0, C14:0, C18:0, C16:1, and C18:1) that were less prevalent.

摘要

近红外反射光谱法(NIRS)被评估为一种可能替代气相色谱法(GC)用于牧草中脂肪酸定量分析的方法。从11种温室种植的牧草品种(禾本科、豆科和杂类草)中采集处于三个生长阶段的牧草样本。样本经冷冻干燥、研磨后,采用气相色谱法和近红外反射光谱法进行分析。195个样本中的一半用于为8种脂肪酸分别建立近红外反射光谱法校准文件,另一半用作验证数据集。在1100 - 2498 nm波长范围内收集的光谱数据与气相色谱数据进行回归分析,以建立月桂酸(C12:0)、肉豆蔻酸(C14:0)、棕榈酸(C16:0)、硬脂酸(C18:0)、棕榈油酸(C16:1)、油酸(C18:1)、亚油酸(C18:2)和α-亚麻酸(C18:3)的校准方程。校准方程在校准(0.93 - 0.99)和交叉验证(0.89 - 0.98)方面具有较高的决定系数,校准和交叉验证的标准误差分别小于各自均值的20%。验证数据集的近红外反射光谱法结果与气相色谱数据的简单线性回归的r2值范围为0.86至0.97。C12:0、C14:0、C16:0、C18:0、C16:1、C18:2和C18:3的回归斜率与1.0无显著差异(P = 0.05)。C18:1的回归斜率为1.1。除C12:0(2.6)和C14:0(2.9)外,所有脂肪酸的预测标准误差与标准差之比均大于3.0。验证统计表明,近红外反射光谱法对牧草中脂肪酸具有较高的预测能力。使用所有植物材料的数据建立的校准方程能够准确预测各个植物物种中C16:0、C18:2和C18:3的浓度。对于不太常见的脂肪酸(C12:0、C14:0、C18:0、C16:1和C18:1),预测准确性较低,但可以接受。

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