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使用近红外光谱结合多变量分析验证青贮饲料类型

Verification of silage type using near-infrared spectroscopy combined with multivariate analysis.

作者信息

Cozzolino D, Fassio A, Restaino E, Fernandez E, La Manna A

机构信息

Instituto Nacional de Investigación Agropecuaria, Estación Experimental Alberto Boerger, INIA La Estanzuela, Ruta 50, km 12, Colonia, Uruguay.

出版信息

J Agric Food Chem. 2008 Jan 9;56(1):79-83. doi: 10.1021/jf072566d. Epub 2007 Nov 27.

DOI:10.1021/jf072566d
PMID:18038995
Abstract

The ability to authenticate the feed given to animals has become a major challenge in animal production, where the diet fed to the animal is one of the most important production factors affecting the composition of milk and meat from cattle, sheep, and goats. Hence, there is currently an increased consumer demand for information on herbivore production factors and particularly the animal diet. The aim of this study was to evaluate the reliability and accuracy of near-infrared (NIR) reflectance spectroscopy as a tool to verify and authenticate the type of silage used as fed for ruminants. Grain silage (GrS, n = 94), grass and legume silage (GLegS, n = 121), and sunflower silage (SunS, n = 50) samples were collected from commercial farms and analyzed in the visible and NIR regions (400-2500 nm) in a monochromator instrument in reflectance. Principal component analysis (PCA), partial least-squares discriminant analysis (PLS1-DA), and linear discriminant analysis (LDA) models were used as methods to verify the different silage types. The classification models based on the NIR data correctly classified more than 90% of the silage samples according to their type. The results from this study showed that NIR spectra combined with multivariate analysis could be used as a tool to objectively authenticate silage samples used as a feed for ruminants.

摘要

验证供给动物的饲料已成为动物生产中的一项重大挑战,在动物生产中,动物的饮食是影响牛、羊和山羊奶和肉成分的最重要生产因素之一。因此,目前消费者对草食动物生产因素尤其是动物饮食信息的需求有所增加。本研究的目的是评估近红外(NIR)反射光谱作为一种工具来验证和鉴别反刍动物所用青贮饲料类型的可靠性和准确性。从商业农场收集了谷物青贮饲料(GrS,n = 94)、禾本科和豆科青贮饲料(GLegS,n = 121)以及向日葵青贮饲料(SunS,n = 50)样本,并在一台单色仪仪器中于可见和近红外区域(400 - 2500 nm)以反射模式进行分析。主成分分析(PCA)、偏最小二乘判别分析(PLS1 - DA)和线性判别分析(LDA)模型被用作验证不同青贮饲料类型的方法。基于近红外数据的分类模型根据青贮饲料类型正确分类了超过90%的青贮样本。本研究结果表明,近红外光谱结合多变量分析可作为一种工具来客观鉴别用作反刍动物饲料的青贮样本。

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