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Evaluation of fresh sample of alfalfa silage through near infrared reflectance Spectroscopy (NIRS)

文献类型： 外文期刊

作者： Chen Peng-fei 1 ; Rong Yu-ping 2 ; Han Jian-guo 2 ; Wang Ji-hua 2 ; Zhang Lu-da 2 ; Xu Xiao-jie 2 ;

作者机构： 1.China Agr Univ, Coll Anim Sci & Technol, Beijing 100094, Peoples R China

2.China Agr Univ, Coll Anim Sci & Technol, Beijing 100094, Peoples R China; Natl Engn Res Ctr Informat Technol Agr, Beijing 100089, Peoples R China; China Agr Univ, Coll Sci, Beijing 100094, Peoples R China; Thermal Electron Technol & Instruments Co, Beijing 100032, Peoples R China

关键词： alfalfa silage; nutrient content; undried; near infrared reflectance spectroscopy

期刊名称：SPECTROSCOPY AND SPECTRAL ANALYSIS （ 影响因子：0.589； 五年影响因子：0.504 ）

ISSN： 1000-0593

年卷期： 2007 年 27 卷 7 期

页码：

收录情况： SCI

摘要： It is very important to evaluate the fresh sample of alfalfa silage using near infrared reflectance spectroscopy technology (NIRS) for animal production. The nutrient content of forage means the contents of dry matter (DM), crude protein (CP), neutral detergent fiber (NDF), and acid detergent fiber (ADF) in the forage. Because of the high moisture content, it is difficult to make uniform samples for fresh forage and to get useful information from the spectrum. Therefore, it is hard to use NIRS analysis. In order to evaluate the feasibility of using NIRS to analyse the fresh alfalfa silage, the DM, CP, NDF and ADF contents of fresh alfalfa silage were evaluated by the near infrared reflectance spectroscopy model in this experiment using partial least square regression (PLS), Fourier transform technology and sample preparation with liquid nitrogen technology. The analysis samples were obtained through different cultivars, maturity, cuttings and ensiling method. The cross validation was determined between 0.8846-0.9898. The standard error of cross validation was between 3.9 and 9.7 g . kg(-1) fresh weight. Fifty samples were used to test the performance of the models. The coefficients of correlation between the chemical value and the NIRS value are between 0.9397 and 0.9949, and the root mean square errors of prediction are between 1.9 and 8.3 g . kg(-1) fresh weight. The results showed that NIRS could be used to evaluate the nutrition of fresh forage.

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