Chen Peng-fei, Rong Yu-ping, Han Jian-guo
College of Animal Science and Technology, China Agricultural University, Beijing.
Guang Pu Xue Yu Guang Pu Fen Xi. 2008 Dec;28(12):2799-803.
It is very important to evaluate the fermentation character of alfalfa silage using near infrared reflectance spectroscopy technology (NIRS) for animal production, including the content of NH3-N, lactic acid, acetic acid and butyric acid in silage. In order to evaluate the feasibility of using NIRS to analyze the formation character of alfalfa silage, the near infrared reflectance spectroscopy models were built for NH3-N, lactic acid, zcetic acid and butyric acid in this experiment. Partial least square regression (PLS), Fourier transform technology and sample preparation with liquid nitrogen technology were used to optimize the model. The analyzed samples were obtained with different cultivars, maturity, cuttings and ensiling method. The determination of cross validation was between 0.6024 and 0.9497. The standard errors of cross validation were between 5.59 x 10(-1) and 3.78 g x kg(-1) fresh weight. The validation samples were used to test the performance of the models. The correlation coefficients between the chemical value and the NIRS value were between 0.8826 and 0.9853, and the root mean square errors of prediction were between 5.71 x 10(-1) and 3.15 g x kg(-1) fresh weight. The results showed the NIRS could evaluate the fermentation of the fresh forage.
利用近红外反射光谱技术(NIRS)评估苜蓿青贮饲料的发酵特性对于动物生产非常重要,包括青贮饲料中氨态氮、乳酸、乙酸和丁酸的含量。为了评估使用NIRS分析苜蓿青贮饲料形成特性的可行性,本实验建立了氨态氮、乳酸、乙酸和丁酸的近红外反射光谱模型。采用偏最小二乘回归(PLS)、傅里叶变换技术和液氮制样技术对模型进行优化。分析样品来自不同品种、成熟度、刈割次数和青贮方法。交叉验证的测定值在0.6024至0.9497之间。交叉验证的标准误差在5.59×10⁻¹至3.78 g·kg⁻¹鲜重之间。使用验证样品测试模型性能。化学值与NIRS值之间的相关系数在0.8826至0.9853之间,预测的均方根误差在5.71×10⁻¹至3.15 g·kg⁻¹鲜重之间。结果表明,NIRS可以评估新鲜草料的发酵情况。