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Position: Home > Articles > Predicting fecal composition of grazing beef cattle by near infrared spectroscopy Pratacultural Science 2020 (1) 178-184

近红外技术预测放牧肉牛粪便组分

作  者：
徐锦前;侯路路;蒋梦宇;闫瑞瑞;王亚君;辛晓平;孙海霞
单  位：
东北林业大学野生动物资源学院;东北农业大学动物科学技术学院;中国农业科学院农业资源与农业区划研究所;中国科学院东北地理与农业生态研究所
关键词：
近红外光谱分析;预测;放牧肉牛;牛粪;组分;模型;可行性
摘  要：
在中国农业科学院呼伦贝尔草原生态系统国家野外科学观测研究站,以全粪收集法收集放牧牛粪便72份,采用偏最小二乘法(PLS),结合不同光谱处理和软件分析,建立放牧牛粪便中组分的近红外分析定标模型,分析碳(C)、氮(N)、有机物(OM)、酸性洗涤纤维(ADF)和中性洗涤纤维(NDF)的预测结果,探讨利用近红外光谱分析技术(NIRS)对放牧肉牛粪便组分进行分析的可行性。结果表明,C、N、OM、ADF、NDF的建模时决定系数(R~2)分别为0.90、0.96、0.91、0.23、0.49;相对分析误差(RPD)分别为2.45、2.81、1.94、1.00、1.09。说明应用NIRS技术测定粪便中C、N含量可行,后续应用还需扩充模型数据量,提高精确度;对于OM、ADF、NDF则不可行,还需进一步研究分析。
译  名：
Predicting fecal composition of grazing beef cattle by near infrared spectroscopy
作  者：
XU Jinqian;HOU Lulu;JIANG Mengyu;YAN Ruirui;WANG Yajun;XIN Xiaoping;SUN Haixia;College of Wildlife Resources, Northeast Forestry University;Institute of Agricultural Resources and Regional Planing, Chinese Academy of Agricultural Science;Animal Science and Technology College of Northeast Agricultural University;Northeast Institute of Geography and Agroecology, CAS;
关键词：
near infrared spectroscopy;;prediction;;grazing beef cattle;;beef feces;;component;;model;;feasibility
摘  要：
The study evaluated the feasibility of near infrared spectroscopy(NIRS) to predict the feces composition of grazing beef cattle. The experiment was conducted in the long-term grazing experimental platform of the National Field Observation and Research Station of the Hulun Buir Grassland Ecosystem in the Chinese Academy of Agricultural Sciences.The feces samples of 72 grazing beef cattle were collected using the whole fecal collection method and analyzed using the partial least squares(PLS) method, combined with different spectral processing and software analyses. A calibration model for near infrared analysis of fecal components was established and evaluated by the predicting parameters of C, N, OM, ADF and NDF. The coefficient of determination(R~2) of C, N, OM, ADF and NDF was 0.90, 0.96, 0.91, 0.23, and 0.49, and the relative analysis error(RPD) was 2.45, 2.81, 1.94, 1.00, and 1.09, respectively. The model could be used to predict the fecal content of C and N in grazing beef cattle, but the prediction accuracy needs further improvement. For OM, ADF and NDF need further study and analysis.

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