玉米秸秆饲料营养成分NIRS在线检测  

On-line Measurement of Nutrient Content of Corn Stover Using NIRS

作　　者：薛俊杰[1] 韩鲁佳[1] 杨增玲[1] 沈广辉 刘雨晨 

机构地区：[1]中国农业大学工学院,北京100083

出　　处：《农业机械学报》2016年第7期216-223,共8页Transactions of the Chinese Society for Agricultural Machinery

基　　金：'十二五'国家科技支撑计划项目(2014BAD08B11-2);国家自然科学基金项目(31471407);公益性行业(农业)科研专项(201003063)

摘　　要：玉米秸秆本身营养成分含量低,需作为粗饲料和其它饲料混合生产全混合日粮或经黄贮等技术工艺改善其品质。为在利用和改善处理过程中对其营养成分含量进行实时检测,采用217个玉米秸秆样品,利用优化后的近红外在线光谱采集系统,探索了利用近红外光谱技术在线检测玉米秸秆水分、粗蛋白、酸性洗涤纤维和可溶性糖等营养成分含量的可行性。研究结果表明利用近红外光谱技术可以实现对玉米秸秆饲料营养成分的定量分析。水分、粗蛋白、酸性洗涤纤维、可溶性糖含量模型的相对标准偏差和相对分析误差分别为9.03%和1.97、11.36%和2.31、3.75%和2.02、16.18%和3.61。Corn stover contains abundant nutrients for animals and it is the main source of roughage for large domestic animals. To guarantee the quality of feed,the on-line measurement of the nutrient content of corn stover is essential when it is being used as a roughage feed or a raw material for silage. In the present study,the on-line determination of moisture,crude protein（ CP）,acid detergent fiber（ ADF）and water-soluble carbohydrate（ WSC） of corn stover was investigated using near infrared spectroscopy（ NIRS） operating over a conveyor belt moving at 20 cm/s. The distance between the sample surface and the scanning window was 100 mm. The 217 corn stover samples,collected from three provinces of China,were crushed to not more than 5 cm for spectral analysis. The relative standard deviation（ RSD） and ratio of standard error of performance to standard deviation（ RPD） of the models developed for moisture,CP,ADF and WSC were 9. 03% and 1. 97,11. 36% and 2. 31,3. 75% and 2. 02 and 16. 18% and 3. 61,respectively. The results showed that it was feasible to determine the moisture,CP,ADF and WSC contents of corn stover using on-line NIRS,which would help raise the efficiency of nutrient measurement and thus guarantee the quality of feed. The sensitive bands of the models were investigated,which could help to simplify the models and thus reduce the cost of the specific spectrometers for practical application.

关 键 词：玉米秸秆 营养成分 在线检测 近红外光谱 

分 类 号：S216.2[农业科学—农业机械化工程]