首页> 外文期刊>Chilean Journal of Agricultural Research >Prediction of the chemical composition and fermentation parameters of pasture silage by near infrared reflectance spectroscopy (NIRS)
【24h】

Prediction of the chemical composition and fermentation parameters of pasture silage by near infrared reflectance spectroscopy (NIRS)

机译:近红外反射光谱法(NIRS)预测牧场青贮饲料的化学成分和发酵参数

获取原文
           

摘要

The capability of near infrared reflectance spectroscopy (NIRS) was evaluated to predict the content of total ash (TA), crude protein (CP), crude fiber (CF), neutral detergent fiber (NDF), acid detergent fiber (ADF) and metabolizable energy (ME); as well as pH and ammonia nitrogen content (N-NH3), in pasture silage, with and without additives. Nine hundred and twenty dried and ground samples of pasture silage, with known chemical composition, were scanned over the visible and NIR region (400 to 2500 nm) at 2 nm intervals. Calibration equations were developed by modified partial least square regression models (MPLS) with different mathematical treatments and light scatter correction as standard normal variation and Detrend (SNV & D) of the spectra. For each parameter, the optimum calibration was evaluated on the basis of the cross validation determination coefficient (1-VR) and standard error of cross validation (SECV). NIRS showed a high predictive ability, with 1-VR > 0.89 and SECV (%) of 5.14, 6.69, 9.96, 16.01 and 9.15 for A, CP, CF, NDF and ADF, respectively. NIRS showed moderate accuracy for ME, with 1-VR > 0.87, SECV: 0.07Mcal kg-1 and low accuracy, although with feasibility as a ranking method, for pH and N-NH3, with 1-VR > 0.72 and SECV of 0.14 and 1.49, respectively. It is concluded that the equations obtained can be used to predict the nutritional composition of pasture silages.
机译:评估近红外反射光谱(NIRS)的能力,以预测总灰分(TA),粗蛋白(CP),粗纤维(CF),中性洗涤剂纤维(NDF),酸性洗涤剂纤维(ADF)和可代谢物质的含量能量(ME);以及添加和不添加添加剂的青贮饲料中的pH值和氨氮含量(N-NH 3 )。在可见光和近红外区域(400至2500 nm)上,以2 nm的间隔扫描了920个干燥和粉碎的牧草青贮样品,它们具有已知的化学成分。通过修改后的偏最小二乘回归模型(MPLS)开发校准方程,该模型具有不同的数学处理和光散射校正,作为标准正态变化和光谱的趋势(SNV&D)。对于每个参数,根据交叉验证确定系数(1-VR)和交叉验证的标准误差(SECV)评估最佳校准。 NIRS具有较高的预测能力,其中A,CP,CF,NDF和ADF的1-VR> 0.89,SECV(%)分别为5.14、6.69、9.96、16.01和9.15。 NIRS对ME的准确度中等,1-VR> 0.87,SECV:0.07Mcal kg -1 ,尽管可以作为一种排序方法,但对pH和N-NH 3的准确性较低,其中1-VR> 0.72和SECV分别为0.14和1.49。结论是,所获得的方程可用于预测牧场青贮饲料的营养成分。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号