动物营养学报2019，Vol.31Issue(10)：4684-4690,7.DOI:10.3969／j.issn.1006⁃267x.2019.10.033
苜蓿干草常规营养成分含量近红外预测模型的建立
Near Infrared Prediction Model Establishment for Routine Nutritional Component Contents of Alfalfa Hay
摘要
Abstract
In order to establish the near infrared prediction model of routine nutritional component contents of alfalfa hay used by manufacturing enterprises, a total of 265 alfalfa hay bale samples were collected from dairy farms and forage production enterprises in nine provinces. Using near?infrared spectroscopy by partial least squares ( PLS) method with four spectral pretreatments and ten derivative treatments, this study established the near infrared prediction models of five indexes [ including dry matter ( DM) , crude protein ( CP) , neutral de?tergent fiber ( NDF) , acid detergent fiber ( ADF) and ash ( Ash) contents] of the alfalfa hay. The results showed that the coefficient of determination for validation ( RSQV ) and the ratio of performance to deviation for validation ( RPDV ) of CP content were the highest, while those of DM, NDF and ADF contents were slightly lower than those of CP content. The RSQV and RPDV of DM, CP, NDF and ADF contents were higher than 0.80 and 2.50, respectively, indicating that the modeling effects of the four indexes were good and could be used to detect the actual content. However, the RSQV of Ash content was 0.793 and was lower than 0.80, while the RPDV was 2.102 and was lower than 2.50. It showed that the model of Ash content could only be used for the rough prediction and could not be used to detect the actual content. In conclusion, the near?infrared prediction models of DM, CP, NDF and ADF contents of alfalfa hay are preliminarily established, which im?proves the convenience for the rapid and efficient determination of these four indexes in production.[ Chinese Journal of Animal Nutrition, 2019, 31(10) :4684?4690]关键词
近红外光谱技术/苜蓿干草/常规营养成分Key words
near⁃infrared spectroscopy/alfalfa hay/routine nutritional components分类
农业科技引用本文复制引用
何云,张亮,武小姣,郑爱荣,刘薇,贺永惠,牛岩,王跃先,张晓霞..苜蓿干草常规营养成分含量近红外预测模型的建立[J].动物营养学报,2019,31(10):4684-4690,7.基金项目
河南省畜牧业发展资金(奶业发展专项)资助项目 （奶业发展专项）
河南科技学院大学生创新训练项目(2017CX033) （2017CX033）
