Quality Evaluation of Alfalfa Hay by the Spectroscopic Analysis of Near Infrared Reflectance

doi:10.11733/j.issn.1007-0435.2015.05.027

Acta Agrestia Sinica ›› 2015, Vol. 23 ›› Issue (5): 1080-1085.DOI: 10.11733/j.issn.1007-0435.2015.05.027

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Quality Evaluation of Alfalfa Hay by the Spectroscopic Analysis of Near Infrared Reflectance

GAO Yan-li¹, SUN Yan²

1. Institute of Animal Science, CAAS, Beijing 100193, China;
2. Institute of Grassland Science, China Agricultural University, Beijing 100193, China

Received:2015-05-06 Revised:2015-06-11 Online:2015-10-15 Published:2015-12-01

利用近红外光谱分析预测紫花苜蓿干草品质

高燕丽¹, 孙彦²

1. 中国农业科学院北京畜牧兽医研究所, 北京 100193;
2. 中国农业大学草地研究所, 北京 100193

通讯作者: 孙彦
作者简介:高燕丽(1987-),女,山西忻州人,博士,研究方向为牧草种质资源与育种,E-mail:gaoyanli.025@163.com
基金资助:
公益行业科研专项"苜蓿高效种植技术研究与示范"(201403048);现代农业产业技术体系建设专项基金(CARS-35)资助

Abstract

Abstract:

The contents of crude protein(CP), neutral detergent fiber(NDF), acid detergent fiber(ADF) are used as important factors to evaluate the hay quality of harvested alfalfa. Relative feed value(RFV) is used to evaluate the quality of feed in America, but forage grading index(GI) is used in China. The quality parameters of alfalfa hay including CP, NDF, ADF, RFV, GI were predicted using fourier transform near infrared reflectance spectroscopy with PLS regression in this test. Then five models were validated by cross validation and external validation. Results indicated that the FT-NIR models of alfalfa hay quality had considerable accuracy and precision. The correlation coefficient of cross-validation of CP was 0.9129. The correlation coefficient of external-validation is 0.901. Therefore, FT-NIR can be used to determine the quality of alfalfa hay rapidly and accurately without any chemical reagent.

Key words: Near infrared reflectance spectroscopy, Alfalfa hay, Crude protein, Relative feed value, Forage grading index

摘要：

粗蛋白(CP)、中性洗涤纤维(NDF)和酸性洗涤纤维(ADF)的含量是评价苜蓿(Medicago sativa)产品质量的重要指标。美国现行较多的是使用相对饲用价值(RFV)评估粗饲料产品的质量,我国则用粗饲料分级指数(GI)来评估粗饲料产品的质量。应用偏最小二乘法(PLS)、傅里叶变换近红外光谱技术,建立了适合不同收获期(现蕾期至盛花期)的CP,ADF,NDF,RFV和GI的近红外预测模型。结果表明:粗蛋白的交互验证决定系数(R_cv²)为0.9129,外部验证中预测决定系数为0.901,模型准确性最高。CP, ADF, NDF, RFV和GI外部验证RPD均大于2.5。本文首次探索紫花苜蓿品质评价指标的模型建立,以期为紫花苜蓿品质育种提供数字依据。

关键词: 近红外光谱, 紫花苜蓿干草, 粗蛋白, 相对饲料价值, 粗饲料分级指数

CLC Number:

S541

GAO Yan-li, SUN Yan. Quality Evaluation of Alfalfa Hay by the Spectroscopic Analysis of Near Infrared Reflectance[J]. Acta Agrestia Sinica, 2015, 23(5): 1080-1085.

高燕丽, 孙彦. 利用近红外光谱分析预测紫花苜蓿干草品质[J]. 草地学报, 2015, 23(5): 1080-1085.

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Quality Evaluation of Alfalfa Hay by the Spectroscopic Analysis of Near Infrared Reflectance

利用近红外光谱分析预测紫花苜蓿干草品质

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