期刊:Bioscience, Biotechnology and Biochemistry ISSN:09168451 , 年:2018 . 卷:82 . 期:5 页码:768-774
语种:
English
原文链接:http://doi.org/10.1080/09168451.2018.1445519
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- 摘要
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The drumstick tree has traditionally been used as foodstuff and fodder in several countries. Due to its high nutritional value and good biomass production, interest in this plant has increased in recent years. It has therefore become important to rapidly and accurately evaluate drumstick quality. In this study, we addressed the optimization of Near-infrared spectroscopy (NIRS) to analyze crude protein, crude fat, crude fiber, iron (Fe), and potassium (K) in a variety of drumstick accessions (N = 111) representing different populations, cultivation programs, and climates. Partial least-squares regression with internal cross-validation was used to evaluate the models and identify possible spectral outliers. The calibration statistics for these fodder-related chemical components suggest that NIRS can predict these parameters in a wide range of drumstick types with high accuracy. The NIRS calibration models developed in this study will be useful in predicting drumstick forage quality for these five quality parameters.
© 2018 Japan society for Bioscience, Biotechnology, and agrochemistry.
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关键词
Chemometrics - Drumstick - Moringa oleifera lams - Near infra-red reflectances - Near infrared reflectance spectroscopy - Partial least squares regression - Quality parameters - Spectroscopic method
- 作者信息
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通讯作者:
Chen, Xiaoyang(xychen@scau.edu.cn)
作者机构:
[1]
State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources, South China Agricultural University, Guangzhou, China
[2]
Guangdong Key Laboratory for Innovative Development and Utilization of Forest Plant Germplasm, Guangzhou, China
[3]
Guangdong Province Research Center of Woody Forage Engineering Technology, Guangzhou, China
[4]
College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, China
