利用近红外反射光谱技术预测旱地谷物品种的纤维和营养成分含量。

Using NIRS to predict fiber and nutrient content of dryland cereal cultivars.

机构信息

Crop and Soil Sciences Department, Washington State University, Pullman, Washington 99164-6420, USA.

出版信息

J Agric Food Chem. 2010 Jan 13;58(1):398-403. doi: 10.1021/jf9025844.

PMID:19961223

Abstract

Residue from cultivars of spring wheat (Triticum aestivum L.), winter wheat, and spring barley (Hordeum vulgare L.) was characterized for fiber and nutrient traits using reference methods and near-infrared spectroscopy (NIRS). Calibration models were developed for neutral detergent fiber (NDF), acid detergent fiber (ADF), acid detergent lignin (ADL), carbon (C), sulfur (S), nitrogen (N), and C:N. When calibrations were tested against validation sets for each crop year, NIRS was an acceptable method for predicting NDF (standard error of prediction (SEP)<0.87; R2>0.90) and ADF (SEP< 0.81; R2>0.92) and moderately successful for ADL in 1 year of the study (SEP=0.44; R2=0.81) but less successful for C, S, N, and C:N (R2 all<0.57). These results indicate that NIRS can predict the NDF and ADF of cereal residue from dryland cropping systems and is a useful tool to estimate residue decomposition potential.

摘要

利用参考方法和近红外光谱（NIRS）对春小麦（Triticum aestivum L.）、冬小麦和春大麦（Hordeum vulgare L.）品种的残渣进行了纤维和营养特性分析。为中性洗涤剂纤维（NDF）、酸性洗涤剂纤维（ADF）、酸性洗涤剂木质素（ADL）、碳（C）、硫（S）、氮（N）和 C:N 开发了校准模型。当针对每个作物年份的验证集测试校准时，NIRS 是一种可接受的预测 NDF 的方法（预测标准误差（SEP）<0.87；R2>0.90）和 ADF（SEP<0.81；R2>0.92），在研究的 1 年中对 ADL 的预测效果也较为成功（SEP=0.44；R2=0.81），但对 C、S、N 和 C:N 的预测效果较差（R2 均<0.57）。这些结果表明，NIRS 可以预测旱地作物系统中谷物残渣的 NDF 和 ADF，是一种估计残渣分解潜力的有用工具。