黄土高原紫花苜蓿产草量与营养品质预测

The Prediction of Alfalfa Forage Composition and Yield Established on Loess Plateau

为了预测紫花苜蓿(Medicago sativa)的产草量和营养品质,通过2009年和2010年两年的田间试验,获得不同刈割时间的紫花苜蓿株高、产量(包括茎产量和叶产量)和干草样品,分析了样品的中性洗涤纤维、酸性洗涤纤维、粗纤维、粗蛋白,并比较了各指标之间的相互关系。分别建立了基于株高的产草量与营养品质预测模型(草产量:y_(Total)=0.1256x^(2.2866),R^2=0.8898,粗蛋白含量:yCP=50.103x^(-0.369),R^2=0.8625,中性洗涤纤维:y_(NDF)=0.4902x+13.728,R^2=0.8586,酸性洗涤纤维:y_(ADF)=0.371x+9.3476,R^2=0.8678,粗纤维:y_(CF)=0.3556x+4.598,R^2=0.8855),以及基于产草量的产量构成和营养品质预测模型,基于产量构成的营养品质预测模型,基于株高、草产量和产量构成的营养品质预测模型,和营养品质之间相互预测模型等。结果表明预测模型的准确性较高,成本降低96%,可以为黄土高原雨养耕作区紫花苜蓿的管理提供科学依据。

For predicting the yield and quality of alfalfa, different mowing time of alfalfa plant height, yield （including stem yield and leaf yield） data and hay samples were got through the field experiment in 2009 and 2010, the neutral detergent fiber, acid detergent fiber, crude protein, crude fiber and the relationship between the indexes were analyzed. the yield and nutritional quality prediction models were seperately established based on plant height （hay yield：yTotal=0.1256x2.2866, R2=0.8898, crude protein content：yCP=50.103x-0.369, R2=0.8625, neutral detergent fiber：yNDF=0.4902x＋13.728, R2=0.8586, acid detergent fiber：yADF=0.371x＋9.3476,R2=0.8678,crude fiber：yCF=0.3556x＋4.598, R2=0.8855）, yield components and nutritional quality prediction model based on hay yield, nutritional quality prediction model based on yield components, based on the plant height, hay yield and yield components of nutritional quality prediction model, and the prediction model between nutritional quality. Test results showed that the accuracy of the forecasting model was higher, and cost reduced by 96%. The results of the study could provide scientific reference and management of alfalfa in the area of rainfed farming region on the loess plateau.