摘要
作物水肥生产函数研究是非充分灌溉理论的重要内容,也是提高农田水、肥利用效率的基础。在作物水分生产函数Jensen模型的基础上,引入肥料因子构造了水肥生产函数的Jensen模型;同时构造了作物水肥生产函数的人工神经网络模型。利用北京地区冬小麦田间试验资料对以上2个模型进行了分析,表明以上模型均可用于描述水分、肥料等因素对作物产量的影响,进而可对作物产量进行预测,且模型都具备一定的精度。
The study of crop waterfertilizer production function is an important aspect of deficit irrigation theory and will provide the base for increasing use efficiency of soil water and nutrient The Jensen model and the artificial neural networks (ANN) model are used to describe crop waterfertilizer production function Both models are validated by field experiments of winter wheat The results show that both the ANN model and the Jensen model are capable of predicting crop yield on the basis of water and fertilizer used in the field with acceptable precision
出处
《水科学进展》
EI
CAS
CSCD
北大核心
2003年第3期280-284,共5页
Advances in Water Science
基金
国家自然科学基金资助项目(50179017
59839320)
关键词
冬小麦
水肥生产函数
人工神经网络
JENSEN模型
winter wheat
water-fertilizer production function
water sensitivity index
artificial neural networks
Jensen model
prediction of crop yield