Abstract:

Prediction models of neural network and partial least squares for wheat scab are proposed，which provides a scientific basis for prevention of wheat scab.The meteorological factors and morbidity rate between 2004 and 2014 in Anhui are chosen as independent variables and dependent variable，respectively.The alternating gradient back-propagation algorithm of Flecher-Reeves is employed to build the neural network model.Since the simple functional relationship between meteorological factors and morbidity rate can't be provided by the model，the correlation among meteorological factors is analyzed and the partial least squares model is built through principal component analysis and regression analysis.The accuracy of the neural network model is about 99%，through which the topology between meteorological factors and morbidity rate is provided.The linear function is obtained through the partial least squares model and the accuracy is about 97%.Both the neural network model and the partial least squares model can achieve high prediction accuracy and provide scientific guidance for the prevention of Anhui wheat scab.

Key words: scab, correlation analysis, neural network, partial least squares