BP neural network model for the measurement of the leaf area of litchi

In order to measure leaf area of Litchi, a BP neural network model was designed, whose input parameters are leaf length and leaf maximum width, and output parameter is leaf area. The sample data, which were obtained by measuring the leaves of Litchi using LI-3000A leaf area instrument, were employed to train the neural network model. The R-square of regression function between output and target of neural network model for testing samples is 0.99609. It indicates that the neural network model is valid. The trained neural network model was applied to measure the areas of ten pieces of leaves respectively, which had not been used to establish the neural network model, the sum squared error of measurement is 1.2929, better than the sum square error of regression function, which is 2.0795. The trained neural network model could be applied to measure numerous leaf area of litchi simply, quickly and economically, and need not destroy the measured leaves.