Abstract
In order to predict storage life of navel orange, The model for the variable regularity of total soluble sugar, total acidity, vitamin C, soluble solids, the sugar-acidity ratio in navel orange according to storage time was established based on BP artificial neural network . The results show that the multi-factor BP artificial neural network model has better predicted effect than single-factor one. When the number of the hidden layer neuron is 8, the multi-factor BP artificial neural network model of total soluble sugar, total acidity, vitamin C, soluble solids, the sugar-acidity ratio according to storage time was the most accurate, the correlation coefficient R between prediction and true value of storage time reached 0.98, the prediction and true value of the model was 0.99. As a result, the multi -factor BP artificial neural network model could be used to predict the navel orange storage life.
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Xia, J., Hu, R. (2011). Study on Storage Characteristic of Navel Orange Based on ANN. In: Li, D., Liu, Y., Chen, Y. (eds) Computer and Computing Technologies in Agriculture IV. CCTA 2010. IFIP Advances in Information and Communication Technology, vol 345. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-18336-2_81
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DOI: https://doi.org/10.1007/978-3-642-18336-2_81
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