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Conference Papers Year : 2011

Study on Storage Characteristic of Navel Orange Based on ANN

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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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hal-01562725 , version 1 (17-07-2017)

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Attribution - CC BY 4.0

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Junfang Xia, Runwen Hu. Study on Storage Characteristic of Navel Orange Based on ANN. 4th Conference on Computer and Computing Technologies in Agriculture (CCTA), Oct 2010, Nanchang, China. pp.667-673, ⟨10.1007/978-3-642-18336-2_81⟩. ⟨hal-01562725⟩
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