Concerning the issue that the traditional price prediction model for agricultural product cannot predict the market price of apple quickly and accurately under the big data scenario， an apple price prediction method based on distributed neural network was proposed. Firstly， the relative factors that affect the market price of apple were studied， and the historical price of apple， historical price of alternatives， household consumption level and oil price were selected as the input of the neural network. Secondly， a distributed neural network prediction model containing price fluctuation law was constructed to implement the short-term prediction for the market price of apple. Experimental results show that the proposed model has a high prediction accuracy， and the average relative error is only 0.50%， which satisfies the requirements of apple market price prediction. It indicates that the distributed neural network model can reveal the price fluctuation law and development trend of apple market price through the characteristic of self-learning. The proposed method not only can provide scientific basis for stabilizing apple market order and macroeconomic regulation of market price， but also can reduce the harms brought by price fluctuations， helping farmers to avoid the market risks.
