人工神经网络从植物数据中学习非线性基本过程的能力可有助于发酵过程的控制。本文旨在研究柠檬发酵过程，并建立了两个柠檬发酵过程的人工神经网络模型。我们研究了网络模型在优化和状态跟踪上的应用并得出优化的柠檬发酵过程控制。用这种方法，可缩短发酵时间，降低能量消耗。 The ability of artificial neural networks to learn non-linear basic processes from plant data can contribute to the control of the fermentation process. The purpose of this paper is to study the fermentation process of lemon and to establish two artificial neural network models of lemon fermentation. We studied the application of network models in optimization and status tracking and derived optimized lemon fermentation process control. In this way, fermentation time can be shortened and energy consumption reduced.