采后苹果电特性与生理特性的关系及其应用

为了了解果蔬的电学特性，并为果蔬品质自动化识别提供新方法，该文从生理特性角度分析了影响采后苹果电参数变化的原因。基于电参数的变化，将BP神经网络技术应用于苹果新鲜等级的识别。研究结果指出：采后红富士苹果相对介电常数的变化规律与乙烯释放量变化规律相似，电阻率与乙烯释放量变化规律相反，在乙烯释放峰出现时，相对介电常数达到最大值，电阻率达到最小值。根据采后苹果可溶性固形物含量和pH值的变化，将苹果分为3个新鲜等级，以相对介电常数和电阻率作为BP神经网络的输入特征参数，在2-20-3的网络结构下，苹果新鲜等级平均识别率达到79%。该研究为了解采后果品电特性变化的原因提供了信息，为基于电特性的新型果品内部品质检测技术的研究提供了基础。

Relationship between electrical properties and physiological properties of postharvest apples and its application

Physiological causes that influence electrical parameter values of post-harvest apples were analyzed in order to obtain electrical properties of fruits and vegetables and provide new methods for automatically evaluating quality of fruits and vegetables. Based on changes of electrical properties, BP neural network technique was used to distinguish freshness of apples. Results showed the change regularities of relative dielectric constant and the amount of released ethylene from Fuji apples were similar, and both of them were reversed to resistivity. When the amount of released ethylene was at climacteric, relative dielectric constant was maximum and resistivity reached the minimum. Apples were divided into three freshness degrees according to the changes of total soluble solid (TSS) and pH values. The relative dielectric constant and resistivity were selected as the input data of BP neural network, and the average distinguishing rate for apple freshness was 79% under the 2-20-3 network structure. The study provides new evidence for understanding the causes of electrical property changes of post-harvest apples, and offers experimental basis for studying methods to distinguish internal quality of fruits based on electrical properties.