基于遗传算法与SVM的香蕉果实成熟度判别模型  

Discriminant model of banana fruit maturity based on genetic algorithm and SVM

作　　者：莫松涛 董涛[3] 赵汐璇 阚江明[1,2] MO Songtao;DONG Tao;ZHAO Xixuan;KAN Jiangming(School of Technology,Beijing Forestry University,Beijing 100083,China;Key Laboratory of State Forestry Administration on Forestry Equipment and Automation,Beijing 100083,China;Institute of Fruit Tree Research,Guangdong Academy of Agricultural Sciences,Guangzhou 510640,Guangdong,China)

机构地区：[1]北京林业大学工学院,北京100083 [2]林业装备与自动化国家林业和草原局重点实验室,北京100083 [3]广东省农业科学院果树研究所,广州510640

出　　处：《果树学报》2022年第12期2418-2427,共10页Journal of Fruit Science

基　　金：广东省重点领域研发计划(2019B020223003)。

摘　　要：【目的】探究香蕉果实外形棱角特征与成熟度之间的关系,构建一种基于遗传算法与SVM的香蕉果实成熟度判别方法。【方法】采用同一种类不同成熟度的176个香蕉果实,根据果身长度进行横向平均切割,获取果实在上、中、下三个部位的横切面,再通过手工测量的方法获取横切面中每个棱角的夹角值,并以测量出的棱角特征作为判别成熟度的特征,通过遗传算法优化SVM分类模型参数,使成熟度判别模型能有效地将不同成熟度的香蕉果实进行区分。【结果】基于遗传算法与SVM的香蕉果实成熟度判别模型经过10次预测后,模型的平均准确率为86.20%。【结论】该方法能较为准确地得到香蕉果实成熟度判别结果,验证了香蕉果实的外形棱角特征与香蕉果实成熟度之间存在相关性,并可建立模型进行判别。【Objective】Harvest maturity is the key factor affecting storage performance of banana fruits.The existing discriminant methods of banana fruit maturity,such as hardness sensor,odor sensor and spectral technology,cannot be applied to the picking site of banana fruits,and the discriminant method based on the pigment composition of banana fruit skin is only suitable for commercial trade.At present,in the process of banana fruit harvesting,experienced farmers still need to observe the fullness of fruit body by experience and judge whether banana fruits should be harvested according to the length of storage time.This method not only is inefficient but also may lead to wrong judgment.The purpose of this study is to explore the relationship between the appearance characteristics and maturity of banana fruits,so as to build a banana fruit maturity discrimination model depending upon the edge and corner characteristics of banana fruits as input vector,and propose a banana fruit maturity discrimination method based on genetic algorithm and SVM.【Methods】In this experiment,11 banana plants were selected,and the maturity of their banana fruits were set to level 5 maturity.The test samples were selected from the third row on a banana hand from top to bottom,and two hands of bananas were randomly cut from each plant.Each group of samples was collected at an interval of two days,and the collected samples of bananas were labeled,and the judgment of banana farmer on the maturity of the collected samples was asked and recorded.Samples were collected from level 5 maturity to level 8 maturi-ty of banana fruits.During the experiment,a total of 176 banana fruits were collected from 8 sets of data.In this paper,the maturity of banana fruit samples was divided into four levels(level 5,level 6,level 7 and level 8).In this method,176 banana fruit samples of the same species with different maturity were cut evenly according to the length of fruit body by three cuts.The transverse sections of the top,middle and bottom parts of the ba

关 键 词：香蕉 果实棱角 支持向量机 遗传算法 成熟度判别 

分 类 号：S668.1[农业科学—果树学]