基于图像识别的枇杷资源果肉褐变鉴定方法研究与应用  

Research and application of image recognition-based identification for flesh browning of loquat fruits

作　　者：陈宇佳 邓朝军[2] 张婷婷 王秀平 陈秀萍[2] 赵加宁 马翠兰[1] 蒋际谋[2] CHEN Yujia;DENG Chaojun;ZHANG Tingting;WANG Xiuping;CHEN Xiuping;ZHAO Jianing;MACuilan;JIANG Jimou(College of Horticulture,Fujian Agriculture and Forestry University,Fuzhou 350002,Fujian,China;Fruit Tree Research Institute of Fujian Academy of Agricultural Sciences/Fujian Longan and Loquat Breeding Engineering and Technology Research Center,Fuzhou 350013,Fujian,China)

机构地区：[1]福建农林大学园艺学院,福州350002 [2]福建省农业科学院果树研究所·福建省龙眼枇杷育种工程技术研究中心,福州350013

出　　处：《果树学报》2025年第2期288-299,共12页Journal of Fruit Science

基　　金：福建省属公益类科研院所基本科研专项(2024R1027003);“5511”协同创新工程(XTCXGC2021006);科技部、财政部国家科技资源共享服务平台项目(NHGRC2023-NH18-1);福建省农业科学院科技创新团队(CXTD2021004-1)。

摘　　要：【目的】建立一种准确、快速的枇杷果肉褐变抗性检测方法,实现枇杷种质资源果肉褐变抗性的高效鉴定筛选。【方法】以10份枇杷资源成熟果实为材料,利用MATLAB R2022a函数算法,对相机拍摄的原始照片进行颜色空间转换,筛选适宜测算枇杷果肉的颜色空间。进一步对枇杷果肉切面图像进行二值分割,提取切后不同时间果肉图像像素值,计算褐变指数及褐变面积,并进行褐变分级。【结果】MATLAB转化的Lab颜色空间能准确识别不同资源果肉褐变表型,与色差仪测定评价结果最接近。根据褐变指数和褐变面积进行隶属函数排名,可综合评价10份枇杷资源抗褐变能力。【结论】利用MATLAB图像分割技术可实现对枇杷果肉褐变抗性的准确快速鉴定,该技术亦适用于枇杷种质资源颜色性状的鉴定评价。【Objective】Loquat[Eriobotrya japonica(Thunb.)Lindl.]is a kind of fruit tree of the genus Loquat in the Rosaceae,maloideae,and its fruit is tasteful,rich in nutrients,and reputed as‘the first fruit of the early spring’.Browning of flesh can affect the quality of fresh-cut product of the fruit.So far there has been no report on the research of fresh-cut loquat fruit.Exploring the fast and efficient identification and evaluation of the flesh browning of loquat fruit is conducive to the efficient screening of browning-resistant germplasm resources of loquat.【Methods】The mature fruits of five whitefleshed loquat resources,including Zhongbai,Sanyuebai,Baixuezao,Guifei,and Guofenben,and five red-fleshed resources,including Zhongshudaxiang,Huangjinkuai,Ruisui,Muluo,and Yanhong collected from the National Loquat Germplasm Resource Nursery(Fuzhou,China),were used as materials.After the loquat flesh was freshly cut,it was placed in a simple soft light photographic light box with fixed light source and temperature.The browning phenotypes of loquat flesh cuts were photographed and recorded in 0 min,10 min,30 min and 60 min.And then the Photoshop software was used to pre-process the background purification of the original photos taken by the camera,and the rgb2lab and rgb2hsi function algorithms of the MATLAB R2022a were used to convert the color space of the pre-processed pictures of the cut surface of the fruit flesh,the recognizabilities of the loquat fruit flesh under each color component of the three color spaces of RGB,Lab,and HSI were compared,and the suitable color spaces were accordingly chosen for measuring loquat flesh.Then based on the MATLAB edge detection algorithm,the Sobel operator was used for binary segmentation of the loquat flesh cut image,to extract the change of Lab value of the flesh image pixels at different time points after cutting,and calculate the browning index according to the formula of color change value.Additionally,the MATLAB ROI function was used to select the irregular representa

关 键 词：枇杷 果肉褐变 图像分割 鉴定评价 

分 类 号：S667.3[农业科学—果树学]