Abstract:【Objective】Loquat (Eriobotrya japonica (Thunb.) Lindl.) is a plant of the genus Loquat in the Rosaceae，maloideae，with sweet and sour flavor, rich in nutrients, and the reputation of “the first fruit of the early spring”, which is favored by the consumers, but so far there has been no report on the research and product development of fresh-cut loquat.Exploring the fast and efficient identification and evaluation of loquat flesh browning is conducive to the efficient screening of browning-resistant germplasm resources, and lays the foundation for the innovative utilization of excellent resources.【Methods】Mature fruits of five white-fleshed resources, including Zhongbai, Sanyuebai, Baixuezao, Guifei, and Guofenben, as well as the five red-fleshed resources, including the Zhongshudaxiang, Huangjinkuai, Ruisui, Muluo, and Yanhong, all 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 at 0 min, 10 min, 30 min and 60 min were photographed and recorded. And then use Photoshop software to pre-process the background purification of the original photos taken by the camera, using the rgb2lab and rgb2hsi function algorithms of MATLAB R2022a to convert the color space of the pre-processed pictures of the cut surface of the fruit flesh, comparing the recognizability of the loquat fruit flesh under each color component of the three color spaces of RGB, Lab, and HSI, and accordingly choosing the suitable color space for measuring loquat flesh; Further based on MATLAB edge detection algorithm, Sobel operator was used to binary segmentation of loquat flesh cut image, extracted the change of Lab value of the flesh image pixels at different time points after cutting, and calculated the browning index according to the formula of color change value; Additionally, the MATLAB ROI function is used to select the irregular representative loquat flesh browning area, extract the color feature value, and complete the browning area segmentation of the original image by using the Euclidean distance. Finally, according to the characteristics of Lab value change, browning index and browning area during the browning process of loquat flesh section, the principal components were extracted and ranked by the affiliation function, which comprehensively realized the browning resistance grading of 10 loquat resources.【Results】A method based on MATLAB image segmentation algorithm was established to rapidly identify loquat flesh browning, and the CIE-Lab color space transformed by MATLAB could accurately identify the flesh browning phenotypes of different resources, which was the closest to the results determined by colorimeter. It is worth mentioning that the L value and a value can effectively distinguish the flesh color characteristics of the two major types of red flesh and white flesh, which can be used for the flesh color phenotype identification analysis of loquat germplasm resources. Using the color difference formula to calculate the browning index (BI) of the 10 resources at different time intervals based on Lab values, the browning index of loquat resources with white flesh was significantly higher than that of red flesh, and the browning index of Baixuezao, Guifei, Zhongbai, Zhongshudaxiang, Ruisui, and Yanhong increased with the prolongation of time, whereas that of Sanyuebai, Guofenben, Huangjinkuai, and Muluo loquat reached the threshold for browning after 30 min of fresh-cutting, and then tended to be stabilized. The Euclidean distance algorithm found that the percentage of browning area was significantly higher in the white flesh type than in the red flesh type, and among the 10 resources, the browning process was fastest and the browning area was the largest in Guofenben, while the browning process was the slowest and the browning area was the smallest in Yanhong at 60 min. It indicates that splitting the browning area can distinguish and localize the phenotypic differences in browning between red and white flesh types more precisely. According to the membership function ranking by principal component analysis, the Browning resistance of 10 loquat resources from strong to weak was:Yanhong、Ruisui、 Huangjinkuai、Zhongshudaxiang、Muluo Loquat、 Zhongbai、Guifei,、Sanyuebai、Baixuezao、Guofenben。【Conclusion】The MATLAB image segmentation algorithm has a wide recognition range and fast computational speed, which is suitable for quantitative analysis of the color change process of intensive resources. In the evaluation of loquat flesh browning, the browning index and browning area of the MATLAB algorithm describe the browning situation from different dimensions, and the combination of the two methods can maximize the characterization of the browning resistance of varietal resources. The MATLAB image segmentation technique can be used to accurately and rapidly identify the browning resistance of loquat flesh, and the technique is also applicable to the identification and evaluation of color traits of loquat germplasm resources.
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