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Jia | Nanjing Agricultural University pear research group has developed a new tool for the efficient detection of stone cell phenotype of pear fruit

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Pear is the third largest fruit tree species in China, with cultivation area and yield accounting for about 70% of the world total. However, the stone cell content of Asian pear is generally higher than that of western pear, especially for some traditional cultivars, which leads to rough texture and taste, and affects the quality and market competitiveness of pear. Stone cell is a special character of pear fruit. At present, frozen hydrochloric acid separation method is the most commonly used method to measure the content of stone cell, but this method can not completely separate stone cell and pulp, and the operation is tedious and time-consuming, which can not meet the needs of efficient evaluation of pear variety resources and genetic breeding.
To solve this problem, recently, pear research group of Nanjing Agricultural University developed a tool "pear process" based on computer image processing to detect the phenotype of pear stone cells. Researchers only need to use simple section dyeing and photographing, and collect and analyze image data through visual software, then they can comprehensively analyze the differences of stone cell number, size, area and density parameters of pear fruit Different. This research breaks through the traditional method of pear fruit phenotypic physiological evaluation, and combines with computer image processing technology to achieve the efficient collection and accurate analysis of the phenotype data of stone cell traits, which provides a valuable reference for the efficient evaluation of other phenotypes of pear. The research results are entitled "Pearl process: a new phenomenal tool for stone cell trail evaluation in pear fruit" and published in Journal of integrated agriculture (JIA) No. 6, 2020.
In this study, 395 pear varieties were analyzed by the "Pearl process" software. It was revealed that the number, size, area and density of stone cells varied from 138-2866, 2e-4 cm2-1e-3 cm2, 0.06 cm2-2.02 cm2, 0.0019 cm2 / cm2-0.0632 cm2 / cm2 among different pear varieties. At the same time, it was found that the stone cell content of sand pear was the highest, that of white pear was the second, and that of western pear was the lowest. In addition, by comparing the phenotype data of stone cell characters with the correlation analysis of taste, it is found that stone cell density is the most important factor affecting the essence of pear. The results are of great significance to the selection of excellent pear varieties and the genetic improvement of stone cell characters.
Figure 1 flow chart of "Pearl process" image processing and data analysis
Fig. 2 distribution of stone cell characters in Different Pear Varieties
Xue yongsong, master degree candidate and Xu shaozhuo, Ph.D. candidate of Nanjing Agricultural University are the co first authors of this paper, and Professor Wu Jun is the corresponding author. Professor Zhang Shaoling, director of pear engineering technology research center of Nanjing Agricultural University, Dr. Zhang Mingyue and Dr. Li Jiaming also participated in the study. The research was supported by National Science Foundation for Distinguished Young Scholars (31725024), national key research and development plan (2018yfd1000200), national pear industry technology system (cars-28) and Jiangsu agricultural industry technology system special fund (JATS 2018-277).
Click the link to read the full text: http://www.chinaagrisci.com/jwk zgnykxen/file/pdf/jia-2019-1497.pdfcite the article:
LIU Xin, WANG Wen-xin, LIN Xiang, GU Shu-bo, WANG Dong. 2020. The effects of intraspecific competition and light transmission within the canopy on wheat yield in a wide-precision planting pattern. Journal of Integrative Agriculture 2020, 19(6): 1577–1585.
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Journal of integrated agriculture (JIA) is an English academic journal jointly sponsored by the Chinese Academy of Agricultural Sciences and the Chinese agricultural society and organized by the Agricultural Information Research Institute. Founded in 2002, its chief editor is wan Jianmin, vice president of the Chinese Academy of Agricultural Sciences. The influence factor of SCI in 2018 is 1.337, which is located in Q2 area (18 / 56) of JCR agricultural comprehensive discipline. At present, it is a monthly magazine with 12 issues in the whole year, and it is published on the Elsevier Science Direct (SD) platform OA. Focus on publishing reviews, research papers, briefs and reviews in the frontier and hot fields of international agricultural science, such as crop science, horticulture, plant protection, animal science, animal medicine, resources and environment, food science, agricultural economy and management.
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