Received: 30-08-2022
Accepted: 18-04-2023
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Assessment of Genetic Diversity on Fruit Traits of Cherry Tomato Germplasm Based on Images
Abstract
This study aimed to assess the fruit trait diversity of cherry tomato germplasm through image-based phenotyping for the nutritious cherry tomato breeding program in Vietnam. Fruit images of sixty-eight cherry tomato accessions grown in winter crop season 2021 at the Vietnam National University of Agriculture were collected at the harvest stage and then were analyzed by SmartGrain software. Comparing the accuracy with the manual measurement using a simple linear regression model, the obtained results show that the fruit length and width extracted from the image had a high determination coefficient (0.81 and 0.76, respectively) and low root mean square error (2.95 and 2.35, respectively) compared with manual measurements. The image-extracted fruit traits were more closely and positively correlated with fruit weight as compared to manual measurements. The tomato germplasm were classified into 6 groups at the similarity coefficient of 65.95 from 5 image-extracted fruit traits. Fruit image-based phenotyping can replace the manual measurement and apply in tomato breeding, testing system, and further apply to other cultivars.
References
Causse M., Friguet C., Coiret C., Lépicier M., Navez B., Lee M., Holthuysen N., Sinesio F., Moneta E. & Grandillo S. (2010). Consumer preferences for fresh tomato at the European scale: A common segmentation on taste and firmness. Journal of Food Science. 75(9): S531-S541.
Đoàn Xuân Cảnh, Nguyễn Đinh Thiều, Đoàn Thị Thanh Thúy & Nguyễn Thị Thanh Hà (2021). Kết quả nghiên cứu chọn tạo và khảo nghiệm giống cà chua lai VT15. Tạp chí Nông nghiệp và Phát triển nông thôn. 9: 34-41.
He Z., Li M., Cai Z., Zhao R., Hong T., Yang Z. & Zhang Z. (2021). Optimal irrigation and fertilizer amounts based on multi-level fuzzy comprehensive evaluation of yield, growth and fruit quality on cherry tomato. Agricultural Water Management. 243: 106360.
Jin L., Zhao L., Wang Y., Zhou R., Song L., Xu L., Cui X., Li R., Yu W. & Zhao T. (2019). Genetic diversity of 324 cultivated tomato germplasm resources using agronomic traits and InDel markers. Euphytica. 215(4): 1-16.
Kong L., Wen Y., Jiao X., Liu X. & Xu Z. (2021). Interactive regulation of light quality and temperature on cherry tomato growth and photosynthesis. Environmental and Experimental Botany. 182: 104326.
Liu H., Meng F., Miao H., Chen S., Yin T., Hu S., Shao Z., Liu Y., Gao L., Zhu C., Zhang B. & Wang Q. (2018). Effects of postharvest methyl jasmonate treatment on main health-promoting components and volatile organic compounds in cherry tomato fruits. Food Chemistry. 263: 194-200.
Marefatzadeh-Khameneh M., Fabriki-Ourang S., Sorkhilalehloo B., Abbasi-Kohpalekani J. & Ahmadi J. (2021). Genetic diversity in tomato (Solanum lycopersicum L.) germplasm using fruit variation implemented by tomato analyzer software based on high throughput phenotyping. Genetic Resources and Crop Evolution. 68(6): 2611-2625.
Nankar A.N., Tringovska I., Grozeva S., Ganeva D. & Kostova D. (2020). Tomato phenotypic diversity determined by combined approaches of conventional and high-throughput tomato analyzer phenotyping. Plants. 9(2).
Nguyễn Hồng Minh, Kiều Thị Thư & Phạm Quang Tuân (2011). Tạo giống cà chua lai quả nhỏ HT144. Tạp chí Khoa học và Phát triển. 9(1): 16-21.
Nguyen Trung Duc, Pham Quang Tuan, Nguyen Thi Nguyet Anh & Vu Van Liet (2022). Phenotypic variation and correlation of fruit traits in diverse muskmelon materials. Vietnam Journal of Agriculture & Rural Development. 2(2): 23-31.
R Development Core Team (2022). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. Retrieved from https://cran.r-project.org/bin/windows/base on March 10, 2022.
Ranc N., Munos S., Santoni S. & Causse M. (2008). A clarified position for solanum lycopersicum var. cerasiforme in the evolutionary history of tomatoes (solanaceae). BMC Plant Biology. 8(1): 130.
Rodriguez G.R., Moyseenko J.B., Robbins M.D., Morejon N.H., Francis D.M. & Van Der Knaap E. (2010). Tomato Analyzer: a useful software application to collect accurate and detailed morphological and colorimetric data from two-dimensional objects. JoVE (Journal of Visualized Experiments). 10.3791/1856(37): e1856.
Tanabata T., Shibaya T., Hori K., Ebana K. & Yano M. (2012). Smartgrain: High-throughput phenotyping software for measuring seed shape through image analysis Plant Physiology. 160(4): 1871-1880.
Tống Văn Hải, Phan Hữu Tôn, Phan Thị Hiền & Nguyễn Quốc Trung (2021). Chọn tạo giống cà chua thuần kháng bệnh xoăn vàng lá bằng chỉ thị phân tử ADN. Tạp chí Khoa học Nông nghiệp Việt Nam. 19(3): 399-409.
Tran Thien Long, Nguyen Hong Minh, Nguyen Tuan Anh, Tran Thi Minh Hang, Nguyen Thi Hoa, Nguyen Tien Long & Nguyen Thi Minh (2020). The comprehensive analysis of morphological variation among 24 tomato (Solanum lycopersicum) genotypes oriented to ornamental breeding in Vietnam. Vietnam Journal of Agricultural Sciences. 3(1): 555-569.
Zhu Y., Gu Q., Zhao Y., Wan H., Wang R., Zhang X. & Cheng Y. (2022). Quantitative extraction and evaluation of tomato fruit phenotypes based on image recognition. Frontiers in Plant Science. 13.