Volume 17, Issue 2 (5-2025)
J Crop Breed 2025, 17(2): 1-11 |
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Alavi-Siney S M, Abedi M. (2025). Selection of Superior Tomato Lines using Multivariate Statistical Methods in the Jiroft Region. J Crop Breed. 17(2), 1-11. doi:10.61186/jcb.2024.1568
URL: http://jcb.sanru.ac.ir/article-1-1568-en.html
URL: http://jcb.sanru.ac.ir/article-1-1568-en.html
1- Crop and Horticultural Science Research Department, Southern Kerman Agricultural and Natural Resources Research and Education Center, AREEO, Jiroft, Iran
2- Institute of Seed and Plant Improvement, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
2- Institute of Seed and Plant Improvement, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
Abstract: (1353 Views)
Extended Abstract
Background: Tomato (Solanum lycopersicum L.) is one of the most important crops in the world. The cultivated area of this plant in Iran is 103,000 hectares, and its production amount is more than 5 million tons, which indicates the importance of this plant. In plant breeding, different methods are used in genotype selection. To select the best genotypes, a method is needed that can consider all traits based on desirability and undesirability in selections. The ideal genotype selection index (SIIG) is one of the methods that can determine the distance between genotypes in addition to selecting ideal genotypes. In this method, it is possible to identify genotypes with special characteristics. For example, genotypes with high yield and early maturity can be identified and selected with the SIIG method. This study aimed to evaluate tomato genotypes through quantitative and qualitative traits and to select the best ones for climatic conditions in southern Kerman.
Methods: To evaluate and select the best tomato lines in the Jiroft region, an experiment with 11 genotypes (10 promising lines and the Karoon variety) based on a randomized complete blocks design with three replications was carried out in the research farm of the Southern Kerman Agricultural and Natural Resources Research and Education Center during two crop years (2021-2022 and 2022-2023). Cultivation was carried out under plastic on 20 February. Following drip irrigation, weeds were controlled by hand. During the growing season and after harvesting (May), qualitative traits, including uniformity, growth crack, green shoulders, type of inflorescence, and having an abscission layer, were recorded for each genotype. Brix, pH, tissue firmness, the number of locules, fruit length, fruit width, fruit weight, and the yield of each plant were measured in the laboratory. The days to flowering, days to ripening, and the number of inflorescences were also the traits recorded in each plot. Statistical analyses were performed using SAS software (9.4), and calculations related to the SIIG method were performed using the relevant matrices.
Results: A compound variance analysis during the two years of the experiment showed that the effect of the year was significant on all studied traits, except for the number of locules trait. This shows the different conditions during the two experimental years and the influence of the studied traits on the experimental conditions. The effect of the genotype and the interaction of the genotype in the year were significant on all studied traits, except for the number of inflorescences, showing the diversity between the tested genotypes in terms of the studied traits. The mean comparison results of genotype effect showed that lines 14 and 6-33 were able to reach maturity earlier due to early flowering. Genotypes 8 and 32 produced the highest fruit yield, and the lowest amount of this trait belonged to lines 33-6 and 22-7. Since the traits were compared separately, a mean comparison among the genotypes showed that it was not possible to select the best based on all traits. If the selection was based only on yield, they would be placed in the top group 2 lines 8 and 32. Grouping based on cluster analysis placed four lines (8, 7-22, 11, and the Karoon variety) in the top group. Grouping tomato lines based on the SIIG index placed six lines in the top group. The superiority of the SIIG method compared to other methods is the grouping of lines based on the desirability of the traits (for example, low-average genotypes in the days to flowering and days to ripening are desirable traits). Therefore, the lines selected through the SIIG index are introduced as superior lines considering all traits in the south of Kerman. The SIIG method considers only quantitative traits, and non-parametric traits are not involved in this selection. Therefore, the Karoon cultivar, due to the fruit growth crack and line 7, due to the lack of uniformity and lack of the abscission layer, are not suitable for selection in the south of Kerman.
Conclusions: By using the SIIG method and using all the traits, lines 33-4, 11, 13, and 8 were selected as the best lines in Jiroft conditions.
Background: Tomato (Solanum lycopersicum L.) is one of the most important crops in the world. The cultivated area of this plant in Iran is 103,000 hectares, and its production amount is more than 5 million tons, which indicates the importance of this plant. In plant breeding, different methods are used in genotype selection. To select the best genotypes, a method is needed that can consider all traits based on desirability and undesirability in selections. The ideal genotype selection index (SIIG) is one of the methods that can determine the distance between genotypes in addition to selecting ideal genotypes. In this method, it is possible to identify genotypes with special characteristics. For example, genotypes with high yield and early maturity can be identified and selected with the SIIG method. This study aimed to evaluate tomato genotypes through quantitative and qualitative traits and to select the best ones for climatic conditions in southern Kerman.
Methods: To evaluate and select the best tomato lines in the Jiroft region, an experiment with 11 genotypes (10 promising lines and the Karoon variety) based on a randomized complete blocks design with three replications was carried out in the research farm of the Southern Kerman Agricultural and Natural Resources Research and Education Center during two crop years (2021-2022 and 2022-2023). Cultivation was carried out under plastic on 20 February. Following drip irrigation, weeds were controlled by hand. During the growing season and after harvesting (May), qualitative traits, including uniformity, growth crack, green shoulders, type of inflorescence, and having an abscission layer, were recorded for each genotype. Brix, pH, tissue firmness, the number of locules, fruit length, fruit width, fruit weight, and the yield of each plant were measured in the laboratory. The days to flowering, days to ripening, and the number of inflorescences were also the traits recorded in each plot. Statistical analyses were performed using SAS software (9.4), and calculations related to the SIIG method were performed using the relevant matrices.
Results: A compound variance analysis during the two years of the experiment showed that the effect of the year was significant on all studied traits, except for the number of locules trait. This shows the different conditions during the two experimental years and the influence of the studied traits on the experimental conditions. The effect of the genotype and the interaction of the genotype in the year were significant on all studied traits, except for the number of inflorescences, showing the diversity between the tested genotypes in terms of the studied traits. The mean comparison results of genotype effect showed that lines 14 and 6-33 were able to reach maturity earlier due to early flowering. Genotypes 8 and 32 produced the highest fruit yield, and the lowest amount of this trait belonged to lines 33-6 and 22-7. Since the traits were compared separately, a mean comparison among the genotypes showed that it was not possible to select the best based on all traits. If the selection was based only on yield, they would be placed in the top group 2 lines 8 and 32. Grouping based on cluster analysis placed four lines (8, 7-22, 11, and the Karoon variety) in the top group. Grouping tomato lines based on the SIIG index placed six lines in the top group. The superiority of the SIIG method compared to other methods is the grouping of lines based on the desirability of the traits (for example, low-average genotypes in the days to flowering and days to ripening are desirable traits). Therefore, the lines selected through the SIIG index are introduced as superior lines considering all traits in the south of Kerman. The SIIG method considers only quantitative traits, and non-parametric traits are not involved in this selection. Therefore, the Karoon cultivar, due to the fruit growth crack and line 7, due to the lack of uniformity and lack of the abscission layer, are not suitable for selection in the south of Kerman.
Conclusions: By using the SIIG method and using all the traits, lines 33-4, 11, 13, and 8 were selected as the best lines in Jiroft conditions.
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