Genotype-environment interaction for production characteristics in cherry tomato (Solanum spp.)
Much of the tomato diversity is found in cherry-type populations. There are promising wild cherry tomato species with good behavior in terms of yield and quality that can be produced with a minimum of agro-inputs. The genetic expression of genotypes is influenced by the optimal environment they can...
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Main Authors: | , , |
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Format: | Online |
Language: | eng |
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Sociedad Colombiana de Ciencias Hortícolas-SCCH and Universidad Pedagógica y Tecnológica de Colombia-UPTC
2021
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Online Access: | https://revistas.uptc.edu.co/index.php/ciencias_horticolas/article/view/12608 |
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Summary: | Much of the tomato diversity is found in cherry-type populations. There are promising wild cherry tomato species with good behavior in terms of yield and quality that can be produced with a minimum of agro-inputs. The genetic expression of genotypes is influenced by the optimal environment they can develop in. The genotype-environment interaction must be known to estimate the phenotypic adaptability in different environments. The objective of this research was to evaluate the genotype-environment interaction for 10 cherry tomato introductions in nine environments, four of which were artificial environments (0, 60, 120 and 180 kg ha-1 of potassium) established in natural environments on the Farms Montelindo, Tesorito and CEUNP. The experiment design used randomized complete blocks with four replicates; the experiment unit consisted of five effective plants per introduction. The evaluated variables were production per plant (PFT) (kg/pl), number of fruits per plant (NFT), and average fruit weight (AWF) (g/fruit). The genotype×environment interaction and the stability of the 10 genotypes were estimated with the AMMI multivariate model. The environments for T120K and T180K were optimal for the variables associated with production (PFT, NFT and AWF), with IAC1621, IAC426 and IAC1624 being the most promising genotypes per environment on the Farms Tesorito, Montelindo and CEUNP, respectively. The results are useful for the identification of genotypes in key locations for selection and evaluation in breeding programs. |
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