با همکاری انجمن فیزیولوژی گیاهی ایران
نوع مقاله : مقاله پژوهشی
نویسندگان
1 بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان لرستان، سازمان تحقیقات، آموزش و ترویج کشاورزی، خرمآباد، ایران
2 بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان ایلام، سازمان تحقیقات، آموزش و ترویج کشاورزی، ایلام، ایران
3 بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی اردبیل، سازمان تحقیقات، آموزش و ترویج کشاورزی، مغان، ایران
4 مؤسسه تحقیقات کشاورزی دیم کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، گچساران، ایران
کلیدواژهها
عنوان مقاله English
نویسندگان English
Introduction
Lentil (Lens culinaris Medik) is considered one of the most important legumes due to its protein content and high nutritional value. Its yield, like that of other crops, is an important and challenging trait for genetic improvement, because it is influenced by various factors that have detrimental effects on seed yield and traits related to seed quality. One of the key aspects in plant breeding studies is the understanding of the interaction between genotypes and different environments. The existence of genotype-by-environment interaction (GEI) in field trials of many crop plants indicates that yield stability, along with high average yield, should be considered as an important aspect of yield comparison trials. The aim of the present study was to determine stable and high-yielding lentil genotypes across different environments using various stability indices.
Materials and Methods
In this study, fourteen advanced lentil genotypes along with two check cultivars (Gachsaran and Sepehr) were evaluated based on a randomized complete blocks design with three replications at Khorramabad, Gachsaran, and Ilam Agricultural Research Stations for two cropping seasons (2020-2022), and at the Mughan Station for one crop year (2020-2021). Seeds were sown with a Wintersteiger research seeder in four rows, each 4 m long, with 25 cm spacing between rows (plot area of 4 m²). Weed control was carried out using a hand cultivator in two stages during the vegetative growth period. Before harvesting, the two outer rows and 0.5 m from both ends of the two central rows were discarded, and the remaining area of each plot (1.5 m²) was harvested manually and grain yield was calculated. Grain yield, 100 seed weight, plant height, days to flowering, days to maturity, kernel filling period, kernel filling rate, rain water productivity, seed yield formation rate, and weight of single seed were measured in all seven environments for each genotype. All statistical analyses were performed using GGE and the multi-environmental analysis package “metan” in R software.
Results and Discussion
The mosaic diagram showed that the contribution of the sum of squares of genotype and the genotype-by-environment interaction (GEI) in the total sum of squares was 2.2 and 43.19%, respectively. The likelihood ratio test showed that the genotype by environment interaction was significant on grain yield, 100-grain weight, plant height, days to flowering, kernel filling rate, rain water productivity, and weight of single seed. The Scree test showed that the first two principal components had a significant contribution to the GEI matrix derived from BLUP, as the first and second principal components explained 44.4% and 32.2% of the GEI variation, respectively. The predicted grain yield means using BLUP method indicated that the highest predicted yield using BLUP method was for genotype 2, followed by genotypes 7, 14, 6, 10, 12, 1 and 4, all of which showed predicted yields higher than the overall mean. Genotypes 12, 1 and 4 had predicted yield very close to the average, and the lowest predicted yield with a large distance from the total average was related to genotypes 15, 3 and 9 (Gachsaran). Factor analysis based on the traits measured in the studied genotypes showed that four main components remained in the model, and the cumulative variance of these four components was 91.85%. For grain yield, the genotype-by-environment interaction (GEI) coefficient of explanation and average genotypic heritability were 0.4319 and 0.2065, respectively. The accuracy of genotype selection and the correlation between genotype values across environments were 0.454 and 0.442, respectively. Also, the genotypic coefficient of variation, the residual coefficient of variation, and the ratio of these two coefficients of variation were 4.48%, 21.9%, and 0.204, respectively. The traits of grain yield formation rate, rain water productivity, and plant height showed the greatest contribution to seed yield.
Conclusions
In general, the results showed that the genotype-by-environment interaction was significant on grain yield, 100-seed weight, plant height, days to flowering, days to maturity, grain filling period, grain filling rate, grain yield formation rate, rain water productivity, and single grain weight. Overall, based on the results of all methods and simultaneous selection for grain yield stability and associated traits, genotypes 4, 2, 13, 14, 1, 7, and 10 were identified as stable and superior to the average of all genotypes. Notably, genotype 2 outperformed the others, with a grain yield of 969 kg ha⁻¹, plant height of 46.6 cm, seed yield formation rate of 63.6 kg ha⁻¹ day⁻¹, and rainwater productivity of 82.2 kg mm⁻¹, exceeding the average values across all measured traits in this study.
Acknowledgement
Financial support for this research (approved code: 00-59-15-018-001055) is from the Dryland Agriculture Research Institute (DARI), Agricultural Research Education and Extension Organization (AREEO), Iran.We would like to express our gratitude to the Agricultural Research, Education and Extension Organization.
کلیدواژهها English
Authors retain the copyright. This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0)
