Evaluation of Grain Yield Stability of Durum Wheat (Triticum turgidum L. var. durum) Promising Lines in Moderate Regions of Iran

بوم شناسی کشاورزی

Article 10, Volume 12, Issue 2 - Serial Number 44, June 2020, Pages 345-358   

Document Type: Scientific - Research

DOI: 10.22067/jag.v12i2.85729

Authors

Ali Akbar Moayedi^{* 1}; Toohid Najafi Mirak²; Majid Taherian¹; Shahryar Sasani³; Davood Amin azarm⁴

¹Department of Horticulture Crop Research , Khorasan Razavi Agricultural and Natural Resources Research and Education Center, AREEO, Mashhad, Iran

²Cereal Research Department, Seed and Plant Research Improvement Institute, AREEO, Karaj, Iran

³Department of Horticulture Crop Research , Kermanshah Agricultural and Natural Resources Research and Education Center, AREEO, Kermanshah, Iran.

⁴Department of Horticulture Crop Research , Isfahan Agricultural and Natural Resources Research and Education Center, AREEO, Isfahan, Iran

Abstract

Introduction
Durum wheat (Triticum turgidum L. var durum) consist of only 5% of the world’s total cultivated wheat area and contributes about 10% to the total global wheat production. Durum wheat in Iran is grown on 300-400 thousand hectares with an average annual production of 500-600 thousand tons. Similar to other crops, insufficient yield stability in durum wheat is recognized as a one of the factors responsible for the gap between actual yield and potential yield. In breeding programs, the identification of superior genotypes is difficult due to environmental variability of target locations and the interaction of these variabilities with the investigated genotypes. Therefore, it is important to evaluate the advanced agronomic lines across various environments and over multiple years to ensure their yield stability and production (Yan & Rajcan, 2002). Many statistical models have been suggested to analyze genotype (G)× environment (E) interaction. GGE (genotype plus genotype-by-environment) biplot method is a multivariate model, which is based on principal component analysis that simultaneously represents G, E and G×E interaction on a graph known as biplot. GGE biplot is widely used in agricultural research as it provides a simple graphical interpretation of G×E interaction. The aim of the study was to evaluate the grain yield stability and adaptability in some promising durum wheat lines grown in moderate regions of Iran.
Materials and Methods
Eighteen promising durum wheat lines (G1-G18) along with two control cultivars (durum wheat cv. Hana and bread wheat cv. Parsi), were investigated based on a randomized complete block with three replications for two cropping seasons (2016-2017 and 2017-2018) at four Agricultural Research Stations (including Karaj, Ahwaz, Kermanshah, Neishabour and Isfahan cities, Iran). Combined analysis of variance for grain yield was performed using ADEL-R software. The GGE biplot methodology was employed to analyze G×E interaction (Yan, 2001). The GGE biplot model was used for the following purposes; (i) evaluation of yield stability, (ii) the simultaneous selection for yield and stability, (iii) identification of ideal durum wheat genotypes, and (iv) assessment of the characteristics of and relationships among the testing environments.
Results and Discussion
About 70% of variation was related to environment, 1.7% to genotype and 13.5% to genotype× environment interaction. Overall the grain yield of the lines ranged from 6.57 to 7.26 t.ha-1 and the G20 and G2 lines had the lowest and highest grain yield, respectively. Also, G6 and G16 lines had higher yield than Dena cultivar (G1). Surveying Polygon of GGE biplot showed that genotypes G2, G16, G5, G4, G20, G8 and G6 which had the most distance from Bipolt center and located in Polygon vertices that they were premier genotypes. The lines which designed from Biplot center divided the shape of Polygon to four environments. The first environment was included into the Isfahan in which genotype G6 had the most performance. The second environment was included into the Karaj that G2 was premier genotypes of this environment. The third environment was included into Kermanshah that genotype G16 was high performance genotype in this environment. The fourth environment was included into the Neishabour in which genotype G20 was premier genotype. The G12, G3, and G10 genotypes, which were located near the center of the biplot, had performance in all environments. Simultaneous evaluation of grain yield and stability through environment coordinate (AEC) biplot showed that genotypes G2, G1 and G18 with the higher grain yield were the most stable genotypes. There were many similarities between Karaj and Kermanshah environments as well as Karaj and Isfahan. The angles between these two environmental groups were less than 90 degrees. In contrast, the angle between Neishabour environment and Kermanshah and Karaj environments was distorted and near 180 degrees. These results verified the Karaj station was close to the ideal environment. G2 and G16 genotypes were identified as favorable genotypes in Karaj environment.
Conclusion
GGE Biplot was an appropriate graphical method for simultaneous selection of performance and stability of cultivars and lines. Based on the results, genotype G6 in Karaj, G6 in Isfahan and G20 in Neishabour were the best genotypes in terms of yield and stability. Generally, G18 can be considered as a favorite promising line compared to the control cultivar Hana and as a candidate in the temperate climates.

Keywords

Genotype × Environment Interaction; GGE biplot; Sustainability; Superior Genotype

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