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Combining ability analysis of drought tolerance in wheat over different water regimes

Authors:
  • Kermanshah Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Kermanshah, Iran

Abstract

To study the properties of some drought tolerance criteria and agronomic characters in wheat, an eight-parental diallel cross, excluding reciprocals, was grown in a randomized complete block design with three replications under two different water regimes (irrigated and rainfed) for two years in the College of Agriculture at Razi University, Kermanshah, Iran. High broad-sense heritability estimates were observed for harvest index, grain yield, and earliness. Additive gene action was found to be predominant for grain yield, harvest index, relative water content and chlorophyll fluorescence. The results of combining ability analysis revealed that Plainsman was the best general combiner and Plainsman × Kobomugi was the best specific combination for improving drought tolerance. The pooled analysis of variance for combining ability over rainfed conditions reflected that the GCA × environment interaction was not significant for harvest index and chlorophyll fluorescence, and the SCA × environment interaction was non-significant for relative water content and relative water loss, indicating that genes controlling osmoregulation and the other physiological traits mentioned are not affected in these varieties by different rainfed conditions and hence show static stability.
... ( Table 5). The results of this study were supported by the earlier findings of [20] for spike length while interaction results confirmed the findings of [18,19]. The results of negative effect of spike length on grains spike -1 and days to heading corroborated the findings of [20]. ...
... The results of this study were supported by the earlier findings of [20] for spike length while interaction results confirmed the findings of [18,19]. The results of negative effect of spike length on grains spike -1 and days to heading corroborated the findings of [20]. The negative effect of spike length on grain yield may be due to different environmental conditions and genetic background of breeding materials investigated [21]. ...
Article
Wheat (Triticum aestivum L.) is an important crop also known as the king of cereals and consumed as a staple crop by one-third of the global population. However, wheat production under rainfed conditions is restrained by water scarcity. The experiment was conducted to evaluate wheat breeding lines for yield. Fifteen F 4:7 bread wheat lines along with two check cultivars Tatara and AUP-5008 were tested in RCB design in three replications under irrigated and rainfed conditions. Analysis of variance showed significant (p<0.01) differences among the genotypes for days to heading, plant height, spike length, grains spike-1, grain weight spike-1 , 1000-grains weight and grain yield while non-significant for rest of the traits. Genotype by environment (GE) interaction was significant (P<0.05) for grain yield and non-significant for the remaining traits.1000-grains weight showed positive significant
... ( Table 5). The results of this study were supported by the earlier findings of [20] for spike length while interaction results confirmed the findings of [18,19]. The results of negative effect of spike length on grains spike -1 and days to heading corroborated the findings of [20]. ...
... The results of this study were supported by the earlier findings of [20] for spike length while interaction results confirmed the findings of [18,19]. The results of negative effect of spike length on grains spike -1 and days to heading corroborated the findings of [20]. The negative effect of spike length on grain yield may be due to different environmental conditions and genetic background of breeding materials investigated [21]. ...
... The genotypeenvironment interaction reduces association between phenotypic and genotypic values leads to bias in the estimates of gene effect combining ability for various characters sensitive to environmental fluctuations. Such traits are less preferable to selection [5]. The existence of genotype-environment interaction (GEI) complicates the identification of superior genotypes for a range of environments and calls for the evaluation genotypes in many environments to determine their true genetic potential [24]. ...
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In order to determine stable linseed genotypes with high grain yield, field experiments were conducted with 14 genotypes for two years (2014-2015) at three locations in the highlands of Bale zone, Ethiopia. The genotypes were laid out in randomized complete design with four replications in each environment. The objective of this study was to identify and recommend high yielder, stable genotypes for testing sites and similar agro-ecologies using the stability parameters. The combined analysis of variance showed highly significant differences for the genotypes, environment, and genotype by environment interaction indicating the possible existence of stable genotypes among the tested once. The results of AMMI (additive main effect and multiplicative interaction) analysis indicated that the first two AMMI (AMMI1-AMMI2) were highly significant (P<0.01). The partitioning of the total sum of square exhibited that the effect of environment was a predominant source of variation followed by genotypes and GE interaction effect. Based on the stability parameters regression coefficient, deviation from regression and mean grain yield out of the tested G6, G9, G11, and G8 were found to be stable. However, the AMMI Stability Value (ASV) discriminated genotypes G12, G4, G6, G13, and G9 as stable genotypes respectively. Based on the Genotypes Selection Index (GSI) the most stable genotypes with high grain yield were G6 and G9. Therefore these two genotypes were identified as candidate genotypes to be verified for possible release.
... An ideal selection index or indices could correlate with grain yield under contrasting conditions (Mitra 2001). According to Farshadfar et al. (2001), a perfect selection index is effectively and highly associated with grain yield under stress and control environments. ...
Article
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Pigeonpea (Cajanus cajan L. Millspaugh) is mainly grown in the rainfed ecosystem during the monsoon season on deep vertisols, and it often faces transient waterlogging problems due to continuous and heavy downpours during early monsoon seasons. Thus, waterlogging has become a significant issue in most of the pigeonpea growing areas of the semi-arid tropics due to heavy rain during the initial crop growth stage, which causes 30 to 40% economic yield loss in India and around the world. Only a few sources of waterlogging tolerant genotypes are available in pigeonpea but are not in the required duration. Hence, the present investigation was carried out to identify waterlogging tolerant pigeonpea genotypes in different durations suitable for different agroecologies of India and to find ideal selection indices as appropriate strategies to identify waterlogging tolerant genotypes. In this study, 162 genotypes were screened under in vitro conditions for 2, 4, 6, and 8 days by submerging seeds. Of these, 33 genotypes could survive for eight days. Further, following a standard screening protocol; these 33 pigeonpea genotypes were screened under pot culture for two years (2020 and 2021). Based on different morpho-physiological parameters and waterlogging tolerant coefficient, genotypes ICP-10397, ICP-7507, ICP-7869, ICP-7148, ICP-4903 ICP-16309, ICP-7375, ICP-6815, ICP-7507, and ICP-6128 were identified as tolerant to transient waterlogging. In addition, this study reports the existence of substantial genetic variation for waterlogging tolerant traits in pigeonpea. Stress indices, such as stress tolerance index) (STI), mean relative performance (MRP) and relative efficiency index (REI) were identified as the ideal selection index. Therefore, identified genotypes are further validated and can be deployed in waterlogging tolerance pigeonpea breeding programs
... Based on the results out turned from all the tolerance and susceptible indices along with SES score (Table 2), eight BILs along with parents and checks were grouped into tolerant 5,and 6) in relevance with Vandana NIL SES score (1), moderately tolerant (IL-1, 2, and7) in comparison with tolerant SES score (3), and susceptible (IL-3 and 8) with SES score (7) under DS. Farshadfar et al. (2001) demonstrated that the most appropriate index for selecting the stress-tolerant genotypes is an index that effectively and highly correlated with grain yield under stress and control conditions. Our results are in accordance with Toorchi et al. (2012) in canola and Golabadi et al. (2006) in wheat. ...
Article
Drought stress during the reproductive stage is an evident limitation of rice grain yield. The present study aimed to assess the reproductive stage drought tolerance of eight promising backcross inbred lines (BILs) with complete fertility restoration in the genetic background of KMR-3R. Various stress indices based on grain yield under Non-stress (NS) and drought-stress (DS) conditions were used to assess BILs drought tolerance potential. Based on correlation analysis, the best indices for determining drought-tolerant genotypes were K2STI, YI, HM, SNPI, GMP, and DTI. By ensuring stable performance, the indices K2STI and YI were crucial criteria in identifying DS genotypes. The stress-tolerant and susceptible genotypes were best differentiated under DS using the susceptible indices TOL and ATI, which had considerably low values. The IL-1, IL-2, and IL-7 (RP6340-NRR-5, RP6340-NRR-11, and RP 6340-NPVR-25) were identified as promising drought-tolerant genotypes based on lower grain yield reduction under DS. The improved restorers with drought tolerance performed well under DS in terms of agronomy, and it may be exploited in hybridization programs to develop elite drought-tolerant rice hybrids for unfavorable ecologies.
... One part includes the systematic structure of the interaction between genotype and environment, which is used to model and interpret the interaction of genotypes with the environments. The other part includes the residual (error) interpretable structure of the genotype and environment interaction (Farshadfar et al., 2011). ...
Article
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Investigating the interaction of genotype and environment in multi‐environment experiments (MET) is one of the reliable techniques to demonstrate the most stable and compatible cultivars. The main contribution of this study is to evaluate the stability and compatibility of rapeseed cultivars using additive main effects and multiplicative interaction (AMMI) and genotype plus genotype environment interaction (GGE) bi‐plot methods for grain yield and oil content. For this purpose, an experiment in a randomized complete block design (RCBD) with three replications was conducted for 10 rapeseed cultivars across 10 environments (five regions in 2 years). Hence, the proposed technique can be used to identify the superior cultivars corresponding to the multivariant properties including yield and oil content. To do so, a case‐study analysis was conducted over rapeseed, while more than 96% of the data variance for grain yield and more than 94% of the data variance for oil content were explained based on the AMMI model. According to the AMMI model, it was observed that the “Zarfam” and “Licord” genotypes were introduced as favorable genotypes for grain yield and oil content, respectively. “Karaj1” and “Sanandaj1” were selected as the superior environments for yield trait, “Kashmar2” for oil content, and “Licord” and “Kashmar2” were identified as the superior genotypes and environment for oil content, respectively. Graphical GGE bi‐plot illustrated that “Hyola401,” “Okapi,” and “Sarigol” for grain yield and “Option500” and “Sunday” for oil content were identified as stable and high‐yield genotypes. “Sanandaj1” for grain yield and “Karaj2” for oil content were identified as environments with high differentiation and screening power. This study was performed to evaluate the stability and compatibility of rapeseed cultivars in terms of grain yield and oil content in ten rapeseed cultivars in ten environments
... Since most, if not all of the evaluations in the varietal development process are typically carried out in multiple environments to better identify environment-specific or broadly adapted varieties, it is of critical importance to understand the relationship between the genotype and environment concerning agronomic performance to facilitate the breeding process in selection and cultivar release and to identify suitable production and test environments (Manrique and Hermann 2000). Additionally, as yield is a complex trait, selection of high-yielding genotypes is difficult due to the complexity of the response of genotypes across environments (Farshadfar et al. 2001) and warrants investigations into the interaction between genotypes and environments to varietal performance. This is important because it has been posited by Yan et al. (2000) that G × E analysis from multi-environment evaluation enables the identification of superior genotypes with better stability and adaptability. ...
Article
Agronomic performance of Robusta coffee (Coffea canephora) is affected by genotype by environment interaction, which demands multi-environment testing of genotypes to identify superior genotypes. The objectives of this study were to (1) estimate genetic parameters and analyze the effects of genotype (G), environment (E), and genotype by environment (G × E) interaction on growth and yield traits of C. canephora genotypes, (2) identify superior genotypes that exhibit high stability by combining high growth and yield with broad or specific environmental adaptation, and (3) identify environments that best represent the target environment for high trait expression. Thirty-nine C. canephora hybrids were evaluated using a randomized-complete-block design with three replications at New Tafo-Akim and Bechem in the Eastern and Ahafo regions of Ghana, respectively. Additive main effect and multiplicative interaction (AMMI) analysis of variance revealed highly significant (p < 0.001) differences among G, E, and G × E interaction effects for all traits. AMMI2 biplot analysis revealed the presence of 3, 2, 3, 2, and 3 mega environments for trunk cross-sectional area, height, span, number of laterals, and yield, respectively. Identifying mega environments for these traits will help expedite Robusta coffee breeding through the reduction of the number of test environments needed for phenotype evaluations. The AMMI analyses indicated genotypes G17 (E138 × C180), G35 (PA193 × C180), G4 (197 × PA413), G1 (149 × C193) and G30 (E152 × 149) have high and stable yields across all test environments. The promising candidate genotypes are recommended for further stability tests and release in Ghana or comparable environments.
... La RWL a été suggéré comme une technique d'examen fondamental pour identifier les génotypes sous stress hydrique et salin (Gunes et al., 2008). En effet, ce paramètre est une mesure directe du déficit en eau des plantes et un bon critère pour la sélection de plantes tolérantes à la sécheresse (Farshadfar et al., 2001). ...
Book
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