ABSTRACT
BACKGROUND: Chickpea is a key pulse crop grown in the spring in dryland regions. The cold resistance potential of chickpeas allows for the development of genotypes with varying sowing dates to take advantage of autumn and winter rainfall, particularly in dryland regions. In this study, we assessed grain yield, plant height, 100-seed weight, days to maturity, and days to flowering of 17 chickpea genotypes in five autumn-sown dryland regions from 2019 to 2021. Additionally, the response of selected chickpea genotypes to cold stress was examined at temperatures of -4 °C, 4 °C, and 22 °C by analyzing biochemical enzymes. RESULTS: Mixed linear model of ANOVA revealed a significant genotype × environment interaction for all traits measured, indicating varying reactions of genotypes across test environments. This study reported low estimates of broad-sense heritability for days to flowering (0.34), days to maturity (0.13), and grain yield (0.08). Plant height and seed weight exhibited the highest heritability, with genotypic selection accuracies of 0.73 and 0.92, respectively. Moreover, partial least square regression highlighted the impactful role of rainfall during all months except of October, November, and February on grain yield and its interaction with environments in autumn-planted chickpeas. Among the genotypes studied, G9, G10, and G17 emerged as superior based on stability parameters and grain yield. In particular, genotype G9 stood out as a promising genotype for dryland regions, considering both MTSI and genotype by yield*trait aproaches. The cold assay indicated that - 4 °C is crucial for distinguishing between susceptible and resistant genotypes. The results showed the important role of the enzymes CAT and GPX in contributing to the cold tolerance of genotype G9 in autumn-sown chickpeas. CONCLUSIONS: Significant G×E for agro-morphological traits of chickpea shows prerequisite for multi-trial analysis. Chickpea`s direct root system cause that monthly rainfall during plant establishment has no critical role in its yield interaction with dryland environment. Considering the importance of agro-morphological traits and their direct and indirect effects on grain yield, the utilization of multiple-trait stability approches is propose. Evaluation of chickpea germplasm reaction against cold stress is necessary for autumn-sowing. Finally, autumn sowing of genotype FLIP 10-128 C in dryland conditions can led to significant crop performance.
Subject(s)
Cicer , Genotype , Seasons , Cicer/genetics , Cicer/growth & development , Cicer/enzymology , Cicer/physiologyABSTRACT
Ascochyta blight caused by Ascochyta rabiei (Pass.) Lab. (Telomorph: Didymella rabiei) (Kov.) is one of the most important fungal diseases in chickpea worldwide. Knowledge about pathogen aggressiveness and identification resistance sources to different pathotypes is very useful for proper decisions in breeding programs. In this study, virulence of 32 A. rabiei isolates from different part of Iran were analyzed on seven chickpea differentials and grouped into six races based on 0-9 rating scale and susceptibility/resistant pattern of chickpea differentials. The least and most frequent races were race V and race I, respectively. Race V and VI showed highly virulence on most of differential, while race I showed least aggressiveness. Resistance pattern of 165 chickpea genotypes also were tested against six different A. rabiei races. ANOVA analysis showed high significant difference for isolate, chickpea genotypes and their interactions. Overall chickpea × isolate (race) interactions, 259 resistance responses (disease severity ≤ 4) were identified. Resistance spectra of chickpea genotypes showed more resistance rate to race I (49.70%) and race III (35.15%), while there were no resistance genotypes to race VI. Cluster analysis based on disease severity rate, grouped chickpea genotypes into four distinct clusters. Interactions between isolates or races used in this study, showed the lack of a genotype with complete resistance. Our finding for virulence pattern of A. rabiei and newly identified resistance sources could be considerably important for integration of ascochyta blight resistance genes into chickpea breeding programs and proper decision in future for germplasm conservation and diseases management.
ABSTRACT
Characterization of genetic diversity, population structure, and linkage disequilibrium is a prerequisite for proper management of breeding programs and conservation of genetic resources. In this study, 186 chickpea genotypes, including advanced "Kabuli" breeding lines and Iranian landrace "Desi" chickpea genotypes, were genotyped using DArTseq-Based single nucleotide polymorphism (SNP) markers. Out of 3339 SNPs, 1152 markers with known chromosomal position were selected for genome diversity analysis. The number of mapped SNP markers varied from 52 (LG8) to 378 (LG4), with an average of 144 SNPs per linkage group. The chromosome size that was covered by SNPs varied from 16,236.36 kbp (LG8) to 67,923.99 kbp (LG5), while LG4 showed a higher number of SNPs, with an average of 6.56 SNPs per Mbp. Polymorphism information content (PIC) value of SNP markers ranged from 0.05 to 0.50, with an average of 0.32, while the markers on LG4, LG6, and LG8 showed higher mean PIC value than average. Unweighted neighbor joining cluster analysis and Bayesian-based model population structure grouped chickpea genotypes into four distinct clusters. Principal component analysis (PCoA) and discriminant analysis of principal component (DAPC) results were consistent with that of the cluster and population structure analysis. Linkage disequilibrium (LD) was extensive and LD decay in chickpea germplasm was relatively low. A few markers showed r2 ≥ 0.8, while 2961 pairs of markers showed complete LD (r2 = 1), and a huge LD block was observed on LG4. High genetic diversity and low kinship value between pairs of genotypes suggest the presence of a high genetic diversity among the studied chickpea genotypes. This study also demonstrates the efficiency of DArTseq-based SNP genotyping for large-scale genome analysis in chickpea. The genotypic markers provided in this study are useful for various association mapping studies when combined with phenotypic data of different traits, such as seed yield, abiotic, and biotic stresses, and therefore can be efficiently used in breeding programs to improve chickpea.