Genetic Architecture and Yield Stability of Autumn-Sown Chickpea Landraces in Semi-Arid Environments

Articles in Press

Document Type : Original Article

Authors
Mojtaba Bagheri 1
Zahra Tahmasebi 1
Mahdi Geravandi 2
1 Department of Agronomy and Plant Breeding, Faculty of Agriculture, Ilam University, Ilam, Islamic Republic of Iran.
2 Dryland Agricultural Research Institute (DARI), Agricultural Research, Education and Extension Organization (AREEO), Sararood Branch, Kermanshah, Islamic Republic of Iran.
Abstract
Shifting chickpea (Cicer arietinum L.) cultivation from spring to autumn is a promising strategy to escape terminal drought and maximize yield potential in semi-arid regions; however, success depends on identifying genotypes with suitable phenology and yield performance. This study evaluated 332 desi chickpea genotypes (330 landraces, two checks) over two seasons (2021–2022) under autumn-sown rainfed conditions in western Iran, using Linear Mixed Models (LMM), Genotype × Yield × Trait (GYT) biplots, Structural Equation Modeling (SEM), and the Multi-Trait Genotype-Ideotype Distance Index (MGIDI). Results revealed trait-dependent genetic variation, with heritability highest for hundred-seed weight (H² = 94.9%) and moderate for plant height (H²= 40.6%) and days to flowering (H²= 35.1%), while seed yield showed no detectable genotypic variance under the single-replicate design. No genotype excelled across all GYT combinations, though G313 ranked highest for yield × hundred-seed weight in both years, a promising parental candidate. SEM identified plant height as the dominant trait underlying agronomic performance in both seasons, with a direct positive association with seed yield emerging in 2022, while the top genotype for the yield–height combination shifted between years (G33 in 2021, G49 in 2022). Integrating both seasons, MGIDI ranked 114 landraces above the better commercial check, with G5 first overall, confirming its identification as a GYT winner. Plant height should be one component of a broader selection strategy rather than a standalone target, given genotype × year variability and lodging risk. The identified superior landraces (G5, G313) offer valuable genetic resources for breeding climate-resilient chickpea cultivars.
Keywords
Augmented design
Cicer arietinum L
GYT biplot
MGIDI
Structural Equation Modeling
Terminal drought tolerance
Subjects
1.      Akaike, H. (2003). A new look at the statistical model identification. IEEE transactions on automatic control, 19(6), 716-723.
2.      Annicchiarico, P., Laouar, M., Thami-Alami, I., Crosta, M., Nazzicari, N., Pecetti, L., & Russi, L. (2025). Comparison of phenotypic selection of inbred lines, genomic selection of inbred lines, and evolutionary populations for field pea breeding in three Mediterranean regions. Frontiers in plant science, 16, 1565087.
3.      Aparicio, J., Gezan, S. A., Ariza-Suarez, D., Raatz, B., Diaz, S., Heilman-Morales, A., & Lobaton, J. (2024). Mr. Bean: a comprehensive statistical and visualization application for modeling agricultural field trials data. Frontiers in Plant Science, 14, 1290078.
4.      Barmukh, R., Roorkiwal, M., Garg, V., Khan, A. W., German, L., Jaganathan, D., Chitikineni, A., Kholova, J., Kudapa, H., & Sivasakthi, K. (2022). Genetic variation in CaTIFY4b contributes to drought adaptation in chickpea. Plant Biotechnology Journal, 20(9), 1701-1715.
5.      Brooks, M. E., Kristensen, K., Van Benthem, K. J., Magnusson, A., Berg, C. W., Nielsen, A., Skaug, H. J., Mächler, M., & Bolker, B. M. (2017). glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling.
6.      Burnham, K. P., & Anderson, D. R. (2004). Multimodel inference: understanding AIC and BIC in model selection. Sociological methods & research, 33(2), 261-304.
7.      Devlieger, I., & Rosseel, Y. (2017). Factor score path analysis. Methodology.
8.      Epskamp, S., Stuber, S., Nak, J., Veenman, M., & Jorgensen, T. (2019). semPlot: Path diagrams and visual analysis of various SEM packages’ output. R package version, 1(2).
9.      FAOSTAT. (2022). FAOSTAT online database. https://www.fao.org/faostat/
10.  Fayaz, H., Mir, A. H., Tyagi, S., Wani, A. A., Jan, N., Yasin, M., Mir, J. I., Mondal, B., Khan, M. A., & Mir, R. R. (2022). Assessment of molecular genetic diversity of 384 chickpea genotypes and development of core set of 192 genotypes for chickpea improvement programs. Genetic Resources and Crop Evolution, 69(3), 1193-1205.
11.  Federer, W. T. (1956). Augmented (or hoonuiaku) designs.
12.  Frutos, E., Galindo, M. P., & Leiva, V. (2014). An interactive biplot implementation in R for modeling genotype-by-environment interaction. Stochastic Environmental Research and Risk Assessment, 28(7), 1629-1641.
13.  Golpira, H. (2013). Conceptual design of a chickpea harvesting header. Spanish Journal of Agricultural Research, 11(3), 635-641.
14.  Holland, J. B., Nyquist, W. E., & Cervantes-Martínez, C. T. (2003). Estimating and interpreting heritability for plant breeding: an update. Plant breeding reviews, 22, 9-112.
15.  IBPGR. (1993). IBPGR ICRISAT.
16.  Istanbuli, T., Nassar, A. E., Abd El-Maksoud, M. M., Tawkaz, S., Alsamman, A. M., & Hamwieh, A. (2024). Genome-wide association study reveals SNP markers controlling drought tolerance and related agronomic traits in chickpea across multiple environments. Frontiers in Plant Science, 15, 1260690.
17.  Jorben, J., Rao, A., Bharadwaj, C., Nitesh, S., Tiwari, N., Kumar, T., Saxena, D., Yasin, M., Sontakke, P., & Jahagirdar, J. E. (2022). Multi-trait multi environment analysis for stability in MABC lines of Chickpea (Cicer arietinum). Indian J. Agric. Sci, 92, 1005-1009.
18.  Kendal, E. (2019). Comparing durum wheat cultivars by genotype× yield× trait and genotype× trait biplot method. Chilean journal of agricultural research, 79(4), 512-522.
19.  Lê, S., Josse, J., & Husson, F. (2008). FactoMineR: an R package for multivariate analysis. Journal of statistical software, 25, 1-18.
20.  Maleki, H. H., Khoshro, H. H., Kanouni, H., Shobeiri, S. S., & Ashour, B. M. (2024). Identifying dryland-resilient chickpea genotypes for autumn sowing, with a focus on multi-trait stability parameters and biochemical enzyme activity. BMC Plant Biology, 24(1), 750.
21.  Meuwissen, T. H., Sonesson, A. K., Gebregiwergis, G., & Woolliams, J. A. (2020). Management of genetic diversity in the era of genomics. Frontiers in genetics, 11, 880.
22.  Olivoto, T., & Nardino, M. (2021). MGIDI: Toward an effective multivariate selection in biological experiments. Bioinformatics, 37(10), 1383-1389.
23.  Pandey, P., Irulappan, V., Bagavathiannan, M. V., & Senthil-Kumar, M. (2017). Impact of combined abiotic and biotic stresses on plant growth and avenues for crop improvement by exploiting physio-morphological traits. Frontiers in plant science, 8, 537.
24.  Piepho, H., Möhring, J., Melchinger, A., & Büchse, A. (2008). BLUP for phenotypic selection in plant breeding and variety testing. Euphytica, 161(1), 209-228.
25.  Piepho, H. P., Boer, M. P., & Williams, E. R. (2022). Two‐dimensional P‐spline smoothing for spatial analysis of plant breeding trials. Biometrical Journal, 64(5), 835-857.
26.  R Core Team. (2025). R: A language and environment for statistical computing. In (Version 4.5.0) R Foundation for Statistical Computing. https://www.R-project.org/
27.  Roorkiwal, M., Bharadwaj, C., Barmukh, R., Dixit, G. P., Thudi, M., Gaur, P. M., Chaturvedi, S. K., Fikre, A., Hamwieh, A., & Kumar, S. (2020). Integrating genomics for chickpea improvement: achievements and opportunities. Theoretical and Applied Genetics, 133(5), 1703-1720.
28.  Rosseel, Y. (2012). lavaan: An R package for structural equation modeling. Journal of statistical software, 48(1), 1-36.
29.  Self, S. G., & Liang, K.-Y. (1987). Asymptotic properties of maximum likelihood estimators and likelihood ratio tests under nonstandard conditions. Journal of the American Statistical Association, 82(398), 605-610.
30.  Smith, A. B., Cullis, B. R., & Thompson, R. (2005). The analysis of crop cultivar breeding and evaluation trials: an overview of current mixed model approaches. The Journal of Agricultural Science, 143(6), 449-462.
31.  Theodoridis, S., Patsiou, T. S., Randin, C., & Conti, E. (2018). Forecasting range shifts of a cold‐adapted species under climate change: are genomic and ecological diversity within species crucial for future resilience? Ecography, 41(8), 1357-1369.
32.  Thudi, M., Chitikineni, A., Liu, X., He, W., Roorkiwal, M., Yang, W., Jian, J., Doddamani, D., Gaur, P. M., & Rathore, A. (2016). Recent breeding programs enhanced genetic diversity in both desi and kabuli varieties of chickpea (Cicer arietinum L.). Scientific Reports, 6(1), 38636.
33.  Turner, N. C., Wright, G. C., & Siddique, K. (2001). Adaptation of grain legumes (pulses) to water-limited environments.
34.  Vadithya, A. S., Bindra, S., Sharma, N., Sanwal, S. K., S, S. P., Singh, I., Bharadwaj, C., & Singh, M. (2025). Multi-model statistical approaches for assessing the stability of Cicer interspecific derivatives in the trans and upper gangetic regions of India. Scientific reports, 15(1), 22230.
35.  Varshney, R. K., Roorkiwal, M., Sun, S., Bajaj, P., Chitikineni, A., Thudi, M., Singh, N. P., Du, X., Upadhyaya, H. D., & Khan, A. W. (2021). A chickpea genetic variation map based on the sequencing of 3,366 genomes. Nature, 599(7886), 622-627.
36.  Yadav, S. S., Redden, R., Chen, W., & Sharma, B. (2007). Chickpea breeding and management. CABI.
37.  Yan HongPing, Y. H., Kang MengZhen, K. M., Reffye, P. d., & Dingkuhn, M. (2004). A dynamic, architectural plant model simulating resource-dependent growth.
38.  Yan, W., & Frégeau-Reid, J. (2018). Genotype by yield* trait (GYT) biplot: a novel approach for genotype selection based on multiple traits. Scientific reports, 8(1), 8242.
39.  Zhu, H., Wang, L., Li, X., Shi, J., Scanlon, M., Xue, S., Nosworthy, M., & Vafaei, N. (2024). Canola seed protein: Pretreatment, extraction, structure, physicochemical and functional characteristics. Foods, 13(9), 1357.
Journal of Agricultural Science and Technology

Articles in Press, Accepted Manuscript
Available Online from 18 August 2026