Yield response of Kabuli-type chickpea genotypes to different environmental conditions using AMMI and GGE biplot methods

Document Type : Research Paper

Authors

1 Field and Horticultural Crops Research Department, Agriculture and Natural Resources Research and Education Center of Kurdistan, AREEO, Sanandaj, Iran.

2 Food Legume Department, Dryland Agricultural Research Institute, AREEO, Maragheh, Iran.

3 Field and Horticultural Crops Research Department, Agriculture and Natural Resources Research and Education Center of Zandjan, AREEO, Zandjan, Iran.AREEO, Zandjan, Iran.

Abstract

To evaluate the genotype × environment (G × E) interaction and stability of grain yield in the Kabuli type chickpea (Cicer arietinum L.), 15 white chickpea genotypes were evaluated in a randomized complete block design with four replications in Kurdistan, Maragheh, and Zandjan stations during three successive years under spring dryland conditions. Combined analysis of variance showed significant variation (p < 0.05) among the genotypes for grain yield. The results of AMMI (additive main effects and multiplicative interaction) analysis showed that the two first components (PC1 and PC2) of interaction were highly significant (p < 0.01) and accounted for 52% and 34% of the G × E interaction, respectively. The AMMI model determined the best combinations of genotypes and environments for grain yield. FLIP 09-369C had the highest level of stability under the present test conditions, which can be considered as a new cultivar. Also, the interaction effect of GE was studied by the GGE biplot method. According to the singular value decomposition, the first two principal components explained 52% and 34% of the total variation. Based on the GGE biplot method, the genotypes FLIP 09-369c, FLIP 09-365c, and FLIP 09-247c had higher grain yield and stability than other genotypes. The GGE biplot analysis divided the environments into two mega-environments including KURDISTAN-MARAGHEH and ZANDJAN, and for each mega-environment, FLIP 09-369C and FLIP 09-251C lines were recommended, respectively. The study also indicated that FLIP 09-364C, Samin, and FLIP 09-212C were identified as lines with general adaptability.

Keywords

Main Subjects

Article Title [Persian]

بررسی پاسخ عملکرد ژنوتیپ های نخود تیپ کابلی به شرایط متفاوت محیطی با استفاده از روش های AMMI و بای پلات GGE

Authors [Persian]

  • همایون کانونی 1
  • یداله فرایدی 2
  • سودابه شبیری 3
1 بخش تحقیقات زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان کردستان، سازمان تحقیقات، آموزش و ترویج کشاورزی، سنندج
2 بخش تحقیقات حبوبات، موسسه تحقیقات کشاورزی دیم کشور، سازمان تحقیقات، آموزش و ترویج کشاورزی، مراغه
3 بخش تحقیقات زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان زنجان، سازمان تحقیقات، آموزش و ترویج کشاورزی، زنجان
Abstract [Persian]

برای بررسی اثر متقابل ژنوتیپ × محیط و پایداری عملکرد دانه در نخود تیپ کابلی، 15 ژنوتیپ نخود سفید در قالب طرح بلوک‌های کامل تصادفی با چهار تکرار در ایستگاه‌های کردستان، مراغه و زنجان طی سه سال متوالی در شرایط دیم بهاره مورد ارزیابی قرار گرفتند. تجزیه واریانس مرکب نشان داد که تغییرات بین ژنوتیپ ­ها از لحاظ عملکرد دانه معنی دار است (p≤ 0.05). نتایج تجزیه اثرات اصلی افزایشی و اثرات متقابل ضربی (AMMI) نشان داد که دو مؤلفه اصلی اول (PC1) و دوم (PC2) بسیار معنی­ دار هستند (p≤ 0.01) که به ترتیب 52% و 34% از اثرمتقابل ژنوتیپ × محیط را به خود اختصاص دادند. مدل AMMI بهترین ترکیب ژنوتیپ ­ها و محیط­ ها را برای عملکرد دانه تعیین کرد. بر اساس نتایج حاصل، FLIP 09-369C بالاترین سطح پایداری را در شرایط آزمایش حاضر داشت که می ­تواند به عنوان رقم جدید در نظر گرفته شود. همچنین، اثرمتقابل GE  توسط روش بای پلات بررسی شد. با توجه به تجزیه مقادیر منفرد، دو مؤلفه اصلی اول (PC1 و PC2) به ترتیب 52٪ و  %34 تغییرات در کل داده ها را توجیه کردند.  بر اساس نمودارهای بای پلات GGE، ژنوتیپ های C 396 ،C365 و C247 نسبت به سایر ژنوتیپ­ ها عملکرد و پایداری بیشتری داشتند. تجزیه و تحلیل بای پلات GGE محیط­ ها را به دو محیط کلان شامل کردستان+ مراغه و زنجان تقسیم کرد و برای هر محیط کلان به ترتیب ژنوتیپ­ های FLIP 09-369C  و FLIP 09-251C توصیه شدند. همچنین در این مطالعه FLIP 09-364C ،Samin  و FLIP212C  به عنوان ژنوتیپ­ های با سازگاری عمومی شناسایی شدند.
 

Keywords [Persian]

  • بای پلات GGE
  • پایداری
  • تجزیه AMMI
  • کشاورزی دیم
  • نخود (.Cicer arietinum L)

References

Abebe T, Nega Y, Mehari M, Mesele A, Workineh A, Beyene H. 2015. Genotype by environment interaction of some faba bean genotypes under diverse broomrape environments of Tigray. Ethiopian J. Plant Breed. and Crop Sci. 7(3): 79-86.
Agahi K, Ahmadi J, Amiri Oghan H, Fotokian MH, Fabriki Orang S. 2020. Analysis of genotype × environment interaction for seed yield in spring oilseed rape using the AMMI model. Crop Breed Appl Biotechnol. 20(1): e26502012.
Bartlett MS. 1937. Properties of sufficiency and statistical tests. Proc Royal Stat Soc, Ser A. 160: 268-282.
Bhat S, Aditya KS, Kumari B, Acharya KK, Sendhil R. 2022. Pulses production, trade and policy imperatives: A global perspective. In: Ram Swaroop Meena RS, Sandeep K, editors. Advances in legumes for sustainable intensification. Cambridge, Massachusetts: Academic Press. p.  639-656.
Crossa J, Gauch HG, Zobel RW. 1990. Additive main effects and multiplicative interactions analysis of two international maize cultivar trials. Crop Sci. 30: 493-500.
Erdemci I. 2018. Investigation of genotype× environment interaction in chickpea genotypes using AMMI and GGE biplot analysis. Turk J Field Crops 23(1): 20-26.
FAOSTAT. 2021. Crops. http://www.fao.org/faostat/en/#data/QC/Accessed 28 September 2020.
Farshadfar E, Sabaghpour SH, Zali H. 2012. Comparison of parametric and non-parametric stability statistics for selecting stable chickpea (Cicer arietinum L.) genotypes under diverse environments. Aust J Crop Sci. 6: 514-524.
Finlay K, Wilkinson G. 1963. The analysis of adaptation in a plant-breeding programme. Crop Pasture Sci. 14: 742-754.
Gauch HG. 2006. Statistical analysis of yield trials by AMMI and GGE. Crop Sci. 46: 1488-1500.
Gurmu F, Shimelis H, Laing M, Mashilo J. 2020. Genotype-by-environment interaction analysis of nutritional composition in newly-developed sweet potato clones. J Food Compost Anal. 88: 103426.
Kang MS. 1993. Simultaneous selection for yield and stability in crop performance trials: Consequences for growers. Agron J. 85: 754-757.
Kanouni H, Sadeghzadeh Ahari D, Saeid A, Shobeiri S, Mahdieh M, Haji Hasani M, Sotoudeh-Maram K, Beheshti Danalou M. 2021. Investigation of grain yield stability of Desi type chickpea across different environments and introducing promising lines. J Agric Sci Sustain Prod. 31(1): 295-312.
Karimizadeh R, Pezeshkpour P, Mirzaei A, Barzali M, Keshavarzi K, Sharifi P. 2022. Evaluation of seed yield stability of chickpea genotypes using GGE Biplot method. J Crop Prod Process.11(4): 81-92 (In Persian with English abstract).
Kaya Y, Palta C, and Taner S. 2002. Additive main effects and multiplicative interactions of yield performance in bread wheat genotypes across environments. Turk J Agric For. 26: 275-279.
Maya M, Maphosa M. 2020. Current status of chickpea production: Opportunities for promoting, adoption and adapting the crop in Zimbabwe: A review. J Dryland Agric. 6(1): 1-9.
Mohammadi M, Armion M, Zadhassan E, Eskandari M. 2013. Analysis of genotype × environment interaction for grain yield in rainfed durum wheat. Iranian J Dryland Agric. 1: 1-15.
Muehlbauer FJ, Sarker A. 2017. Economic importance of chickpea: Production, value, and world trade. In: Varshney R, Thudi M, Muehlbauer F, editors. The chickpea genome. Compendium of Plant Genomes. Cham: Springer. p. 5-12
Nowosad K, Liersch A, Popawska W, Bocianowski J. 2016. Genotype by environment interaction for seed yield in rapeseed (Brassica napus L.) using additive main effects and multiplicative interaction model. Euphytica 208: 187-194.
SAS Institute. 2008. Statistical analysis systems. Version 9.1. Cary, North Carolina, USA: SAS Institute Inc.           
Singh KB. 1997. Chickpea (Cicer arietinum L.). Field Crops Res. 53: 161-170.
Sundaram P, Srinivasan Samineni S, Sajja SB, Roy C, Singh SP, Joshi P, Gaur PM. 2018. Inheritance and relationships of flowering time and seed size in Kabuli chickpea. Euphytica 215: 144.
Tadesse T, Tekalign A, Sefera G, Muligeta B.2017. AMMI model for yield stability analysis of linseed genotypes for the highlands of Bale, Ethiopia. Plant 5(6): 93-98.
Vargas HM and Crossa J. 2000. The AMMI analysis and the graphing the biplot in SAS. Mexico: CIMMYT. 42 p.
Yadav SS, Redden RJ, Chen W, Sharma B. 2007. Chickpea breeding and management. Wallingford, UK: CAB International. 638 p.
Yan W. 2009. GGE-biplot software version 5.2. The complete biplot analysis system: GGEbiplot Pattern Explorer. Copy Right Weikai Yan, 2001-2009, USA.
Yan W, Kang MS. 2003. GGE biplot analysis: A graphical tool for breeders, geneticists and agronomists Boca Raton, FL: CRC Press. 271 p.
Yan W, Kang MS, Ma B, Woods S, Cornelius PL. 2007. GGE biplot vs. AMMI analysis of genotype-by-environment data. Crop Sci. 47: 643-653.
Journal of Plant Physiology and Breeding
Volume 13, Issue 2
December 2023
Pages 29-42

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