ارزیابی پتانسیل عملکرد ژنوتیپ‌های گندم دیم در شرایط بهره‌بردار

نوع مقاله : مقاله پژوهشی

نویسندگان

1 بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی لرستان، سازمان تحقیقات، آموزش و ترویج کشاورزی، خرم آباد، ایران

2 کارشناس زراعت مرکز خدمات کشاورزی خوشناموند، مدیریت جهاد کشاورزی شهرستان کوهدشت، کوهدشت، ایران

3 کارشناس زراعت سازمان جهاد کشاورزی لرستان، خرم‌آباد، ایران

چکیده

ارزیابی و نمایش پتانسیل ارقام جدید و لاین‌های امید‌بخش در مزارع زارعین به منظور معرفی ارقام و لاین‌های جدید اصلاحی و نفوذ بیشتر آن­ها در مزارع حائز اهمیت است. به همین منظور، تعداد 33 رقم و لاین‌ انتخابی از برنامه­های اصلاحی گندم مؤسسه تحقیقات کشاورزی دیم و ارسالی از مرکز تحقیقات بین‌المللی ایکاردا در قالب طرح بلوک‌های کامل تصادفی در مزارع زارعین شهرستان کوهدشت ارزیابی شدند. نتایج عملکرد دانه ژنوتیپ‌ها نشان داد، ارقام کبیر و پایا و لاین‌های G17، G18 و G31 به ترتیب با میانگین‌های عملکرد دانه 5280، 3985، 4210، 4003 و 3950 کیلوگرم در هکتار بیشترین عملکرد دانه را دارا بودند. ارزیابی ژنوتیپ‌ها از نظر شاخص انتخاب ژنوتیپ ایده‌آل (SIIG) نیز نشان داد، ارقام کبیر و پایا و لاین‌های G31، G18، G29، G17، G16 با بیشترین مقدار شاخص SIIG (به ترتیب 0/822، 0/720، 0/791، 0/779، 0/767، 0/736 و 0/745) جزء برترین ژنوتیپ‌ها بودند. ژنوتیپ‌های G13 و G27 با مقدار SIIG کمتر (به ترتیب 0/582 و 0/576) جزء ژنوتیپ‌های ضعیف از نظر اکثر صفات مورد ‌ارزیابی بودند. نتایج این مطالعه نشان داد عملکرد بیوماس، تعداد دانه در سنبله، شاخص برداشت و زودرسی را می‌توان بعنوان معیار گزینش مناسب برای شناسایی ژنوتیپ‌های پرمحصول در برنامه به‌نژادی گندم دیم در نظر گرفت. همبستگی مثبت و قوی بین شاخص SIIG و عملکرد دانه بیانگر سهم بیشتر عملکرد دانه در مقدار شاخص SIIG بود. بر اساس نتایج تجزیه خوشه‌ای، ژنوتیپ‌ها به سه گروه ژنوتیپ‌های زودرس با عملکرد دانه بالا (گروه 1)، ژنوتیپ‌های دیررس با عملکرد دانه پایین (گروه 2) و ژنوتیپ‌های زودرس با عملکرد دانه پایین (گروه 3) گروه‌بندی شدند. ژنوتیپ‌های با عملکرد بالا و زودرس در گروه 1 می‌توانند به عنوان ژنوتیپ‌های امیدبخش برای کاشت در دیم­زارهای مناطق گرمسیر و یا به عنوان والدین برای بهبود عملکرد و سایر خصوصیات مطلوب زراعی در برنامه به‌نژادی گندم دیم در نظر گرفته شوند.

کلیدواژه‌ها


عنوان مقاله [English]

Grain yield potential of wheat genotypes on farmers' fields under rainfed conditions

نویسندگان [English]

  • Mahnaz Rahmati 1
  • Ali Ahmadi 1
  • Ali Minapoor 2
  • Kiyanoush Hamidiyan 3
1 Crop and Horticultural Science Research Department, Lorestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Khorramabad, Iran
2 Agronomy Expert, Agricultural Service center of Khoshnamvand, Jahad-Agriculture Management of Kouhdasht, Kouhdasht, Iran
3 Agronomy Expert, Jahad-Agriculture Organization of Lorestan, Khorramabad, Iran
چکیده [English]

Introduction: It is crucial  to introduce and develop new high-yielding dryland wheat cultivars with resistance to biotic and abiotic stresses, given the extent of wheat cultivation in tropical regions and the occurrence of drought in recent years. On-farm experimentation provides new insights and is a suitable method for informing farmers about novel technologies, such as new crop varieties. Using the SIIG index and cluster analysis, the current study aimed to identify the superior wheat genotypes for grain yield and other agronomic traits in tropical drylands and introduce them to farmers.
Material and Methods: In current study, 33 varieties/ pure lines selected from the DARI and ICARDA wheat breeding programs were cultivated on farmers' fields of Lorestan province using a randomized complete block design (RCBD) with two replications during 2017-18 cropping season. The genotypes evaluated consisted of 12 cultivars and 21 pure lines of bread wheat and durum wheat, respectively. The pedigree of all genotypes is presented in table 1. The following nine characteristics were recorded: days to heading (DH), plant height (PH), Days to maturity (DM), spikes per square meter (SSM), number of grains per spike (NGPS), 1000 kernel weight (TKW), biological yield (BY), Grain yield (GY), and harvest index (HI). Using ANOVA, all investigated characteristics were analyzed. Genotypes means were compared using the least significance difference (LSD) at 5% and 1% probability level. Correlation analysis was performed using the Pearson method. Selection index of ideal genotype (SIIG) was utilized to select the genotypes with the highest yield and agronomic traits. In addition, cluster analysis using the WARD method and principal component analysis were employed to categorize genotypes. To analyze the data, MSTATC, IBM SPSS Statistics ver. 22 and Excel were utilized.
Results and Discussion:  Paya and Kabir varieties and G17, G18, and G31 lines had the highest average grain yields, with yields of 5,280, 3,985, 4,210, 4,003, and 3,950 kg/ha, respectively. The SIIG index indicated that Kabir and Paya varieties, and G31, G18, G29, G17 and G16 lines with a high SIIG value (0.822, 0.720, 0.791, 0.779, 0.767, 0.736 and 0.745, respectively) were superior genotypes, whereas G13 and G17 lines with a low SIIG (0.582 and 0.576, respectively) were the weakest genotypes for the majority of traits evaluated in the current study. Grain yield exhibited a significant and positive correlation with biological yield (BY), number of grains per spike (NGPS), and harvest index, according to correlation analysis (HI). Days to heading and maturity correlated negatively with grain yield. Therefore, BY, NGPS, HI, and early maturity may be suitable indicators for selecting high-performing genotypes in wheat breeding programs under rainfed conditions. Strong and positive correlation was observed between the SIIG index and grain yield. This issue reflected a larger proportion of grain yield in the SIIG index. Cluster analysis classified genotypes into three primary classes. Class 1 consisted of maturity date genotypes with high yield, Class 2 consisted of early maturity genotypes with low yield, and Class 3 consisted of early maturity genotypes with low yield. In the current study, first -class genotypes with high yield and earliness were deemed promising genotypes for planting in tropical regions under rainfed conditions or as parents for improving yield and desirable agronomic traits in wheat breeding programs.
Conclusion: The best genotypes, as determined by the SIIG index and cluster analysis, are the Kabir and Paya varieties and the G31, G18, G29, G17, and G16 lines, which are suitable for planting in drylands and further breeding programs. Significant and positive correlations between grain yield and biological yield (BY), number of grains per spike (NGPS), and harvest index (HI) indicated that these traits could be regarded as suitable indicators for enhancing grain yield in wheat under rainfed conditions. In the current study, genotypes with higher grain yield and desirable agronomic traits had the highest SIIG index. SIIG index could therefore be utilized as a suitable method for identifying the best genotypes on various crops.

کلیدواژه‌ها [English]

  • Cluster analysis
  • Correlation
  • SIIG index
Abdollahi Hesar, A., Sofalian, O., Alizadeh, B., Asghari, A. and Zali, H. 2020. Evaluation of some autumn canola genotypes based on agronomy traits and SIIG index. Journal of Crop Breeding, 12(34): 151-159. (In Persian).
Arifuzzaman, M., Barman, S., Hayder, S., Azad, M.A.K., Turin, M.T.S., Amzad, M.A. and Masuda, M.S. 2020. Screening of bread wheat (Triticum aestivum L.) genotypes under drought stress conditions using multivariate analysis. Cereal Research Communications, 48(3): 301-308.
Arzhang, S., Bernosi, I., Abdollahi Mandolakoni, B. and Hassanzadeh Ghoorttappeh, A. 2017. Genetic diversity of grain yield and some morphological traits in local bread wheat lines. Seed and Plant Journal, 32(4): 493-510. (In Persian).
Khoshgoftarmanesh, A.H., Sharifi, H.R., Afiuni, D. and Schulin, R. 2012. Classification wheat genotypes by yield and densities of grain zinc and iron using cluster analysis. Journal of Geochemical Exploration, 121: 49-54. (In Persian).
Liu, B., Asseng, S. and Muller, C. 2016. Similar estimates of temperature impacts on global wheat yield by three independent methods. Nature Climate Change, 6: 1130-1136.
Modarresi, M., Mohammadi, V. and Zali, A. 2010. Response of wheat yield and yield related traits to high temperature. Cereal Research Communications, 38: 23-31.
Mondal, S., Joshi, A.K., Huerta-Espino, J. and Singh, R.P. 2015. Early maturity in wheat for adaptation to high temperature stress. PP. 239-252, In: Y. Ogihara (ed.), Advances in Wheat Genetics.
Rahmati, M., Hosseinpour, T. and Ahmadi, A. 2020. Assessment of interrelationship between agronomic traits of wheat genotypes under rain-fed conditions using double and triple biplots of genotype, trait and yield. Iranian Journal of Dryland Agriculture, 9(1): 1-20. (In Persian).
Sadeghzadeh, B. and Abediasl, G. 2012. Evaluating agronomic traits related to grain yield of durum wheat landraces in dry lands conditions. Iranian Journal of Dryland Agriculture, 1(1): 40-62. (In Persian).
Shirvani, F., Daneshvar, M., Mohammadi, R. and Ismaili, A. 2021. Evaluation of agro-physiological characteristics and drought tolerance in some of durum wheat breeding genotypes. Journal of Crop Breeding, 12(13): 117-135. (In Persian).
Soleymanifard, A. and Naseri, R. 2020. Evaluation of relationships between grain yield and agro-physiological traits of bread wheat genotypes under rainfed conditions. Environmental Stresses in Crop Sciences, 13(3): 701-714. (In Persian).
Tadili, S., Asghari, A., Karimizadeh, R., Sofalian, O. and Mohammaddoust Chamanabad, H.R.  2020. Evaluation of drought stress tolerance in advanced lines durum wheat using the selection index of ideal genotype (SIIG). Journal of crop Ecophysiology, 14(1): 45-61. (In Persian).
Tahmasebi, S., Dastfal, M., Zali, H. and Rajaie, M. 2018. Drought tolerance evaluation of bread wheat cultivars and promising lines in warm and dry climate of the south. Cereal Research, 8(2): 209-225. (In Persian).
Würschum, T., Leiser, W.L., Langer, S.M., Tucker, M.R. and Longin, C.F.H. 2018. Phenotypic and genetic analysis of spike and kernel characteristics in wheat reveals long-term genetic trends of grain yield components. Theoretical and Applied Genetics, 131: 2071-2084.
Yaghoutipoor, A., Farshadfar, E. and Saeedi, M. 2017. Evaluation of wheat genotype for drought tolerance using a suitable combination method. Environmental Stresses in Crop Science, 10(2): 247-256. (In Persian).
Zali, H., Hasanloo, T., Sofalian, O., Asghari, A. and Shariatpanahi, M.E.  2020. Identifying drought tolerant canola genotypes using selection index of ideal genotype. Journal of Crop Breeding, 11(29): 117-126. (In Persian).
Zali, H. and Barati, A. 2020. Evaluation of selection index of ideal genotype (SIIG) in other to selection of barley promising lines with high yield and desirable agronomy traits. Journal of Crop Breeding, 12(34): 93-104. (In Persian).