تحقیقات علوم زراعی در مناطق خشک

تحقیقات علوم زراعی در مناطق خشک

ارزیابی لاین‌های امیدبخش گندم نان با عملکرد بالا و خصوصیات زراعی مطلوب با استفاده از شاخص انتخاب ژنوتیپ ایده‌آل در جنوب استان فارس

نوع مقاله : مقاله پژوهشی

نویسندگان
1 بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی فارس، سازمان تحقیقات، آموزش و ترویج کشاورزی (AREEO)، داراب، ایران
2 موسسه تحقیقات اصلاح و تهیه نهال و بذر، سازمان تحقیقات، آموزش و ترویج کشاورزی (AREEO)، کرج، ایران
3 بخش تحقیقات علوم زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی فارس، سازمان تحقیقات، آموزش و ترویج کشاورزی، شیراز (AREEO)، ایران
چکیده
شناسایی و انتخاب لاین‌ها و ارقام مناسب برای کشت گندم نان در هر ناحیه جغرافیایی اهمیت زیادی دارد. بدین منظور، این پژوهش به‌منظور ارزیابی و انتخاب لاین‌های برتر گندم نان واجد صفات مطلوب زراعی در مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی فارس در سال‌های زراعی 1398-1399 و 1399-1400 انجام گردید. در سال اول، 315 لاین خالص و چهار شاهد بررسی و 65 لاین برتر با استفاده از شاخص انتخاب ژنوتیپ ایده­آل (SIIG) انتخاب و در سال دوم، این لاین‌ها تحت طرح آلفا لاتیس در دو تکرار آزمایش شدند. در سال اول، نتایج نشان داد که میانگین عملکرد دانه در لاین‌های انتخاب شده 7/69 تن در هکتار بود که از میانگین عملکرد ژنوتیپ­های شاهد (6/97 تن در هکتار) و مجموع ژنوتیپ­ها (6/50 تن در هکتار) بیشتر بود. در سال دوم، تفاوت‌های معنی‌داری بین لاین‌ها در اکثر صفات مورد بررسی مشاهده شد. از نظر دیفرانسیل گزینش، بیشترین و کمترین مقدار به ترتیب مربوط به صفات وزن هزار دانه (4/80 درصد) و ارتفاع با (0/89- درصد) بود. علاوه بر این، دیفرانسیل کل مطلوب مثبت و منفی به ترتیب 5/60 درصد و 2/69- درصد به‌ دست آمد. شاخص SIIG لاین‌ها را به شش گروه تقسیم کرد. ژنوتیپ‌های شماره 28، 36، 60، 25، 45، 53، 35، 12، 33، 11، 37، 16، 34، 19، 59، 48، 49، 8 و 30 با عملکرد بالاتر از ارقام شاهد به عنوان بهترین ژنوتیپ‌ها شناسایی شدند. با توجه به نتایج، لاین‌های منتخب برای بررسی سازگاری در آزمایشات یکنواخت سراسری اقلیم گرم کشور معرفی گردیدند.
کلیدواژه‌ها

عنوان مقاله English

Evaluation of promising high-yield bread wheat lines with desirable agronomic traits using the selection index of ideal genotype (SIIG) in southern Fars province

نویسندگان English

Ali Reza Askari Kelestani 1
Mohsen Esmaeilzadeh Moghadam 2
Sirous Tahmasebi 3
Manouchehr Dastfal 1
1 Crop and Horticultural Science Research Department, Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Darab, Iran
2 Seed and Plant Improvement Department, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran
3 Crop and Horticultural Science Research Department, Fars Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Shiraz, Iran
چکیده English

Introduction: Identifying and selecting suitable lines and varieties for wheat cultivation in each geographical area is of great importance. New wheat lines are commonly evaluated through advanced experiments in similarly climatic regions, using the results to identify appropriate varieties for cultivation in each area within most breeding programs worldwide. The aim of this research is to conduct an initial assessment of wheat lines and identify superior lines for further testing, with the goal of introducing new varieties in the southern region of Fars province.
Materials and Methods: This research was conducted to evaluate and select superior bread wheat lines with desirable agronomic traits at the Agricultural Research Station of Darab during the agricultural years 2019-2020 and 2020-2021. The lines used in this research were selected from various experiments conducted in Zabol, Darab, and Karaj, as well as from international trials. Additionally, double haploid lines derived from a joint program between the Seed and Plant Improvement Institute and Florimond Desprez in France were included.. In the first year, 315 pure bread wheat lines were examined, and 65 superior lines were selected using the Selection index of ideal genotype (SIIG). In the second year, these lines, along with three control cultivars, were planted and evaluated in an alpha lattice design.
Results and Discussion: The analysis of variance for quantitative traits in the control varieties indicated no significant differences between the blocks. Performance analysis of the traits shows that the two traits of grain yield (equivalent to 16.45) and grain filling rate (equivalent to 14.78) had the highest coefficients of variation, thus exhibiting the greatest diversity among the quantitative traits. Additionally, the minimum and maximum grain yield of the evaluated lines were 1.83 and 8.33 tons per hectare, respectively. The results of the coefficient of variation parameters, along with the minimum and maximum values, confirm the presence of high diversity in grain yield. Consequently, using the selection index SIIG, lines were selected with an average yield of 7.49 tons per hectare, which was higher than the average yield of the control genotypes (6.97 tons per hectare) and the total lines (6.50 tons per hectare). In the second year, significant differences were observed between the lines for most examined traits. The results of this study also indicate that the average performance of 65 selected lines in the second year was 5.04 tons per hectare, which represents a decrease of approximately 2 tons per hectare compared to the performance of the same lines in the first year. The rainfall recorded in the first year was 486.2 mm, while in the second year, it was 73.7 mm. An analysis of the average temperatures during the two critical months of grain filling, namely April and May, shows that the weather in the first year during these months was cooler than in the second year. This contributed to the reduction of the thousand-grain weight from 42.19 gr in the first year to 33.50 gr in the second year. Regarding selection differential, the highest and lowest values corresponded to the traits thousand grain weight (4.80%) and height (-0.89%), respectively. Additionally, the total selection differential, both positive and negative, was obtained as 5.60% and -2.69%, respectively. The SIIG categorized the lines into six groups. Genotypes number 28, 36, 60, 25, 45, 53, 35, 12, 33, 11, 37, 16, 34, 19, 59, 48, 49, 8, and 30 were identified as the best genotypes with yields exceeding that of the control cultivars. Examination of the pedigree of the top selected lines showed that several of the top selected lines included parents PASTOR, BORL14, KACHU, and WBLL1. These parents likely played a crucial role in the success of these lines compared to other tested lines. The selected parents in this research possess beneficial genes (such as drought resistance genes from the top selected lines originating from SAWYT, temperature tolerance from HTWYT, rust resistance from 13STEMRRSN, etc.) that have enhanced yield and quality of wheat under specific climatic conditions.
Conclusion: The results demonstrated the effectiveness of the SIIG in classifying the genotypes, and based on the findings, the selected lines were introduced for adaptability testing in national uniform trials in the hot climate of the country.

کلیدواژه‌ها English

Alpha lattice design
Grain yield
Thousand grain weight
SIIG index
Adilova, S.S., Qulmamatova, D.E., Baboev, S.K., Bozorov, T.A. and Morgunov, A.I., 2020. Multivariate cluster and principle component analyses of selected yield traits in uzbek bread wheat cultivars. American Journal of Plant Sciences, 11(6), pp.903-912. https://doi.org/10.4236/ajps.2020.116066
Aglan, M.A., Abd EL- Hamid, E.A. and Morsy, A.M., 2020. Effect of Sowing date on yield and its components for some breads wheat genotypes Zagazig. Agricultural Research, 47, pp.117-122. https://doi.org/10.21608/zjar.2020.70058
Banerjee, K., Krishnan, P. and Das, B., 2020. Thermal imaging and multivariate techniques for characterizing and screening wheat genotypes under water stress condition. Ecological Indicators, 119, No.106829. https://doi.org/10.1016/j.ecolind.2020.106829
Barati, A., Zali, H., Marzoqian, A., Naghipour, F., Pour-Aboughadareh, A. and Kelestani, A.A., 2022. Selection of hull-less barley lines using the selection index of ideal genotype (SIIG) in Ahvaz and Darab regions. Crop Productin, 15(2), pp.161-181. https://doi.org/10.22069/ejcp.2022.19690.2468
Brim, C.A., Johnson, H.W. and Cockerham, C.C., 1959. Multiple selection criteria in soybeans 1. Agronomy Journal, 51(1), pp.42-46. https://doi.org/10.2134/agronj1959.00021962005100010015x
Croissant, R., Peterson, G. and Westfall, D., 1998. Dryland cropping systems (Bulletin No. 0.516). Colorado State University, Cooperative Extension.
Dastfal, M., Aghaee-Sarbarzeh, M. and Zali, H., 2022. Genetic diversity and selection of durum wheat pure lines with desirable agronomy traits using SIIG index. Iranian Journal of Field Crop Science, 53, pp.161-174. [In Persian]. https://doi.org/10.22059/ijfcs.2021.298388.654691
Devesh, P., Moitra, P., Shukla, R. and Pandey, S., 2019. Genetic diversity and principal component analyses for yield, yield components and quality traits of advanced lines of wheat. Journal of Pharmacognosy and Phytochemistry, 8(3), pp.4834-4839.
Egli, D.B., 2004. Seed-fill duration and yield of grain crops. Advances in Agronomy, 83, pp.243-279. https://doi.org/10.1016/s0065-2113(04)83005-0
FAO., 2023. World food situation: Crop prospects and food situation. https://www.fao.org/worldfoodsituation/csdb/en
Gholizadeh, A., Ghaffari, M. and Shariati, F., 2021. Use of selection index of ideal genotype (SIIG) in order to select new high yielding sunflower hybrids with desirable agronomic characteristics. Journal of Crop Breeding, 13(38), pp.116-123. https://doi.org/10.52547/jcb.13.38.116
Gui, Y., Sheteiwy, M.S., Zhu, S., Zhu, L., Batool, A., Jia, T. and Xiong, Y., 2021. Differentiate responses of tetraploid and hexaploid wheat (Triticum aestivum L.) to moderate and severe drought stress: A cue of wheat domestication. Plant Signaling and Behavior, 16(1), 1839710. https://doi.org/10.1080/15592324.2020.1839710
Kamrani, M., Mehraban, A. and Shiri, M., 2018. Identification of drought tolerant genotypes in dryland wheat using drought tolerance indices. Journal of Crop Breeding, 10(28), pp.13-26. [In Persian]. https://doi.org/10.29252/jcb.10.28.13
Keshavarz Nia, R., Esmaeilzadeh Moghaddam, M. and Tabib Ghaffary, S.M., 2023. Evaluation and preliminary identification of superior lines of bread wheat in the north of khuzestan province. Iranian Journal of Field Crop Science, 54(4), pp.177-186. [In Persian]. https://doi.org/10.22059/ijfcs.2023.360719.655011
Koocheki, A., 1994. Crop production in dry region: Cereals, Legumes, Industrial and forage crops (Translated in Persian). Jihad Daneshghahi Mashhad Press. 202p.
Lin, C., 1978. Index selection for genetic improvement of quantitative characters. Theoretical and Applied Genetics, 52, pp.49-56. https://doi.org/10.1007/bf00281316
Mondal, S., Singh, R., Mason, E., Huerta-Espino, J., Autrique, E. and Joshi, A., 2016. Grain yield, adaptation and progress in breeding for early-maturing and heat-tolerant wheat lines in South Asia. Field crops research, 192, pp.78-85. https://doi.org/10.1016/j.fcr.2016.04.017
Olivoto, T. and Lúcio, A.D.C., 2020. Metan: An R package for multi-environment trial analysis. Methods in Ecology and Evolution, 11, pp.783-789. https://doi.org/10.1111/2041-210X.13384
Olivoto, T. and Nardino, M., 2021. MGIDI: Toward an effective multivariate selection in biological experiments. Bioinformatics, 37(10), pp.1383-1389. https://doi.org/10.1093/bioinformatics/btaa981
Rosielle, A. and Hamblin, J., 1981. Theoretical aspects of selection for yield in stress and non‐stress environment 1. Crop Science, 21(6), pp.943-946. https://doi.org/10.2135/cropsci1981.0011183x002100060033x
Shan, Y. and Osborne, C.P., 2024. Diversification of quantitative morphological traits in wheat. Annals of Botany, 133(3), pp.413-426. https://doi.org/10.1093/aob/mcad202
Shirzad, A., Asghari, A., Zali, H., Sofalian, O. and Chamanabad, H.M., 2022. Application of the multi-trait genotype-ideotype distance index in the selection of top barley genotypes in the warm and dry region of Darab. Journal of Crop Breeding, 14)44), pp.65-76. [In Persian]. https://doi.org/10.52547/jcb.14.44.65
Tadili, S., Asghari, A., Karimizadeh, R., Sofalian, O. and Chamanabad, H.M., 2020. Evaluation of drought stress tolerance in advanced lines durum wheat using the selection index of ideal genotype (SIIG). Journal of Crop Ecophysiology, 1(53), pp.45-62. [In Persian]. https://doi.org/10.30495/jcep.2020.671640
Tahmasebi, S., Dastfal, M., Zali, H. and Rajaiee, M., 2018. Drought tolerance evaluation of bread wheat cultivars and promising lines in warm and dry climate of the south. Cereal Research, 8(2), pp.209-225. [In Persian]. https://doi.org/10.22124/c.2018.10434.1398
Yaghotipoor, A., Farshadfar, E.A. and Saeidi, M., 2017. Evaluation of Drought Tolerance in Bread Wheat Genotypes using new mixed method. Environmental Stresses in Crop Sciences, 10(2), pp.247-256. [In Persian]. https://doi.org/10.22077/escs.2017.581
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), pp.93-104. [In Persian]. https://doi.org/10.29252/jcb.12.34.93
Zali, H., Barati, A., Pour-Aboughadareh, A., Gholipour, A., Koohkan, S., Marzoghiyan, A., Bocianowski, J., Bujak, H. and Nowosad, K., 2023. Identification of superior barley genotypes using selection index of ideal genotype (SIIG). Plants, 12(9), No.1843. https://doi.org/10.3390/plants12091843
Zali, H., Hasanloo, T., Sofalian, O., Asgharii, A. and Enayati Shariatpanahi, M., 2019. Identifying drought tolerant canola genotypes using selection index of ideal genotype . Journal of Crop Breeding, 11(29), pp.117-126. https://doi.org/10.29252/jcb.11.29.117

  • تاریخ دریافت 02 مهر 1403
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