مطالعه روند رشد دانه ارقام گندم تحت شرایط تنش خشکی با استفاده از مدل‌های ریاضی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشیار، گروه مهندسی تولید و ژنتیک گیاهی، دانشکده کشاورزی، دانشگاه زنجان، زنجان، ایران

2 دانشجوی دکتری، گروه مهندسی تولید و ژنتیک گیاهی، دانشکده کشاورزی، دانشگاه زنجان، زنجان، ایران

3 استادیار، گروه مهندسی تولید و ژنتیک گیاهی، دانشکده کشاورزی، دانشگاه زنجان، زنجان، ایران

چکیده

مقدمه: تنش خشکی، یکی از مهم‌ترین تنش‌های محیطی در مناطق مختلف دنیا‌ است که باعث ناپایداری عملکرد در گیاهان زراعی‌ می‌شود. بیش از 20 درصد از زمین‌های زراعی دنیا تحت تاثیر خشک‌سالی متوسط تا شدید قرار دارند. مرحله پر شدن دانه، آخرین مرحله در نمو گیاهان زراعی‌ و مهم‌ترین مرحله در تجمع ماده خشک در دانه است. با استفاده از مدل‌های ریاضی می‌توان سرعت و مدت زمان پرشدن دانه و تاثیر عوامل مختلف محیطی و زراعی بر این دو ویژگی مهم تاثیرگذار بر وزن دانه را پیش‌بینی کرد. مدل‌های کوادراتیک، مکعب چند جمله‌ای و لجستیک از جمله مدل‌های ریاضی هستند که به‌صورت کارآمد جهت پیش‌بینی روند رشد دانه استفاده شده‌اند. هدف از اجرای این تحقیق، بررسی روند رشد دانه و تجمع مواد فتوسنتزی در دانه ارقام مختلف گندم تحت شرایط بدون تنش (شاهد) و تنش خشکی انتهای فصل با استفاده از مدل‌های ریاضی و بررسی تاثیر ویژگی‌های رشد دانه بر عملکرد دانه بود.
مواد و روش‌ها: آزمایش به‌صورت کرت‌های خرد شده در قالب طرح بلوک‌های کامل تصادفی با چهار تکرار در مزرعه تحقیقاتی دانشکده کشاورزی دانشگاه زنجان در سال زراعی 99-1398 اجرا شد. آبیاری معمولی (شاهد) و تنش خشکی پس از گل‌دهی به‌عنوان فاکتور اصلی و چهار رقم گندم (شیراز، مرودشت، آذر2 و روشن) به‌عنوان فاکتور فرعی در نظر گرفته شدند. تنش خشکی با قطع آبیاری تا رسیدن پتانسیل آب خاک به حدود 2- مگاپاسکال اعمال شد. جهت بررسی روند رشد دانه، پس از اتمام گلدهی به فاصله هفت روز یک‌بار از سنبله‌های اصلی نمونه‌گیری و پس از خشک شدن سنبله‌ها، دانه‌ها از سنبله جدا و وزن تک‌دانه محاسبه و سپس با استفاده از مدل‌های ریاضی مختلف، روند رشد دانه‌ها ارزیابی شد. به‌منظور تعیین بهترین مدل از شاخص‌های آماری مجذور میانگین مربعات خطا (RMSE)، آکائیک تصحیح شده (AICc) و شاخص i∆ استفاده و مدلی که کم‌ترین میزان این شاخص‌ها را داشت، به‌عنوان بهترین مدل انتخاب شد. در انتها حداکثر سرعت پر شدن دانه، میانگین سرعت پر شدن دانه و مدت زمان پر شدن دانه با استفاده از مدل برگزیده برآورد شد. علاوه بر روند رشد دانه، صفات ارتفاع بوته، طول سنبله اصلی، عملکرد دانه، عملکرد زیستی و شاخص برداشت نیز اندازه‌گیری شد.
یافته‌های تحقیق: مقایسه مدل‌های مختلف با استفاده از شاخص‌های RMSE، AICc و i∆ نشان داد که مدل داروچ و بیکر (مدل شماره یک) بهترین مدل در ارزیابی روند رشد دانه‌ها در این تحقیق بود. بررسی رشد دانه با این مدل نشان داد که وزن نهایی دانه در تمامی ارقام در شرایط تنش خشکی کاهش یافت و طبق پیش‌بینی این مدل، کم‌ترین و بیش‌ترین وزن نهایی دانه به‌ترتیب متعلق به رقم‌های آذر2 و شیراز بود. مدت زمان پرشدن دانه نیز تحت شرایط تنش خشکی کاهش 9.3 درصدی نشان داد و رقم‌های شیراز (42.3 روز)  و آذر2 ( 34.4 روز) به‌ترتیب بیش‌ترین و کم‌ترین مدت زمان پرشدن دانه را داشتند. تنش خشکی، سرعت فتوسنتز، دوام سطح برگ و تعداد دانه در سنبله را نیز کاهش داد، اما میانگین و حداکثر سرعت پرشدن دانه تحت تاثیر تنش خشکی قرار نگرفت که احتمالاً ناشی از افزایش انتقال مجدد مواد فتوسنتزی تحت شرایط تنش خشکی باشد. همبستگی مثبت و معنی‌داری بین مدت زمان پر شدن دانه با عملکرد دانه تحت شرایط تنش خشکی (0.375=r) و شاهد (0.634=r) مشاهده شد و می‌توان نتیجه گرفت که در این تحقیق مدت زمان پر شدن دانه مهم‌تر از سرعت پر شدن دانه بود. تنش خشکی، وزن هزار دانه ارقام مورد مطالعه را در حدود 18.3 درصد کاهش داد و رقم آذر2 و مرودشت به‌ترتیب با 47.70 و 33.50 گرم، بیش‌ترین و کم‌ترین وزن هزار دانه را داشتند. عملکرد دانه و شاخص برداشت ارقام مورد مطالعه نیز به‌ترتیب در حدود 40.8 درصد و 22.4 درصد تحت شرایط تنش خشکی کاهش یافتند و رقم‌های شیراز (4747.4 کیلوگرم) و آذر2 (3179 کیلوگرم) بیش‌ترین و کم‌ترین عملکرد دانه را تولید کردند. کاهش شاخص برداشت نشان داد که تنش خشکی عملکرد دانه را بیش از عملکرد زیستی کاهش داده است که احتمالاً به‌دلیل کوتاه شدن دوره پرشدن دانه و اختلال در فرایند پر شدن دانه است.
نتیجه‌گیری: در مجموع نتایج این آزمایش نشان داد که تنش خشکی پایان فصل به‌طور معنی‌داری سرعت فتوسنتز، دوام سطح برگ، تعداد دانه در سنبله، وزن هزار دانه و مدت زمان پر شدن دانه ارقام مورد مطالعه را کاهش داد و در نهایت منجر به کاهش عملکرد دانه شد.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Studying the grain growth process of wheat varieties under drought stress conditions using mathematical models

نویسندگان [English]

  • Afshin Tavakoli 1
  • Akireza Hasani 2
  • Kamran Afsahi 3
1 Associate Professor, Department of Plant Production and Genetics, Faculty of Agriculture, University of Zanjan, Zanjan, Iran
2 PhD Student, Department of Plant Production and Genetics, Faculty of Agriculture, University of Zanjan, Zanjan, Iran
3 Assistant Professor, Department of Plant Production and Genetics, Faculty of Agriculture, University of Zanjan, Zanjan, Iran
چکیده [English]

Introduction
Drought stress is one of the most important environmental stresses in different regions of the world, which causes the instability of crop production. More than 20% of the world's agricultural lands are affected by moderate to severe drought stress. The seed filling stage is the last stage in the plant development and the most important stage in the accumulation of dry matter in the seed. Seed filling rate and period and the effect of various environmental and agronomical factors on these two important parameters affecting seed weight can be predicted using the mathematical models. Quadratic, polynomial cubic, and logistic models are among the mathematical models that have been used efficiently to predict the grain growth process. The purpose of this research was to investigate the grain growth process and the accumulation of photosynthetic substances in the grain of different wheat cultivars under non-stress (control) and late season drought stress conditions using mathematical models and to investigate the effect of grain growth parameters on grain yield.
Materials and methods
This experiment was conducted as split plots based on randomized complete block design with four replications in the research field of Faculty of Agriculture, University of Zanjan, Zanjan, Iran, in 2018-2019. Normal irrigation (control) and drought stress after flowering were considered as main factor and four wheat cultivars (Shiraz, Marvdasht, Azar2 and Roshan) as sub-factor. Drought stress was applied by interrupt irrigation until the soil water potential reached about -2 MPa. To investigate the grain growth process, samples were taken from the main spikes after flowering every week. After drying the spikes, the grains were separated from the spike, the weight of single-grain was calculated, and the grain growth process was investigated using different mathematical models. To determine the best model, various statistical indices including root mean square error (RMSE), corrected Akaike (AICc) and ∆i were used, and the model with the lowest values of these indices was selected as the best model. Then, maximum and average grain filling rate, and grain filling period was estimated using the best selected model. The traits of plant height, main spike length, grain yield, biological yield and harvest index were also measured in addition to the grain growth process.
Research findings
Comparison of different models using RMSE, AICc and i∆ indices showed that Darroch and Baker model (model number one) was the best model to evaluate seeds growth process in this research. Investigating the growth of grains with this model showed that the final grain weight decreased in all cultivars under drought stress conditions, and according to the prediction of this model, the lowest and highest final grain weight was belonged to Azar2 and Shiraz, respectively. Grain filling period decreased by 9.3% under drought stress conditions, and Shiraz (42.3 days) and Azar2 (34.4 days) had the highest and lowest grain filling period, respectively. Drought stress also reduced photosynthetic rate, leaf area durability, and number of grains per spike, but average and maximum grain filling rate were not affected by drought stress, which is probably due to the increase in the remobilization of photosynthetic materials under drought stress conditions. A positive and significant correlation was observed between grain filling period and grain yield under drought stress (r=0.375) and control (r=0.634) conditions. It can be concluded that the grain filling period was more important than the grain filling rate in this research. Drought stress decreased 1000-grain weight of the studied varieties by 18.3%, and Azar2 (47.70 g) and Marvdasht (33.50 g) had the highest and lowest 1000-grain weight, respectively. Grain yield and harvest index of the studied varieties also decreased by 40.8% and 22.4% under drought stress conditions, respectively, and Shiraz (4747.4 kg) and Azar2 (3179 kg) varieties produced the highest and lowest grain yield. Decrease in the harvest index indicated that drought stress reduced the grain yield more than the biological yield, which is probably due to the reducing of the grain filling period as well as disturbance in the grain filling process.
Conclusion
The results of this experiment showed that late season drought stress significantly reduced the photosynthetic rate, leaf area durability, number of grains per spike, 1000-grain weight and grain filling period, and finally led to a decrease in grain yield of the studied cultivars.

کلیدواژه‌ها [English]

  • Grain filling period
  • Grain filling rate
  • Grain yield and yield components
  • Late season drought stress

مراجع

Abdoli, M. and Saeidi, M. 2012. Using different indices for selection of resistant wheat cultivars to post anthesis water deficit in the west of Iran. Annals of Biological Research. 3(3): 1322-1333. : https://www.scholarsresearchlibrary.com/archive/abr-volume-3-issue-3-year-2012.html##Abdolshahi, R. A., Taleii, A., Omidi, M. and Yazdi Samadi, B. 2010. Study of Physiological and Morphological Traits Related to Drought Tolerance in Bread Wheat. Iranian journal of field crop science. 41(2): 247-258. [In Persian]. https://doi.org/20.1001.1.20084811.1389.41.2.5.6##Acquaah, G. 2012. Principles of Plant Genetics and Breeding. Second Edition. Hoboken, NJ: Wiley.##Ahmadi, A., Baker, D.A., 2001. The effect of water stress on grain filling processes in wheat. Journal of Agricultural Science. 136, 257-269. https://doi.org/10.1017/S0021859601008772##Ahmadi, A., Joodi, M., Janmohammdi, M., 2009. Late defoliation and wheat yield: little evidence of post anthesis source limitation. Field Crops Research. 113, 90-93. https://doi.org/10.1016/j.fcr.2009.04.010##Ahmadizadeh, M., Shahbazi, H., Valizadeh, M. and Zaefizadeh, M. 2011. Genetic diversity of durum wheat landraces using multivariate analysis under normal irrigation and drought stress conditions. African Journal of Agricultural Research. 6(10): 2294-2302. https://doi.org/10.5897/AJAR11.157##Ahmadi Lahijani, M. J. and Emam, Y. 2013. Response of Wheat Genotypes to Terminal Drought Stress Using Physiological Indices. Journal of Crop Production and Processing. 3(9): 163-176. [In Persian]. http://jcpp.iut.ac.ir/article-1-1943-en.html##Araus, J. L., Slafer, G. A., Reynolds, M. P. and Royo, C. 2002. Plant breeding and drought in C3 cereals: what should we breed for?. Annals of Botany. 89: 925-940. https://doi.org/10.1093/aob/mcf049##Baghbankhalilabad, S., Khazaee, H. R. and Kafi, M. 2019. Effect of deficit irrigation on kernel yield, yield components and some physiological traits of different varieties of bread wheat and durum wheat. Applied Field Crops Research. 32(1): 1-12. [In Persian] https://doi.org/10.22092/AJ.2018.116367.1220##Barzegari, M., Emam, Y. and Zamani, A. 2020. Yield Components and Grain Yield Responses of Four Wheat Cultivars to Growth Retardant Cycocel under Terminal Drought Stress Conditions. Journal of Crop Production and Processing. 10(3): 139-156. [In Persian]. https://doi.org/10.47176/jcpp.10.3.20124##Bauer, A., Frank, A. B. and Black A. L. 1985. Estimation of Spring Wheat Grain Dry Matter Assimilation from Air Temperature. Agronomy Journal. 77(5): 743-752. https://doi.org/10.2134/agronj1985.00021962007700050019x ##Brdar-jokanovic, M., K. Borislav, M. Balalić-Kraljević. 2006. Grain filling parameters and yield components in wheat. Genetika 38(3) : 175-181. https://doi.org/10.2298/GENSR0603175B##Bruckner, P. L. and Frohberg, R. C. 1987. Stress Tolerance and Adaptation in Spring Wheat. Crop Science. 27: 31-36. https://doi.org/10.2135/cropsci1987.0011183X002700010008x##Cao, L.; Shi, P.-J.; Li, L.; Chen, G. 2019. A New Flexible Sigmoidal Growth Model. Symmetry 11, 204. https://doi.org/10.3390/sym11020204##Darroch, B. A. and Baker, R. J. 1990. Grain filling in three spring wheat genotypes: statistical analysis. Crop Science. 30: 525-529. https://doi.org/10.2135/cropsci1990.0011183X003000030009x##Dastfal, M., Brati, V., Emam, Y., Haghighatnia, H. and Ramazanpour, M. 2011. Evaluation of grain yield and its components in wheat genotypes under terminal drought stress conditions in Darab region. Seed and Plant Production Journal. 27(2): 195-217 [In Persian].  https://doi.org/10.22092/SPPJ.2017.110432##Dastoor, A., asghari-zakaria, R. and Shahbazi, H. 2014. Evaluation of wheat genotypes for yield and grain- filling rate of wheat genotypes under non stress and post anthesis drought stress conditions. Journal of Agroecology. 6(3): 561-570. [In Persian]. https://doi.org/10.22067/JAG.V6I3.23874##Duguid, S. D. and A. L. Brule-Babel. 1994. Rate and duration of grain filling in five spring wheat (Triticum aestivum L.) genotypes. Canadian Journal of Plant Science . 74: 681-686. https://doi.org/10.4141/cjps94-123##Ehdaie, B., Alloush, G. A. and Waines, J. G. 2008. Genotypic variation in linear rate of grain growth and contribution of stem reserves to grain yield in wheat. Field Crops Research. 106(1): 34-43. https://doi.org/10.1016/j.fcr.2007.10.012##Engel, R. E., Long, D. S. and Carlson, G. R. 2003. Predicting straw yield of hard red spring wheat. Agronomy journal. 95(6): 1454-1460. https://doi.org/10.1016/j.fcr.2007.10.012##FAO. 2021. FAOSTAT agriculture. Food and Agriculture Organization of United Nations. From http://fao.org/crop/statistics.##Gebeyehou, G., Knott, D. R. and Baker R. J. 1982. Rate and Duration of Grain Filling in Durum Wheat Cultivars. Crop Science. 22(2): 337–340. https://doi.org/10.2135/cropsci1982.0011183X002200020033x##Ghasemi Maham, S., Torabi, B. and Dadrasi, A. 2016. Modeling growth and yield of winter wheat in Hamadan province. Journal of EcoPhysiology. 10(33): 186-199. [In Persian].  https://doi.org/20.1001.1.20085958.1397.10.33.17.4##Golipour, S., Ebadi, A. and parmoon, G. 2016. components of different genotypes of grain of bread wheat. Crop Physiology Journal. 8(31): 111-128. [In Persian] https://doi.org/ 20.1001.1.2008403.1395.8.31.7.1##Gonzalez, A., Bermejo, V. and Gimeno. B. S. 2010. Effect of different physiological traits on grain yield in barley grown under irrigated and terminal water deficit conditions. The Journal of Agricultural Science. 148(3): 319–328. https://doi.org/10.1017/S0021859610000031##Guttieri, M. J., Stark, J. C., O'Brien, K. and Souza, E. 2001. Relative sensitivity of spring wheat grain yield and quality parameters to moisture deficit. Crop Science. 41(2): 327-335. https://doi.org/10.2135/cropsci2001.412327x##Honar, T., Sabet-Sarvestani, A., Sepaskhah, A., Kamgar-Haghighi1, A. A. and Shams, Sh. 2012. Simulation of Soil Water Content and Yield of Canola Using CRPSM. Journal of Water and Soil Science. 16(59): 45-57. [In Persian]. ‎ https://doi.org/20.1001.1.24763594.1391.16.59.4.7##Khavari, F., A. Soltani, F. Ghaderi,GH. Gazanchian, and  R. Arabameri. 2009. Modeling leaf production and senescence in wheat. Journal of Crop Production. 1(3): 17-32. https://www.idosi.org/aejaes/jaes6(5)##Kimurto, P. K., Kinyua, M. G. and Nijoroge. M. J. 2003. Response of bread wheat genotypes to drought stimulation under a mobile rain shelter in Kenya. African Crop Science Journal. 11(3): 225-234. https://doi.org/10.4314/acsj.v11i3.27572##Kirigwi, F. M., Van Ginkel, M., Trethowan, R., Sears, R. G., Rajaram, S. and Paulsen, G. M. 2004. Evaluation of selection strategies for wheat adaptation across water regimes. Euphytica. 135: 361–371. https://doi.org/10.1023/B:EUPH.0000013375.66104.04##Kogan, F., Guo, W. and Yang, W. 2019. Drought and food security prediction from NOAA new generation of operational satellites. Geomatics, Natural Hazards and Risk Journal. 10(1): 651–666. https://doi.org/10.1080/19475705.2018.1541257##Li, A., Y. Hou and A. Trent. 2001. Effects of elevated atmospheric CO2 and drought stress on individual grain filling rates and durations of the main stem in spring wheat. Agricultural and Forest Meteorology 106: 289–301. https://doi.org/10.1016/S0168-1923(00)00221-5##Malek, M. M., galavi, M., Ramroudi, M. and Nakhzari Moghaddam, A. 2019. Evaluation of drought tolerance of wheat cultivars under water deficiency stress after flowering. Journal of Crop Production. 12(2): 123-136. [In Persian]. https://doi.org/10.22069/EJCP.2019.15545.2161##Meskini Vishkaei, F., Mohammadi, M. H., Neishabouri, M. R. and Farid, Shekari. 2017. A model to estimate soil water depletion coefficient using plant and soil properties. Iranian journal of soil and water research. 49(4): 749-758. [In Persian]. https://doi.org/10.22059/IJSWR.2017.212087.667505##Mohammadi Gonbad, R., M. Esfahani, M. Roustaei and H. Sabouri. 2016. Effect of planting dates on grain filling of bread wheat genotypes under rain-fed condition of Gonbad-e-Qabus region. Cereal Research. 6( 3), 307-321. [In Persian]. https://doi.org/20.1001.1.22520163.1395.6.3.4.6##Nabipour, A. R., Yazdi-Samadi, B., Zali, A. A. and Poustini, K. 2002. Effect of morphological traits and their Relations to stress susceptibility index in several wheat genotypes. Desert journal. 7(1): 31-48. [In Persian]. https://www.sid.ir/paper/5330##Naderi, A., Hashemi Dezfouli, A., Rezaie, A., Majidi Heravan, E., Nourmohammadi, G. and Yar Mohammad, M. 2000. Exponential Model Parameters Evaluation Of Dry Matter And Nitrogen Accumulation Trends In Grain Of Spring Wheat Genotypes Using Linear Regression Method. Seed and plant journal. 16(4): 471-480. [In Persian] https://doi.org/ 10.22092/SPIJ.2017.110920##Nasiri Khalilelahi, S., Sasani, S., Ahmadi, G. H. and Daneshvar, M. 2020. Effect of terminal drought stress on some agronomic traits of 20 elite bread wheat genotypes. Environmental stresses in crop sciences. 13(3): 683-699. [In Persian]. https://doi.org/10.22077/escs.2020.2226.1564##Nass, H. G. and Reiser, B. 1975. Grain filling period and grain yield relationships in spring wheat. Canadian Journal of Plant Science. 55: 673-678. https://doi.org/10.4141/cjps75-107##Olivares-Villegas, J. J., Reynolds, M. P. and McDonald, G. K. 2007. Drought adaptive attributes in the Seri/Babax hexaploid wheat population. Functional Plant Biology 34: 189-203. 10.1071/FP06148##Rajala, A., Hakala, K., Makela, P., Muurinen, S. and Peltonen-Sainio, P. 2009. Spring wheat response to timing of water deficit through sink and grain filling capacity. Field Crops Research. 114(2): 263–271. https://doi.org/10.1016/j.fcr.2009.08.007##Richards, F. J. 1959. A flexible growth functions for empirical use. Journal of Experimenral Botany. 10(2): 290-301. https://doi.org/10.1093/jxb/10.2.290##Riedesel L, Mo¨ller M, Horney P, Golla B, Piepho H-P, Kautz T, et al. 2023. Timing and intensity of heat and drought stress determine wheat yield losses in Germany. PLoS ONE 18(7): e0288202. https://doi.org/10.1371/journal. pone.0288202##Sanjari, P. A. and Yazdansepas, A. 2008. Evaluation of Wheat (Triticum aestivum L.) Genotypes under Pre- and Post-anthesis Drought Stress Conditions. Journal of Agricultural Science and Technology. 10(2): 109-121. https://doi.org/ 20.1001.1.16807073.2008.10.2.1.5##Sehgal, A., K. Sita, K. H. M. Siddique, R. Kumar, S. Bhogireddy, R. K. Varshney, B. HanumanthaRao, R. M. Nair, P. V. Vara Prasad and H. Nayyar. 2018. Drought or/and Heat-Stress Effects on Seed Filling in Food Crops: Impacts on Functional Biochemistry, Seed Yields, and Nutritional Quality. Frontiers in Plant Science. 9:1705. https://doi.org/10.3389/fpls.2018.01705##Shah, N.H., Paulsenl, G.M., 2003. Interaction of drought and high temperature on photosynthesis and grain-filling of wheat. Plant and Soil. 257, 219-226. https://doi.org/10.1023/A:1026237816578##Shahbazi, H., Arzani, A. and Esmaelzadeh moghadm, M. 2016. Effects of Drought Stress on Physiological Characteristics in Wheat Recombinant Inbred Lines. Journal of plant process and function 5(15): 123-132. [In Persian]. https://doi.org/20.1001.1.23222727.1395.5.15.1.4##Tavakoli, A., A. Ahmadi and H. Alizadeh. 2009. A study of some physiological aspects of yield in drought tolerant vs susceptible wheat (Triticum aestivum L.) cultivars under post anthesis drought stress conditions. Iranian Journal of Field Crop Science. 40 (1): 197-211. [In Persian]. https://doi.org/20.1001.1.20084811.1388.40.1.19.1##Yang, J., Zhang, J. Wang, Z., Xu, G. and Zhu, Q. 2004. Activities of Key Enzymes in Sucrose-to-Starch Conversion in Wheat Grains Subjected to Water Deficit during Grain Filling. Plant Physiology. 135: 1621-1629. https://doi.org/10.1104/pp.104.041038##Yu, S. M., S. F. Lo and T. H. D. Ho. 2015. Source–sink communication: regulated by hormone, nutrient, and stress cross-signaling. Trends Plant Scince. 20, 844–857. https://doi.org/10.1016/j.tplants.2015.10.009##Zavieh Mavadat, L. 2018. Timing of nitrogen application effect on source-sink limitation in wheat cultivars under terminal water deficid stress. Ph.D. Dissertation. Urmia University. [In Persian]##Zhang, L. X., Chang, Q. S., Hou, X. G., Wang, J. Z., Chen, S. D., Zhang, Q. M., 2022. The effect of High−Temperature stress on the physiological indexes, chloroplast ultrastructure, and photosystems of two herbaceous peony cultivars. Journal of Plant Growth Regulation. https://doi.org/10.1007/s00344-022-10647-9.

فایل ها

هم رسانی

ارجاع به این مقاله

آمار