ارزیابی مدل SSM-wheatدر شبیه‎سازی رشد و نمو ارقام گندم(Triticum aestivum L.) در تراکم‌های مختلف کاشت

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه تولیدات گیاهی، دانشکده کشاورزی و منابع طبیعی، دانشگاه گنبد کاووس، گنبد کاووس، ایران

2 بخش زراعی و باغی، مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی استان گلستان، سازمان تحقیقات، آموزش و ترویج کشاورزی، گرگان، ایران

چکیده

گندم (Triticum aestivum L.) یکی از مهم‌ترین و پرمصرف‌ترین گیاهان زراعی شناخته‌شده در جهان می‌باشد. یکی از شاخه‌های علم زراعت و فیزیولوژی گیاهان زراعی مدل‌سازی گیاهان زراعی است. در مدل SSM شبیه‌سازی ساده‌ای برای تخمین عملکرد و مراحل فنولوژیک محصولات مختلف به‌کار رفته است. هدف از این آزمایش ارزیابی مدلSSM-Wheat در شرایط تراکم‌های متفاوت و تنش خشکی انتهای فصل رشد است. این آزمایش در سال زراعی 1401-1400 در ایستگاه تحقیقات کشاورزی گنبدکاووس به اجرا در آمد. آزمایش فاکتوریل عوامل آزمایش شامل تراکم بوته در 6 سطح (شامل 200، 250، 300، 350، 400 و 450 بذر در متر مربع) و ژنوتیپ در 6 سطح (شامل N-93-9، تکتاز، آراز، آرمان، کلاته و تیرگان) بودند. در این تحقیق برای شبیه‌سازی رشد و نمو گندم نان از مدل SSM-wheat استفاده شد. نتایج مدل با استفاده از آماره‌های مبتنی بر اختلاف مقادیر شبیه‌سازی و مشاهده‌شده شامل ضریب تبیین (R2)، جذر میانگین مربعات خطا (RMSE)، جذر میانگین مربعات خطای نرمال شده (nRMSE) و خط یک به یک نشان داد که مدل توانست از میان مراحل فنولوژیک اصلی و عملکرد را با دقت قابل قبولی برآورد کند. در حالی که روز تا پنجه‌زنی و روز تا ساقه رفتن با دقت کمتری برآورد شد. به طور کلی، مطالعه حاضر تأیید کرد که SSM -Wheat یک مدل ساده، قوی و شفاف است که برای کاربردهای زراعی با هدف بهبود تصمیم‌گیری فنی در مدیریت محصولات زراعی مناسب است.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Evaluation of SSM-Wheat Model in Simulating the Growth and Development of Wheat (Triticum aestivum L.) Cultivars in Different Planting Densities

نویسندگان [English]

  • Ali Rahemi karizki 1
  • Faramarz Sayyedi 2
  • Habib allah Soghi 2
  • Arazqlych Marfy 1
  • Mojtaba Salehi SHaikhi 1
  • Saeed Bagherikia 2
1 Department of Plant Production, Faculty of Agriculture and Natural Resources, Gonbad Kavous University, Gonbad Kavous, Iran
2 Agricultural and Horticultural Department, Golestan Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education and Extension Organization (AREEO), Gorgan, Iran
چکیده [English]

Introduction
Wheat (Triticum aestivum L.) is one of the most important and widely consumed crops in the world. Changing the density towards an optimal density can alter the ratio of soil evaporation to plant transpiration in such a way that water use efficiency improves. One of the branches of crop science and crop physiology is crop modeling. Quantifying the growth and development of a crop in response to environmental conditions in a system is called modeling, which helps the user make better decisions about crop management. One of the simple models of crops is the SSM model, which provides a simple simulation for estimating yield and phenological stages of various crops. Models have the ability to be used with physiological and ecological analysis based on research and empirical observations. The aim of this experiment is to evaluate the SSM-Wheat model under different density conditions and late-season drought stress.
 
Materials and Methods
This experiment was conducted in the cropping year 2021-2022 at the Gorgan Agricultural Research Station. The factorial experiment included factors such as plant density at six levels (200, 250, 300, 350, 400, and 450 seeds per square meter) and genotype at six levels (N-93-9, Taktaz, Araz, Arman, Kalateh, and Tirgan). In this study, the SSM-Wheat model was used to simulate the growth and development of bread wheat. The meteorological data file, including precipitation, total sunshine hours, average relative humidity, average temperature, and average maximum temperature, was collected daily and defined in the model. The parameters related to soil characteristics were considered from the base data of the model. To evaluate the model, the coefficient of determination (R2), root mean square error (RMSE), normalized root mean square error (nRMSE), and the 1:1 line were used.
 
 
Results and Discussion
The results of the model, using statistics based on the differences between simulated and observed values, including the coefficient of determination, root mean square error, normalized root mean square error, and the 1:1 line, showed that the model was able to accurately estimate the main phenological stages of days to emergence, days to flowering, and days to physiological maturity. The highest coefficient of determination was obtained for days to emergence, days to physiological maturity, and days to flowering, at 0.97, 0.77, and 0.71, respectively. The root mean square error (RMSE) for these traits was 2.8, 4.9, and 8.8, respectively. However, the traits "days to tillering" and "days to stem elongation" were estimated with lower accuracy, with a coefficient of determination and RMSE of 0.44 and 15.2 for days to tillering, and 0.17 and 6.8 for days to stem elongation, respectively. The results suggest that with an increase in maximum, minimum, and average temperature, and annual precipitation, the number of days required to reach each phenological stage decreases, which is logical. The maximum and minimum model-predicted values for grain yield were 410.4 and 547.6 grams per square meter, respectively, with a mean of 467.8 grams per square meter. The coefficient of determination and root mean square error for grain yield were 0.63 and 35.3, respectively. The distribution of simulated and observed points for the main phenological stages of days to emergence, days to flowering, and days to physiological maturity, as well as grain yield, fell within the 1:1 line range, indicating the model's high accuracy in predicting yield.
 
Conclusion
In general, the  results showed that the SSM-Wheat model was useful in simulating the main stages of wheat phenology and its performance under different conditions in different cultivars. The evaluation of the model using statistical indices of the coefficient of determination and root mean square error also confirmed the model's strength. Overall, the present study confirmed that SSM-Wheat is a simple, robust, and transparent model suitable for agricultural applications aimed at improving technical decision-making in crop management. In general, according to the results obtained for the SSM-Wheat model, it can be used for correct management in terms of the density and suitable cultivars of wheat cultivation in the field and its performance analysis in Gonbad Kavus weather conditions.
 







 




 

کلیدواژه‌ها [English]

  • Grain yield
  • Normalized root mean square error
  • Phonological Stage
  • Root mean square error
 

©2023 The author(s). This is an open access article distributed under Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source.

 

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بوم شناسی کشاورزی
دوره 17، شماره 1 - شماره پیاپی 63
فروردین 1404
صفحه 109-122

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  • تاریخ دریافت: 08 شهریور 1403
  • تاریخ بازنگری: 20 آبان 1403
  • تاریخ پذیرش: 14 بهمن 1403
  • تاریخ اولین انتشار: 01 فروردین 1404

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