استفاده از ویژگی‌های خاک برای برآورد عملکرد گندم آبی در کشتزارهای نظرآباد استان البرز

نوع مقاله : مقاله پژوهشی

نویسندگان

1 دانشجوی دکتری، گروه خاکشناسی، دانشکده کشاورزی، دانشگاه زنجان، زنجان، ایران

2 استاد، گروه خاکشناسی، دانشکده کشاورزی، دانشگاه زنجان، زنجان، ایران

3 استادیار، موسسه تحقیقات خاک و آب، سازمان تحقیقات آموزش و ترویج کشاورزی، کرج، ایران

چکیده

عملکرد گندم تحت تأثیر عوامل مختلف از جمله اقلیم، شیوه­های مدیریت زمین و ویژگی­­های خاک است. بررسی روابط بین عملکرد گندم و ویژگی­های فیزیکی و شیمیایی خاک مهم است. در این مطالعه، ویژگی­های فیزیکی و شیمیایی خاک سطحی (30-0 سانتی­متر) و عملکرد محصول گندم در 34 مزرعه­ی کشت گندم در اراضی زراعی شهرستان نظرآباد استان البرز در سال زراعی 1397 تعیین شد. تجزیه به مؤلفه‌های اصلی (PCA) جهت انتخاب داده­های مؤثر بر عملکرد گندم و رگرسیون چند­متغیره خطی برای تحلیل روابط بین عملکرد گندم و ویژگی­های خاک مورد استفاده قرار گرفت و چهار معادله رگرسیونی استخراج شد. در معادله اول، از روش تجزیه به مؤلفه‌های اصلی (PCA)، در معادله دوم، از روش رگرسیون خطی به صورت گام به گام، در معادله سوم، از روش بالاترین همبستگی و در معادله چهارم، از تمام ویژگی­های اندازه­گیری شده استفاده شد. ارزیابی معادله­ها با استفاده از آماره­های میانگین هندسی نسبت خطا (GMER)، انحراف استاندارد هندسی نسبت خطا (GSDER)، جذر میانگین مربعات باقیمانده نرمال شده (NRMSE) و ضریب تبیین (R2) انجام شد. نتایج نشان داد که عملکرد گندم در منطقه از 2750 تا 10500 کیلوگرم در هکتار متغیر است و معادله ارائه شده با استفاده از مقادیر رس، فسفر قابل­استفاده، مس، تخلخل، کربنات کلسیم معادل و واکنش خاک به ترتیب با مقادیر GMER، GSDER، NRMSE و R2 برابر 99/0، 19/1، 17/0 و 64/0، مناسب­ترین معادله برای تعیین عملکرد گندم در منطقه تشخیص داده شد. لذا در مناطقی با شرایط اقلیمی و ویژگی­های فیزیکی و شیمیایی خاک مشابه منطقه مورد مطالعه می­توان بر اساس معادله پیشنهادی عملکرد گندم را در حد قابل قبول برآورد کرد.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Using Soil Properties to Estimate the Irrigated Wheat Yield in Agricultural Lands of Nazarabad Region in Alborz Province

نویسندگان [English]

  • Rasoul Mirkhani 1
  • Ali Reza Vaezi 2
  • HAMED REZAEI 3
1 Ph.D. Student, Department of Soil Science, Faculty of Agriculture, Univrsity of Zanjan, Zanjan, Iran
2 Full Professor, Department of Soil Science, Faculty of Agriculture, Univrsity of Zanjan, Zanjan, Iran
3 Assistant Professor, Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran.
چکیده [English]

The yield of Wheat is influenced by various factors including climate, land management practices and soil properties. It is important to investigate the relations between soil physical and chemical properties and the yield of wheat. In this study, the physical and chemical properties of the soil top layer (0-30 cm) and the yield of Wheat were determined in 34 wheat fields of Nazarabad region in Alborz province, during wheat crop year of 2018. Principal Component Analysis (PCA) was used to select the effective parameters on wheat yield and multivariate linear regression was applied to analyze the relationship between wheat yield and soil properties. Finally four regression equations were presented. Principal Component Analysis (PCA), stepwise linear regression, the highest correlation method and all the measured properties were used respectively to prepare four equations to estimate the Wheat yield. The evaluation of each equation was performed by Geometric Mean Error Ratio (GMER), Geometric Standard Deviation of the Error Ratio (GSDER), Normalized Root Mean Squared Error (NRMSE), and determination coefficient (R2). The results showed that wheat yield varies from 2750 to 10500 kg/ha in the region and the proposed equation using clay, Pava, Cu, porosity, calcium carbonate equivalent and pH with GMER, GSDER, NRMSE and R2 values of 0.99, 1.19, 0.17, and 0.64 respectively, is the most appropriate equation for determining of wheat yield. Therefore, in regions with climatic conditions and soil physical and chemical properties similar to the study area, the yield of wheat can be estimated with an acceptable level, based on the proposed equation.

کلیدواژه‌ها [English]

  • Principal component analysis
  • multivariate regression
  • Wheat Yield
  • Nazarabad
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