ارزیابی نقش سامانه‌های مدیریتی مختلف بر شاخص کیفیت خاک با استفاده از عملکرد محصول (مطالعه موردی: دشت نیشابور)

نوع مقاله : مقالات پژوهشی

نویسندگان

• فرشته مقامی مقیم ¹
• علی رضا کریمی ¹
• محسن باقری بداغ آبادی ²
• حجت امامی ¹

¹ گروه علوم خاک، دانشکده کشاورزی، دانشگاه فردوسی مشهد، مشهد، ایران

² موسسه تحقیقات خاک و آب، سازمان تحیقات، آموزش و ترویج کشاورزی، کرج، ایران

https://doi.org/10.22067/jsw.2022.74026.1120

چکیده

این مطالعه با هدف ارزیابی شاخص کیفیت خاک در دو سطح لایه شخم و خاک‌رخ (عمق 0 تا 100 سانتی­متر)، در اراضی مرتعی و کشاورزی با مدیریت‌های خرده­مالک، عمده­مالک شخصی و اراضی شرکت کشاورزی و دامپروری بینالود در نیشابور انجام شد. 21 خاک‌رخ در سامانه‌های مدیریتی مزبور، حفر و از افق­های آن­ها نمونه‌برداری گردید. پرسش‌نامه­های لازم به کمک کشاورزان و کارشناسان منطقه به روش تحلیل سلسله مراتبی (AHP)، تهیه و تحلیل­های مورد نظر انجام گرفت. از بین ویژگی­های موثر بر کیفیت خاک، کربنات کلسیم معادل، کربن آلی، درصد رس، شن، سیلت، قابلیت هدایت الکتریکی، pH، نیتروژن کل، فسفر و پتاسیم قابل استفاده، سدیم و مجموع کلسیم و منیزیم مورد تجزیه آزمایشگاهی قرار گرفت. شاخص کیفیت خاک در مجموعه حداقل داده (MDS) به دو روش تجزیه به مؤلفه‌های اصلی (PCA) و نظر کارشناس (EO) و به دو شیوه تجمعی و وزنی محاسبه شد. برای رسیدن به یک مقدار واحد از هر ویژگی در هر خاک‌رخ، از دو روش میانگین وزنی و ضریب وزنی استفاده گردید و به‌منظور بررسی صحت ارزیابی، ارتباط بین شاخص کیفیت خاک با عملکرد یونجه و کلزا نیز به روش رگرسیون خطی بررسی شد. نتایج نشان داد که بیشترین شاخص کیفیت تجمعی و وزنی خاک در هر دو سطح لایه شخم و خاکرخ، در هر دو روش PCA و EO مربوط به اراضی مرتعی و سیستم عمده مالک بود. در تمام واحدهای مدیریتی نیز شاخص وزنی محاسبه‌‌شده به روش EO، بیشترین کیفیت خاک سطحی و خاک‌رخ (به روش ضریب وزنی) را به خود اختصاص داد. ارتباط بین شاخص کیفیت خاک با عملکرد یونجه و کلزا نیز نشان داد که در مجموعه EO، شاخص وزنی خاک‌رخ (به روش ضریب وزنی) نسبت به خاک سطحی، توانسته است ارتباط بیشتری با عملکرد محصول، به‌خصوص کلزا، در سیستم مدیریتی عمده مالک (خاک سطحی R² = 0.75 و خاک­رخ R² = 0.68) و شرکت بینالود (خاک سطحی R² = 0.65 و خاک­رخ R² = 0.63) نشان دهد. ارتباط نسبتاً خوب عملکرد محصولات مورد مطالعه، با شاخص کیفیت خاک نشان داد که به‌منظور افزایش عملکرد، نیازمند یک مدیریت اصولی در جهت حفظ و بهبود کیفیت خاک، به‌خصوص در سیستم خرده­مالکی در جهت تامین نیازهای تغذیه­ای که نقش مهم­تری دارند، هستیم.

کلیدواژه‌ها

• تجزیه به مولفه اصلی
• سامانه مدیریتی
• شاخص کیفیت خاک
• عملکرد محصول
• کارشناس خبره

20.1001.1.20084757.1401.36.1.7.9

موضوعات

• علوم خاک

عنوان مقاله [English]

Evaluating the Role of Different Management Systems on Soil Quality Index Using Crop Yield (Case Study: Neyshabour Plain, Iran)

نویسندگان [English]

• F. Maghami Moghim ¹
• A.R. Karimi ¹
• M. Bagheri Bodaghabadi ²
• H. Emami ¹

¹ Department of Soil Science, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran

² Soil and Water Research Institute, Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran

چکیده [English]

Introduction
 The type of management operations and land use systems are the key parameters affecting the soil quality and sustainable land use. The exploitation systems by efficient use of soil and water recourse can decrease productions costs and increase the yield as well as conserve the natural resources. However, farmers and stakeholders need to be aware that through their management practices, they affect soil quality and, with the short-term goal of production and greater profitability, lead to soil degradation. They can both use the land economically and improve and maintain soil quality by balancing production inputs and refining their management approaches. There are different management systems of productivity in agricultural lands in Neyshabour plain in northeastern Iran. In addition to the water and soil limitations in the study area, the prevalence of the smallholder system and the unwillingness of farmers to integrate smallholder, has further increased the destruction of soils in the study area. The objective of this study was to assess the changes in soil quality index in surface soil and profile (0-100 cm) and calculate the correlation between soil quality index and alfalfa and rapeseed yield in rangeland and agricultural areas managed by smallholders, total owners, and Binalood Company in the study area.
Materials and Methods
 A total of 21 soil profiles were described in the total owner, smallholder and Binalood company management system and sampled from the alfalfa and rapeseed lands. Questionnaires were prepared with the help of farmers and experts in the study area based on Analytic Hierarchical analysis (AHP) method. The physical and chemical characteristics of the soil samples were determined. The important soil characteristics affecting plant growth were determined by interviewing farmers and experts study area. Soil quality index in the minimum data set (MDS) was calculated by two methods of principal component analysis (PCA) and expert opinion (EO), by additive and weighted methods in surface soil and profile. To achieve a single value for each soil properties in the soil profile, two methods of weighted mean and weighted factor were used. To evaluate the accuracy of the assessment, the correlation between soil quality index and alfalfa and rapeseed yield was investigated of the various management system.
Result and Discussion
The results showed that the highest additive and weighted soil quality index at both surface and soil profile in both PCA and EO methods were in rangeland. It was due to lack of cultivation and maintaining organic matter comparing to agricultural land. The total owner management system due to its economic power and the use of appropriate and scientific methods comparing to smallholder management system, showed the highest additive and weighted soil quality index. In all management system, the EO-calculated weight index by weighted factor method had the highest value due to assigning the suitable weight for soil characteristics. The correlation analyses soil quality indices with canola and alfalfa indicated that the EO soil quality calculated by weighted factor for the soil profile were more correlated than surface soil in total owner system and the Binalood company. Weight coefficient method due to the application of different weights to each layer based on their importance, showed a higher soil quality index in both EO and PCA sets than the weighted average method. The reason for better EO performance probably is that the PCA is a reducing the dimensions, meanwhile, the minimum data selection in the EO method is based on regional experts which are familiar with cause-and-effect relationship of the soil properties. Due to the relatively good correlation of the yield of the studied products, with the soil quality index, an appropriate management needs to maintain and improve soil quality, especially in the smallholder system, as well as meeting the nutritional needs of these products.
Conclusion
 Soil quality assessment in this study indicated that calculation of the soil quality index only considering the surface soil properties may not provide complete information for the farmers and land managers. Then inclusion of both surface and profile soil properties with farmers' knowledge and study area experts are essential for sustainable soil management. On the other hand, the differences in the management system also affected the soil quality index. Although the smallholder management system due to low input, especially chemical fertilizers, water and agricultural implements, had a high potential concerning environmental issues, but in terms of production, total owner and Binalood company management systems because of their high economic strength had the higher soil quality index. The farmers and stakeholders of the total owner management systems should be considered despite the proper management, however due to high inputs of fertilizer and water, especially in the Binalood company, the production may not be sustainable. Therefore, for further studies, calculating the water consumption in the desired management systems is recommended.

کلیدواژه‌ها [English]

• Crop yield
• Expert opinion
• Management system
• Principal component analysis
• Soil quality index

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