نوع مقاله : کاربردی

نویسندگان

• سینا بیگدلی ¹
• حیدر غفاری ²
• مجتبی نوروزی مصیر ³
• عبدالامیر معزی ⁴

¹ دانشجوی سابق کارشناسی ارشد، گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه شهید چمران اهواز، اهواز، ایران

² استادیار گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه شهید چمران اهواز، اهواز، ایران

³ دانشیار گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه شهید چمران اهواز، اهواز، ایران

⁴ استاد گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه شهید چمران اهواز، اهواز، ایران

چکیده

امروزه مفهوم کیفیت خاک (SQ) به طور گسترده‌ای برای آگاهی از ظرفیت و محدودیت خاک‌ها در سیستم‌های مختلف محیطی مورد استفاده قرار گرفته است. باتوجه به اهمیت اراضی دیم در تولیدات کشاورزی هدف اصلی این تحقیق مدل‌سازی و کمی‌سازی کیفیت خاک بخشی از اراضی کشاورزی دیم شهرستان دزپارت با استفاده از تحلیل چند متغیره یکپارچه و همچنین تعیین حداقل مجموعه داده‌های موثر می-باشد. تعداد ۱۱۹ نمونه خاک به روش مرکب از عمق 30-0 سانتی‌متری خاک اراضی کشاورزی تهیه شد. نمونه‌ها به آزمایشگاه منتقل و ویژگی‌های شیمیایی-حاصلخیزی و فیزیکی اندازه‌گیری شدند. سپس کیفیت خاک‌ها با استفاده از دو مجموعه داده کل (TDS) و حداقل (MDS) و روش تحلیل-های چندمتغیره با سه شاخص نمرو (NQI)، تجمعی وزنی (IQI) و تجمعی ساده (AQI) تعیین گردید. نتایج آزمون تجزیه مولفه-های اصلی (PCA) حاکی از آن بود که سه مولفه اصلی وجود دارد که در مجموع 78 درصد تغییرات واریانس کل را پوشش می‌دهند. مولفه اول به تنهایی حدود 31 درصد و مولفه دوم و سوم نیز به ترتیب 25 و 12 درصد واریانس کل داده‌ها را بیان کردند. هفت ویژگی شامل نیتروژن زیتوده میکروبی، کربن آلی، هدایت هیدرولیکی اشباع، آب قابل‌استفاده گیاه، میزان شن، pH و EC به عنوان اعضای MDS انتخاب شدند. در مجموعه TDS بیشترین وزن‌ها مربوط به سیلت و شن (به ترتیب با 093/0 و 095/0) و کمترین وزن با مقدار 050/0 به جرم مخصوص ظاهری اختصاص پیدا کرد. در مجموعه MDS، بیشترین وزن مربوط به ماده آلی و سیلت و کمترین وزن مربوط به pH بود. به‌طور کلی، بر اساس دو شاخص AQI و WQI کیفیت خاک منطقه مورد مطالعه در کلاس متوسط قرار گرفتند. اما مقادیر بدست آمده از روش NQI برای کیفیت خاک بیانگر پایین بودن کیفیت خاک منطقه بود. شاخص کیفیت خاک وزنی با مجموعه داده حداقل و تابع غیرخطی (WQI_MDS_NL) به دلیل دارا بودن شاخص حساسیت بیشتر (یا انحراف از معیار بزرگتر) به عنوان مدل برتر انتخاب شد. در نهایت نقشه کیفیت خاک منطقه با استفاده از روش معکوس فاصله وزن‌دار تهیه شد. بر اساس نقشه تهیه شده حدود 53 درصد اراضی منطقه کیفیت خاک متوسط و 47 درصد اراضی کیفیت خاک پایینی دارند.

کلیدواژه‌ها

• مجموعه حداقل داده‌ها
• شاخص نمورو
• تجزیه مولفه های اصلی
• درونیابی معکوس فاصله
• شخم حفاظتی

موضوعات

• ارزیابی و تناسب اراضی

عنوان مقاله [English]

Assessment and modeling of soil quality using multivariate analysis approach (Case study of rainfed agricultural land in Dezpart city)

نویسندگان [English]

• Sina Bigdeli ¹
• Heidar Ghafari ²
• Mojtaba Norouzi Masir ³
• Abdolamir Moezzi ⁴

¹ Former MSc.student, Department of Soil Sciences , Faculty of Agriculture, Shahid Chamran University of Ahvaz, Ahvaz, Iran

² Assistant professor, Department of Soil Sciences, Faculty of Agriculture, Shahid Chamran University of Ahvaz, Ahvaz, Iran

³ Associate Professor, Department of Soil Sciences, Faculty of Agriculture, Shahid Chamran University of Ahvaz, Ahvaz, Iran

⁴ Professor, Department of Soil Sciences, Faculty of Agriculture, Shahid Chamran University of Ahvaz, Ahvaz, Iran

چکیده [English]

Introduction: Today, the concept of soil quality (SQ) has been widely used to know the capacity and limitations of soils in different environmental systems. The degree of suitability of land is determined by its capacity to provide services and its flexibility against external conditions. Production of plant biomass is one of the most important functions of soil in relation to food security. The share of dry land in Iran's agricultural production, especially wheat, is very significant. So that in terms of area, about half of the total area of agricultural lands, in terms of volume of production, about 10% of all agricultural products and about 30% of the country's wheat production are related to these lands. Therefore, maintaining the soil quality of these lands is very important. The main goal of this research is to model and quantify the soil quality of part of the rainfed agricultural lands of Dezpart city using integrated multivariate analysis and also to determine the minimum effective data set.

Materials and methods: This study was carried out in a part of the rainfed agricultural area of Dezpart County. First, 119 soil samples were prepared using the composite method from the soil depth of 0-30 cm. Soil sampling was done in a stratified random manner to include all the different geomorphological units. The geographic location of the sampling points was also recorded. The samples were transferred to the laboratory and their chemical-fertility and physical characteristics include reaction (pH), electrical conductivity (EC), organic matter (OM), total nitrogen, available potassium, absorbable phosphorus, calcium carbonate equivalent (CCE), texture, bulk density, mean weight diameter (MWD) of soil aggregates, soil gravel content and cation exchange capacity (CEC) were measured. Then the soil quality was determined using two datasets of total (TDS) and minimum (MDS), and multivariate analysis method. In this method, by using appropriate scoring functions, a score between zero and one was considered for each member of the data set. Also, a weight coefficient was calculated for each member, and finally, the soil quality index, which indicates its degree of desirability, was obtained by three indices including Nemero (NQI), cumulative weighted index (IQI) and simple cumulative index (AQI). Finally, a spatial variation map of soil quality was prepared using the Inverse Distance Weighting (IDW) method in geographic information system (GIS) software.

Results and Discussion: The results of the principal component analysis (PCA) test indicated that there are three main components that cover 78% of the total variance changes. The first component alone accounts for about 41% and the second and third components account for 25% and 12% of the total data variance, respectively. Based on the correlation analysis between soil components and characteristics, five characteristics including organic matter (OM), silt content, gravel, pH and EC were selected as MDS members. Became in the TDS collection, the highest weights related to silt and sand (0.093 and 0.095, respectively) and the lowest weight with 0.050 was assigned to bulk density (BD). In the MDS set, the highest weight was related to organic matter and silt and the lowest weight was related to pH. The soil quality of the region was generally classified as medium based on the two indexes of AQI and WQI. However, the NQI method indicated that the soil quality was low. Among the three selected indices with different functions and data sets, the weighted soil quality index with the minimum data set and nonlinear function (WQI_MDS_NL) was chosen as the superior model due to having a higher sensitivity index (or a larger standard deviation). The spatial soil quality map, which was prepared for this study, showed that approximately 50% of the lands in the region had an average soil quality and 50% had a low soil quality.

Conclusion: Organic matter, silt, pH, gravel and EC are the main characteristics to determine the soil quality of the region. In addition, stability of soil aggregates, bulk density and lime are the most important limiting factors of soil quality in the region. Therefore, it is suggested to use appropriate management practices such as conservation tillage and use of organic fertilizers to improve these characteristics.

Conclusion: Organic matter, silt, pH, gravel and EC are the main characteristics to determine the soil quality of the region. In addition, stability of soil aggregates, bulk density and lime are the most important limiting factors of soil quality in the region. Therefore, it is suggested to use appropriate management practices such as conservation tillage and use of organic fertilizers to improve these characteristics.

کلیدواژه‌ها [English]

• Conservation Tillage
• Food Security
• Inverse distance weighting
• Nemero Index
• Soil Functions