ارزیابی تعیین مجموعه حداقل داده ها برای ارزیابی کیفیت خاکهای شور - سدیمی

نوع مقاله : مقاله پژوهشی

نویسندگان

1 علوم خاک دانشگاه زنجان

2 گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه ارومیه

3 گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه زنجان

4 دانشیار گروه علوم خاک، دانشکده کشاورزی، دانشگاه زنجان

10.30466/asr.2026.56064.1880

چکیده

ارزیابی کیفیت خاک برای بررسی قابلیت تولیدی اراضی حائز اهمیت است. لذا در جهت نیل به این هدف روش‌های گوناگونی پیشنهاد گردیده است. لکن بدلیل تعدد زیاد داده‌ها، وجود روشی که بتواند با بررسی تعداد داده کمتر هدف مورد نظر را تبیین نماید، از دیرباز مطرح بوده است. استفاده از حداقل مجموعه داده‌ها (MDS) یکی از روش‌های فوق است. در این تحقیق 24 ویژگی مختلف شامل فیزیکی، شیمیایی و فلزهای سنگین متعلق به 80 نمونه خاک از اراضی شور – سدیمی حاشیه دریاچه ارومیه جهت تعیین محموعه حداقل داده‌ها توسط روش تجزیه به مولفه‌های اصلی (PCA) مورد تجزیه و تحلیل قرار گرفت. نتایج نشان داد که 8 ویژگی دارای ارزش ویژه بیش از یک بودند. این ویژگی‌ها که بعنوان مجموعه حداقل داده  انتخاب شدند، شامل هدایت الکتریکی، کربن آلی، سرب کل، جرم مخصوص ظاهری، درصد سیلت و رس، کادمیم کل و کربنات کلسیم معادل بودند و بیش از 78 درصد از واریانس کل را تشریح کردند. از میان این شاخص‌ها کمترین وزن مربوط به سرب و کادمیوم بود که بیان کننده تاثیر کمتر عناصر فوق در تعیین شاخص کیفیت خاک و بالاترین وزن نیز مربوط به کربن آلی و درصد رس بود که نشان دهنده تاثیر بالای آنها در تعیین شاخص کیفیت خاک محدوده مورد پژوهش است. ضریب تبیین بین دو مجموعه داده‌های TDS و MDS برای مدل‌های خطی و غیرخطی 54/0 و 64/0 بود که بیانگر قابل اطمینان بودن استفاده از مجموعه داده‌های حداقل به جای مجموعه کل داده‌ها و کارائی بهتر مدل غیرخطی برای ارزیابی کیفیت خاک منطقه مورد مطالعه بود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Evaluating the minimum data set determination to assess saline-sodic soil quality

نویسندگان [English]

  • hossein rezazadeh 1
  • salar rezapour 2
  • parisa alamdari 3
  • Mohammad Sadegh Askari 4
1 soil scince zanjan university
2 Department of Soil Science and Engineering, Faculty of Agriculture, University of Urmia
3 Department of Soil Science and Engineering, Faculty of Agriculture, University of Zanjan
4 Assistant Professor, Department of Soil Science, Faculty of Agriculture, University of Zanjan
چکیده [English]

Soil quality assessment is very important for studying the condition of all lands. Therefore, numerous methods have been proposed to achieve this objective. However, given the vast amount of data involved, there has long been a need for an approach that can effectively explain the desired outcome using a smaller dataset. The use of minimum data sets (MDS) is one of these methods. In this study, 24 different soil attributes, including physical, chemical, and heavy element properties, were analyzed in 80 soil samples from saline-sodic soils on the margins of Lake Urmia to determine the MDS approach using principal component analysis (PCA). The results revealed that eight indicators had eigenvalues greater than one. These indicators, identified as the MDS, were soil electrical conductivity, organic carbon, total Pb, bulk density, silt and clay, total Cd, and calcium carbonate equivalent, and together they accounted for over 78% of the total variance. Among the eight indicators, Pb and Cd had the lowest weights, suggesting the least influence on the soil quality index. Conversely, organic carbon and clay had the highest weights, highlighting their key role in determining the soil quality index for the study region. The coefficients of determination (R²) between the TDS and MDS datasets were 0.54 for the linear model and 0.64 for the nonlinear model, indicating that the MDS can reliably replace the TDS for soil quality assessment. Additionally, the higher R² value of the nonlinear model suggests its greater efficiency in evaluating soil quality in the study area.

کلیدواژه‌ها [English]

  • Saline-Soil Soil
  • Heavy Metals
  • Soil Quality Index
  • Total Data Set
  • Minimum Data Set

مراجع

Amirpour, A., Rezapour, S., & Davalit, B. (2015). The effects of continuous and long-term horticulture operations on the distribution of potassium forms and their absorption properties in Urmia region. Water and Soil, 30(4), 1202-1218. (In Persian).
Andrews, S. S., Karlen, D. L., & Cambardella, C. A. (2004). The soil management assessment framework. Soil Science Society of America Journal, 68(6), 1945-1962.
Armenise, E., Redmile-Gordon, M. A., Stellacci, A. M., Ciccarese, A., & Rubino, P. (2013). Developing a soil quality index to compare soil fitness for agricultural use under different managements in the Mediterranean environment. Soil and Tillage Research, 130, 91-98.
Barrios, E., Delve, R. J., Bekunda, M., Mowo, J., Agunda, J., Ramisd, J., Trejo, M. T., & Thomas, R. J. (2006). Indicators of soil quality: A south-south development of a methodological guide for linking local and technical knowledge. Geoderma, 135, 248-259.
Barikloo, A., & Alamdari, P. (2023). Application of Minimal Data Sets for Quantitative Assessment and Investigation of Spatial Autocorrelation of Soil Quality in Southwestern Lands of Urmia Plain. JWSS-Isfahan University of Technology, 27(4), 93-111. (In Farsi).
Bi, C. J., Chen, Z. L., Wang, J., & Zhou, D. (2013). Quantitative assessment of different planting patterns and soil types. Pedosphere, 23(2), 194-204.
Brady, N. C., & Weil, R. R. (2016). The nature and properties of soils. Pearson.
Burt, R. (2004). Soil survey laboratory methods manual (Soil Survey Investigations Report No. 42). United States Department of Agriculture, Natural Resources Conservation Service.
Dahnke, W. C., & Joural, G. V. (1990). [Chapter title unknown]. In R. L. Westerma (Ed.), Agronomy (Vol. 6, pp. 120-140). Agronomy Inc.
Deputy of Human Environment Office of Water and Soil (DHEOWS). (2020). Soil Source Pollution Standards and Guidelines. (In Persian).
Doran, J. W., & Parkin, B. T. (1994). Defining and assessing soil quality. In J. W. Doran et al. (Eds.), Defining soil quality for a sustainable environment (pp. 3-21). Soil Science Society of America. (Special Publication No. 35).
Emami, H., Neyshabouri, M. R., & Shorafa, M. (2012). Relationships between some soil quality indicators in different agricultural soils from Varamin, Iran. Agriculture Science and Technology, 14, 951-959. (In Persian with English abstract).
Gee, G. W., & Or, D. (2002). Particle‐size analysis. In Methods of Soil Analysis: Part 4 Physical Methods (Vol. 5, pp. 255-293). American Society of Agronomy.
Gorji, M., Kakeh, J., & AliMohammadi, A. (2017). Quantitative soil quality assessment in different land uses at some Parts of south eastern of Qazvin. Iranian Journal of Soil and Water Research (IJSWR), 48(5), 941-950. (In Persian with English abstract).
Govaerts, B., Sayre, K. D., & Deckers, J. (2006). A minimum data set for soil quality assessment of wheat and maize cropping in the highlands of Mexico. Soil and Tillage Research, 87, 163–174.
Havlin, J. L., Beaton, J. D., Tisdal, S. L., & Nelson, W. L. (2005). Soil fertility and fertilizers: An introduction to nutrient management (7th ed.). Pearson.
Hazelton, P., & Murphy, B. (2016). Interpreting soil test results: What do all the numbers mean? CSIRO Publishing.
Jiang, P., & Telen, K. D. (2004). Effect of soil and topographic properties on crop yield in a north central corn-soybean cropping system. Agronomy Journal, 96, 252-258.
Karlen, D. L., Mausbach, M. J., Doran, J. W., Cline, R. G., Harris, R. F., & Schuman, G. E. (1997). Soil quality: a concept, definition, and framework for evaluation (a guest editorial). Soil Science Society of America Journal, 61(1), 4-10.
Kabata-Pendias, A. (2010). Trace elements in soils and plants. CRC Press.
Kafe, F., Dalalian, M., Rezapour, S., Sabbaghtazeh, E., & Rafieyan, O. (2024). Determining the minimum data set to evaluate soil quality in Piranshahr Region wheat fields. Applied Soil Research, 11(4), 30-42.
Liu, Z., Zhou, W., Shen, J., Li, S., He, P., & Liang, G. (2014). Soil quality assessment of Albic soils with different productivities for eastern China. Soil and Tillage Research, 140, 74-81.
Leoppert, R. H., & Suarez, D. L. (1996). Methods of Soil Analysis: Part 3. Chemical Methods. Soil Science Society of America and American Society of Agronomy.
Mohammadi, J., Khademi, H., & Nael, M. (2005). Study the variability of soil quality in selected ecosystems of Central Zagros. Journal of Science and Technology of Agriculture and Natural Resources (Isfahan University of Technology), 9(3), 105-120. (In Persian with English abstract).
Masto, R. E., Chhonkar, P. K., Singh, D., & Patra, A. K. (2008). Alternative soil quality indices for evaluating the effect of intensive cropping, fertilization and manuring for 31 years in the semi-arid soils of India. Environmental Monitoring and Assessment, 136, 419–435.
Nelson, D. W., & Sommers, L. E. (1982). Total carbon, organic carbon, and organic matter. In A. L. Page (Ed.), Methods of Soil Analysis (2nd ed., Part 2, pp. 539-579). American Society of Agronomy.
Olaniya, M., Kumar Bora, P., Das, S., & Chanu, P. H. (2020). Soil erodibility indices under different land uses in Ri-Bhoi district of Meghalaya (India). Scientific Reports, 10, 14986.
Olsen, S. K., & Sommers, L. E. (1982). Phosphorus. In A. L. Page et al. (Eds.), Methods of Soil Analysis (2nd ed., Part 2, pp. 403-430). American Society of Agronomy.
Page, A. L., Miller, R. H., & Keeney, D. R. (1982). Methods of Soil Analysis: Part 2. Chemical and Microbiological Properties (Vol. 2). American Society of Agronomy.
Pieri, C., Dumanski, J., Hamblin, A., & Young, A. (1995). Land Quality Indicators (World Bank Discussion Papers No. 315). World Bank.
Pieri, C. J. (2012). Fertility of soils: A future for farming in the West African Savannah (Vol. 10). Springer.
Qi, Y., Darilek, J. L., Huang, B., Zhao, Y., Sun, W., & Gu, Z. (2009). Evaluating soil quality indices in an agricultural region of Jiangsu Province, China. Geoderma, 149(3-4), 325-334.
Rezapour, S., Nouri, A., Jalil, H. M., Hawkins, S. A., & Lukas, S. B. (2021). Influence of Treated Wastewater Irrigation on Soil Nutritional-Chemical Attributes Using Soil Quality Index. Sustainability, 13, 1952.
Shukla, M. K., Lal, R., & Ebinger, M. (2004). Soil quality indicators for the North Appalachian experimental watersheds in Coshocton, Ohio. Soil Science, 169, 195–205.
Sun, B., Zhou, S., & Zhao, Q. (2003). Evaluation of spatial and temporal changes of soil quality based on geostatistical analysis in the hill region of subtropical China. Geoderma, 115(1), 85-99.
Swift, R. S., & Sparks, D. L. (1996). Methods of Soil Analysis: Chemical Methods, Part 3. Soil Science Society of America.
Shahab Arkhazloo, H., Emami, H., & Haghnia, G. H. (2012). Evaluation of the relationship of soil quality models and sustainability indices of agricultural and rangeland soils in south Mashhad. Iranian Journal of Soil Research (Soil and Water Science), 26(3). (In Persian).
Walkley, A., & Black, I. A. (1934). An examination of the Degtjareff method for determining soil organic matter and a proposed modification of the chromic acid titration method. Soil Science, 37(1), 29-38.
Wilding, L. P. (1985). Spatial variability: its documentation accommodation and implication to soil surveys. In D. R. Nielsen & J. Bouma (Eds.), Soil Spatial Variability (pp. 166-194). Pudoc.
Williams, J. R., Jones, C. A., & Dyke, P. T. (1984). A modeling approach to determining the relationship between erosion and soil productivity. Transactions of the ASAE, 27(1), 129-144.
Yao, R. J., Yang, J. S., Zhao, X. F., Li, X. M., & Liu, M. X. (2013). Determining minimum data set for soil quality assessment of typical salt-affected farmland in the coastal reclamation area. Soil and Tillage Research, 128, 137-148.

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  • تاریخ دریافت: 27 اسفند 1403
  • تاریخ بازنگری: 07 مهر 1404
  • تاریخ پذیرش: 15 شهریور 1405

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