استفاده از توابع انتقالی و طیفی خاک در برآورد ظرفیت تبادل کاتیونی خاک‌های آهکی استان فارس

نوع مقاله : مقاله پژوهشی

نویسندگان

1 گروه علوم و مهندسی خاک، دانشکده کشاورزی، دانشگاه شیراز، شیراز، ایران

2 گروه منابع طبیعی و محیط زیست، دانشکده کشاورزی، دانشگاه شیراز، شیراز، ایران

چکیده

ظرفیت تبادل کاتیونی (CEC) از مهم‌ترین ویژگی‌های شیمیایی خاک است که در حاصلخیزی خاک نقش بسزایی دارد. با این حال، روش‌های استاندارد آزمایشگاهی برای اندازه‌گیری CEC دشوار، هزینه‌بر و زمان‌بر است. این پژوهش با هدف برآورد CEC خاک با به­کارگیری روش‌های نوین مانند 1) توابع انتقالی خاک (PTF) بر اساس ویژگی‌های زودیافت خاک با استفاده از رگرسیون خطی چندگانه (MLR)، 2) طیف‌سنجی خاک (,Vis - NIR2500 تا 400 نانومتر) با استفاده از رگرسیون حداقل مربعات جزئی (PLSR) و رگرسیون­بردار پشتیبان (SVR) انجام شده است. همچنین با استفاده از نتایج تجزیه و تحلیل ضریب رگرسیون، طول موج‌های کلیدی برای برآورد CEC معرفی شدند. برای این منظور، CEC در آزمایشگاه با استفاده از روش سدیم استات برای 72 نمونه خاک جمع آوری شده از خاک‌های آهکی استان فارس اندازه‌گیری شد و بازتاب طیفی نمونه‌های خاک با دستگاه طیف‌سنج اندازه‌گیری شد. این روش‌ها از مجموعه واسنجی (70% داده‌ها) ساخته شده و با مجموعه اعتبارسنجی (30% داده‌ها) ارزیابی شدند. نتایج نشان داد دقت نتایج روش  طیف‌سنجی از دقت نتایج PTF بیشتر بود. در این پژوهش، طول موج‌های 566، 854، 1354، 1418، 1906، 2071، 2203، 2319 و 2341 نانومتر به­عنوان طول موج‌های کلیدی برای برآورد CEC خاک به دست آمد. مدل‌ SVR در مقایسه با PLSR عملکرد بهتری داشت. به طور کلی این پژوهش نشان داد که روش طیف‌سنجی (Vis- NIR) یک روش امیدوارکننده برای برآورد CEC خاک می‌باشد.

کلیدواژه‌ها


عنوان مقاله [English]

Using Soil Pedotransfer and Spectrotransfer Functions to Estimate Cation Exchange Capacity in Calcareous Soils, Fars Province

نویسندگان [English]

  • Monireh Mina 1
  • mahrooz rezaei 1
  • abdolmajid sameni 1
  • Ali Akbar Moosavi 1
  • RASHID FALLAH SHAMSI 2
1 Department of Soil Science and Engineering, Faculty of Agriculture, Shiraz University, Shiraz, Iran
2 Department of Natural Resources and Environmental Science, Faculty of Agriculture, Shiraz University, Shiraz, Iran
چکیده [English]

Cation exchange capacity (CEC) is one of the most important soil chemical properties that plays an important role in soil fertility. However, standard laboratory methods for measuring CEC are difficult, costly, and time-consuming. The aim of this study was to use new methods such as 1) Pedotransfer Functions (PTF) based on the basic soil properties using Multiple Linear Regression (MLR), 2) soil spectroscopy (Vis–NIR, 400 – 2500 nm) using Partial Least Squares Regression (PLSR), and Support Vector Regression (SVR), for estimating soil CEC. Also, from the regression coefficient analysis, key wavelengths were introduced. For this purpose, CEC was measured using the sodium acetate method for 72 soil samples collected, and spectral reflection of soil samples was determined using spectroscopy. These methods are made from a calibration set (70% of data) and evaluated with a validation set (30% of data). The results showed that Vis - NIR method performed better than PTF. In this study, wavelength ranges around 566, 854, 1354, 1418, 1906, 2071, 2203, 2319, and 2341 nm were investigated as the key wavelengths for estimation of CEC. Furthermore, the results of prediction models showed that SVR has a better performance than PLSR. This study proved that Vis-NIR is a promising method for soil CEC estimation.

کلیدواژه‌ها [English]

  • Support Vector Regression
  • Partial least squares regression
  • Multiple Linear Regression
  • Key Wavelength
Abbasi, M., Darvish, A. and Shapman, M. (2010). Spectral reflection curve of Northern rice cultivars in red edge. Region. Geomatics Conferences and Exhibitions. (In Farsi).
Amini, M., Abbaspour, K. C., Khademi, H., Fathianpour, N., Afyuni, M., & Schulin, R. (2005). Neural network models to predict cation exchange capacity in arid regions of Iran. European Journal of Soil Science. 56(4), 551-559.
Arnaud, R. j. St., and A. R. Mermut. 1993. Carbonates. In: Carter, M. R., Soil sampling and analysis. American Society of Agronomy, Madison, WI. pp:177-186.
Arthur, E. (2017). Rapid estimation of cation exchange capacity from soil water content. European Journal of Soil Science. 68(3), 365-373.
Babaeian, E., Homaee, M., Vereecken, H., Montzka, C., Norouzi, A. A., & van Genuchten, M. T. (2015). A comparative study of multiple approaches for predicting the soil–water retention curve: Hyperspectral information vs. basic soil properties. Soil Science Society of America Journal. 79(4), 1043-1058.
Bazoobandi, A., Ghorbani, H., Emamgholizadeh, S., & Novbarian, M. R. (2017). Prediction of cation exchange capacity in the soils of gilan province using intelligent models. Iranian Journal of Soil Research, 31(3), 375-391.
Bellon-Maurel, V., Fernandez-Ahumada, E., Palagos, B., Roger, J. M., & McBratney, A. 2010. Critical review of chemometric indicators commonly used for assessing the quality of the prediction of soil attributes by NIR spectroscopy. TrAC Trends in Analytical Chemistry, 29(9), 1073-1081.
Ben-Dor, E., Y. Inbar, and Y. Chen. (1997). The reflectance spectra of organic matter in the visible near-infrared and short wave infrared region (400–2500 nm) during a controlled decomposition process. Remote Sens. Environ. 61:1–15.
Bower, C. A., Reitemeier, R. F., & Fireman, M. (1952). Exchangeable cation analysis of saline and alkali soils. Soil science. 73(4), 251-262.
Castellet, J. T., García, M. D. C. C., & de Torre, V. B. L. (2015). Predicting cation exchange capacity from hygroscopic moisture in agricultural soils of Western Europe. Spanish journal of agricultural research. 13(4), 31.
Clark, R.N., T.V.V. King, M. Klejwa, G.A. Swayze, and N. Vergo. (1990). High spectral resolution reflectance spectroscopy of minerals. J. Geophys. Res. 95(B8):12653–12680.
Galvdo, L.S., I. Vitorello, and A.R. Formaggio. 1997. Relationships of spectral reflectance and color among surface and subsurface horizons of tropical soil profiles. Remote Sens. Environ. 61:24–33.
Gee, G. H. (1986). j. W. Bauder. 1986. Particle size analysis. Methods of Soil Analysis. Part, 1.
Ghorbani, H., Kashi, H., Hafezi Moghadas, N., & Emamgholizadeh, S. (2015). Estimation of soil cation exchange capacity using multiple regression, artificial neural networks, and adaptive neuro-fuzzy inference system models in Golestan Province, Iran. Communications in Soil Science and Plant Analysis. 46(6), 763-780.
Gomez, C., Lagacherie, P., & Coulouma, G. (2008). Continuum removal versus PLSR method for clay and calcium carbonate content estimation from laboratory and airborne hyperspectral measurements. Geoderma. 148(2), 141-148.
Haaland, D. M., & Thomas, E. V. (1988). Partial least-squares methods for spectral analyses. 1. Relation to other quantitative calibration methods and the extraction of qualitative information. Analytical chemistry, 60(11), 1193-1202.
Hermansen, C., Knadel, M., Moldrup, P., Greve, M. H., Karup, D., & de Jonge, L. W. (2017). Complete soil texture is accurately predicted by visible near‐infrared spectroscopy. Soil Science Society of America Journal. 81(4), 758-769.
Hezarjaribi, A., Nosrati, K. F., Abdollahnezhad, K., & Ghorbani, K. (2013). The Prediction Possibility of Soil Cation Exchange Capacity by Using of Easily Accessible Soil Parameters. Journal of Water and Soil. 27(4), 712- 719.
Hoogsteen, M. J., Lantinga, E. A., Bakker, E. J., Groot, J. C., Tittonell, P. A. (2015). Estimating soil organic carbon through loss on ignition: effects of ignition conditions and structural water loss. European Journal of Soil Science. 66(2), 320-328.
Ji, W., Adamchuk, V. I., Biswas, A., Dhawale, N. M., Sudarsan, B., Zhang, Y., ... & Shi, Z. (2016). Assessment of soil properties in situ using a prototype portable MIR spectrometer in two agricultural fields. Biosystems Engineering, 152, 14-27.
Karimi, S. A., Davari, M., & Babaeian, E. (2017). Deriving and assessing spectrotransfer function and pedotransfer function in predicting soil cation exchange capacity. Iranian Journal of Soil Research. 31(4), 641-653.
Kashi, H., Emamgholizadeh, S., & Ghorbani, H. (2014). Estimation of soil infiltration and cation exchange capacity based on multiple regression, ANN (RBF, MLP), and ANFIS models. Communications in Soil Science and Plant Analysis. 45(9), 1195-1213.
Khorshidi, M., & Lu, N. (2017). Determination of cation exchange capacity from soil water retention curve. Journal of Engineering Mechanics. 143(6), 04017023.
Krogh, L., Breuning-Madsen, H., & Greve, M. H. (2000). Cation-exchange capacity pedotransfer functions for Danish soils. Acta Agriculturae Scandinavica, Section B-Plant Soil Science. 50(1), 1-12.
Mahmoodabadi, M., & Mazaheri, M.R. (2012). Effect of some soil physical and chemical properties on permeability in field conditions. Journal of Irrigation and Water Engineering. 2(8), 14-25.
McCartney, A. B., Minasny, B., Cattle, S. R., & Vervoort, R. W. (2002). From pedotransfer functions to soil inference systems. Geoderma. 109(1-2), 41-73.
Moradi, H. R., Rajabi, M., Faragzadeh, M. (2011). Investigation of meteorological drought characteristics in Fars province, Iran. Catena. 84(1-2), 35-46.
Mozaffari, H., Moosavi, A. A., & Ahmadi, F. (2021). Improving the Estimation of Soil Cation Exchange Capacity Using Fractal Dimensions. Iranian Journal of Soil and Water Research, 51(12), 3102-3087.
Nelson, R.E. (1982). Carbonate and gypsum. In: Page, A.L. (Ed.), Methods of Soil Analysis: Part 1. Agronomy Handbook 9. American Society of Agronomy and Soil Science Society of America, Madison (WI). 6, 181–197.
Nikseresht, F., Honarbakhsh, A., Ostovari, Y., & Afzali, S. F. (2019). Model development to predict CEC using the intelligence data mining approaches. Communications in Soil Science and Plant Analysis. 50(17), 2178-2189.
Olorunfemi, I., Fasinmirin, J., & Ojo, A. (2016). Modeling cation exchange capacity and soil water holding capacity from basic soil properties. Eurasian Journal of Soil Science. 5(4), 266-274.
Page, A.L., Miller, R.H., Jeeney, D.R., 1992. Methods of soil analysis, part 1. In: Physical and Mineralogical Methods. Soil Science Society of American Publication, Madison, pp. 1750.
Pinheiro, É. F., Ceddia, M. B., Clingensmith, C. M., Grunwald, S., & Vasques, G. M. (2017). Prediction of soil physical and chemical properties by visible and near-infrared diffuse reflectance spectroscopy in the central Amazon. Remote Sensing, 9(4), 293.
Raj, A., Chakraborty, S., Duda, B. M., Weindorf, D. C., Li, B., Roy, S., & Paulette, L. (2018). Soil mapping via diffuse reflectance spectroscopy based on variable indicators: An ordered predictor selection approach. Geoderma, 314, 146-159.
Razzaghi, F., Arthur, E., & Moosavi, A. A. (2021). Evaluating models to estimate cation exchange capacity of calcareous soils. Geoderma, 400, 115221.
Rehman, H. U., Knadel, M., de Jonge, L. W., Moldrup, P., Greve, M. H., & Arthur, E. (2019). Comparison of cation exchange capacity estimated from Vis–NIR spectral reflectance data and a pedotransfer function. Vadose Zone Journal. 18(1), 1-8.
Sherman, D. M., & Waite, T. D. (1985). Electronic spectra of Fe3+ oxides and oxide hydroxides in the near IR to near UV. American Mineralogist, 70(11-12), 1262-1269.
Smola, A. J., & Schölkopf, B. (2004). A tutorial on support vector regression. Statistics and computing, 14(3), 199-222.
Sorenson, P. T., Quideau, S. A., & Rivard, B. (2018). High resolution measurement of soil organic carbon and total nitrogen with laboratory imaging spectroscopy. Geoderma. 315, 170-177.
Soriano-Disla, J. M., Janik, L. J., Viscarra Rossel, R. A., Macdonald, L. M., & McLaughlin, M. J. (2014). The performance of visible, near-, and mid-infrared reflectance spectroscopy for prediction of soil physical, chemical, and biological properties. Applied Spectroscopy Reviews. 49(2), 139-186.
Stenberg, B., Rossel, R. A. V., Mouazen, A. M., & Wetterlind, J. (2010). Visible and near infrared spectroscopy in soil science. Advances in agronomy, 107, 163-215.
Taghizadeh-Mehrjardi, R., Sarmadian, F., Zolfaghari, A. A., & Jafari, A. (2015). Prediction Cation Exchange Capacity using Different Methods in Soils of Iran. Journal of Agricultural Engineering Soil Science and Agricultural Mechanization, (Scientific Journal of Agriculture). 38(1), 59-77.
Ulusoy, Y., Tekin, Y., Tümsavaş, Z., & Mouazen, A. M. (2016). Prediction of soil cation exchange capacity using visible and near infrared spectroscopy. Biosystems Engineering. 152, 79-93.
Van Groenigen, J. W., Mutters, C. S., Horwath, W. R., & Van Kessel, C. (2003). NIR and DRIFT-MIR spectrometry of soils for predicting soil and crop parameters in a flooded field. Plant and Soil, 250(1), 155-165.
Vapnik, V., Guyon, I., & Hastie, T. (1995). Support vector machines. Mach. Learn, 20(3), 273-297.
Viscarra Rossel, R. A., Behrens, T. (2010). Using data mining to model and interpret soil diffuse reflectance spectra. Geoderma. 158, 46–54.
Xu, S., Zhao, Y., Wang, M., & Shi, X. (2018). Comparison of multivariate methods for estimating selected soil properties from intact soil cores of paddy fields by Vis–NIR spectroscopy. Geoderma. 310, 29-43.