Determination of soil C:N suitability zones for organic farming using an unsupervised classification in eastern Croatia

Abstract Soil carbon-to-nitrogen ratio (C:N) represents an indicator of soil quality and fertility, having a major impact on agricultural land management for organic farming. Determination of soil C:N suitability zones is a necessary procedure in the process, enabling effective land management. A total of 72 soil samples at two soil layers at 0–10 cm and 20–30 cm were used in the study, evenly distributed in the Osijek-Baranja County in eastern Croatia. Ordinary kriging (OK) and Lognormal kriging (LK) using linear, Gaussian and spherical mathematical models, alongside Inverse distance weighted (IDW) were evaluated for the spatial prediction of soil C:N. Inner accuracy representing retention of input sample values in the interpolation results and outer accuracy representing a prediction accuracy at unknown locations were used to determine optimal interpolation parameters. K-means unsupervised classification algorithm was used for the objective determination of soil C:N suitability zones in five classes specified by the Food and Agriculture Organization (FAO). IDW resulted in the highest inner accuracy, while OK with the Gaussian model produced the highest outer accuracy with the average R2 = 0.7908 and NRMSE = 0.0544. Contrary to the previous research, higher mean soil C:N results in a lower soil layer of 20–30 cm with 13.41, compared to 12.03 at 0–10 cm soil layer. The highest soil C:N suitability was determined in only 4.8% of the study area, with the suitability index of 18.44. Meanwhile, the two largest classes were marginally suitable and currently unsuitable class, covering 35.5% and 27.7% of the study area, respectively. These results indicated a necessity for the adjustment of agricultural land management practices to enable sustainable organic farming.

[1]  W. Wang,et al.  Soil organic carbon active fractions as early indicators for total carbon change under straw incorporation , 2011, Biology and Fertility of Soils.

[2]  C. Ballabio,et al.  Mapping topsoil physical properties at European scale using the LUCAS database , 2016 .

[3]  Özer Çinar,et al.  Comparison of artificial neural network and regression pedotransfer functions for prediction of soil water retention and saturated hydraulic conductivity , 2006 .

[4]  F. Guan,et al.  Spatial variability of soil nitrogen, phosphorus and potassium contents in Moso bamboo forests in Yong'an City, China , 2017 .

[5]  V. Seufert,et al.  Many shades of gray—The context-dependent performance of organic agriculture , 2017, Science Advances.

[6]  U. Mishra,et al.  Exploring the spatial variability of soil properties in an Alfisol soil catena , 2017 .

[7]  Shaoshan An,et al.  Changes in Soil Organic Carbon and Total Nitrogen at a Small Watershed Scale as the Result of Land Use Conversion on the Loess Plateau , 2018, Sustainability.

[8]  J. Dewulf,et al.  Environmental sustainability of conventional and organic farming: Accounting for ecosystem services in life cycle assessment. , 2019, The Science of the total environment.

[9]  Pete Smith,et al.  Sustainability in global agriculture driven by organic farming , 2019, Nature Sustainability.

[10]  Margaret A. Oliver,et al.  A tutorial guide to geostatistics: Computing and modelling variograms and kriging , 2014 .

[11]  Luuk Fleskens,et al.  Soil quality – A critical review , 2018 .

[12]  T. Kätterer,et al.  Modelling C, N, water and heat dynamics in winter wheat under climate change in southern Sweden , 2001 .

[13]  Weidong Zhang,et al.  Addition of External Organic Carbon and Native Soil Organic Carbon Decomposition: A Meta-Analysis , 2013, PloS one.

[14]  K. Paustian,et al.  Spatial variability of soil organic carbon in grasslands: implications for detecting change at different scales. , 2002, Environmental pollution.

[15]  R. Lal,et al.  The Depth Distribution of Soil Organic Carbon in Relation to Land Use and Management and the Potential of Carbon Sequestration in Subsoil Horizons , 2005 .

[16]  H. Tunney,et al.  Spatial patterns of potentially hazardous metals in paddy soils in a typical electrical waste dismantling area and their pollution characteristics , 2019, Geoderma.

[17]  Hossein Asadi,et al.  Spatial variability of soil organic matter using remote sensing data , 2016 .

[18]  R. Kerry,et al.  Assessing the effects of slope gradient and land use change on soil quality degradation through digital mapping of soil quality indices and soil loss rate , 2018 .

[19]  M. Oliver,et al.  Determining nugget:sill ratios of standardized variograms from aerial photographs to krige sparse soil data , 2008, Precision Agriculture.

[20]  M. Castro,et al.  Effects of rehabilitation strategies on soil aggregation, C and N distribution and carbon management index in coffee cultivation in mined soil , 2019 .

[21]  M. Schrama,et al.  Crop yield gap and stability in organic and conventional farming systems , 2018 .

[22]  F. Guan,et al.  Spatial distribution of soil organic carbon stock in Moso bamboo forests in subtropical China , 2017, Scientific Reports.

[23]  Shraban Sarkar,et al.  Soil depth estimation through soil-landscape modelling using regression kriging in a Himalayan terrain , 2013, Int. J. Geogr. Inf. Sci..

[24]  E. Tipping,et al.  The C:N:P:S stoichiometry of soil organic matter , 2016, Biogeochemistry.

[25]  Minghua Zhang,et al.  Spatial and temporal trends of soil total nitrogen and C/N ratio for croplands of East China , 2020 .

[26]  Bernd Marschner,et al.  Advantages of fuzzy k-means over k-means clustering in the classification of diffuse reflectance soil spectra: A case study with West African soils , 2019, Geoderma.

[27]  Gaohuan Liu,et al.  Prediction of soil salinity in the Yellow River Delta using geographically weighted regression , 2017 .

[28]  Enrique Ortiz,et al.  Interpolation of Mexican soil properties at a scale of 1:1,000,000 , 2014 .

[29]  Liang Zhang,et al.  Large-scale spatial variability of eight soil chemical properties within paddy fields , 2020 .

[30]  Yanyan Li,et al.  Hydrodynamic impact on trace metals in sediments in the cascade reservoirs, North China. , 2020, The Science of the total environment.

[31]  Yankun Sun,et al.  Spatial Heterogeneity of Soil C:N Ratio in a Mollisol Watershed of Northeast China , 2016 .

[32]  Shu-Duan Liu,et al.  Comparison of Kriging Interpolation Precision With Different Soil Sampling Intervals for Precision Agriculture , 2010 .

[33]  E. Davidson,et al.  Sensitivity of decomposition rates of soil organic matter with respect to simultaneous changes in temperature and moisture , 2015 .

[34]  Lydia M. Chabala,et al.  Application of Ordinary Kriging in Mapping Soil Organic Carbon in Zambia , 2017 .

[35]  Mingkai Qu,et al.  Optimal interpolation methods for farmland soil organic matter in various landforms of a complex topography , 2020 .

[36]  Qingsong Shen,et al.  Comparing interpolation methods to predict soil total phosphorus in the Mollisol area of Northeast China , 2019, CATENA.

[37]  Zhou Shi,et al.  Delineation of site-specific management zones using fuzzy clustering analysis in a coastal saline land , 2007 .

[38]  K. Lajtha,et al.  Depth trends of soil organic matter C:N and 15N natural abundance controlled by association with minerals , 2017, Biogeochemistry.

[39]  Shuzlina Abdul Rahman,et al.  Soil classification: An application of self organising map and k-means , 2010, 2010 10th International Conference on Intelligent Systems Design and Applications.

[40]  Jian Liu,et al.  Spatial distribution of soil organic carbon stocks in Masson pine (Pinus massoniana) forests in subtropical China , 2019, CATENA.

[41]  Dorijan Radočaj,et al.  Suitability Calculation for Red Spicy Pepper Cultivation (Capsicum annum L.) Using Hybrid GIS-Based Multicriteria Analysis , 2019, Agronomy.

[42]  K. Abdullah,et al.  Combining Multiple Electrode Arrays for Two-Dimensional Electrical Resistivity Imaging Using the Unsupervised Classification Technique , 2015, Pure and Applied Geophysics.

[43]  Marco Painho,et al.  Geographical Information Systems Principles of Ordinary Kriging Interpolator , 2010 .

[44]  C. Nick,et al.  Long-term changes in organic matter stocks and quality in an Oxisol under intensive vegetable cultivation , 2020 .

[45]  Yufeng Ge,et al.  VNIR DIFFUSE REFLECTANCE SPECTROSCOPY FOR AGRICULTURAL SOIL PROPERTY DETERMINATION BASED ON REGRESSION-KRIGING , 2007 .

[46]  G. Heuvelink,et al.  A generic framework for spatial prediction of soil variables based on regression-kriging , 2004 .

[47]  M. Cave,et al.  Identifying geogenic and anthropogenic controls on different spatial distribution patterns of aluminium, calcium and lead in urban topsoil of Greater London Authority area. , 2019, Chemosphere.

[48]  Andrea Szilágyi Kishné,et al.  Comparison of Ordinary and Lognormal Kriging on Skewed Data of Total Cadmium in Forest Soils of Sweden , 2003, Environmental monitoring and assessment.

[49]  D. Chalise,et al.  Digital soil mapping in the Bara district of Nepal using kriging tool in ArcGIS , 2018, PloS one.

[50]  R. Bilonick.  An Introduction to Applied Geostatistics , 1989 .

[51]  Dorijan Radočaj,et al.  Delineation of Soil Texture Suitability Zones for Soybean Cultivation: A Case Study in Continental Croatia , 2020, Agronomy.

[52]  Kabindra Adhikari,et al.  Role of environmental variables in the spatial distribution of soil carbon (C), nitrogen (N), and C:N ratio from the northeastern coastal agroecosystems in China , 2018 .

[53]  G. Metternicht,et al.  Testing the performance of spatial interpolation techniques for mapping soil properties , 2006 .

[54]  C. Silva,et al.  Spatial distribution of soil carbon stocks in the Cerrado biome of Minas Gerais, Brazil , 2020 .

[55]  Mateo Gasparovic,et al.  Optimal Soybean (Glycine max L.) Land Suitability Using GIS-Based Multicriteria Analysis and Sentinel-2 Multitemporal Images , 2020, Remote. Sens..

[56]  J. Bai,et al.  Estimating the spatial distribution of soil total nitrogen and available potassium in coastal wetland soils in the Yellow River Delta by incorporating multi-source data , 2020, Ecological Indicators.

[57]  Precision Agriculture For Sustainability And Environmental Protection Earthscan Food And Agriculture Ebooks Download , 2021 .

[58]  J. Leifeld.  How sustainable is organic farming , 2012 .

[59]  Richard C. Olsen,et al.  Combining spectral and spatial information into hidden Markov models for unsupervised image classification , 2005 .

[60]  Chuanrong Zhang,et al.  Comparison of Geographically Weighted Regression and Regression Kriging for Estimating the Spatial Distribution of Soil Organic Matter , 2012 .