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

• Soil C:N is an indicator of soil quality for sustainable organic farming. • K-means algorithm was implemented for the determination of soil C:N deficiency zones. • Ordinary kriging outperformed lognormal kriging and inverse distance weighted. • A total of 45.6% of the study area was determined as unsuitable for organic farming. 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. [ABSTRACT FROM AUTHOR]