Knowledge of the relationship between soil sampling density and spatial autocorrelation with interpolation accuracy allows more time- and cost-efficient spatial analysis. Previous studies produced contradictory observations regarding this relationship, and this study aims to determine and explore under which conditions the interpolation accuracy of chemical soil properties is affected. The study area covered 823.4 ha of agricultural land with 160 soil samples containing phosphorus pentoxide (P₂O₅) and potassium oxide (K₂O) values. The original set was split into eight subsets using a geographically stratified random split method, interpolated using the ordinary kriging (OK) and inverse distance weighted (IDW) methods. OK and IDW achieved similar interpolation accuracy regardless of the soil chemical property and sampling density, contrary to the majority of previous studies which observed the superiority of kriging as a deterministic interpolation method. The primary dependence of interpolation accuracy to soil sampling density was observed, having R² in the range of 56.5–83.4% for the interpolation accuracy assessment. While this study enables farmers to perform efficient soil sampling according to the desired level of detail, it could also prove useful to professions dependent on field sampling, such as biology, geology, and mining.

Soil degradation and climate change are the most destructive (human- and/or naturally induced) processes, making agricultural production more challenging than ever before. Traditional tillage methods, characterized by intensive mechanical soil disturbance (dominantly using a plow), have come under question for their role in exacerbating soil erosion, depleting organic matter, and contributing to the decline in soil biodiversity and other soil devastating processes. These practices, while effective in the short term for crop production, undermine the sustainability of agricultural systems, posing a threat to food security and environmental stability. This review examines the adoption and implementation of Conservation Soil Tillage (CST) across six European countries: Croatia, Serbia, Hungary, Slovakia, Czech Republic, and Poland. The main objective is to analyze the historical development, current status, and future prospects of CST in these countries, highlighting the challenges and opportunities in transitioning from conventional tillage methods. Conservation Soil Tillage (CST) emerges as a promising alternative platform to still dominant conventional plowing tillage approach. By reducing the intensity and frequency of tillage, CST practices aim to maintain adequate soil cover, minimize erosion, and encourage biological activity and organic matter accumulation, thus, ensuring soil productivity and resilience against additional degradation and climate variation. Efforts made by scientists and the government to go over it sometimes are not sufficient. Farmers’ expectations of benefits are the final keystone for the integration of CST as a dominant sustainable practice. Analyses from six European countries pointed to a high level of diversity in readiness and willingness to accept, as well as different levels of knowledge about the adoption of CST. Our study suggested that the adoption of CST is increasing, and it represents a key strategy for soil degradation prevention and climate change mitigation.

Effects of soil tillage (CTconventional, SS-subsoiling, CH-chiselling, DH-disk-harrowing and NT-no-till) and nitrogen rate (reduced N1, optimal N2 and luxury N3) on yield and yield components of maize and winter wheat in two different agricultural subregions of Croatia (Magadenovac and Cacinci site), were studied in the years 2013–2014 as part of a long-term experiment. Maize yield and yield components were influenced by site properties, tillage and nitrogen treatments. The highest yields and yield components were recorded at the Magadenovac site with N2 and N3. The lowest values of the yield and yield components of maize were recorded on NT and were significantly lower than CT, SS, CH and DH, among which no significant differences were recorded. Winter wheat yield and yield components were affected by site properties and nitrogen rates while soil tillage treatments only had an influence on grain and straw yield and plant height. Winter wheat achieved maximum yield and yield components on a N3 and N2 and at the Magadenovac site. Winter wheat grain yield decreased in the following order: SS > DH > CH > NT > CT. The obtained results indicate the importance of optimal nitrogen fertilization and the possibility of the implementation of conservation tillage for maize and winter wheat production in different agroecological conditions.

The aim of this study was to narrow the research gap of ambiguity in which machine learning algorithms should be selected for evaluation in digital soil organic carbon (SOC) mapping. This was performed by providing a comprehensive assessment of prediction accuracy for 15 frequently used machine learning algorithms in digital SOC mapping based on studies indexed in the Web of Science Core Collection (WoSCC), providing a basis for algorithm selection in future studies. Two study areas, including mainland France and the Czech Republic, were used in the study based on 2514 and 400 soil samples from the LUCAS 2018 dataset. Random Forest was first ranked for France (mainland) and then ranked for the Czech Republic regarding prediction accuracy; the coefficients of determination were 0.411 and 0.249, respectively, which was in accordance with its dominant appearance in previous studies indexed in the WoSCC. Additionally, the K-Nearest Neighbors and Gradient Boosting Machine regression algorithms indicated, relative to their frequency in studies indexed in the WoSCC, that they are underrated and should be more frequently considered in future digital SOC studies. Future studies should consider study areas not strictly related to human-made administrative borders, as well as more interpretable machine learning and ensemble machine learning approaches.

At present there is little information available concerning the relationship between the tillage system applied and the soil moisture tension, penetration resistance, soil moisture content, and temperature responses to the temporal variability of precipitation under the semi-arid Mediterranean...

As conservation tillage becomes one of the foundations of sustainable crop production, important questions arise about its value, which needs to be defined and evaluated. One of the most important indicators of soil compaction is penetration resistance (PR), which comes as a short-term response to the state of soil physics. The objective of this work is to compare different tillage treatments (TT) on soil compaction on silty clay loam Stagnosol and silt Gleysol in the continental part of Croatia. The research included three tillage treatments: ST—conventional tillage, CTD—deep conservation tillage, and CTS—shallow conservation tillage. PR was determined on each soil depth of 5 cm up to 80 cm, and measuring was provided on two measuring dates. The obtained results showed a higher influence of the year factor than TT. In the upper layers (up to 35 cm), PR values between TT were with significant differences, but in most cases below root-limiting critical values, while in deeper soil layers (35–80 cm), we found that penetration values on each tillage treatment begin to stabilize and smooth out in most cases, with similar dynamics on both soil types and measurement dates. In most of the cases, the highest PR was measured for conservation treatments in wetter soil conditions.