No abstract

Climate change (CC) is undoubtedly induced and accelerated by human activity and can pose a serious threat to mankind by reducing food production. Significant weather aberrations in form of the uneven precipitation pattern, more frequent and intense occurrence of temperature fluctuations accompanied by changes in wind intensity and frequency, amount of clouds, intensity and quality of sunlight can be expected. Maybe the most vulnerable sector affected by CC is agriculture. So, it is important to mitigate and adapt to a new situation through different and most adaptable agricultural strategies. Accordingly, scientists, experts, politicians, decisionmakers, and others increasingly emphasize the need for further development of sustainable agricultural production, whose management will be compatible with different ecosystems (agroecosystem compliance with global ecosystems), while simultaneously restoring degraded agricultural land. One of the best solutions for sustainable agricultural production, under CC conditions, can be Conservation agriculture. Climate change is not only an abstraction, which is why one of the most important roles of conservation agriculture today is its ability to adapt and mitigate these changes. The basis of conservation agriculture production is in management set on three fundamental postulates, which contextually unify climate-soil-plant, while respecting agroecological and socioeconomic differences.

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.

Four different tillage systems were compared in soybean [Glycine max (L.) Merr.] production on one experimental field (chernozem) located in the Baranya region of northeastern Croatia in 2002 and 2003. The dry conditions experienced in 2003 exacerbated the negative effects of no-tillage on soybean yield. The 2-year average yield of soybean was significantly lower under no-tillage (NT) than in the conventional tillage (CT), soil loosening (SL) and disc harrowing (DH) treatments. The soybean oil and protein contents were very similar in all the tillage systems over the 2-year average. Soybean crude fibre (%) was affected by the main effect of tillage. Averaged over 2 years the crude fibre (%) of soybean grain was greater under NT than in the CT, DH and SL treatments. The ash (%) generally increased as tillage declined.

Eight different tillage systems were compared in soybean production on one experimental field (chernozem) located in the Baranya region of Croatia over a 4-year period (2001/2002, 2002/2003, 2003/2004, 2004/2005). The dry conditions experienced in 2003 exacerbated the effects of NT and CWNS on the soybean yield. The most stable grain yield was obtained using CSNW and CSDW in all four experimental years. DH, CH and CWDS did not result in any significant reduction in crop yield compared to CT. There was no clear trend regarding the applied tillage systems and grain yield components. The greatest effects on soybean yield and yield components were due to climatic conditions. Different tillage systems had a significant effect on the soybean grain yield and yield components in the four experimental years. The largest differences in stem height were determined between CSNW and NT. The number of pods per plant, the hectolitre mass and the grain yield were significantly lower under NT than under the other tillage systems. The number of fertile nodes of soybean and the number of branches per plant in the experimental years had approximately the same values for all the tillage systems. To sum up, the results achieved with DH, CH, CSDW, CWDS and CSNW were on par with each other and slightly better than CT, and these systems could represent adequate replacements for conventional tillage. No tillage could not be considered as the most favourable for soybean growing.