Influence of physical and chemical properties of different soil types on optimal soil moisture for tillage

• Published in: Poljoprivreda (Osijek, Croatia) Vol. 23; no. 2; pp. 10 - 18
• Main Authors: Zebec, Vladimir, Semialjac, Zoran, Marković, Monika, Tadić, Vjekoslav, Radić, Domagoj, Rastija, Domagoj
• Format: Journal Article
• Language: English
• Published: Faculty of Agrobitechnical Sciences Osijek 01-01-2017
• ISSN: 1330-7142; 1848-8080
• DOI: 10.18047/poljo.23.2.2

Soil plasticity is the area of soil consistency, i.e. it represents a change in soil condition due to different soil moisture influenced by external forces activity. Consistency determines soil resistance in tillage, therefore, the aim of the research was to determine the optimum soil moisture condition for tillage and the influence of the chemical and physical properties of the arable land horizons on the soil plasticity on three different types of soil (fluvisol, luvisol and humic glaysol). Statistically significant differences were found between all examined soil types, such as the content of clay particles, the density of packaging and the actual and substitution acidity, the cation exchange capacity and the content of calcium. There were also statistically significant differences between the examined types of soil for the plasticity limit, liquid limit and the plasticity index. The average established value of plasticity limit as an important element for determining the optimal moment of soil tillage was 18.9% mass on fluvisol, 24.0% mass on luvisol and 28.6% mass on humic glaysol. Very significant positive direction correlation with plasticity limits was shown by organic matter, clay, fine silt, magnesium, sodium and calcium, while very significant negative direction correlation was shown by hydrolytic acidity, coarse sand, fine sand and coarse silt. Created regression models can estimate the optimal soil moisture condition for soil cultivation based on the basic soil properties. The model precision is significantly increased by introducing a greater number of agrochemical and agrophysical soil properties, and the additional precision of the model can be increased by soil type data.