Heavy metals are the most environmentally hazardous pollutions in agricultural soils, threatening humans and several ecosystem services. Cadmium (Cd) is a highly toxic element but distinctively different from other heavy metals with its high mobility in soil environments. The study aimed to evaluate the Cd concentration of soils in the Konya plain with a specific attribute to soil fertilization, mainly phosphorous fertilizers. A total of 538 surface (0–20 cm) soil samples were analyzed to determine basic physical and chemical properties and total phosphorus (P) and Cd concentrations. Descriptive statistics, machine learning, and regression models were used to assess the accumulation of Cd in soils. Decision Trees, Linear Regression, Random Forest, and XGBoost machine learning methods were used in Cd prediction. The XGBoost model proved to be the best prediction model, with a coefficient of determination of 98.1%. Electrical conductivity, pH, CaCO₃, silt, and P were used in the Cd estimation of the XGBoost model and explained 56.51% of the total variance in relation to measured soil properties. The results revealed that a machine learning algorithm could be useful for estimating Cd concentration in soils using basic physical and chemical soil properties.

One of the strategies of the plants growing in phosphorus (P)-deficient environments is to exudate low-molecular-weight organic acids (LMWOA). Thus, we aimed to investigate the effect of LMWOA on phosphorus uptake of barley from either fertilizer or inherited soil phosphorus. The experiment was set up in full factorial arrangement in completely randomised design with two phosphorus (0 and 50 mg P kg⁻¹), five organic acids, LMWOA (malic acid, oxalic acid, citric acid, acetic acid, ascorbic acid), and four organic acid rates (0, 10, 20, and 30 mmol kg⁻¹). The effects of LMWOA on yield in descending order were: oxalic acid > ascorbic acid > malic acid > acetic acid > citric acid. The maximum P concentration in grain was obtained at 30 mmol kg⁻¹ LMWOA treatments. As a result, it was found that oxalic acid was the most effective LMWOA in increasing nutrient uptake induced grain yield with and without phosphorous fertilizer application.

Priming the seeds with plant nutrients containing solutions is economically feasible and easy way of preventing plants from future nutrient deficiency problems by enriching seed nutrition content; therefore, it has been commonly used in the last decades. Seeds of barley (Hordeum vulgare L., Tokak 157/57) and common wheat (Triticum aestivum L., Esperia) were kept in priming solutions containing phosphorus (P), copper sulphate (Cu) and zinc sulphate (Zn) in different concentrations for 10 h and washed in pure water then dried back to the initial moisture content. The chemical compositions of seeds were analysed and then the efficiency tests of priming practices were conducted in completely randomised design pot experiment with three replications. There were priming-induced increases in seeds up to 10.5, 13.4 and 1.61 fold for Cu, Zn and P respectively. The treatments resulted in an increase in the 50% emergence time. Phosphorus treatment (3%) reduced the germination rate by 33% comparing with the control. Seedling nutrient concentrations on the subject were positively responded to nutri-priming treatments. Therefore, these priming techniques could be used to improve seedling’s nutrient contents to better perform in the preceding growth stages.