Assessing fertility complexity of Agro-gray soil on the East European Plain using correlation-regression analysis

According to classical concepts, soil fertility is an integrating indicator of soil properties. Correlation-regression analysis allows for the evaluation of the complexity of Agro-gray soil fertility in the East European Plain of Russia. The participation of all recorded soil properties and their equal contribution is the criteria for optimal assessment. The initial data array on soil properties divided into two clusters using the cluster analysis method. The absence of significant differences between clusters and some parameters in the model determined the need for correction. An acceptable level of fertility of Agro-gray soil established. The minimum requirements for the soil include 3.2% humus, 181 mg/kg of mobile phosphorus, and 144 mg/kg of exchangeable potassium pH and 1.5 mg-eq/100 g, respectively, the ratio of saturation of the soil with bases is not lower than 92%. With such a numerical combination of soil properties, the complexity of fertility ensured

Prospects for the development and use of a clay-nitrogen mixture as a fertilizer

The purpose of this work is to obtain and evaluate the fertilizing ability of the clay-nitrogen mixture. The relevance of the research lies in studying issues related to the minimization of nitrogen losses when producing the clay-nitrogen fertilizer, the transformation of nitrogen from fertilizer into the soil, and the effectiveness of fertilization when growing barley. The data on the content of nitrate nitrogen (250,986 mg/kg) and the total one (5.0%) indicate the effective binding of nitric acid by clay. The fertilizer can be considered potassium-containing, since the content of mobile and total potassium is respectively 1,250 mg/kg and 0.20%. Mobile phosphorus in the fertilizer is low compared to potassium (76 mg/kg), although the total pool is twice as large (0.45%). The content of the gross form of copper (8.9 mg/kg) and zinc (9.5 mg/kg) corresponded to the MPC