Desarrollo y validación de nuevas composiciones fertilizantes de alta bioasimilabilidad y bajo riesgo contaminante

Resumen

In order to optimize the economical cost of each unit of fertilizer applied and to reduce the environmental contamination caused by nutrient losses the development of highly efficient granulated fertilizers is of great importance. This study proposes a strategy that consists of developing specific fertilizers whose nutrient release pattern is dependent on plant activity in the rhizosphere, thus becoming more sensitive to plant nutritional needs These fertilizers are known as rhizosphere controlled fertilizer (RCF). They can supply an adequate nutrition to plants while minimizing nutrient losses. This fertilizer family is based on the presence a phosphoric matrix, composed of metal-humic-phosphates, soluble not in water but in the rhizospheric acids released by plant roots as an expression of nutritional needs, principally citric acid. This study shows the chemical and structural characterization of the organomineral matrix, as well as its efficiency in slowing the nutrient release rate of other nutrient inserted in the matrix. This is reflected in the significant reduction in volatilization leaching and soil retrogradation phenomenon. In this way, RCF fertilizer efficiency was tested in alkaline and acid soils resulting higher than other common fertilizers in both types of soil. The phospho-metal-humates are potentially more available to plants. This fact may be associated with action of the humic moiety protecting the double metal phosphates from precipitation. The capacity of the plant to mobilize P from the RCF matrix was also tested. Therefore, the matrix is able to supply available P to plants. This occurs by matrix mobilization through plant root exudation of organic acids so that plants with different P efficiency can gradually take up the nutrients presented in the matrix. We describe a fast and simple methodology for the extraction and determination of these organic acids by LC/MS/MS that does not require sample pre-purification or sample derivatization to improve sensibility. Moreover, the sensibility of the method is in general better than that of previous methodologies