Variáveis influenciadoras das características físico-químicas em compostagem e predição da relação C/N

Abstract

There is a worldwide trend in increasing the generation of solid waste and alternatives to mitigate its negative effects have gained more and more prominence. A most widespread methods for the treatment of organic waste is composting, this process can be defined as the controlled biological decomposition of organic matter in an aerobic environment. During the composting process, several transformations occur in the organic material, these transformations are mediated by several factors such as the performance of microorganisms, carbon / nitrogen ratio, pH, temperature and humidity of the compost pile. All of these factors interact with each other to regulate the process of transformation of organic material, so understanding these factors can contribute to better biological and economic efficiency of the process. The objective of this study was to evaluate the impact of including different proportions of plant residues in composting cattle manure on the physical-chemical characteristics of the compost produced and using them to estimate the C/N ratio using linear equations selected with the aid of the method Best-subsets Selection. Different compost mixtures were created using three types of waste: bovine manure, pruning and sweeping remains and perobeira wood shavings. Variables such as organic matter content (OM), pH, electrical conductivity (EC), total organic carbon (TOC), total nitrogen (NT) and C/N ratio were monitored throughout the process. There was a difference between the different waste compositions throughout the composting process. The results suggest that the inclusion of bulking agents contributes to the concentration of NT in the compound, while the low inclusion of these materials may favor the loss of this nutrient. However, high levels of bulking agents can generate a compound with a high C/N ratio after the composting period, which could make its agronomic use unfeasible. In addition, among the evaluated parameters, organic matter is one of the main factors associated with the C/N ratio, being possible to estimate the C / N ratio with a regression model considering only the OM content. When the time factor was added to the model, better statistical indexes were obtained, such as best adjusted R², Mallows' Cp statistic, residual sum of squares and Bayesian Information Criterion, without prejudice to the practical application of the model.