Patent Landscape of Composting Technology: A Review

Application of Multivariate Regression and Artificial Neural Network Modelling for Prediction of Physicochemical Properties of Grape-Skin Compost

The reusability of by-products in the food industry is consistent with sustainable and greener production; therefore, the aim of this paper was to evaluate the applicability of multiple linear regression (MLR), piecewise linear regression (PLR) and artificial neural network models (ANN) to the prediction of grape-skin compost's physicochemical properties (moisture, dry matter, organic matter, ash content, carbon content, nitrogen content, C/N ratio, total colour change of compost samples, pH, conductivity, total dissolved solids and total colour change of compost extract samples) during in-vessel composting based on the initial composting conditions (air-flow rate, moisture content and day of sampling). Based on the coefficient of determination for prediction, the adjusted coefficient of determination for calibration, the root-mean-square error of prediction (RMSEP), the standard error of prediction (SEP), the ratio of prediction to deviation (RPD) and the ratio of the error range (RER), it can be concluded that all developed MLR and PLR models are acceptable for process screening. Furthermore, the ANN model developed for predicting moisture and dry-matter content can be used for quality control (RER >11). The obtained results show the great potential of multivariate modelling for analysis of the physicochemical properties of compost during composting, confirming the high applicability of modelling in greener production processes.

Composting municipal solid waste and animal manure in response to the current fertilizer crisis - a recent review

The dynamic price increases of fertilizers and the generation of organic waste are currently global issues. The growth of the population has led to increased production of solid municipal waste and a higher demand for food. Food production is inherently related to agriculture and, to achieve higher yields, it is necessary to replenish the soil with essential minerals. A synergistic approach that addresses both problems is the implementation of the composting process, which aligns with the principles of a circular economy. Food waste, green waste, paper waste, cardboard waste, and animal manure are promising feedstock materials for the extraction of valuable compounds. This review discusses key factors that influence the composting process and compares them with the input materials' parameters. It also considers methods for optimizing the process, such as the use of biochar and inoculation, which result in the production of the final product in a significantly shorter time and at lower financial costs. The applications of composts produced from various materials are described along with associated risks. In addition, innovative composting technologies are presented.