A flexible control system designed for lab-scale simulations and optimization of composting processes.

Understanding and optimization of composting processes can benefit from the use of controlled simulators of various scales. The Agricultural Research Organization Composting Simulator (ARO-CS) was recently built and it is flexibly automated by means of a programmable logic controller (PLC). Temperature, carbon dioxide, oxygen and airflow are monitored and controlled in seven 9-l reactors that are mounted into separate 80-l water baths. The PLC program includes three basic heating modes (pre-determined temperature profile, temperature-feedback ("self-heating"), and carbon dioxide-dependent temperature), three basic aeration modes (airflow dependence on temperature, carbon dioxide, or oxygen) and enables all possible combinations among them. This unique high flexibility provides a robust and valuable research tool to explore a wide range of research questions related to the science and engineering of composting. In this article the logic and flexibility of the control system is presented and demonstrated and its potential applications are discussed.

Optimization of waste combinations during in-vessel composting of agricultural waste.

In-vessel composting of agricultural waste is a well-described approach for stabilization of compost within a short time period. Although composting studies have shown the different combinations of waste materials for producing good quality compost, studies of the particular ratio of the waste materials in the mix are still limited. In the present study, composting was conducted with a combination of vegetable waste, cow dung, sawdust and dry leaves using a 550 L rotary drum composter. Application of a radial basis functional neural network was used to simulate the composting process. The model utilizes physico-chemical parameters with different waste materials as input variables and three output variables: volatile solids, soluble biochemical oxygen demand and carbon dioxide evolution. For the selected model, the coefficient of determination reached the high value of 0.997. The complicated interaction of agricultural waste components during composting makes it a nonlinear problem so it is difficult to find the optimal waste combinations for producing quality compost. Optimization of a trained radial basis functional model has yielded the optimal proportion as 62 kg, 17 kg and 9 kg for vegetable waste, cow dung and sawdust, respectively. The results showed that the predictive radial basis functional model described for drum composting of agricultural waste was well suited for organic matter degradation and can be successfully applied.

Carbon decomposition by inoculating Phanerochaete chrysosporium during drum composting of agricultural waste.

The effect of Phanerochaete chrysosporium inoculation during drum composting of agricultural waste was performed at different composting stages. Three trials were carried out with (5:4:1) combination of vegetable waste, cattle manure, and sawdust along with 10 kg of dried leaves with a total mass of 100 kg in a 550 L rotary drum composter. Trial 1 was a control without inoculation of fungus, while trial 2 was inoculated during the initial day (0th day of composting), and trial 3 was inoculated after the thermophilic phase, i.e., on the 8th day of composting period. The inoculation of fungus increased the volatile solids reduction by 1.45-fold in trial 2 and 1.7-fold in trial 3 as compared to trial 1 without any fungal inoculation. Total Kjeldahl Nitrogen (TKN) was observed with 2.31, 2.62, and 2.59% in trials 1, 2, and 3, respectively, at the end of 20 days of composting period. Hence, it can be concluded that inoculation of white-rot fungus increased the decomposition rate of agricultural waste within shorter time in drum composting. However, inoculation after the thermophilic phase was found more effective than inoculation during initial days of composting for producing more stabilized and nutrient-rich compost.