Skewer method validation for moisture estimation in home composting

Abstract

Compost is a product obtained from the degradation of organic matter that can be used as a soil fertilizer or amendment. The process to obtain it is an important way of recycling all the organic matter that is produced every day, basically from food leftovers. The process of composting can be carried out either at an industrial scale or at home. In the first case, there are big infrastructures to help the degradation of the organic matter, and exhaustive control of the process and the properties of the composting material. When it is done at home, though, the budget is not the same, and the process is smaller in production. Nevertheless, it is vital to control all the properties of the compost, such as its temperature and moisture, during the process so that it develops correctly. In the case of the moisture level, it is necessary to consider than when it’s too low, the reaction rate of the degradation is very low too. On the other hand, if it’s too high, anaerobic conditions may appear. It is important, then, to place the process in the suitable moisture range. Nevertheless, it is necessary a cheap and reliable method to measure the moisture in home composting. Thus, the aim of this project is to develop a method that allows to know the moisture of this composting material. The proposed system is to introduce a skewer into the composting material and, from its appearance once it’s been pulled out, knowing if its moisture is right or not. Three moisture levels have been differentiated: too dry, correct and too wet. This way, this simple, clean, cheap and reliable method can help composters to control their process. To establish the method, different factors that could affect it were studied: the contact time of the material, the kind of skewers to be used, the compression level of the material and the presence of a dry material layer in the composter. Then, samples of compost at different moisture levels were prepared, and the skewer obtained in each sample was photographed. Once these photos were analyzed, they were used as a pattern to validate the method with other people. The outcome was generally positive, with a high percentage of correct answers, which proved the well-functioning of the proposed method.