Application of fuzzy logic in recognition of tomato fruit maturity in smart farming

Abstract

The tomato crop (Solanum lycopersicum L.) is of great importance in the world. It is useful not just for the livelihood it provides for farmers, but also for its health benefits. Tomato is also rich in vitamin C and lycopene. Lycopene can lower the risk of breast and prostate cancer, osteoporosis and it can also cure male infertility. With the help of Smart Farming technology, the production of tomato fruit in season or not is made possible. This study deals more of the appearance of the fruit because it is the most important characteristic because it defines the product's commercialization value. The tomato's good appearance as well as its good quality will only be met if it reaches its maturity. Tomato maturity is closely relevant to its surface color, so evaluating the tomato's level of maturity by visual recognition is a feasible mean (Choi et al., 1995; Gejima et al., 2004). Tomato color maturity is divided into six stages: Green stage, breakers stage, turning stage, pink stage, light red stage and red stage (USDA, 1991). The researchers used the color, size, and shape of tomato fruit to be the basis of its maturity using the knowledge of fuzzy logic under smart farming implementation.