Enhancing Vegetable Quality Prediction with Fuzzy Interference System

We are living in this hurly burly world of Tumult and Turmoil where many problems arises who have not any exact solution/answer like we have health and nutrition problems people facing difficulties to select best vegetable for their health and if they select best vegetable for themselves they don't know about the quality of the vegetable which they have selects. In the vegetable processing industry, some manufacturers add extra ingredients to prolong the shelf life and maintain the quality of their products. However, excessive amounts of these ingredients can have negative health implications such as palpitations, headaches, allergies, and even cancer. Therefore, it is crucial to implement a system to assess the quality of vegetables being used, which can provide consumers and patients with information regarding their quality content. This system is particularly beneficial for addressing human-related issues, especially in determining the percentage of quality. Various methods have been established to achieve optimal solutions in response to rapidly changing living conditions. This paper proposes the development of a fuzzy-based system that takes inputs such as season, time, and condition to detect the quality of vegetables. The output of this system is determined using Kappa statistics.