Development of expert system for wild edible plant

Wild edible plants defined by Food and Agricultural Organization (FAO) are the plants that grow spontaneously in self-maintaining populations in natural or semi-natural ecosystems and can exist independently of direct human action. A plant considered to be an edible one could also have poisonous, medicinal, bitter, woody and hairy parts as well. Edible wild plants are also have been identified as part of solution to the issues of food insecurity. So, it is very critical to identify which part of the plant is an edible one; in other case it could have disastrous consequences. The identification of plants by conventional keys is complex, time consuming, and due to the use of specific botanical terms frustrating for non-experts. This creates a hard to overcome hurdle for novices interested in acquiring species knowledge. Today, there is an increasing interest in automating the process of species identification. Thus, this project will implement expert system using MATLAB to classify the wild edible plants and characterise its physical properties. This system able to detect the species as well as its medicinal properties that is believed to cure certain disease. The expert systems will be developed based on vision and machine learning techniques. Within this study also there are 37 GUI for 37 wild edible plant species that has been accomplished along with the updated database that consist of traditional medicinal properties for each of the species. This updated database along with the GUI would facilitate in many aspect such as the use of the wild edible plant as it gives out information such as the medicinal properties and the images of the species