Mobile phone application for identification of nutrients and microbial contamination in fruits and vegetables

Objectives: In agricultural science, the quality identification of fruits and vegetables were categorized with differentiating colour, shape, dimension and texture. The proposed technique will enable to develop a smart phone
application which uses intelligent image processing algorithms to scan the attributes of the fruit sex habited in a supermarket and assess its nutritional values like total carbohydrates including sugars like glucose, fructose, sucrose, potassium, magnesium and vitamins like vitamin A and vitamin C, antioxidants along with microbial contamination. This instant information received by the customers, once they capture the images of the fruits using the smart phone will kindle their interest to purchase the fruits based on their requirement. Another added feature of this smart phone App is that, it will enable the customers to identify the microbial contamination in fruits and vegetables. Method: This simple technology which is user friendly will facilitate the measurements related to the nutritional value which includes parameters like sugar content, carbohydrates, potassium and vitamins by embedding an intelligent image
processing algorithm to process the various images of the fruits captured by the camera in the smart phone. This
advanced technology of using smart phone App, extracts the color, shape, average intensity and Sum of Absolute
Difference (SAD) for various fruits like Mango, banana, orange, papaya and tomato to classify them into three categories like High or Good Quality (HQ or GQ), Medium or Average Quality (MQ or AQ ) and Low or Poor Quality (LQ or
PQ)with specific and accurate measurements of the total carbohydrates including sugars like glucose, fructose, sucrose, potassium, magnesium, antioxidants and vitamins like vitamin A and vitamin C, displayed on mobile phone screen, instantly.