Maize nitrogen deficiency detector

Abstract

Maize growing is very popular in Uganda as the crop is widely grown for both commercial and subsistence use. This is supported by the fact that there are several uses for the maize products which are produced and processed in the country. These products are also on high demand in countries like Kenya and Burundi which are neighboring Uganda. Because of this, a lot of attention has to be directed towards the quality of these products partly by ensuring that they are safe for both human and animal consumption. It should be noted that one of the major factors that bring about a concern for the quality of the maize products is the concentration aflatoxin contamination. If this concentration is too high, the maize products can be harmful when consumed by humans. One of the ways of controlling the rate at which aflatoxins are formed in maize when it is still growing in the garden is by ensuring that the plant has a balanced amount of the nitrogen nutrient in its system. This project was created to support maize farmers in making sure that their crops always have a balanced amount of nitrogen by enabling them to easily and quickly identify the deficiencies in real-time by scanning the leaves for the symptoms of the said deficiency. It is in the form of a mobile application which uses an image classification machine learning model which enables it to scan the leaves of a maize plant and immediately return a diagnosis of whether or not the scanned leaf contains the symptoms of a deficiency in nitrogen. In the event that the scanned plant does not have the necessary amount of nitrogen in its system, the application immediately advises the farmer (user) on how to restore the nutrient to the right amount in the plant. There is no study or project that fulfills the same purpose as this one.