An Evolving Expert System for Maize Plant Nutrient Deficiency using Image Processing Technique

Maize is an important cereal crop grown widely throughout the world in a range of agro-ecological environments. The crop can be used for food and non-foods products. Nonetheless, despite the nutritional and economic significance of the maize crop, the diseases incidence on maize plantations is fast becoming a constraint in farmers quest for a bountiful harvest. The efforts of agricultural extension agents seem not to be sufficient in tackling this menace since there is always a limit to how far the human capacity can be stretched in the face of highly demanding situations. Hence, this paper proposed expert system which infers nutrient deficiency of maize crop namely Nitrogen, Phosphorus and potassium using Multivariate Image Analysis and Multivariate Partial Least Square Approach. The expert system would provide immediate and instant information to the possible disease affecting the life of maize with the consideration of several known symptoms supplied. It would fast-track information service delivery on the part of the large-scale industrial grain farmers which make use of it for emergency situations of disease outbreak on the farm, pending the arrival of the agricultural extension agent.