Application of Modified Mitscherlich Equation to Yellow Hybrid Corn Optimized Nutrient e-Advisor
DOI:
https://doi.org/10.61569/6vhfj482Keywords:
Decision support tool, Recommended rate, Inorganic fertilizer, Mitscherlich equation, N-use efficiencyAbstract
This study deals with the design and development of a Yellow Hybrid Corn Optimized Nutrient e-Advisor, a PC-based decision support tool to enhance the Philippine Nuclear Research Institute’s electronic spreadsheet calculation of recommendations. The existing system does not have an irrigation advisory, lacks plant population computation, user’s Recommended Rate (RR) of Nitrogen-Phosphorus-Potassium (NPK) and the user’s cost of the possible combination of inorganic fertilizers. The e-Advisor implemented the modified Mitscherlich equation developed and tested by Rallos et al. The modified equation can also calculate the crop’s agronomic N-use efficiency by using the established efficiency indices from several conducted field trials. It takes the following parameters as inputs: field location, soil type, soil analysis results, cultivar, field size, potential yield, target yield and date of planting. It generates the following recommendations: RR in kg per hectare and RR in kg per user’s area of NPK nutrient needed based on user’s field characteristics, location’s climatic type, lime requirement of the field, possible combinations of inorganic fertilizers and their costs, and irrigation advisory. The application was developed using C#, a multi-paradigm and an object-oriented programming language. Based on the acceptability testing and evaluation using ISO 9126, the application has been found out to be generally acceptable by 52 corn farmers, commercial corn growers, researchers, scientists, provincial/municipal agriculturists, agricultural technicians, faculty, students, and soil laboratory personnel. It is highly recommended that this application be implemented in both mobile and web-based platforms and other adaptable environments to make it portable and more accessible. The integration of corn pest and diseases diagnosis is also recommended.
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