Data Science

Determining Optimal Fertilizer Mixes

Agriculture Industry

A farmer will provide a company sales representative with information about previous crop yields and his or her target yields and the company representatives will visit the farm to obtain soil samples, which are analyzed in the company labs. A report is generated, which indicates the soil requirements for nutrients, including nitrogen, phosphorus, potassium, boron, magnesium, sulfur, and zinc. Given these soil requirements, company experts determine an optimal fertilizer blend, using a linear programming model that includes constraints for the nutrient quantities required by the soil (for a particular crop) and an objective function that minimizes production costs.

Benefits for the company

Previously the company determined fertilizer blend recommendations by using a time-consuming manual procedure conducted by experts. The linear programming model enables the company to provide accurate, quick, low-cost (discounted) estimates to its customers, which has helped the company gain new customers and increase its market share



Type of expertise/ AI domain

Linear Programming Model and Operations Research

Internal data required

Soil Type, Soil Constituent

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