🚜 The Problem

When farmers consult experts for fertilizer recommendations, they typically receive nutrient requirements in the form of elements — for example, for sugarcane cultivation:

However, fertilizers sold in the market (like Urea, DAP, MOP, SSP, etc.) contain only a certain percentage of each nutrient. For instance:

So, if a farmer buys a 50 kg bag of SSP, it contains only 8 kg of actual Phosphorus (P) (16% of 50 kg).

As a result, determining the exact quantity of each fertilizer required to meet crop nutrient needs becomes a highly complex calculation. To achieve accurate nutrient balance, one must:

• Consider multiple fertilizers with varying N, P, K and S compositions.
• Calculate how much actual Nitrogen (N), Phosphorus (P), Potassium (K), and Sulphur (S) each bag contributes.
• Ensure that the total nutrients supplied precisely match the target requirement.
• Minimize the total cost, since fertilizer prices differ widely across brands and regions.
• Respect availability constraints, as some fertilizers may not always be in stock.

Performing all these steps manually across 8–10 different fertilizer options involves solving multiple simultaneous equations with several unknowns — a process that is nearly impossible for most farmers or even experienced consultants. Moreover, with constant price fluctuations and varying compositions, manual cost optimization becomes both time-consuming and error-prone.

💡 The Solution: Fertilizer Cost Optimizer

The Fertilizer Cost Optimizer by eKrishi Smart Services (OPC) Pvt. Ltd. simplifies this entire process using smart mathematical optimization and automation.

🧩 How It Works

Input Requirements:

The user (farmer or shopkeeper) enters:

• Crop nutrient requirement (in kg per acre) — e.g., N, P, K, S
• Available fertilizers with details such as:
  • Nutrient composition (% of N, P, K, S)
  • Bag weight (e.g., 50 kg, 45 kg)
  • Cost per bag

Optimization Engine:

The software calculates the most efficient combination of fertilizers that will:

• Fulfill the required nutrient quantities exactly or approximately
• Minimize total cost
• Respect constraints (e.g., availability limits, bag sizes)

Output – Smart Recommendation:

The system provides an optimized purchase plan, showing:

• Which fertilizers to buy
• Quantity of each fertilizer (in bags or kg)
• Total cost and nutrient coverage
• Comparative savings versus traditional manual selection

Example Case Study: Sugarcane Fertilization Optimization

Crop Requirement (per acre)

To achieve optimal sugarcane growth, the recommended nutrient requirement is as follows:

Conventional Farmer Approach

In general practice, farmers meet these nutrient requirements using commonly available fertilizers such as DAP, MOP, SSP, and Urea.

💬 Note: Fertilizer prices vary depending on brand and region.

Thus, to fulfill the nutrient requirement of N = 100 kg, P = 50 kg, K = 20 kg, S = 20 kg, the total cost comes to approximately ₹6,222 per acre under traditional purchasing methods.

Optimized Solution by Fertilizer Cost Optimizer

Using the Fertilizer Cost Optimizer, the system analyzes all available fertilizer options, their nutrient compositions, bag weights, and costs. It then applies a advanced mathematical algorithm to find the most cost-effective combination while precisely meeting the nutrient requirement.

🔹 Recommended Combination (Optimized Result)

💰 Cost Comparison & Savings

Note: Savings will vary based on the cost and weight of fertilizers available in the local market.