v1.0

Crop Yield Forecaster

Predict your expected crop yield based on environmental and farming conditions using advanced machine learning

Linear RegressionR² Score: 0.7935MAE: 261.38 kg/ha

Input Parameters

Enter your field conditions to get an accurate yield prediction

💧 Total annual rainfall in your region. Optimal: 1500-2500mm

🌱 Total fertilizer per hectare. Optimal: 80-150 kg/ha

☀️ Average hours of direct sunlight per day. Optimal: 6-8 hours

🧪 Soil acidity/alkalinity. Optimal: 6.0-7.0 (slightly acidic to neutral)

📖 How It Works

Our yield forecaster uses Linear Regression—a proven statistical method that models linear relationships between environmental factors and rice productivity using ordinary least squares (OLS) optimization.

🌾 Key Input Factors:

  • 💧
    Rainfall: Optimal around 2000mm annually; too little causes drought stress, too much floods crops
  • 🌱
    Fertilizer: Strong positive correlation (+8 kg yield per kg NPK applied)
  • ☀️
    Sunlight: Powers photosynthesis; 6-8 hours optimal for rice production
  • 🧪
    Soil pH: Optimal at 6.0; affects nutrient availability and microbial activity

📊 Model Performance:

R² Score

0.7935

79% variance explained

Avg Error (MAE)

261 kg/ha

±10% typical farms

✓ Trained on 1,200 Philippine farm records (2020-2024)
✓ Covers Luzon, Visayas, Mindanao rice regions
✓ Provides ±261 kg/ha confidence intervals (95% reliability)