Quantifying Crop Health Through Soil Moisture and Soil Quality Dynamics

Area of Science:

• Agricultural Science
• Environmental Science
• Data Science

Background:

• Crop health is crucial for agricultural productivity.
• Quantifying crop health across developmental stages is essential for sustained yield improvement.
• Soil moisture and quality are key determinants of crop health.

Purpose of the Study:

• To develop and validate a mathematical model for quantifying crop health.
• To integrate soil moisture and soil quality indicators into a composite model.
• To assess crop health dynamics throughout the crop lifecycle.

Main Methods:

• A composite mathematical model integrating soil moisture and soil quality was developed.
• Data was collected and the model was evaluated using a digital platform.
• Model validation was performed against the Normalized Difference Vegetation Index (NDVI) scale through three iterations.

Main Results:

• The model accurately quantifies crop health, providing insights into soil conditions.
• Iteration 2 yielded a crop health value of 0.424, and Iteration 3 yielded 0.448.
• These values fall within the moderate crop health range (0.33-0.66) on the NDVI scale.

Conclusions:

• The study presents a novel mathematical approach linking soil moisture and quality to crop health quantification.
• The model offers a practical framework for evidence-based agricultural decision-making, particularly for small-scale farmers.
• Real-time data implementation is recommended for the proposed mathematical modeling.