CROP YIELD PREDICTION USING MACHINE LEARNING

Abstract

Agricultural productivity hinges on a myriad of factors, each playing a vital role in shaping crop growth 
and yield. This abstract offers an insight into the significance of key factors such as nitrogen, phosphorus, 
potassium, pH, temperature, humidity, rainfall, and type of soil in agricultural practices. Nitrogen, 
phosphorus, and potassium are the indispensable nutrients critical for plant metabolic functions, growth, 
and productivity. Their availability in soil profoundly impacts crop health, necessitating precise fertilization 
strategies. Soil pH, governing nutrient uptake and microbial activity, underscores the importance of 
maintaining optimal levels for crop development. Temperature dictates crucial growth stages, with crops 
exhibiting specific temperature requirements for germination, growth, and reproduction. Humidity 
influences transpiration rates, disease susceptibility, and overall plant vigor, necessitating judicious 
irrigation and crop management practices. Rainfall patterns profoundly influence agricultural outcomes. 
Adequate rainfall ensures soil moisture, sustains plant growth, and supports crop yields. Soil type, defined 
by texture, structure, and composition, shapes water retention, nutrient availability, and root growth. 
Tailored soil management, including amendments and rotations, optimizes fertility and productivity.