DETERMINE THE OPTIMAL DOSE OF IRRIGATION WATER AND NPK FERTILIZER FOR TOMATO PLANTS IN SON LA PROVINCE BASED ON SOIL SENSOR DATA

Abstract

In the context of precision agriculture, optimizing irrigation and fertilizer application is critical to improving crop yield while minimizing resource use. This study aimed to determine the optimal doses of irrigation water and NPK fertilizer for tomato cultivation in greenhouse conditions in Son La province, Vietnam, using data collected from IoT-based soil sensors. The experiment was conducted on 15 plots with five different fertilization and irrigation treatments (D1 to D5), where soil relative humidity and available N, P₂O₅, and K₂O levels were monitored in real time throughout the tomato growth stages. Crop indicators including plant height, stem diameter, number of leaves, flowers, fruits, and fruit diameter were measured, and yield was recorded over three harvests. Statistical analyses revealed that increasing fertilization improved growth and yield parameters significantly up to D4. The D5 treatment showed slight improvements, particularly in potassium levels, but with diminishing returns. Regression models demonstrated strong correlations (R² > 0.82) between fertilizer dose and nutrient increase in soil, and a moderate correlation (R² = 0.6997) between irrigation and soil moisture. The findings suggest that D4 provides an optimal balance between resource use and crop performance. These results support the development of a sensor-based recommendation system for precise irrigation and fertilization management in tomato production under greenhouse conditions.