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Pi Driven IoT–Machine Learning Analysis of BioBoost vs. Synthetic Fertilizers on Phaseolus vulgaris Growth and Soil Heal

CSEF · 2026 Plant Biology (Senior Division)

Arvin Agrawal

Overview

The San Joaquin Valley is one of the most productive agricultural regions in the world; however, heavy reliance on synthetic fertilizers has disrupted soil nutrient balance and electrical conductivity, resulting in reduced crop yield. In addition, many farmers lack affordable, real-time soil monitoring tools to support data-driven decisions for fertilization and irrigation. To address these challenges, Trifusion BioBoost (TFB) was developed and evaluated using a Raspberry Pi–based IoT platform connected to a multi parameter soil sensor via RS-485 communication. TFB is a combination of Azolla, Rhizobium, and Mycorrhizae to improve nutrient availability and soil health. Sensor data were preprocessed and calibrated to ensure accuracy. Key soil parameters, including nitrogen (N), phosphorus (P), potassium (K), pH, electrical conductivity (EC), and soil moisture were analyzed using Python. Real-time data were transmitted to a cloud server via Application Programming Interface. A machine-learning classification model categorized soil health as Very Bad, Bad, Normal, Good, or Excellent and generated crop recommendations through Android mobile application. This study compared the effects of TFB versus synthetic fertilizer on garden beans (Phaseolus vulgaris). Results showed that synthetic fertilizer caused a rapid spike in NPK and EC levels followed by a sharp decline, indicating nutrient leaching. In contrast, TFB resulted in a steady increase in nutrient availability, stabilized soil pH, maintained moderate EC, improved soil moisture retention, and produced highest plant height and biomass. This demonstrates that TFB combined with real-time soil monitoring can enhance crop yield, improve soil health, and support sustainable, water-efficient agriculture in drought-prone regions.

Competition history

  • CSEF 2026 Plant Biology (Senior Division) · Entry S-18-13

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