Automatic nutrient estimator: distributing nutrient solution in hydroponic plants based on plant growth.

Area of Science:

• Agricultural Engineering
• Plant Science
• Automation

Background:

• Hydroponics offers soil-less cultivation, minimizing water and pesticide use.
• Challenges in hydroponics include uneven nutrient distribution and pH/EC fluctuations.
• Optimizing nutrient delivery is crucial for plant health and yield in hydroponic systems.

Purpose of the Study:

• To develop an automated system for precise nutrient delivery tailored to plant growth stages.
• To address challenges in nutrient management, pH, and electrical conductivity (EC) adjustments in hydroponics.
• To minimize resource wastage and manual labor in hydroponic farming.

Main Methods:

• An automatic hydroponic nutrient estimator was developed using an Arduino board and four peristaltic pumps.
• A Plant Growth Stage Identification algorithm was implemented to recognize seedling, vegetative, flowering, and fruiting stages.
• Nutrient consumption was monitored and adjusted based on identified plant growth stages.

Main Results:

• The system achieved 97.5% accuracy in identifying the vegetative stage (weeks 1-5) with 1,715 ppm nutrient intake.
• The flowering stage (weeks 6-9) was identified with 97.5% accuracy, requiring 2,380 ppm nutrients.
• The fruiting stage (weeks 10-15) was identified with 99.4% accuracy, needing 2,730 ppm nutrients.

Conclusions:

• The automated system accurately estimates and delivers stage-specific nutrients, enhancing hydroponic cultivation.
• The Plant Growth Stage Identification algorithm effectively optimizes nutrient management for increased yield.
• This technology streamlines hydroponic farming, reducing manual labor and improving resource efficiency.