Decision-tree-based ion-specific dosing algorithm for enhancing closed hydroponic efficiency and reducing carbon...

Area of Science:

• Agricultural Science
• Environmental Science
• Chemical Engineering

Background:

• Maintaining ion balance in hydroponic systems is crucial for crop quality and nutrient solution recycling.
• Challenges in managing specific ions (P, Mg) and salt coupling hinder precise nutrient control.

Purpose of the Study:

• To develop and evaluate a decision-tree-based dosing algorithm for precise nutrient management in closed hydroponic systems.
• To assess the algorithm's effectiveness in optimizing nutrient solution composition and reducing environmental impact.

Main Methods:

• A decision-tree algorithm was created to calculate optimal nutrient stock solution volumes for five key ions (NO3, K, Ca, P, Mg).
• Ion concentrations (NO3, K, Ca) and remaining solution volume were used as inputs.
• Performance was validated using an ion-selective electrode array and a five-step replenishment test.

Main Results:

• The ion-selective electrode array showed good accuracy for NO3, K, and Ca measurements.
• The system accurately formulated nutrient solutions within specified targets, with low relative errors.
• The decision-tree method reduced fertilizer injections by 12.8% and carbon emissions by 20.6%.

Conclusions:

• The decision-tree algorithm offers superior nutrient solution reuse efficiency compared to the simplex method.
• This approach demonstrates significant potential for reducing fertilizer consumption and carbon footprint in hydroponics.
• The findings support the development of sustainable agricultural practices through advanced nutrient management.