AI model predicts whether biochar helps or harms soil phosphorus levels for farms

Researchers have developed an AI model that predicts how biochar, a charcoal-like material from burnt plant waste, affects phosphorus in farm soil. The model, called Random Forest, achieved about 91% accuracy by analyzing data from 32 earlier studies. This could help farmers decide when to use biochar to boost crop nutrients or to prevent phosphorus runoff into waterways. Phosphorus is a key fertilizer nutrient, but crops only use about 20% of what is applied in a season. The rest can pollute rivers and lakes. Biochar has been unpredictable in how it affects phosphorus availability. The new AI tool removes much of that guesswork, making biochar a more reliable option for sustainable farming and reducing fertilizer waste. The study was led by Yutao Peng at Sun Yat-Sen University and published in the journal Biochar. It marks progress toward practical, data-driven soil management that could lower agricultural emissions and improve water quality.