Using solar drying and math models to reduce banana waste and save energy

What is it about?

Bananas spoil quickly after harvest, leading to significant food waste. One way to preserve them is by drying, which reduces moisture and extends shelf life. In this study, we tested how banana slices dry in a solar dryer and compared the results with computer models. By running simulations in MATLAB, we identified the most reliable models that can predict how fast bananas lose moisture during drying. This helps in designing better dryers, saving energy, and reducing waste. In simple terms, the study shows how mathematics and solar technology can work together to make food preservation more efficient and sustainable.

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Photo by Wolfgang Weiser on Unsplash

Photo by Wolfgang Weiser on Unsplash

Why is it important?

This work is important because it addresses the global challenge of food waste—nearly one-third of harvested crops are lost before reaching consumers. Drying is a proven preservation method, but its efficiency depends on how well the process is controlled. Traditional sun drying is inconsistent, while fossil-fuel-based dryers consume high energy. By combining solar energy with predictive mathematical models, this research provides a sustainable and cost-effective way to preserve bananas and similar crops. The findings are timely, as they support energy-efficient food processing methods and help in designing dryers that reduce energy costs while retaining nutrients. The Page model and Approximation Diffusion model identified here can serve as reliable tools for predicting drying behavior, guiding engineers and food technologists in building better drying systems.

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