Design of a low-cost natural convection solar tunnel dryer to reduce postharvest losses of tomatoes, Maize and Mangoes

This study presents the design, development, and evaluation of a low-cost natural convection solar tunnel to reduce postharvest losses of tomatoes, maize, and mangoes under the local weather conditions of Abakaliki, southeastern Nigeria. The dryer consisted of key components, including a solar chimney, collector unit, drying unit, and absorber plate made from galvanized iron, covered with a 200 μm polythene sheet and glass to enhance solar radiation absorption and minimize heat loss. Fresh produce from the local market was dried in the solar dryer, with drying temperatures ranging from 25°C to 73°C over two to three days. The dryer's performance was tested during both wet and dry seasons, and key metrics such as solar radiation, temperature, air velocity, and relative humidity were measured. The results demonstrated a 30-50% reduction in drying time compared to traditional sun drying methods while maintaining product quality. The dryer performed better during dry seasons and peak solar radiation hours, and the drying process exhibited an exponential relationship between temperature and drying time. Additionally, solar drying affected the nutritional composition of the dried products, influencing antioxidant activity, flavor, and nutrient content. The solar tunnel dryer offers a promising solution for reducing postharvest losses and preserving the nutritional quality of fruits and vegetables in the region. This innovative technology can contribute to food security and sustainable agricultural practices in developing communities.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-11-30
DOI
https://doi.org/10.5281/zenodo.15093628
Primary Topic
Neural Networks and Applications
Type
article
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article

Design of a low-cost natural convection solar tunnel dryer to reduce postharvest losses of tomatoes, Maize and Mangoes

Zenodo (CERN European Organization for Nuclear Research)
Neural Networks and Applications
article

Design of a low-cost natural convection solar tunnel dryer to reduce postharvest losses of tomatoes, Maize and Mangoes

article en

Abstract

This study presents the design, development, and evaluation of a low-cost natural convection solar tunnel to reduce postharvest losses of tomatoes, maize, and mangoes under the local weather conditions of Abakaliki, southeastern Nigeria. The dryer consisted of key components, including a solar chimney, collector unit, drying unit, and absorber plate made from galvanized iron, covered with a 200 μm polythene sheet and glass to enhance solar radiation absorption and minimize heat loss. Fresh produce from the local market was dried in the solar dryer, with drying temperatures ranging from 25°C to 73°C over two to three days. The dryer's performance was tested during both wet and dry seasons, and key metrics such as solar radiation, temperature, air velocity, and relative humidity were measured. The results demonstrated a 30-50% reduction in drying time compared to traditional sun drying methods while maintaining product quality. The dryer performed better during dry seasons and peak solar radiation hours, and the drying process exhibited an exponential relationship between temperature and drying time. Additionally, solar drying affected the nutritional composition of the dried products, influencing antioxidant activity, flavor, and nutrient content. The solar tunnel dryer offers a promising solution for reducing postharvest losses and preserving the nutritional quality of fruits and vegetables in the region. This innovative technology can contribute to food security and sustainable agricultural practices in developing communities.

Zenodo (CERN European Organization for Nuclear Research)
Ebonyi State University (NG)
Zero hunger
Openalex Percentile: Top 61%
Neural Networks and Applications
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