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Data on the no-load performance analysis of a tomato postharvest storage system
Orhewere B Ayomide1, Oluseyi O Ajayi1, Solomon O Banjo1
1Mechanical Engineering Department, Covenant University, P.M.B. 1023 Ota, Nigeria.
Data in Brief
|July 21, 2017
Summary
This study presents heat transfer data for tomato postharvest storage systems. It details how humidity affects temperature distribution and provides data for performance analysis.
Area of Science:
- Agricultural Engineering
- Food Science
- Thermodynamics
Background:
- Effective postharvest storage is crucial for maintaining tomato quality and reducing spoilage.
- Understanding heat transfer dynamics within storage systems is essential for optimizing environmental conditions.
- Previous research has not fully detailed empirical data on heat transfer in tomato storage, especially concerning humidity's role.
Purpose of the Study:
- To present original, detailed empirical data on heat transfer in a tomato postharvest storage system.
- To investigate the effect of humidity on temperature distribution within the storage system.
- To acquire data on external cooling component temperatures for performance analysis.
Main Methods:
- Conducted 96-hour no-load tests on a tomato postharvest storage system.
- Acquired heat distribution data at top, middle, and bottom locations every 30 minutes.
- Performed tests with and without introduced humidity to assess its impact on temperature.
- Recorded temperatures of external mechanical cooling components.
Main Results:
- Detailed empirical data on heat transfer within the tomato storage system was collected.
- Temperature distribution at various system locations (top, middle, bottom) was mapped over time.
- The influence of increased humidity levels on internal temperature distribution was quantified.
- Data on external cooling component temperatures were obtained, relevant for performance evaluation.
Conclusions:
- The study provides a comprehensive dataset on heat transfer in tomato postharvest storage.
- Humidity significantly impacts temperature distribution, a critical factor for effective storage.
- The acquired data can inform the design and performance analysis of similar storage systems.
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