Dynamic Assessment of Air Temperature for Tomato (Lycopersicon esculentum Mill) Cultivation in a Naturally Ventilated Net-Screen Greenhouse under Tropical Lowlands Climate

Authors
R. Shamshiri 1, 2
P. van Beveren 3
H. Che Man 2
A. J. Zakaria 4
1 Department of Agricultural and Biological Engineering, University of Florida, Gainesville, FL 32611, USA.
2 Department of Biological and Agricultural Engineering, Universiti Putra Malaysia, Serdang, 43400, Malaysia.
3 Farm Technology Group, Wageningen University, P. O. Box: 16, NL-6700AH Wageningen, The Netherlands.
4 Institute AgroPolis, Universiti Sultan Zainal Abidin, Campus Tembila, Kuala Terengganu, Malaysia.
Abstract
Net-screen covered greenhouses operating on natural ventilation are used as a sustainable approach for closed-field cultivation of fruits and vegetables and to eliminate insect passage and the subsequent production damage. The objective of this work was to develop a real-time assessment framework for evaluating air-temperature inside an insect-proof net-screen greenhouse in tropical lowlands of Malaysia prior to cultivation of tomato. Mathematical description of a growth response model was implemented and used in a computer application. A custom-designed data acquisition system was built for collecting 6 months of air-temperature data, during July to December 2014. For each measured air-Temperature (T), an optimality degree, denoted by , was calculated with respect to different light conditions (sun, cloud, night) and different growth stages. Interactive three-dimensional plots were generated to demonstrate variations in values due to different hours and days in a growth season. Results showed that air temperature was never less than 25% optimal for early growth, and 51% for vegetative to mature fruiting stages. The average in the entire 6 months was between 65 and 75%. The presented framework allows tomato growers to automatically collect and process raw air temperature data and to simulate growth responses at different growth stages and light conditions. The software database can be used to track and record values from any greenhouse with different structure design, covering materials, cooling system, and growing seasons and to contribute to knowledge-based decision support systems and energy balance models.

Keywords

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Journal of Agricultural Science and Technology
Volume 19, Issue 1
January and February 2017
Pages 59-72