Abstract
The objective of this work was to integrate a membership function growth response model for measuring optimality degrees of air temperature (T) and relative humidity (RH) in a tropical greenhouse planted with tomato (Lycopersicon esculentum). Experiment was carried out during spring growing season of 2015, for a total of 147days, in an insect-proof net-screen covered greenhouse in tropical lowlands of Malaysia. An analysis framework with a custom-designed hardware/software was developed for interfacing with the model and data processing. Raw data were separated into three groups of growth stages according to the original model, as early growth, vegetative growth, and flowering to mature fruiting growth stages. For each collected T and RH, an optimality degree denoted by Opt(T) and Opt(rH) with value between 0 and 1 was calculated. Preliminary results showed that maximum T and RH belong to the mature fruiting stage (39.7°C and 98.9%), and were recorded respectively at sun and cloud light conditions. The minimum and maximum values of Opt(T) were equal to 0.16 and 0.95 at the early growth stage, 0.42 and 0.92 at the vegetative stage, and 0.27 and 0.75 at the flowering to mature fruiting stage. These values for Opt(RH) were 0.62 and 1, 0.31 and 0.9, and 0.46 and 1, respectively. Further analysis of results showed that comparison between averaged optimality degrees in different light conditions (night, sun, cloud) depends on the specific growth stage. For example, during early growth stage, night hours had the highest Opt(T) and Opt(RH), while at the vegetative growth stage, Opt(T) did not vary significantly with light conditions. The presented framework contributes to knowledge-based information in greenhouse climate control and management by measuring optimality degrees for addressing specific hours, light conditions and growth stages associated with maximum and minimum cooling requirements.
Published Version
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