The main challenge facing greenhouse designers is to achieve environment-appropriate greenhouses, especially in tropical regions. The excess radiant energy transmitted into the greenhouse predisposes plants to photo-inhibition and consequently reduces crop production. Lately, photovoltaic (PV) modules are equipped as a greenhouse rooftop to minimize the level of irradiation and air temperature in the greenhouse, simultaneously improving its energy consumption. Nevertheless, due to the low level of irradiation, denser conventional PV internal shading would influence the cultivated crops’ growth. Thus, Dye Sensitized Solar Cell (DSSC) possesses several attractive features such as transparent, sensitive to low light levels, and various color options that render DSSC a perfect choice able to serve substantially in energy buildings. This study assessed the microclimate conditions inside the greenhouse with semi-transparent DSSC mounted on top of it, describing the Photosynthetic Photon Flux Density (PPFD) (µmol m⁻² s⁻¹), Vapor Pressure Deficit VPD (kPa), relative humidity (%), and also temperature (°C). The Overall Thermal Transfer Value (OTTV), which indicates the average thermal energy transmission rate across the external layer of a structure envelope, is also presented. The effects of colored DSSC in altering the spectral of sunlight in reference to the Orthosiphon stamineus growth responses were determined. The information of the condition of DSSC greenhouse microclimate helps to identify the information for designing PV greenhouses and to produce income from both electric power and agronomic activity.

The global palm oil industry is targeting an increased oil extraction rate in oil palm milling to meet global demand. This can be achieved through the certification of mills and adherence to bunch grading as part of ensuring that only high-quality and ripe fresh fruit bunches are accepted and processed at all mills. However, the current grading process requires the analysis of oil palm bunches, which is laborious and tedious or prone to error due to human subjectivity. This paper introduces a non-destructive technique to predict the moisture and oil content in oil palm fruitlets using electrical impedance spectroscopy. In total, 90 samples of oil palm fruitlets at different stages of ripeness were acquired. Electrical impedance measurement of each fruitlet was done using electrocardiogram (ECG) electrodes connected to an LCR meter at frequencies of 1 kHz, 10 kHz, 20 kHz, and 100 kHz. The actual oil content in the fruitlets was determined using the Soxhlet extraction method, while the actual moisture content was determined using a standard oven-drying method. The variation of electrical impedance values at each frequency was analyzed. At 100 kHz, the correlation coefficients relating the electrical impedance to the moisture and oil content were around −0.84 and 0.80, respectively. Predictions of the moisture and oil content using linear regression of the impedance measurements at 100 kHz gave RMSE values of 5.85% and 5.71%, respectively. This information is useful for oil palm fruit grading and oil yield production estimation in the palm oil industry.

The confined heat created by the sunlight and ambient temperature is one of the obstacles to greenhouses in the tropics. A conservatory in tropical regions thus requires a proper ventilation and cooling system to provide an ideal greenhouse temperature to support crop production. The main objective of this study is to develop a Decision Support System (DSS) for optimum greenhouse ventilation and cooling control. An equation model to predict the temperature inside was developed by considering heat generation and heat loss inside the greenhouse. The accuracy of the equation model was validated with secondary data from the on-field greenhouse by statistical evaluation metrics. The statistical evaluation proved that the equation model is good with 2.11°C of Root Mean Square Error (RMSE), 6.22% of Percent BIAS (PBIAS) and 0.94 of Nash-Sutcliffe efficiency (NSE) value. A DSS using Microsoft Excel with Visual Basic for Applications (VBA) is developed based on the equation model to provide the ventilation and cooling system information. Input required for the DSS is a climatic condition, dimension and covering greenhouse material. The output of the DSS is the temperature inside the greenhouse, natural ventilation design, forced ventilation, active cooling system design using an evaporative pad and fan, and fogging system. The DSS can be used as an approach for ventilation and cooling design recommendation for the optimum temperature inside the greenhouse.