Effect of automated controlling system using raspberry-pi microprocessor on growth parameters of eggplant in greenhouse

Bilal Ahmad; Raees Ahmed; Muhammad Tahir Younas; Muhammad Saeed; Irfan Jamshed; Sohaib Masroor; Arshad Wahab; Umed Ali; Bilal Hayder; Muzaffar Subhani; Muhammad Abbas; Sohail Tariq; Basharat Mahmood

doi:10.34016/pjbt.2022.19.2.104

To bridge up the quality gaps and excel in the production of eggplant there is a need to switch the conventional production system to smart greenhouse house monitoring system. The study was designed to evaluate the growth parameters using smart greenhouse monitoring system designed with Raspberry-Pi microprocessor and sensors to control the microclimate (temperature and humidity) of a prototype greenhouse. A set of experiment was designed, one in a smart greenhouse system and the 2nd in the conventional greenhouse system to evaluate the growth parameters of eggplant. In a microclimate of smart greenhouse the temperature and humidity was set controlled using two sensors and automation system to control the mist spray and heating/cooling system inside the prototype greenhouse. Standard production technology was adopted in both the experiments and the experiment was replicated thrice. It was observed that the smart greenhouse monitoring system maintained the microclimate inside the prototype greenhouse ultimately effect the growth and yield parameters. The results predicted a progressive increase in growth parameter up to 10-20% in plant height, flowers per plant, fruits per plant and weight of fruit in automated greenhouse using microcontroller. Similarly quality of fruit was significantly affected as maximum fruit diameter 35 mm and fruit firmness 6.9 libre was recorded that was significantly higher than the fruit in the conventional greenhouse. The over average yield of eggplant per plant was recorded 5.6 kg/plant in automated greenhouse while 4 kg/plant fruit yield was recorded in conventional greenhouse that was significantly higher. The findings of current study predicted that the overall yield of eggplant was significantly higher and the growth and quality parameters were also higher in automated greenhouse using microcontroller and can be used for the potential eggplant production in urban agriculture.