ID:
publications-5299
Type:
Conference paper
Year:
2022
Authors:
Fernandez K.C.T.; Baldovino R.G.; Billones R.K.C.
Title:
Digital Twinning to Predict Harvest Weight of Hydroponically Grown Romaine Lettuce
Venue/Journal:
2022 IEEE 14th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management, HNICEM 2022
DOI:
10.1109/HNICEM57413.2022.10109418
Research type:
Water System:
Technical Focus:
Abstract:
As the world population continues to grow, pressure to improve food harvests further increases. This study aims to produce a digital twin of romaine lettuce being grown in a passive, Kratky style hydroponic system to help increase food harvests. Inputs include water pH, nutrient composition and concentration, amount of light received by the plant, and ambient temperature. Data from various studies measuring the effects of these parameters on the growth of lettuce was collected, combined and factored into a digital model through the use of regression modelling in an attempt to predict the harvest weight of a head of lettuce at the end of a standard hydroponic growing period of 5-6 weeks. The model's ideal conditions were predicted to be the use of nutrient treatment 3, a 16-hour photoperiod, an ambient temperature of 26 degrees Celsius, a water temperature of 20 degrees Celsius, and a water pH of 5. The model's predicted harvest of 121 grams per plant which was 4.9% larger than the previous best observed in reference studies. The methodology used also has the advantage of producing equations that will allow producers to estimate harvests without the need for specialized software. It is hoped that the methods used in this study can further be improved and applied to other types of crops to increase yields. Β© 2022 IEEE.
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