Comparison of Energy-use Efficiency for Lettuce Plantation under Nutrient Film Technique and Deep-Water Culture Hydroponic Systems

Syed Abreez Gillani, Rabiya Abbasi, Pablo Martinez Rodriguez, Rafiq Ahmad*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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Abstract

Energy conservation opportunities in closed plant production systems have been widely discussed, however, a comparison of energy-use efficiency (EUE) for different types of hydroponic systems is lacking. This paper compares the EUE of two different hydroponic systems, namely nutrient film technique (NFT) and deep-water culture (DWC), within an aquaponics facility. The energy is monitored in a controlled environment using artificial lighting and its impact on the growth dynamics of the crops is measured, in this case, on a leafy green crop (Lactuca Sativa L. ‘Little Gem’). Offering better efficiency and reliability, light-emitting diode (LED) irradiation is used with a photosynthetic photon flux (PPF) of 140 µmol·s−1 and a photoperiod of 12-hours. The seeds are then placed in growth chambers, kept at an ambient temperature of 18°C for 21 days. These seedlings are then transplanted in rockwool cubes, followed by placement in NFT or DWC systems in equal numbers. Both systems are illuminated with LED irradiation having a PPF of 200 µmol·s−1. Continuous irradiation with a photoperiod of 16-hours is provided to both systems for 5 weeks. Crop growth parameters, such as leaf count and plant height, are measured in both systems resulting in similar numbers obtained, however, shoot fresh weight, leaf area, and root length are significantly different. Furthermore, the NFT system exhibited an EUE of 31.3 g. kWh−1 and outperformed the DWC system with an EUE of 24.53 g. kWh−1; indicating higher growth and better energy savings associated with NFT systems. These results suggest that NFT systems has a higher potential to offer better energy-use efficiency for producing crops in plant factories and aquaponics facilities.
Original languageEnglish
Pages (from-to)11-19
Number of pages9
JournalProcedia Computer Science
Volume217
DOIs
Publication statusPublished - 13 Jan 2023
Event4th International Conference on Industry 4.0 and Smart Manufacturing - Upper Austria University of Applied Sciences - Hagenberg Campus, Linz, Austria
Duration: 2 Nov 20224 Nov 2022
https://www.msc-les.org/ism2022/

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