2018 ASHS Annual Conference
Remote Detection of Growth Dynamics in Red Lettuce
Remote Detection of Growth Dynamics in Red Lettuce
Thursday, August 2, 2018
International Ballroom East/Center (Washington Hilton)
Chlorophyll fluorescence (ChlF) is used as a tool to measure photochemical efficiency, health status, stress and photosynthesis in plants. Remote tracking of the overall health and growth status of plants by ChlF detection can reduce energy requirements for growers by allowing light output to be synchronized with plant needs. However, current ChlF measurement systems are expensive, labor intensive, and invasive, making them impractical for use in controlled environment agriculture (CEA). Here, real time growth dynamics of red lettuce was monitored using a new, custom-made, cost effective and simple to operate ChlF detector. The device remotely measures canopy ChlF in the light-adapted state immediately after an excitation pulse from a blue (470 nm) LED excitation light. The LESA detector requires no physical contact with plants and automated ChlF measurements are taken at user-defined intervals throughout the growth period and stored in a cloud database for easy manual or automated access and analysis. The ChlF system successfully provided automated, real time tracking of growth dynamics in red lettuce over a 17-day period with no observed effect on plant growth. The rate of change in the ChlF signal was closely correlated with changes in biomass and plant area in the growing plants. Polynomial regression modeling from observed values enabled biomass and plant area to be estimated from observed ChlF. Relative growth rate (RGR) and leaf area ratio (LAR) calculated from these estimates were within 10% of those calculated from observed values, demonstrating that ChlF measured by this device can serve as a reasonably-accurate proxy for physical growth dynamics in red lettuce. To our knowledge, the chlorophyll fluorescence detection system described here is the first device of its kind designed for the purpose of remotely monitoring crop health and growth dynamics in real time.