title: An automated plant monitoring system using machine vision.
abstract: A plant growth chamber equipped with a machine vision (MV) system was developed for the continuous, non-contact sampling and near-real-time evaluation of the top projected leaf area (TPLA) of lettuce (Lactuca sativa, cv. Ostinata) seedlings. A rotary table enabled automatic, individual presentation of the lettuce plants to the imaging system. Hourly measurements were continuously made for 16 plants from the first true leaf stage through 30 days from seeding. A near-infrared radiation source illuminated the plants during the dark period, permitting measurements without interrupting the 12 hour photoperiod. Daily minimum hourly change of TPLA for the plants occurred from 3 to 4 hours after the start of the light period. Most rapid increase in TPLA occurred from 4 to 5 hours after the onset of the dark period. The machine vision system was capable of determining a plant physiological response to the nutrient stress within 24 hours of the change of the nutrient regime.
authors.affiliation: Department of Bioresource Engineering, Rutgers University, New Brunswick, New Jersey, USA.
authors.forename: G A
authors.initials: GA
authors.lastname: Giacomelli
authors.forename: P P
authors.initials: PP
authors.lastname: Ling
authors.forename: R E
authors.initials: RE
authors.lastname: Morden
mesh_terms: D018504:Ecological Systems, Closed; D004780:Environment, Controlled; D004784:Environmental Monitoring / Q000379:methods*; D005069:Evaluation Studies as Topic; D005103:Expert Systems; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D018545:Lactuca / Q000254:growth & development*; D008021:Life Support Systems / Q000295:instrumentation; D010781:Photography; D018515:Plant Leaves / Q000254:growth & development*; D018521:Plant Physiological Phenomena