An automated plant monitoring system using machine vision

G. A. Giacomelli, P. P. Ling, R. E. Morden

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)377-382
Number of pages6
JournalActa Horticulturae
Volume440
DOIs
StatePublished - Dec 1 1996

Keywords

  • Automation
  • Controlled environment
  • Lactuca sativa
  • Machine vision
  • Non-contact monitoring
  • Nutritional stress
  • Plant development
  • Stress detection

ASJC Scopus subject areas

  • Horticulture

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