Automated plant growth monitoring system using machine vision

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

Research output: Contribution to journalConference articlepeer-review

Abstract

A noncontact plant-monitoring system for measuring the top projected canopy area (TPCA) of lettuce plants (cv. `Ostinata') was developed using machine vision. It makes automatic hourly measurements of the plants and is capable of detecting the effect of nutrient stress only 17 hours after application, based on the average 24-hour change in TPC. The combined growth and motion of the plants is detectable directly from the hourly measurements. The natural cycles of both growth and motion of the plant are synchronized to the light/dark cycles; thus a sliding 24-hour early in TPCA was selected as the test for detecting stress. Furthermore the plant grows very slowly during the early light period and grows at its peak rate during the early night period. A measurement interval shorter than 24 hours would require a more detailed analysis due to the variable growth rates. This noncontact sensing system is capable of detecting nutrient stress in 17 hours while tracking the hourly performance of the lettuce plants, thus providing further understanding of plant growth and motion.

Original languageEnglish (US)
JournalPaper - American Society of Agricultural Engineers
Volume3
StatePublished - Dec 1 1997
Externally publishedYes
EventProceedings of the 1997 ASAE Annual International Meeting. Part 1 (of 3) - Minneapolis, MN, USA
Duration: Aug 10 1997Aug 14 1997

ASJC Scopus subject areas

  • Agricultural and Biological Sciences (miscellaneous)

Fingerprint Dive into the research topics of 'Automated plant growth monitoring system using machine vision'. Together they form a unique fingerprint.

Cite this