A Binocular Stereovision System for Transplant Growth Variables Analysis

Dong Xian He, Yuuho Matsuura, Toyoki Kozai, K. C. Ting

Research output: Contribution to journalArticlepeer-review

Abstract

Plug transplant production technology has been widely used in the plant production industry and is continuing to expand in scale. In order to achieve optimal control of the environment for a population of transplants growing in multi-cell plug trays, frequent measurement of the population's structural and functional properties is required. A binocular Stereovision system incorporating two digital cameras and two computers was developed, based on a pixel stereological algorithm, to analyze the aggregate growth variables of a plug tray of transplants. Three-dimensional (3-D) color images of the transplant population were reconstructed from pairs of digital two-dimensional (2-D) color images taken under a constant light environment. Sweet potato (Ipomoea batatas (L) Lam.) was used as a test plant. Average height, leaf area, projected leaf area, and mass volume of the transplant population were calculated at a pixel level by extracting four user-selected colors. Image analysis took 2 to 3 min for each transplant population measurement. The aggregate growth variables of the transplant population calculated from image analysis correlated closely with corresponding average height, leaf area, and fresh and dry masses determined from destructive measurements. The binocular Stereovision system using the pixel stereological algorithm successfully estimated the values of the transplant growth variables. This image analysis method has the potential to automatically provide necessary aggregate transplant physical properties for identifying growth responses to various environmental conditions. This technique will in turn lead to the selection of optimum environmental conditions for transplant growth.

Original languageEnglish (US)
Pages (from-to)611-617
Number of pages7
JournalApplied Engineering in Agriculture
Volume19
Issue number5
StatePublished - Sep 1 2003

Keywords

  • Image analysis
  • Pixel stereological algorithm
  • Sweet potato (Ipomoea batatas (L.) Lam.)
  • Transplant population

ASJC Scopus subject areas

  • Engineering(all)

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