18 December 1996 Plant temperature stress detection with machine vision
Author Affiliations +
Abstract
Spectral and morphological features were used to detect temperature induced stress on tomato plants. Top projected canopy area (TPCA) and profile were selected as morphological features and the reflectance of plant under side canopy (USC) and its average gray level were chosen as spectral features. Temperature regimes (day/night, 18/6 hours) 24/21 degrees Celsius, 21/18 degrees Celsius, and 19.5/16.5 degrees Celsius were used. Both spectral and morphological features were capable of detecting temperature stresses. Reflectance and gray level of plant USC correlated with average environment temperatures. The stress was detected after one week from occurrence based on both morphological and spectral features. However, stress was detected more clearly based on spectral features.
© (1996) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Zhiwei Li, Peter P. Ling, "Plant temperature stress detection with machine vision", Proc. SPIE 2907, Optics in Agriculture, Forestry, and Biological Processing II, (18 December 1996); doi: 10.1117/12.262853; https://doi.org/10.1117/12.262853
PROCEEDINGS
9 PAGES


SHARE
RELATED CONTENT

Three-dimensional gauging with stereo computer vision
Proceedings of SPIE (September 01 1991)
Color reproduction in computer vision
Proceedings of SPIE (November 03 2005)
Machine vision applications in power plant inspection
Proceedings of SPIE (March 11 1994)
Vision methods for inspection of greenhouse poinsettia plants
Proceedings of SPIE (February 01 1991)

Back to Top