Share Email Print
cover

Proceedings Paper

Plant temperature stress detection with machine vision
Author(s): Zhiwei Li; Peter P. Ling
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper 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.

Paper Details

Date Published: 18 December 1996
PDF: 9 pages
Proc. SPIE 2907, Optics in Agriculture, Forestry, and Biological Processing II, (18 December 1996); doi: 10.1117/12.262853
Show Author Affiliations
Zhiwei Li, Rutgers Univ. (United States)
Peter P. Ling, Rutgers Univ. (United States)


Published in SPIE Proceedings Vol. 2907:
Optics in Agriculture, Forestry, and Biological Processing II
George E. Meyer; James A. DeShazer, Editor(s)

© SPIE. Terms of Use
Back to Top