Plant temperature stress detection with machine vision

Zhiwei Li; Peter P. Ling

doi:10.1117/12.262853

18 December 1996 Plant temperature stress detection with machine vision

Zhiwei Li, Peter P. Ling

Proceedings Volume 2907, Optics in Agriculture, Forestry, and Biological Processing II; (1996) https://doi.org/10.1117/12.262853
Event: Photonics East '96, 1996, Boston, MA, United States

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.

Citation Download Citation

Zhiwei Li and Peter P. Ling "Plant temperature stress detection with machine vision", Proc. SPIE 2907, Optics in Agriculture, Forestry, and Biological Processing II, (18 December 1996); https://doi.org/10.1117/12.262853

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