REMOTE SENSING OF PLANT PHYSIOLOGICAL PARAMETERS 
By 
D.S.KAMAT AND AJAI 
Space Applications Centre, Ahmedabad 380 053 
India 
S.K,Sinha, G.S.Chaturvedi  anà A.K.Singh 
Water Technology Centre, Indian 
Agricultural Research Institute 
New Delhi 110 012, India 
ABSTRACT 
Two band data were collected with a ground based radio- 
meter for wheat crop under different water conditions throughout 
the growing season, The spectral data viz. reflectance in red and 
infrared region and the derived parameters such as ratio and the 
ratio of their normalized difference were used to monitor growth 
and development, The spectral data were correlated with the plant 
physiological parameters viz. leaf area index, chlrophyll content 
and dry biomass, Significant correlation was found to exist 
between spectral and the physiological parameters. 
1. INTRODUCTION 
Remotely sensed spectral radiance data have been used to 
temporally monitor vegetative conditions for several types of crop 
covers, It has been reported that linear combinations of red and 
photographic infrared spectral data were significantly correlated 
with the green or photosynthetically active portions of plant 
canopies for variety of cover types (e.g. Jordon 1969, Colwell 
et al 1977, Tucker 1979). 
Growth and development of crop plants are represented by 
the temporal variation of its physiological parameters, Stress in 
plants restrict its growth and development as it affects either 
plant's physiological parameters viz, green leaf area index 
chlorophyll density and biomass. The green leaf or photosyntheti- 
cally active biomass is a dynamic biotic entity, which responds 
rapidly, to abiotic and or biotic influences; it in effect inte- 
grates the various conditions affecting plant growth and develop- 
ment, Many conditions, such as water stress, fertilizer stress 
and salt stress, which adversely affect plant growth and develop- 
ment results in a reduction in the phytomass. Because the phyto- 
mass or green leaf area is one of the basic system variables in 
primary production, monitoring this system variable throughout the 
growing season should enable to make inferences regarding total 
dry matter accumulation and grain yield. 
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