Record Details

Field hyperspectral data analysis for discriminating spectral behavior of tea plantations under various management practices

IR@CSIR-IHBT

View Archive Info
 
 
Field Value
 
Title Field hyperspectral data analysis for discriminating spectral behavior of tea
plantations under various management practices
 
Creator Kumar, Amit
Manjunath, K.R.
-, Meenakshi
Bala, Renu
Sud, R K
Singh, R D
Panigrahy, Sushma
 
Subject Plant sciences
Natural Product Chemistry
 
Description The quality and yield of tea depends upon management of tea plantations, which takes into account the
factors like type, age of plantation, growth stage, pruning status, light conditions, and disease incidence.
Recognizing the importance of hyperspectral data in detecting minute spectral variations in vegetation,
the present study was conducted to explore applicability of such data in evaluating these factors. Also
stepwise discriminant analysis and principal component analysis were conducted to identify the appropriate
bands for accessing the above mentioned factors. The Green region followed by NIR region was
found as most appropriate best band for discriminating different types of tea plants, and the tea in sunlit
and shade condition. For discriminating age of plantation, growth stage of tea, and diseased and healthy
bush, Blue region was most appropriate. The Red and NIR regions were best bands to discriminate pruned
and unpruned tea. The study concluded that field hyperspectral data can be efficiently used to know the
plantation that need special care and may be an indicator of tea productivity. The spectral signature of
these characteristics of tea plantations may also be used to classify the hyperspectral satellite data to
derive these parameters at regional scale.
 
Date 2012
 
Type Article
PeerReviewed
 
Format application/pdf
 
Identifier http://ihbt.csircentral.net/1341/1/131_Field_hyperspectral.pdf
Kumar, Amit and Manjunath, K.R. and -, Meenakshi and Bala, Renu and Sud, R K and Singh, R D and Panigrahy, Sushma (2012) Field hyperspectral data analysis for discriminating spectral behavior of tea plantations under various management practices. International Journal of Applied Earth Observation and Geoinformation. pp. 1-8.
 
Relation http://ihbt.csircentral.net/1341/