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Sensing tree for yield forecasting under different irrigation.

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Title Sensing tree for yield forecasting under different irrigation.
Not Available
 
Creator Panigrahi, P., Raman, K.V. and Sharma, R.K.
 
Subject tree sensing; water stress; yield forecasting; principal component analysis
 
Description Not Available
Tree itself is assumed to be a better indicator of water stress. Sensing of plant behavior in relation
to leaf physiology, plant water status and canopy reflectance are the major factors indicating the water need of
the trees. In this study, different response factors (leaf physiological parameters, leaf nutrients, leaf water
content and canopy reflectance) of citrus tree have been observed under differential water stress condition by
supplying deficit irrigation and fruit yield has been forecasted based on these factors. For the first year a yield
response model has been formulated employing principal component regression (PCR) methodology and the
model has been validated for second year data. Among different factors, leaf-N, leaf-K, stem water potential
stress index, stomatal conductance and water band index have been found as the best predictors for yield and
resulted higher accuracy ( ) in yield prediction of citrus tree. Overall, the study reveals that sensing tree is one
of the better options to quantify water stress for efficient irrigation scheduling and to get target yield from
orchards.
Not Available
 
Date 2018-12-01T08:57:24Z
2018-12-01T08:57:24Z
2014-12
 
Type Research Paper
 
Identifier Panigrahi, P., Raman, K.V. and Sharma, R.K. 2014. Sensing tree for yield forecasting under different irrigation. International Journal of Agriculture and Forestry 11 (2): 23–30
2394-5915
http://krishi.icar.gov.in/jspui/handle/123456789/14881
 
Language English
 
Relation Not Available;
 
Publisher sryahwa publication