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Refining Infocrop Model for Drought Severities in Cotton

KrishiKosh

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Title Refining Infocrop Model for Drought Severities in Cotton
 
Creator Somashekhargouda Patil
 
Contributor B.C. Patil
 
Subject Crop Physiology
 
Description About 66 per cent of the cotton grown in India is rainfed, as a result there will
be water deficiency stress of varying level at one or other stages. Even in irrigated
condition, there will be water deficiency at some stages. In recent times, several
systems of integration of multiple factors to forecast the impact of certain agricultural
inputs/factors controlling growth on yield are available. This system is called
simulation model. INFOCROP model is a generic model that integrates variety, soil,
environmental and management practices. The present study aimed at refining this
model for moisture stress situation envisaged both analysis and use of historical data
(from 1996-2010) of cotton as well as weather data of Dharwad location apart from
experiments in field and rain out shelter during 2010-11. The historical rainfall data of
Dharwad showed bimodal distribution of rainfall, the peaks being observed during
July and October. In cotton as water deficit stress increases the yield decreases in
linear trend. The INFOCROP model overestimates the yield to an extent of 8.79
percent. The INFOCROP model simulated more number of days for phenological
observations viz., anthesis (80 days) and maturity (177 days). The simulated boll
weight is less than observed. Similarly INFOCROP model showed 16 percent more
leaf area index in irrigated and 5.6 percent in rainfed condition. The boll weight
deviated to an extent of 40 percent. During 2010-11 in the present study there was 16
percent decrease in yield in rainfed condition as compared to irrigated condition.
There was decrease in growth and yield parameters. Thus considering the overall
performance of the INFOCROP model, it predicts the yield to 91 percent of accuracy
and hence it can be used in the evaluation of inputs and factors controlling growth for
yield prediction in cotton.
 
Date 2016-11-12T14:16:45Z
2016-11-12T14:16:45Z
2011
 
Type Thesis
 
Identifier http://krishikosh.egranth.ac.in/handle/1/85253
 
Format application/pdf
 
Publisher UAS, Dharwad