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DEVELOPMENT OF STATISTICAL METHODOLOGY FOR ASSESSMENT OF LEAF AREA AND YIELD PREDICTION BASED ON GROWTH PARAMETERS IN FINGER MILLET

KrishiKosh

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Title DEVELOPMENT OF STATISTICAL METHODOLOGY FOR ASSESSMENT OF LEAF AREA AND YIELD PREDICTION BASED ON GROWTH PARAMETERS IN FINGER MILLET
 
Creator MANASA, B P
 
Contributor KRISHNAMURTHY, K N
 
Description Appropriate model for non-destructive estimation of leaf area in
finger millet is attempted in the present investigation. Primary data
pertaining to leaf area was measured particularly at ear head emergence
stage irrespective of 1-tiller, 2-tiller and 3-tiller/plant. The leaf area and
optimum position of leaf was determined by using relative leaf positions
(RLP’s). Further, attempt has been made to predict yield based on the
growth parameters through step-wise regression.
It was observed that number of leaves multiplied by relative leaf
position yielded the most optimum position of leaf contributing to a leaf
area irrespective of number of leaves. With respect to yield prediction,
during 40 DAS leaf area index, dry matter and leaf width were found to
be significant with an R2 of 91.4%, at ear head emergence stage, leaf area
index, crop growth rate, leaf area duration, relative growth rate, dry
matter and days to ear head emergence were found to be significant with
an R2 of 91.2% and at harvest stage, leaf area index, total dry matter,
harvest index and threshing percentage were found to be significant with
an R2 of 90.0%. This information intern will be useful in planning
resources, reducing cost and advance prediction of yield.
 
Date 2016-12-06T10:19:54Z
2016-12-06T10:19:54Z
2012-07-04
 
Type Thesis
 
Identifier TH-10283
http://krishikosh.egranth.ac.in/handle/1/89254
 
Language en
 
Format application/pdf
 
Publisher University of Agricultural Sciences GKVK, Bangalore