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International Journal of Current Microbiology and Applied Sciences (IJCMAS)
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Original Research Articles                      Volume : 8, Issue:11, November, 2019

PRINT ISSN : 2319-7692
Online ISSN : 2319-7706
Issues : 12 per year
Publisher : Excellent Publishers
Email : editorijcmas@gmail.com /
submit@ijcmas.com
Editor-in-chief: Dr.M.Prakash
Index Copernicus ICV 2018: 95.39
NAAS RATING 2020: 5.38

Int.J.Curr.Microbiol.App.Sci.2019.8(11): 606-612
DOI: https://doi.org/10.20546/ijcmas.2019.811.074


Correlation Studies and Predictive Models of Kharif Greengram based on Agroclimatic Indices
Mangshatabam Annie1*, Bondita Goswami1, Pranjal Dutta1, Ramani Kanta Thakuria2 and Kakali Konwar2
1Department of Agrometeorology, Assam Agricultural University, Jorhat-785013, Assam, India
2Department of Agronomy, Assam Agricultural University, Jorhat-785013, Assam, India
*Corresponding author
Abstract:

A detailed study on greengram was carried out with treatments comprised of three different micro-climatic environments i.e. MR-I: (25thAug), MR-II: (10th Sep) and MR-III: (25th Sep) with three varieties viz., SG-16, SG-20 and IPBM-02-3. The results obtained from the experiment revealed that total accumulated agroclimatic indices showed a gradual decrease in the three successive micro-climatic regimes irrespective of varieties. The correlation study was carried out between weather variables prevailed during vegetative to maturity stages of different varieties under different microclimatic regimes. Most of the agro-climatic indices and meteorological parameters yielded higher correlation coefficients with final yield irrespective of varieties and microclimatic regimes for all growth stages. Highest correlation coefficient among accumulated indices was found in accumulated rainfall, ADRF (0.952) corresponding to vegetative stages. While the lowest correlation coefficient was obtained in accumulated bright sunshine hours, ABSH (-0.914) corresponding to reproductive stages. A few predictive models involving both accumulated indices and mean parameters were also developed combined over both varieties and microclimatic regimes corresponding to different crop growth stages. The most efficient model was found for the accumulated rainfall (ADRF), accumulated bright sunshine hours (ABSH) and accumulated growing degree days (AGDD) corresponding to vegetative, reproductive and maturity stage respectively. Lower per cent variations (PCV) were indicative of the fact that the predicted models are very effective under agro-climatic conditions of Jorhat.


Keywords: Greengram, Correlation, ADRF, ABSH, AGDD

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How to cite this article:

Mangshatabam Annie, Bondita Goswami, Pranjal Dutta, Ramani Kanta Thakuria and Kakali Konwar. 2019. Correlation Studies and Predictive Models of Kharif Greengram based on Agroclimatic Indices.Int.J.Curr.Microbiol.App.Sci. 8(11): 606-612. doi: https://doi.org/10.20546/ijcmas.2019.811.074
Copyright: This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike license.

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