Crop weather model for sustainable groundnut production under dry land condition
DOI:
https://doi.org/10.54386/jam.v12i2.1310Keywords:
SSH, AET, GDD, dry matter multiple linear regression, groundnutAbstract
A crop weather model to predict the growth and pod yield of groundnut based on the dry matter accumulation at each growth stages has been developed. The multiple linear regression equations relating to GDD, SSH and AET with the accumulated dry matter production during each growth stage and also the final pod yield of kharif crop were generated by using the field experimental data for the period of 2000-2008. The coefficient of determinants indicate that the climatic parameters and the initial TDM used to estimate the final TDM in each stage and could be able to predict an extent of 77 to 98 per cent (coefficients of determinants) in different growth stages. Comparison of the observed and the predicted yields indicates the close agreement between them in all the stages. Considering the observed TDM up to the first four stages and predicted the Total Dry Matter at the harvesting stage. The model has been validated for the year 2009, and there is a good agreement between the observed and the predicted crop yield. The favorable influence of AET at the beginning of peg initiation and peg formation stage, and higher GDD during pod formation and harvest stages were noticed. The increase in AET during pod filling stage did not favor to the pod yield.
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