Statistical Modelling for Pre-Harvest Forecast:An Illustration with Rose
DOI:
https://doi.org/10.24154/jhs.v1i1.680Keywords:
Goodness of Fit Statistics, Statistical Modelling, Yield ForecastAbstract
Crop yield forecast plays a vital role in arriving at pre-harvest yield estimate of a standing crop and to identify the stage at which reliable forecasting could be made before final harvest. In this paper, an attempt has been made to apply the regression technique for prediction of yield in rose. Rose, is an important flower crop not only for internal market but is also intended for export, and since it shrivels, estimation of yield of a standing crop before its actual harvest is essential. Based on results a model was developed, which showed that information from the first two pickings of a standing crop could be used to forecast rose yield to an extent of 77% two months before final harvest. It is also suggested to have a minimum sample size of 20 % to develop such a forecast model.
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References
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Shamasundaran, K. S. and.Singh, K. R 2003. Yield forecasting in tuberose (Polyanthes tuberosa Linn.) as effected by association of various characters. J. Om. Hort., 6:372-75.
Shamasundaran, K. S. Venugopalan, R and Singh, K. R 2003. Optimum sample size for yield estimation in certain commercial crops. J. Orn. Hart., 6:2AA-A1
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Copyright (c) 2006 K S Shamasundaran, R Yenugopalan (Author)
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