Statistical Modelling for Pre-Harvest Forecast:An Illustration with Rose

Authors

  • K S Shamasundaran Author
  • R Yenugopalan Author

DOI:

https://doi.org/10.24154/jhs.v1i1.680

Keywords:

Goodness of Fit Statistics, Statistical Modelling, Yield Forecast

Abstract

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

Agostid'no, R.B. and Stephens M.A.1986. Goodness of Fit Techniques. Marcel Dekker, New York 576p

Lewis-Beck, S. M.1993. Regression Analysis. Sage Publ., New York. 433p

Kvelseth,T.O 1985. Cautionary note about R^. The Amer. Stat., 39:279-85.

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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Published

30-06-2006

Issue

Section

Original Research Papers

How to Cite

Shamasundaran, K. S., & Yenugopalan, R. (2006). Statistical Modelling for Pre-Harvest Forecast:An Illustration with Rose. Journal of Horticultural Sciences, 1(1), 68-70. https://doi.org/10.24154/jhs.v1i1.680

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