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Vegetos

Journal: Vegetos- An International Journal of Plant Research

Article DOI :10.5958/2229-4473.2016.00006.9
Year :2016, Volume : 29, Issue :1
First page : (22) Last page : (24)
Print ISSN : 0970-4078. Online ISSN : 2229-4473.


RESEARCH ARTICLE
A SOCIETY FOR PLANT RESEARCH PUBLICATION

Yield Forecasting Models based on Weather Parameters for Eastern U.P.

Pandey KK1,*, Maurya D2, Gupta G2, Mishra SV3

1Department of Agriculture Station, S K College of Agriculuture & Research Station, Kawardha, Chhattisgarh, India
2Department of Agriculture and Allied Sciences, Baba Farid Institute of Technology, Suddhowala, Dehradun, India
3Department of Agriculture Physics, Indian Agriculture Research Institute, New Delhi, India

*Corresponding author: Pandey KK, Department of Agriculture Stat., S K College of Agriculture & Research Station, Kawardha, Chhattisgarh, India, Tel: 07741233300; E-mail: kkpandeystat@gmail.com

In the present study, attempts have been made to development of pre harvest models for pre harvesting forecasting of rice yield at district level on the basis of generated weather variables. Weekly data (14 meteorological weeks) because Time of the pre harvest forecast is 14th week 2½ month before harvesting flowering stage and seven weather variables over a span of 20 years period (1995 to 2014) has been used along with the annual rice production data for respective year for eastern UP. The data of de-trend yield and generated weather variables for 18 years of has been used for generation of the models.
(1995–2012). Total five models were validated with 2 year independent data set (2013 and 2014). The (PPE) ranging-4.32 to 10.56% from the observed yield for all 5 models. Highest correlation has been found 0.68 between Z231 (Weighted interaction between MaxT and MinT). Significance of models are obtained by on the basis of highest R2 (86%) and by (P-value) (0.08). MBE (Mean Biased Error), RMSE (Root Mean Square Error) and PE (Percent Error) has been used for the Error analysis. On the basis of R2 and other parameter the model IV has been found best.




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