Zonal trend-agrometeorological models for wheat yield estimation in Haryana
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Abstract
An attempt has been made to assess the impact of weather variables for district-level wheat yield estimation in Haryana. Fortnightly weather data and trend based yield were used for developing the zonal trendagrometeorological (agromet) models within the framework of multiple linear regression and discriminant function analyses. The district level wheat yield forecasts, percent deviations from the real time wheat yield (s) and root mean square error(s) at zonal level show a preference of using discriminant/weather scores as regressors in almost all the considered districts of the state. Zonal trend-agromet models provided considerable improvement in district-level wheat yield prediction moreover the yield estimates may be obtained 4-5 weeks in advance of the harvest time. The estimated yield(s) from the selected zonal models showed good agreement with State Department of Agriculture (DOA) wheat yields by showing less than 5 percent deviations in 9 districts and 6-11 percent deviations in the remaining 9 districts under consideration.
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Discriminant/weather score, DOA yield, Percent deviation, Root mean square error, Trend-agromet
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