Journal of the Indian Society of Remote Sensing

, Volume 34, Issue 3, pp 269–277 | Cite as

Pre-harvest wheat yield prediction using agromet-spectral-trend-yield models for hoshiarpur and rupnagar districts of punjab

  • S. Bazgeer
  • R. K. Mahey
  • P. K. Sharma
  • A. Sood
  • S. S. Sidhu


Wheat yield prediction using different agrometeorological indices, spectral index (NDVI, Normalized Difference Vegetation Index) and trend predicted yield (TPY) were developed in Hoshiarpur and Rupnagar districts of Punjab. On the basis of examination of Correlation Coefficients (R), Standard Error of Estimate (SEOE) and Relative Deviation (RD) values resulted from different agromet models, the best agromet subset were selected as Minimum Temperature (Tmin), Maximum Temperature (Tmax) and accumulated Heliothermal Units (HTU) in case of Hoshiarpur district and Minimum Temperature (T--min), accumulated Temperature Difference (TD) and accumulated Pan Evaporation (E) for Rupnagar district at reproductive stage (2nd week of March) of wheat. It was found that Agromet-Spectral-Trend-Yield model could explain 96 % (SEOE = 87 kg/ha) and 91 % (SEOE = 146 kg/ha) of wheat yield variations for Hoshiarpur and Rupnagar districts, respectively.


Normalize Difference Vegetation Index Spectral Index Vapour Pressure Deficit Wheat Yield Regional Research Station 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer 2006

Authors and Affiliations

  • S. Bazgeer
    • 1
  • R. K. Mahey
    • 1
  • P. K. Sharma
    • 2
  • A. Sood
    • 2
  • S. S. Sidhu
    • 3
  1. 1.Department of Agronomy and AgrometeorologyPunjab Agricultural UniversityLudhianaIndia
  2. 2.Punjab Remote Sensing CentreLudhianaIndia
  3. 3.Department of Math., Stat & PhysicsPunjab Agricultural UniversityLudhianaIndia

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