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Models for wheat yield prediction using remotely sensed canopy temperature based indices
Authors:S. K. Saha  Ajai
Affiliation:1. Indian Institute of Remote Sensing, NRSA, Dehra Dun
2. Space Applications Centre, ISRO, Ahmedabad
Abstract:Canopy temperature in differentially irrigated and fertilized wheat plots were collected by hand held infrared thermometer from seedling emergence to maturity for two growing seasons (1981–82 and 1982–83). Canopy temperature indices like stress degree day (SDD) and crop water stress index (CWSI) based four-parameter (crop growth stage partitioned) and two-parameter (Non-partitioned) yield models suitable for remote sensing application were developed and tested with observed yield data. From statistical analysis of the models it was concluded that crop growth stage partitioned CWSI or SDD yield model was better than non-partitioned SDD models for predicting wheat grain as well as biological yields.
Keywords:
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