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• This work estimates harvest index in wheat crops using a RS-based approach. • This paper analyses an extensive HI dataset obtained of commercial fields. • The model integrates series of satellite vegetation indices into crop growth models. • Additional analysis are the effect of water stress in the proposed models. • The results are promising for the operational estimation of wheat production. This paper presents an operational methodology for the estimation of the harvest index (HI) in commercial fields planted with wheat crops (Triticum aestivum L.) using a Remote Sensing based approach. The approach proposed variants from the methodologies reported by Kemanian et al., (2007) and Sadras and Connor (1991) for the estimation of the HI using the ratio between variables related with biomass production, i.e. absorbed photosynthetically active radiation (APAR), crop transpiration (T) and crop transpiration coefficient (K t) as defined in the FAO-66 manual. The estimation of these variables along the growing season integrates time series of Remote Sensing satellite images and meteorological data into the crop growth models. The proposed models for estimation of HI were calibrated using an extensive HI dataset obtained from 19 commercial fields (empirical data) planted with wheat. The fields were subject to different water and nutrient management, resulting in empirical HI values from 0.23 to 0.55. Future applications of the proposed approach are the operational estimation of wheat production at both regional and local scales and the estimation of the within-field variability of crop production considering the variability of HI values within the field. [ABSTRACT FROM AUTHOR]