The normalized difference vegetation index (NDVI) continues to provide easy and fast methodologiesto characterize wheat genetic resources in response to abiotic stresses. This study identifies ways tomaximize green leaf area duration during grain filling and develops NDVI models to predict physio-logical maturity and different stay −green parameters to increase grain yield of rainfed winter wheatunder terminal drought. Three wheat populations were evaluated: one containing 240 landraces fromAfghanistan, the second with 250 modern lines and varieties, tested for two years under low rainfall con-ditions in Turkey, and the third with 291 landraces from Central and Western Asia (grown for one yearin the same location). The onset of senescence, maximum “greenness”, rate of senescence and residual“greenness” at physiological maturity were estimated using sequential measurements of NDVI and haveshown significant correlations with grain yield under low rainfall rainfed conditions. Trade-offs wereidentified among the different stay −green attributes, e.g. delayed onset of senescence and high maxi-mum “greenness” resulted in accelerated rates of senescence and highest yields and were most evidentin the landrace populations. It is concluded, that the use of rate of senescence to select for stay −greenmust be coupled with other stay −green components, e.g. onset of senescence or maximum “greenness”to avoid the effects of the trade-offs on final grain yield. The NDVI decay curves (using the last three NDVImeasurements up to maturity) were used to estimate days to maturity using the NDVI decay during thesenescence period and days to heading. A training and testing set (20 and 80% of each population, respec-tively) were used for calibrations allowing for correlations between predicted and observed maturity ofup to r = +0.85 (P < 0.0001). This procedure will facilitate large −scale wheat phenotyping in the future.