000 03284nab a22003737a 4500
001 58188
003 MX-TxCIM
005 20250211020917.0
008 160126s2016 ne |||p|op||| 00| 0 eng d
024 8 _ahttps://doi.org/10.1016/j.fcr.2016.06.021
040 _aMX-TxCIM
041 _aeng
100 1 _94069
_aMontazeaud, G.
245 1 0 _aPredicting wheat maturity and stay-green parameters by modeling spectral reflectance measurements and their contribution to grainyield under rainfed conditions
260 _aAmsterdam, Netherlands :
_bElsevier,
_c2016.
500 _aPeer review
520 _aThe normalized difference vegetation index (NDVI) continues to provide easy and fast methodologies to characterize wheat genetic resources in response to abiotic stresses. This study identifies ways to maximize green leaf area duration during grain filling and develops NDVI models to predict physiological maturity and different stay −green parameters to increase grain yield of rainfed winter wheat under terminal drought. Three wheat populations were evaluated: one containing 240 landraces from Afghanistan, the second with 250 modern lines and varieties, tested for two years under low rainfall conditions in Turkey, and the third with 291 landraces from Central and Western Asia (grown for one year in 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 have shown significant correlations with grain yield under low rainfall rainfed conditions. Trade-offs were identified among the different stay −green attributes, e.g. delayed onset of senescence and high maximum "greenness" resulted in accelerated rates of senescence and highest yields and were most evident in the landrace populations. It is concluded, that the use of rate of senescence to select for stay −green must 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 NDVI measurements up to maturity) were used to estimate days to maturity using the NDVI decay during the senescence period and days to heading. A training and testing set (20 and 80% of each population, respectively) were used for calibrations allowing for correlations between predicted and observed maturity of up to r = +0.85 (P < 0.0001). This procedure will facilitate large −scale wheat phenotyping in the future.
526 _aWC
_cFP2
546 _aText in English
650 7 _aWheat
_gAGROVOC
_2
_91310
650 0 _94070
_aSpectral analysis
651 0 _94026
_aAsia
700 1 _94071
_aKaratogma, H.
700 1 _94072
_aOzturk, I.
700 1 _94073
_aRoumet, P.
700 1 _94074
_aEcarnot, M.
700 1 _9637
_aOzer, E.
700 1 _9636
_aOzdemir, F.
700 1 _9865
_aLopes, M.S.
_gGlobal Wheat Program
_8INT2835
700 1 _aCrossa, J.
_gGenetic Resources Program
_8CCJL01
_959
773 0 _wu444314
_x0378-4290 (Print)
_dAmsterdam (Netherlands) : Elsevier
_tField Crops Research
_gv. 196, p. 191-198
856 4 _yAccess only for CIMMYT Staff
_uhttp://libcatalog.cimmyt.org/Download/cis/58188.pdf
942 _2ddc
_cJA
999 _c58188
_d58180