000			00595nab|a22002177a|4500
999			_c62269 _d62261
001			62269
003			MX-TxCIM
005			20200717223904.0
008			200712s2017||||ne |||p|op||||00||0|eng|d
022			_a0378-4290
024	8		_ahttps://doi.org/10.1016/j.fcr.2015.12.011
040			_aMX-TxCIM
041			_aeng
100	1		_aNuttall, J.G. _914681
245	1	0	_aModels of grain quality in wheat—A review
260			_aAmsterdam (Netherlands) : _bElsevier, _c2017.
500			_aPeer review
500			_aOpen Access
520			_aMaintaining grain quality of wheat under climate change is critical for human nutrition, end-use functional properties, as well as commodity value. This paper reviews the current knowledge of high temperature and elevated atmospheric CO2 on whole-grain and functional properties of wheat. It also considers the utility of contemporary crop models for investigating the impacts of climate change on wheat quality; and discusses opportunities for advancing model capability. Under elevated CO2 wheat yield can increase by up to 36%, but universally grain protein concentration decreases and a shift in composition translates to reduced functional properties. High temperature during the post-anthesis period of crops can cause a step change reduction in grain-set, grain size and milling yield. Numerous crop models including APSIM-Nwheat, CropSyst, Sirius, GLAM-HTS account for high CO2 effects through modification of RUE, TE or critical leaf-N concentration and high temperature by accelerated leaf senescence, grain number, potential grain weight or HI modifications. For grain quality, however, crop models are typically restricted to predicting average grain size and grain-N content (concentration), although the SiriusQuality model accounts for the major storage proteins, gliadin and glutenin. For protein composition, high temperature stress reduces the glutenin/gliadin ratio and limits the synthesis of the larger SDS-insoluble glutenin polymers which causes wheat dough to have weaker viscoelasticity properties. This link provides an opportunity to model high temperature effects on grain functional properties. Further development and testing, utilizing grain quality data from global FACE programmes will be particularly valuable for validating and enhancing the performance of such models. For whole-grain characteristics, a single-spike model approach, which accounts for intra-spike variation in assimilate deposition may provide an opportunity to predict grain size distribution and associated screenings percentage and milling yield. Taken together expanding the predictive capability of our crop models to grain quality is an important step in providing a powerful tool for developing adaptation strategies for combating the impacts of climate change to global crop production and grain quality.
546			_aText in English
650		7	_2AGROVOC _92569 _aSimulation models
650		7	_2AGROVOC _91224 _aProteins
650		7	_2AGROVOC _91137 _aGlutenins
650		7	_2AGROVOC _99085 _aGliadin
650		7	_2AGROVOC _91971 _aHeat stress
650		7	_2AGROVOC _91045 _aClimate change
700	1		_aO’Leary, G.J. _91779
700	1		_aPanozzo, J.F. _9639
700	1		_aWalker, C.K. _914682
700	1		_aBarlow, K.B. _914683
700	1		_aFitzgerald, G. _95074
773	0		_dAmsterdam (Netherlands) : Elsevier, 2017. _gv. 202, p. 136-145 _tField Crops Research _x0378-4290 _wu444314
856	4		_uhttps://doi.org/10.1016/j.fcr.2015.12.011 _yClick here to access online
942			_cJA _n0 _2ddc