
%0 Journal Article
%A Slafer, GA 
%A Rawson, HM 
%T Sensitivity of Wheat Phasic Development to Major Environmental Factors: a Re-Examination of Some Assumptions Made by Physiologists and Modellers
%J Functional Plant Biology
%D 1994/08/01
%V 21
%N 4
%P 393-426
%K 
%R https://doi.org/10.1071/PP9940393
%U https://www.publish.csiro.au/paper/PP9940393 
%X In this review we assess the universality of several assumptions that are commonly made about development in wheat. The assumptions tested are that:    (1) wheat is most sensitive to the environmental variables of temperature and photoperiod during the vegetative period;    (2) any responses to vernalisation and photoperiod are complete by the time that the apex has become reproductive and the stems begin to elongate;    (3) cultivars differ little in their responses to temperature aside from any responses to vernalisation;    (4) cultivar differences in 'intrinsic earliness' or 'basic development rate' are unaffected by temperature;    (5) photoperiod and vernalisation responses are quantitative and that these responses are well understood and can be generalised.     We show that, in terms of development, all wheats are responsive to temperature throughout their life cycles though to differing degrees, most are responsive to photoperiod at least until heading and, contrary to expectations, with potentially increasing sensitivity once the flowering process is triggered, and many are responsive to a memory of vernalising temperatures to well beyond the double ridge stage. In all these responses we show that there is considerable genotypic variation and that it is usually difficult to guess the responses of one genotype to the main environmental variables from the responses of another. This is partially because overall sensitivity to each of the main variables can differ, and the responses can be interactive, but also because the primary responses and interactions can differ between developmental phases. This can result in a high level of complexity of response whenever any variable is changed. The level of complexity is a negative feature when it comes to modelling and forecasting responses across widely differing environments but a highly positive feature when considering the enormous genotypic variation available for selection. 
