Literature DB >> 19505929

Climate change and the flowering time of annual crops.

P Q Craufurd1, T R Wheeler.   

Abstract

Crop production is inherently sensitive to variability in climate. Temperature is a major determinant of the rate of plant development and, under climate change, warmer temperatures that shorten development stages of determinate crops will most probably reduce the yield of a given variety. Earlier crop flowering and maturity have been observed and documented in recent decades, and these are often associated with warmer (spring) temperatures. However, farm management practices have also changed and the attribution of observed changes in phenology to climate change per se is difficult. Increases in atmospheric [CO(2)] often advance the time of flowering by a few days, but measurements in FACE (free air CO(2) enrichment) field-based experiments suggest that elevated [CO(2)] has little or no effect on the rate of development other than small advances in development associated with a warmer canopy temperature. The rate of development (inverse of the duration from sowing to flowering) is largely determined by responses to temperature and photoperiod, and the effects of temperature and of photoperiod at optimum and suboptimum temperatures can be quantified and predicted. However, responses to temperature, and more particularly photoperiod, at supraoptimal temperature are not well understood. Analysis of a comprehensive data set of time to tassel initiation in maize (Zea mays) with a wide range of photoperiods above and below the optimum suggests that photoperiod modulates the negative effects of temperature above the optimum. A simulation analysis of the effects of prescribed increases in temperature (0-6 degrees C in +1 degree C steps) and temperature variability (0% and +50%) on days to tassel initiation showed that tassel initiation occurs later, and variability was increased, as the temperature exceeds the optimum in models both with and without photoperiod sensitivity. However, the inclusion of photoperiod sensitivity above the optimum temperature resulted in a higher apparent optimum temperature and less variability in the time of tassel initiation. Given the importance of changes in plant development for crop yield under climate change, the effects of photoperiod and temperature on development rates above the optimum temperature clearly merit further research, and some of the knowledge gaps are identified herein.

Entities:  

Mesh:

Year:  2009        PMID: 19505929     DOI: 10.1093/jxb/erp196

Source DB:  PubMed          Journal:  J Exp Bot        ISSN: 0022-0957            Impact factor:   6.992


  54 in total

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Journal:  J Exp Bot       Date:  2010-03-29       Impact factor: 6.992

2.  How do we improve crop production in a warming world?

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4.  Hallauer's Tusón: a decade of selection for tropical-to-temperate phenological adaptation in maize.

Authors:  J E C Teixeira; T Weldekidan; N de Leon; S Flint-Garcia; J B Holland; N Lauter; S C Murray; W Xu; D A Hessel; A E Kleintop; J A Hawk; A Hallauer; R J Wisser
Journal:  Heredity (Edinb)       Date:  2014-11-05       Impact factor: 3.821

5.  Interactions between rising CO2 and temperature drive accelerated flowering in model plants under changing conditions of the last century.

Authors:  S Michael Walker; Joy K Ward
Journal:  Oecologia       Date:  2018-06-28       Impact factor: 3.225

6.  Altitudinal and climatic adaptation is mediated by flowering traits and FRI, FLC, and PHYC genes in Arabidopsis.

Authors:  Belén Méndez-Vigo; F Xavier Picó; Mercedes Ramiro; José M Martínez-Zapater; Carlos Alonso-Blanco
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7.  Synchronization of photoperiod and temperature signals during plant thermomorphogenesis.

Authors:  Young-Joon Park; June-Hee Lee; Jae Young Kim; Chung-Mo Park
Journal:  Plant Signal Behav       Date:  2020-03-12

8.  Improving ecophysiological simulation models to predict the impact of elevated atmospheric CO(2) concentration on crop productivity.

Authors:  Xinyou Yin
Journal:  Ann Bot       Date:  2013-02-06       Impact factor: 4.357

9.  Supermodels: sorghum and maize provide mutual insight into the genetics of flowering time.

Authors:  E S Mace; C H Hunt; D R Jordan
Journal:  Theor Appl Genet       Date:  2013-03-05       Impact factor: 5.699

10.  Simulating adaptation strategies to offset potential impacts of climate variability and change on maize yields in Embu County, Kenya.

Authors:  Sridhar Gummadi; M D M Kadiyala; K P C Rao; Ioannis Athanasiadis; Richard Mulwa; Mary Kilavi; Gizachew Legesse; Tilahun Amede
Journal:  PLoS One       Date:  2020-11-05       Impact factor: 3.240

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