Genomic regions for canopy temperature and their genetic association with stomatal conductance and grain yield in wheat.

Stomata are the site of CO2 exchange for water in a leaf. Variation in stomatal control offers promise in genetic improvement of transpiration and photosynthetic rates to improve wheat performance. However, techniques for estimating stomatal conductance (SC) are slow, limiting potential for efficient measurement and genetic modification of this trait. Genotypic variation in canopy temperature (CT) and leaf porosity (LP), as surrogates for SC, were assessed in three wheat mapping populations grown under well-watered conditions. The range and resulting genetic variance were large but not always repeatable across days and years for CT and LP alike. Leaf-to-leaf variation was large for LP, reducing heritability to near zero on a single-leaf basis. Replication across dates and years increased line-mean heritability to ~75% for both CT and LP. Across sampling dates and populations, CT showed a large, additive genetic correlation with LP (rg=-0.67 to -0.83) as expected. Genetic increases in pre-flowering CT were associated with reduced final plant height and both increased harvest index and grain yield but were uncorrelated with aerial biomass. In contrast, post-flowering, cooler canopies were associated with greater aerial biomass and increased grain number and yield. A multi-environment QTL analysis identified up to 16 and 15 genomic regions for CT and LP, respectively, across all three populations. Several of the LP and CT QTL co-located with known QTL for plant height and phenological development and intervals for many of the CT and LP quantitative trait loci (QTL) overlapped, supporting a common genetic basis for the two traits. Notably, both Rht-B1b and Rht-D1b dwarfing alleles were paradoxically positive for LP and CT (i.e. semi-dwarfs had higher stomatal conductance but warmer canopies) highlighting the issue of translation from leaf to canopy in screening for greater transpiration. The strong requirement for repeated assessment of SC suggests the more rapid CT assessment may be of greater value for indirect screening of high or low SC among large numbers of early-generation breeding lines. However, account must be taken of variation in development and canopy architecture when interpreting performance and selecting breeding lines on the basis of CT.

[1]  S. Chapman,et al.  Evaluation of CIMMYT conventional and synthetic spring wheat germplasm in rainfed sub-tropical environments. II. Grain yield components and physiological traits , 2011 .

[2]  Victor O. Sadras,et al.  Genetic gain in yield and associated changes in phenotype, trait plasticity and competitive ability of South Australian wheat varieties released between 1958 and 2007 , 2011 .

[3]  S. Chapman,et al.  Heat and drought adaptive QTL in a wheat population designed to minimize confounding agronomic effects , 2010, Theoretical and Applied Genetics.

[4]  R. Richards,et al.  Breeding for improved water productivity in temperate cereals: phenotyping, quantitative trait loci, markers and the selection environment , 2010 .

[5]  M. Reynolds,et al.  Partitioning of assimilates to deeper roots is associated with cooler canopies and increased yield under drought in wheat , 2010 .

[6]  Toshiyuki Takai,et al.  Canopy temperature on clear and cloudy days can be used to estimate varietal differences in stomatal conductance in rice , 2010 .

[7]  H. Jones,et al.  Thermal infrared imaging of crop canopies for the remote diagnosis and quantification of plant responses to water stress in the field. , 2009, Functional plant biology : FPB.

[8]  Jose Crossa,et al.  Gene action of canopy temperature in bread wheat under diverse environments , 2009, Theoretical and Applied Genetics.

[9]  R. Richards,et al.  Quantitative trait loci for water-soluble carbohydrates and associations with agronomic traits in wheat , 2008 .

[10]  R. Richards,et al.  Quantitative trait loci for carbon isotope discrimination are repeatable across environments and wheat mapping populations , 2008, Theoretical and Applied Genetics.

[11]  E. Stahl,et al.  Genetic variation in Arabidopsis thaliana for night-time leaf conductance. , 2008, Plant, cell & environment.

[12]  R. Motzo,et al.  Has long-term selection for yield in durum wheat also induced changes in leaf and canopy traits? , 2008 .

[13]  M. Sorrells,et al.  Drought - inducible genes and differentially expressed sequence tags associated with components of drought tolerance in durum wheat , 2008 .

[14]  A. Condon,et al.  Evaluating potential genetic gains in wheat associated with stress-adaptive trait expression in elite genetic resources under drought and heat stress , 2007 .

[15]  Steven R. Evett,et al.  Canopy Temperature Depression Sampling to Assess Grain Yield and Genotypic Differentiation in Winter Wheat , 2007 .

[16]  Matthew P. Reynolds,et al.  Drought-adaptive attributes in the Seri/Babax hexaploid wheat population. , 2007, Functional plant biology : FPB.

[17]  J. Finnigan,et al.  A simple unified theory for flow in the canopy and roughness sublayer , 2007 .

[18]  R. A. Fischer,et al.  PAPER PRESENTED AT INTERNATIONAL WORKSHOP ON INCREASING WHEAT YIELD POTENTIAL, CIMMYT, OBREGON, MEXICO, 20–24 MARCH 2006 Understanding the physiological basis of yield potential in wheat , 2007, The Journal of Agricultural Science.

[19]  H. T. Buck,et al.  Wheat production in stressed environments , 2007 .

[20]  J. Kirkegaard,et al.  Seasonal variation in the value of subsoil water to wheat: simulation studies in southern New South Wales , 2007 .

[21]  J. Holland.  Estimating Genotypic Correlations and Their Standard Errors Using Multivariate Restricted Maximum Likelihood Estimation with SAS Proc MIXED , 2006 .

[22]  Kirk A. Stowe,et al.  Identification and characterization of QTL underlying whole‐plant physiology in Arabidopsis thaliana: δ13C, stomatal conductance and transpiration efficiency , 2005 .

[23]  Lijun Luo,et al.  Correlation analysis and QTL identification for canopy temperature, leaf water potential and spikelet fertility in rice under contrasting moisture regimes , 2005 .

[24]  G. Daggard,et al.  Curation of wheat maps to improve map accuracy and QTL detection , 2005 .

[25]  A. Condon,et al.  Breeding for high water-use efficiency. , 2004, Journal of experimental botany.

[26]  A. Condon,et al.  Phenotypic variation and sampling for leaf conductance in wheat (Triticum aestivum L.) breeding populations , 2001, Euphytica.

[27]  M. T. Assad,et al.  Evaluation of four screening techniques for drought resistance and their relationship to yield reduction ratio in wheat , 1998, Euphytica.

[28]  B. Carver,et al.  Genetic analysis of photosynthetic variation in hexaploid and tetraploid wheat and their interspecific hybrids , 1989, Photosynthesis Research.

[29]  R. G. Smith,et al.  Alternative models for predicting the foliage—Air temperature difference of well irrigated wheat under variable meteorological conditions. I. Derivation of parameters II. Accuracy of predictions , 1986, Irrigation Science.

[30]  A. Condon,et al.  Gene action for leaf conductance in three wheat crosses , 2003 .

[31]  M. Reynolds,et al.  Comparison of leaf, spike, peduncle and canopy temperature depression in wheat under heat stress , 2002 .

[32]  G. Rebetzke,et al.  "Perfect" markers for the Rht-B1b and Rht-D1b dwarfing genes in wheat , 2002, Theoretical and Applied Genetics.

[33]  J. Araus,et al.  Comparative performance of carbon isotope discrimination and canopy temperature depression as predictors of genotype differences in durum wheat yield in Spain , 2002 .

[34]  A. Condon,et al.  Selection for reduced carbon isotope discrimination increases aerial biomass and grain yield of rainfed bread wheat , 2002 .

[35]  R. Voorrips.  MapChart: software for the graphical presentation of linkage maps and QTLs. , 2002, The Journal of heredity.

[36]  R. Eastwood,et al.  Establishment and characterisation of wheat genetic mapping populations , 2001 .

[37]  L. Gentzbittel,et al.  QTL analysis of photosynthesis and water status traits in sunflower (Helianthus annuus L.) under greenhouse conditions. , 2001, Journal of experimental botany.

[38]  Jeffrey C. Stark,et al.  Use of canopy temperature measurements as a screening tool for drought tolerance in spring wheat , 1999 .

[39]  D. Wright,et al.  Inheritance of net photosynthesis and transpiration efficiency in spring wheat, Triticum aestivum L., under drought , 1999 .

[40]  R. A. Fischer,et al.  Wheat Yield Progress Associated with Higher Stomatal Conductance and Photosynthetic Rate, and Cooler Canopies , 1998 .

[41]  J. Clarke,et al.  Considerations in design and analysis of experiments to measure stomatal conductance of wheat , 1996 .

[42]  R. Littell.  SAS System for Mixed Models , 1996 .

[43]  R. A. Fischer,et al.  Canopy Temperature Depression Association with Yield of Irrigated Spring Wheat Cultivars in a Hot Climate , 1996 .

[44]  R. Doerge,et al.  Empirical threshold values for quantitative trait mapping. , 1994, Genetics.

[45]  J. Morgan,et al.  Leaf Gas Exchange and Related Leaf Traits among 15 Winter Wheat Genotypes , 1991 .

[46]  D. McDermitt.  Sources of error in the estimation of stomatal conductance and transpiration from porometer data. , 1990 .

[47]  R. D. Jackson,et al.  Canopy temperature as an indicator of differential water use and yield performance among wheat cultivars. , 1990 .

[48]  R. A. Donahue,et al.  Leaf Orientation of Soybean Seedlings: II. Receptor Sites and Light Stimuli , 1990 .

[49]  R. Richards,et al.  Genotypic Variation in Carbon Isotope Discrimination and Transpiration Efficiency in Wheat. Leaf Gas Exchange and Whole Plant Studies , 1990 .

[50]  Abraham Blum,et al.  Yield stability and canopy temperature of wheat genotypes under drought-stress , 1989 .

[51]  J. T. Musick,et al.  Evaluation of Screening Techniques for Breeding Drought-Resistanct Winter Wheat , 1988 .

[52]  J. E. Quisenberry,et al.  Use of Canopy Temperatures of Identify Water Conservation in Cotton Germplasm 1 , 1987 .

[53]  K. G. McNaughton,et al.  Stomatal Control of Transpiration: Scaling Up from Leaf to Region , 1986 .

[54]  R. B. Austin,et al.  Flag Leaf Photosynthesis of Triticum aestivum and Related Diploid and Tetraploid Species , 1982 .

[55]  L. Stolzy,et al.  Seasonal Drought Response of Selected Wheat Cultivars1 , 1981 .

[56]  H. Rawson,et al.  Effect of Leaf Position, Expansion and Age on Photosynthesis, Transpiration and Water Use Efficiency of Cotton , 1980 .

[57]  J. Zadoks.  A decimal code for the growth stages of cereals , 1974 .

[58]  I. R. Cowan.  Mass, heat and momentum exchange between stands of plants and their atmospheric environment , 1968 .