Screening genetic variation for photosynthetic capacity and efficiency in wheat

The world population is rising, placing increasing demands on food production. One way to contribute to food security is by improving yields of staple crops like wheat. Yield can be calculated from the product of plant biomass and harvest index (the ratio of grain yield to above ground biomass). Since harvest index of wheat has already reached its maximum biological limit in some environments, attention is now focused on increasing crop biomass. Efficient interception of photosynthetically active radiation and effective photosynthetic sugar production underpin yield, however, little breeding has been done for photosynthetic performance. Exploiting existing genetic variation for important photosynthetic traits such as photosynthetic capacity (Pc) and photosynthetic efficiency (Peff) will help to improve wheat yield. CO2 assimilation rate, which is a commonly measured parameter for assessing photosynthetic performance, is found to vary across wheat genotypes. Two additionally important parameters are Rubisco activity (Vcmax) and electron transport rate (J). There is much less information reported regarding genetic variation of these two latter parameters because measurements of CO2 response curves with gas exchange used to derive Vcmax and J are slow and unsuitable for rapid screening of many genotypes in the field. The two main objectives of this project were firstly, to find out if there is genetic variation for these important photosynthetic traits in wheat, and secondly, to develop a rapid method for screening photosynthetic and leaf attributes in different wheat genotypes. To deal with variable leaf temperatures in the field and accurately estimate Vcmax and J, improved values for the temperature dependence of several Rubisco kinetic parameters were needed. These temperature-dependencies were derived from measurements made under controlled conditions. A method for rapidly estimating variation in Pc components Vcmax and J and in other photosynthetic traits was developed based on calibration of leaf reflectance spectra against photosynthetic parameters derived using conventional gas exchange, morphological (leaf mass per unit area, LMA) and chemical (nitrogen and chlorophyll per unit area) measurements of 76 wheat genotypes screened in several different environments. When observed data were compared against predictions from reflectance spectra, correlation coefficients (R2 values) of 0.62 for Vcmax25, 0.71 (J), 0.89 (LMA) and 0.93 (Narea), were obtained. Reflectance spectra from an additional 458 elite and landrace wheat genotypes were measured to further assess variation in photosynthetic traits. There were significant differences between wheat genotypes in Vcmax25 per unit N, which is a good measure of Peff. Environment presented interaction with genotypes for Pc and Peff when measurements performed in glasshouse & field or in Australia & Mexico were compared. In future, linking genotypic variation for photosynthetic traits to DNA-based genetic markers will permit even faster selection of genotypes in breeding. Reflectance spectra should be a good tool to accelerate identification and selection of wheat genotypes and detection of important genomic regions for photosynthetic capacity and efficiency in wheat