Brumbley, S.M., Snyman, S.J., Gnanasambandam, A., Joyce, P., Herman, S.R., da Silva, J.A.G., McQualter, R.B., Wang, M., Egan, B.T. and Patterson, A.H. (2008) Sugarcane. In: Kole, C. and Hall, T.C., Eds., Compendium of Transgenic Crop Plants: Transgenic Sugar, Tuber and Fiber Crops, Blackwell Publishing Ltd., Oxford.

has been cited by the following article:

• TITLE: A Dual Ensemble Agroclimate Modelling Procedure to Assess Climate Change Impacts on Sugarcane Production in Australia

  AUTHORS: Yvette Everingham, Geoff Inman-Bamber, Justin Sexton, Chris Stokes

  KEYWORDS: Agriculture, Sustainable, Global Warming, Adaptation, CMIP

  JOURNAL NAME: Agricultural Sciences, Vol.6 No.8, August 27, 2015

  ABSTRACT: Climate is a key driver of sugarcane production and all its by-products. Consequently, it is important to understand how climate change will influence sugarcane crop productivity. Ensembles from a crop model and climate projections form part of the dual ensemble methodology to assess climate change impacts on sugarcane productivity for three major sugarcane-growing regions in Australia—Burdekin, Mackay and New South Wales (NSW). Different parameterisations of a crop model injected with climate outputs from eleven statistically downscaled general circulation models (GCM) were used to estimate regionally averaged sugarcane yields for the base period 1971 to 2000. The forward stagewise algorithm selected crop model parameterisations that best explained the observed yields. Leave-one-out cross validation assessed the predictive capability of the equally weighted crop ensemble members characterised by the selected crop model parameterizations. A Monte Carlo permutation testing procedure was employed to measure the significance of the predictive correlations. The predictive correlations between historical yields and simulated historical yields for the Burdekin, Mackay and NSW were 0.69 (p = 0.030), 0.83 (p