Publication

Number of items: 13.
Public
  • Bayesian analysis and prediction of hybrid performance. (2019) Alves, F. C., Granato, I. S. C., Galli, g, Hottis-Lyra, Danilo, Fritsche-Neto, R., De los Campos, G.
  • Guidelines for measuring and reporting environmental parameters for experiments in greenhouses. (2015) Both, A. J., Benjamin, L. R., Franklin, J. F., Holroyd, G., Incoll, L. D., Lefsrud, M. G., Pitkin, G.
  • Review of methodologies and a protocol for the Agrobacterium -mediated transformation of wheat. (2005) Jones, Huw, Doherty, Angela, Wu, H.
  • Estimation of vegetation indices for high-throughput phenotyping of wheat breeding lines using aerial imaging. (2018) Khan, Z., Rahimi-Eichi, V., Haefele, Stephan, Garnett, T., Miklavcic, S. J.
  • High Resolution Melt (HRM) analysis is an efficient tool to genotype EMS mutants in complex crop genomes. (2011) O Lochlainn, S., Amoah, S., Graham, N. S., Alamer, K., Rios, J. J., Kurup, Smita, Stoute, A., Hammond, J. P., Ostergaard, L., King, G. J., White, P. J., Broadley, M. R.
  • Standardized gene nomenclature for the Brassica genus. (2008) Ostergaard, L., King, G. J.
  • A dual isotopic approach using radioactive phosphorus and the isotopic composition of oxygen associated to phosphorus to understand plant reaction to a change in P nutrition. (2017) Pfahler, Verena, Tamburini, F., Bernasconi, S. M., Frossard, E.
  • Protocol: precision engineering of plant gene loci by homologous recombination cloning in Escherichia coli. (2005) Roden, L. C., Gottgens, B., Mutasa-Göttgens, E. S.
  • Multi-feature machine learning model for automatic segmentation of green fractional vegetation cover for high-throughput field phenotyping. (2017) Sadeghi-Tehran, Pouria, Virlet, Nicolas, Sabermanesh, Kasra, Hawkesford, Malcolm
  • Universal endogenous gene controls for bisulphite conversion in analysis of plant DNA methylation. (2011) Wang, J., Wang, C., Long, Y., Hopkins, C., Kurup, Smita, Liu, K., King, G. J., Meng, J.
  • Leaf to panicle ratio (LPR): a new physiological trait indicative of source and sink relation in japonica rice based on deep learning. (2020) Yang, Z., Gao, S., Xiao, F., Li, Y., Ding, Y., Guo, Q., Paul, Matthew, Liu, Z.
  • Determination of wheat spike and spikelet architecture and grain traits using X-ray Computed Tomography imaging. (2021) Zhou, H., Riche, Andrew, Hawkesford, Malcolm, Whalley, Richard, Atkinson, B. S., Sturrock, C. J., Mooney, S. J.
  • Restricted
  • Big data from small tissue extraction of high-quality RNA for RNA-Sequencing from different oilseed Brassica seed tissues during seed development. (2020) Siles-Suarez, Laura, Eastmond, Peter, Kurup, Smita