Evaluation of experimental designs and spatial analyses in wheat breeding trials

By C. Qiao, K. Basford, I. DeLacy, Mark Cooper. Theoretical and Applied Genetics, 2000

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Use of crop models to understand genotype by environment interactions for drought in real-world and simulated plant breeding trials (2008, methodology): “Using the genotype means (Best Linear Unbiased Estimates) and relative weights from existing analyses (Qiao et al. 2000), the variance components for genotype and GEI were estimated using the ASREML software (Gilmour et al.”
Spatial analysis methods for forest genetic trials (2002, background): “Our lack of success compared with such efforts in variety trials (Gilmour et al. 1997; Cullis et al. 1998; Qiao et al. 2000) may be due to the much larger array sizes we have used, the more heterogeneous nature of forestry trials and the high proportion of independent error present.”
Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction (2014, methodology): “Consistent with the study by Qiao et al. (2000, 2004) for wheat in Australia, applying the framework of Gilmour et al. (1997) to the maize experiments in the US cornbelt, we interpret the positive impact of the statistical adjustment procedures on the genetic correlation coefficient estimates as an…”