Trait physiology and crop modelling as a framework to link phenotypic complexity to underlying genetic systems

By Graeme L. Hammer, Scott C. Chapman, Erik J. van Oosterom, Dean W. Podlich. 2005

163 citations recorded by the source corpus.

Subfields: Agronomy and Crop Science, Genetics, Plant Science

View Paper: https://www.semanticscholar.org/paper/87e8657066549aaf65ca3a72d6f9e89fd63d22b6

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Citations in the corpus

Use of crop models to understand genotype by environment interactions for drought in real-world and simulated plant breeding trials (2008, methodology): “Adapted from Hammer et al. (2005) (a) Variance Component Var_G Var_GE V ar ia nc e 0 1 2 3 4 5 (b) Gene 1 2 3 4 5 6 7 8 9 101112131415 "A " al le le e ffe ct s iz e 0 5 10 15 20 25 30 35 (c) Gene 1 2 3 4 5 6 7 8 9 101112131415 "A " al le le e ffe ct s iz e -10 0 10 20 30 40 50 Gene 1 2 3 4 5 6 7 8…”
A comprehensive study of plant density consequences on nitrogen uptake dynamics of maize plants from vegetative to reproductive stages (2011, background): “Advances in the knowledge of the physiological mechanisms that govern maize N dynamics will allow us to incorporate this information into simulation models (Hammer et al., 2005; Chenu et al., 2008; van Oosterom et al., 2010).”
The role of root architectural traits in adaptation of wheat to water-limited environments. (2006, background): “Integrating physiological understanding with traditional breeding has been proposed as ameans to enhance the rate of yield improvement (Jackson et al. 1996; Hammer et al. 2005).”
Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction (2014, background): “The potential benefits of adopting this approach include an increase in functional genetic diversity and the recombination of different modes of action into new genotypes at faster rates than would otherwise be likely (Cooper et al. 2002, 2009; Chapman et al. 2003; Hammer et al. 2005; Messina et al.”
Wheat physiology: a review of recent developments (2011, background): “…in models of other crops like beans, soybeans, and barley, and with wheat phenologymentioned earlier (White et al. 2008), while APSIM is the vehicle by which the task is being approached in sorghum (Hammer et al. 2005), maize (Messina et al. 2009), and very recently, wheat (Chenu et al. 2010).”
Model-assisted phenotyping and ideotype design (2015, background): “GeneTiC imProvemenT anD aGronomy (1) simulate phenotypic plasticity for key traits and trait combinations (Dingkuhn et al., 2005; Hammer et al., 2005) in a wide range of environments (rötter et al., 2011; Lobell et al., 2012; asseng et al., 2013); and (2) give a representative description of…”
Statistical models for genotype by environment data: from conventional ANOVA models to eco-physiological QTL models (2005, methodology): “Within a crop growth model such interactions will arise as an emergent property of the framework (Cooper et al. 2002a, 2002b; Yin et al. 2004; Hammer et al. 2005).”
Quantifying potential benefits of drought and heat tolerance in rainy season sorghum for adapting to climate change (2014, methodology): “Hammer et al. 2005, 2010) used the ASPIM modeling framework to hypotheize genetic improvement in sorghum, although they did not focus n issues of adaptation to climate change.”
Potential benefits of drought and heat tolerance in groundnut for adaptation to climate change in India and West Africa (2014, background): “…proposed genetic improvement of crops for higher yields (Landivar et al. 1983; Boote and Jones 1986; Whisler et al. 1986; Boote and Tollenaar 1994; Hammer et al. 1996, 2002, 2004, 2005; Yin et al. 1999; Boote et al. 2001, 2003; Tardieu 2003; White and Hoogenboom 2003; Messina et al. 2006;…”