Sorghum crop modeling and its utility in agronomy and breeding

Hammer, Graeme, McLean, Greg, Doherty, Al, van Oosterom, Erik and Chapman, Scott (2016). Sorghum crop modeling and its utility in agronomy and breeding. In Ignacio Ciampitti and Vara Prasad (Ed.), Sorghum: state of the art and future perspectives (pp. 1-25) Madison, WI United States: ASA and CSSA. doi:10.2134/agronmonogr58.2014.0064

Author Hammer, Graeme
McLean, Greg
Doherty, Al
van Oosterom, Erik
Chapman, Scott
Title of chapter Sorghum crop modeling and its utility in agronomy and breeding
Title of book Sorghum: state of the art and future perspectives
Place of Publication Madison, WI United States
Publisher ASA and CSSA
Publication Year 2016
Sub-type Critical review of research, literature review, critical commentary
DOI 10.2134/agronmonogr58.2014.0064
Open Access Status Not yet assessed
Year available 2016
ISBN 9780891186281
Editor Ignacio Ciampitti
Vara Prasad
Volume number 58
Start page 1
End page 25
Total pages 25
Language eng
Abstract/Summary Crop models are simplified mathematical representations of the interacting biological and environmental components of the dynamic soil–plant–environment system. Sorghum crop modeling has evolved in parallel with crop modeling capability in general, since its origins in the 1960s and 1970s. Here we briefly review the trajectory in sorghum crop modeling leading to the development of advanced models. We then (i) overview the structure and function of the sorghum model in the Agricultural Production System sIMulator (APSIM) to exemplify advanced modeling concepts that suit both agronomic and breeding applications, (ii) review an example of use of sorghum modeling in supporting agronomic management decisions, (iii) review an example of the use of sorghum modeling in plant breeding, and (iv) consider implications for future roles of sorghum crop modeling. Modeling and simulation provide an avenue to explore consequences of crop management decision options in situations confronted with risks associated with seasonal climate uncertainties. Here we consider the possibility of manipulating planting configuration and density in sorghum as a means to manipulate the productivity–risk trade-off. A simulation analysis of decision options is presented and avenues for its use with decision-makers discussed. Modeling and simulation also provide opportunities to improve breeding efficiency by either dissecting complex traits to more amenable targets for genetics and breeding, or by trait evaluation via phenotypic prediction in target production regions to help prioritize effort and assess breeding strategies. Here we consider studies on the stay-green trait in sorghum, which confers yield advantage in water-limited situations, to exemplify both aspects. The possible future roles of sorghum modeling in agronomy and breeding are discussed as are opportunities related to their synergistic interaction. The potential to add significant value to the revolution in plant breeding associated with genomic technologies is identified as the new modeling frontier.
Q-Index Code B1
Q-Index Status Provisional Code
Institutional Status UQ

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Created: Fri, 23 Jun 2017, 13:55:11 EST by Professor Graeme Hammer on behalf of Centre for Plant Science