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Crop design for specific adaptation in variable dryland production environments

Citation

Hammer, GL and McLean, G and Chapman, S and Zheng, B and Doherty, A and Harrison, MT and van Oosterom, E and Jordan, D, Crop design for specific adaptation in variable dryland production environments, Crop and Pasture Science, 65, (7) pp. 614-626. ISSN 1836-0947 (2014) [Refereed Article]

Copyright Statement

Copyright 2014 CSIRO

Official URL: http://www.publish.csiro.au/nid/40/paper/CP14088.h...

DOI: doi:10.1071/CP14088

Abstract

Climate variability in dryland production environments (E) generates crop production risks. Optimal combinations of genotype (G) and management (M) depend strongly on E and thus vary among sites and seasons. Traditional crop improvement approaches seek broadly adapted genotypes to give best average performance under a standard management regime across the entire production region, with some subsequent manipulation of management regionally in the response to average local environmental conditions. This process does not search the full spectrum of potential G X M X E combinations forming the adaptation landscape. Here we examine the potential value (relative to the conventional broad adaptation approach) of exploiting specific adaptation arising from G X M X E. We present an in-silico analysis for sorghum production in Australia using APSIM sorghum model. Crop design (G X M) is optimised for subsets of locations within the production region (specific adaptation) and is compared with the optimum G across all environments with locally modified M (broad adaptation). We find that geographic sub-regions that have substantially different frequencies of major environment types to that for the entire production region, show greatest advantage for specific adaptation. While the specific adaptation approach confers yield and production risk advantages at industry scale, even greater benefits should be achievable with better predictors of environment type likelihood than that conferred by location alone.

Item Details

Item Type:Refereed Article
Keywords:crop improvement, crop modelling, G X E, genotype by environment interaction, plant breeding, trait simulation
Research Division:Agricultural and Veterinary Sciences
Research Group:Agriculture, Land and Farm Management
Research Field:Agricultural Production Systems Simulation
Objective Division:Plant Production and Plant Primary Products
Objective Group:Summer Grains and Oilseeds
Objective Field:Sorghum
Author:Harrison, MT (Dr Matthew Harrison)
ID Code:84660
Year Published:2014
Web of Science® Times Cited:15
Deposited By:Tasmanian Institute of Agriculture
Deposited On:2013-05-24
Last Modified:2017-11-06
Downloads:0

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