SOWMAN: Sowing management for minimising the risk of frost and heat damage

F. A. J Harris; De Li Liu; Bing Wang; Eric Koetz; Peter Martin; Aaron Preston; Graeme A. Sandral; Michael Cashen; Tim Sides

SOWMAN: Sowing management for minimising the risk of frost and heat damage

F. A. J Harris, De Li Liu, Bing Wang, Eric Koetz, Peter Martin, Aaron Preston, Graeme A. Sandral, Michael Cashen, Tim Sides

Research output: Book chapter/Published conference paper › Conference paper › peer-review

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Abstract

Extreme temperature damage to Australian grain crops remains the major production constraint with estimated losses of $1,100M per year. Thus, it is crucial to reduce such losses to improve food security for Australian and international consumers. NSW DPI developed a computer based decision support called SOWMAN to help farmers select the most appropriate varieties at sowing for minimum risk of frost and heat damage. SOWMAN is based on a phenology model that integrates varietal response to vernalisation, temperature and photoperiod and their interactions. The phenological parameters of up to 163 varieties were fitted using multiple regression analysis, based on over 13,000 sowing-flowering observations. The parameterised variety models are established as site-specific models (SSMs) and generic models (GMs).
GMs can be used when site specific field observations for a variety are anavailable. SOWMAN is currently applicable to southern NSW and can be applied to other regions when observed sowing-flowering data are available for model validation.

Original language	English
Title of host publication	Australian Society of Agronomy
Pages	1-4
Number of pages	4
Publication status	Published - 2017

Publication series

Name	18th Australian Society of Agronomy Conference, 24 – 28 September 2017, Ballarat, VIC, Australia

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http://agronomyaustraliaproceedings.org/images/sampledata/2017/144_ASA2017_Harris_Felicity.pdf

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Harris, F. A. J., Li Liu, D., Wang, B., Koetz, E., Martin, P., Preston, A., Sandral, G. A., Cashen, M., & Sides, T. (2017). SOWMAN: Sowing management for minimising the risk of frost and heat damage. In Australian Society of Agronomy (pp. 1-4). (18th Australian Society of Agronomy Conference, 24 – 28 September 2017, Ballarat, VIC, Australia ). http://agronomyaustraliaproceedings.org/images/sampledata/2017/144_ASA2017_Harris_Felicity.pdf

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title = "SOWMAN: Sowing management for minimising the risk of frost and heat damage",

abstract = "Extreme temperature damage to Australian grain crops remains the major production constraint with estimated losses of $1,100M per year. Thus, it is crucial to reduce such losses to improve food security for Australian and international consumers. NSW DPI developed a computer based decision support called SOWMAN to help farmers select the most appropriate varieties at sowing for minimum risk of frost and heat damage. SOWMAN is based on a phenology model that integrates varietal response to vernalisation, temperature and photoperiod and their interactions. The phenological parameters of up to 163 varieties were fitted using multiple regression analysis, based on over 13,000 sowing-flowering observations. The parameterised variety models are established as site-specific models (SSMs) and generic models (GMs). GMs can be used when site specific field observations for a variety are anavailable. SOWMAN is currently applicable to southern NSW and can be applied to other regions when observed sowing-flowering data are available for model validation.",

keywords = "heat stress, wheat variety, barley variety, sowing decision, risk management, phenology",

author = "Harris, {F. A. J} and {Li Liu}, De and Bing Wang and Eric Koetz and Peter Martin and Aaron Preston and Sandral, {Graeme A.} and Michael Cashen and Tim Sides",

year = "2017",

language = "English",

series = "18th Australian Society of Agronomy Conference, 24 – 28 September 2017, Ballarat, VIC, Australia ",

pages = "1--4",

booktitle = "Australian Society of Agronomy",

}

Harris, FAJ, Li Liu, D, Wang, B, Koetz, E, Martin, P, Preston, A, Sandral, GA, Cashen, M & Sides, T 2017, SOWMAN: Sowing management for minimising the risk of frost and heat damage. in Australian Society of Agronomy. 18th Australian Society of Agronomy Conference, 24 – 28 September 2017, Ballarat, VIC, Australia , pp. 1-4. <http://agronomyaustraliaproceedings.org/images/sampledata/2017/144_ASA2017_Harris_Felicity.pdf>

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AU - Harris, F. A. J

AU - Li Liu, De

AU - Wang, Bing

AU - Koetz, Eric

AU - Martin, Peter

AU - Preston, Aaron

AU - Sandral, Graeme A.

AU - Cashen, Michael

AU - Sides, Tim

PY - 2017

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N2 - Extreme temperature damage to Australian grain crops remains the major production constraint with estimated losses of $1,100M per year. Thus, it is crucial to reduce such losses to improve food security for Australian and international consumers. NSW DPI developed a computer based decision support called SOWMAN to help farmers select the most appropriate varieties at sowing for minimum risk of frost and heat damage. SOWMAN is based on a phenology model that integrates varietal response to vernalisation, temperature and photoperiod and their interactions. The phenological parameters of up to 163 varieties were fitted using multiple regression analysis, based on over 13,000 sowing-flowering observations. The parameterised variety models are established as site-specific models (SSMs) and generic models (GMs). GMs can be used when site specific field observations for a variety are anavailable. SOWMAN is currently applicable to southern NSW and can be applied to other regions when observed sowing-flowering data are available for model validation.

AB - Extreme temperature damage to Australian grain crops remains the major production constraint with estimated losses of $1,100M per year. Thus, it is crucial to reduce such losses to improve food security for Australian and international consumers. NSW DPI developed a computer based decision support called SOWMAN to help farmers select the most appropriate varieties at sowing for minimum risk of frost and heat damage. SOWMAN is based on a phenology model that integrates varietal response to vernalisation, temperature and photoperiod and their interactions. The phenological parameters of up to 163 varieties were fitted using multiple regression analysis, based on over 13,000 sowing-flowering observations. The parameterised variety models are established as site-specific models (SSMs) and generic models (GMs). GMs can be used when site specific field observations for a variety are anavailable. SOWMAN is currently applicable to southern NSW and can be applied to other regions when observed sowing-flowering data are available for model validation.

KW - heat stress

KW - wheat variety

KW - barley variety

KW - sowing decision

KW - risk management

KW - phenology

M3 - Conference paper

T3 - 18th Australian Society of Agronomy Conference, 24 – 28 September 2017, Ballarat, VIC, Australia

SP - 1

EP - 4

BT - Australian Society of Agronomy

ER -

SOWMAN: Sowing management for minimising the risk of frost and heat damage

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