crop updates 2011 - cereals - research library

Research Library Research Library

Crop Updates Grain and other field crop research

23-2-2011

Crop Updates 2011 - Cereals Crop Updates 2011 - Cereals

David Bowran Department of Agriculture and Food

Bill Crabtree Morawa, Western Australia

Peter Carberry CSIRO Sustainable Agriculture Flagship

Peter Burges Kalyx Agriculture

Bevan Buirchell Department of Agriculture and Food

See next page for additional authors

Follow this and additional works at: https://researchlibrary.agric.wa.gov.au/crop_up

Part of the Agribusiness Commons, Agronomy and Crop Sciences Commons, Plant Biology

Commons, Plant Breeding and Genetics Commons, and the Soil Science Commons

Recommended Citation Recommended Citation Bowran, D, Crabtree, B, Carberry, P, Burges, P, Buirchell, B, Curtis, B, Ellis, S, Shackley, B, Zaicou, C, Sivapalan, S,

Goldsmith, P, Plunkett, G, Sharma, D, D'Antuono, M, Diggle, A, Mangano, P, Peltzer, S, Renton, M, MacLeod, B, Horiuchi, F, Wyatt, G, Anderson, G, Bell, R, Brennan, R, Chen, W, and Riffkin, P. (2011), Crop Updates 2011 - Cereals. Department of Agriculture and Food, Perth. Conference Proceeding.

This conference proceeding is brought to you for free and open access by the Grain and other field crop research at Research Library. It has been accepted for inclusion in Crop Updates by an authorized administrator of Research Library. For more information, please contact [email protected].

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Authors Authors David Bowran, Bill Crabtree, Peter Carberry, Peter Burges, Bevan Buirchell, Ben Curtis, Sarah Ellis, Brenda Shackley, Christine Zaicou, Siva Sivapalan, Penny Goldsmith, Gae Plunkett, Darshan Sharma, Mario D'Antuono, Art Diggle, Peter Mangano, Sally Peltzer, Michael Renton, Bill MacLeod, Fumie Horiuchi, George Wyatt, Geoff Anderson, Richard Bell, Ross Brennan, Wen Chen, and Penny Riffkin

This conference proceeding is available at Research Library: https://researchlibrary.agric.wa.gov.au/crop_up/50

https://researchlibrary.agric.wa.gov.au/crop_up/50

2011 Agribusiness

Crop Updates

Department ofAgriculture and Food

Burswood Entertainment ComplexPerth, Western AustraliaWednesday 23 and Thursday 24 February 2011

2011 Agribusiness Crop UpdatesWestern Australia

Presented at the Burswood Entertainment Complex, Perth, Western Australia, Wednesday 23 and Thursday 24 February 2011.

Edited by Janet Paterson and Catriona Nicholls. Desktop publishing by Par Excellence.

Permission of the publisher is required for articles being reproduced or presented.

Mention of a trade name or company in this publication does not imply endorsement of any product or company by the Department of Agriculture and Food, WA.

ISSN 1445-0593

Disclaimer

1. The information, representations and statements contained in this publication are provided for general

scientifi c information purposes only.

2. The State of Western Australia, the Minister for Agriculture and Food the Director General of the

Department of Agriculture and Food, the Grains Research and Development Corporation and their

respective offi cers, employees and agents:

a) do not make any representation or warranty as to the accuracy reliability completeness or currency

of the information, representations or statements in this publication (including but not limited to

information which has been provided by third parties); and

b) shall not be liable, in negligence or otherwise, to a person for any loss liability or damage arising

out of an act or failure to act by any person in using or relying on any information, representation or

statements contained in this publication.

3. The State of Western Australia, the Minister for Agriculture and Food the Director General of the


respective offi cers, employees and agents:

a) make no representations or warranty that any of the products specifi ed in this publication (‘Specifi ed

Products’) are registered pursuant to the Agricultural and Veterinary Chemicals Code Act 1994 (WA).

4. a) The State of Western Australia, the Minister for Agriculture and Food the Director General of the


respective offi cers employee and agents do not endorse or recommend any Specifi ed Product or any

manufacturer of a Specifi ed Product. Brand, trade and proprietary names have been be used solely

for the purpose of assisting users of this publication to identify products.

b) Products that are not Specifi ed Products (‘Alternative Products’) may perform as well as or better

than Specifi ed Products.

5. Users of any chemical product should always read the label on the product before use and should follow

the directions specifi ed on the label.

Copyright © Western Australian Agriculture Authority, 2011

Agribusiness Crop Updates 2011

i

GIWA

Grain Industry Association of Western Australia

Morning Day 1 Wednesday 23 February 2011

0850 Welcome

Introduction to Crop Updates

Rob DelaneDirector General, Department of Agriculture

and Food, WA (DAFWA)

0900 Conference opening Welcome to WA - Australia’s Grain State

Hon. Terry Redman Minister for Agriculture and Food

0930 Keynote SpeakerGlobal trends in cropping R&D. Issues and

opportunities for Australian farmers

Sean Gardner

Global Wheat Lead, Monsanto (USA)

1020 Seed of Light AwardPresentation of Seed of Light Award

Neil YoungChairman, GRDC Western Panel

1230 Lunch sponsored by Emerald

1100 Overview of the 2010 grain season

across the WA wheatbelt.

David BowranDirector, Practice and

Systems Innovation DAFWA

Update and outlook on world economic scene and

grain commodities

Michael Creed Economist – Agribusiness National Australia Bank

1115 Economic imperatives advisers need

to consider when providing advice to

growers during 2011

Ken SevensonDirector, Corporate Agriculture Australia

1140 Technical decisions for 2011 and beyond

Geoff FosberyDirector, ConsultAg

Grain production and marketing - the former Soviet

Union / Black Sea region

Brad Gosling Manager, wheat merchandising domestic and

international customer relations, Emerald

1200 Helping your clients remain strong

through good and bad times

Dennis HoibergLessons Learnt Consulting

Plenary 1 (Grand Ballroom)

1030 Morning Tea

Plenary 2a (Grand Ballroom)

Managing after a drought. Chair: Neil Young

Plenary 2b (Grand Ballroom)

Global Grain Outlook. Chair: Robert Loughman

Department ofAgriculture and Food


ii

Variety performance and development

Weed, pest and disease management

Tillage, soils and establishment

Grain quality and market access

Quick or commercial

Astral 1Chair: Tress Walmsley

Astral 3Chair: Stephen Powles

Grand BallroomChair: Ralph Burnett

Astral 2Chair: John Slee

Botanicals 1 & 2Chair: Janet Paterson

1330 2010 National Variety

Trial results - wheat

Peter Burgess,

Kalyx Agriculture

Management of

emerging weeds within

the WA wheatbelt

Abul Hashem, DAFWA

Amelioration of

non-wetting sands

using soil inversion

and partial inversion

techniques

Steve Davies and Peter Newman, DAFWA

Biosecurity changes

and challenges to

improve market

access

Bill Magee,Biosecurity Australia

Map-based web

interface for PestFax

Tactical weed control

with the Weed Seed

Wizard

Art Diggle, DAFWA

1400 Ten minutes moving

1410 New wheat varieties

and agronomy

packages

Ben Curtis,DAFWA

Sakura®, Boxer Gold®,

and Trifl uralin: Potential

for evolution of

resistance in annual

ryegrass and resistance

management strategies

Todd Gaines,Research Associate AHRI

Pros and cons of dry

seeding to counter

variable seasonal

breaks

Michael Robertson, CSIRO

Quality optimisation

trial

Mathew Regan, Grain Quality

Manager CBH

Group

Custom Composts

ALOSCA Technologies

Novozymes Australia


1450 WALAN2289 lupin

- a promising new

variety

Bevan Buirchell, DAFWA

Release of Twilight

and Gunyah peas

Ian Pritchard,Pulse Breeders

Australia

Weedseeker herbicide

options in winter and

summer fallow

Grant Thompson,CropCircle Consulting

Low weed seed banks

are the key to early

sowing

Peter Newman,DAFWA

Nutrition and

health benefi ts of

wholegrain foods

and legumes

Robyn Murray, General Manager,

Go Grains Health &

Nutrition

Pioneer Hi-Bred Australia

Nuseed

Pacifi c Seeds

Canola Breeders WA

1520 Afternoon tea

Afternoon Day 1

Concurrent Sessions

Plenary 3 (Grand Ballroom)

Chair: David Bowran

1730 CBH Group networking function

1555 Meeting the productivity and sustainability challenges to Australian agriculture until 2030

Peter Carberry, Deputy Director, CSIRO Sustainable Agriculture Flagship

1630 William Farrer Medal presentation

1930 Close


iii

Morning Day 2 Thursday 24 February 2011

0855 What’s preventing growers from implementing

precision agriculture?

Roger Mandel, Agronomy Lecturer Curtin University

0855 What the world wants from Australian wheat

Gordon MacAulay,Principal Economist, BRI Australia

0920 Latest developments and global trends in

precision agriculture.

Terry Pickett, Manager, Advanced Engineering,

IVS, John Deere (Iowa, USA)

Is there a viable future for autonomous

tractors/sprayers/headers?

Broughton Boydell, Project Engineer,

John Deere, (NSW)

0940 Emerging demands for wheat fl our in Indonesia and

South East Asia

Jason Craig,President Director, Eastern Pearl Flour Mills

1010 Global and Asia-Pacifi c trends in crop

protection.

Franz Doppmann, Head of Crop Protection,

Syngenta (Singapore)

1025 The Japanese noodle wheat market

Koichi Tojo, General Manager Riverina Perth

1100 Morning tea

0700 Harvest Wrap Breakfast GIWA / AGI

Plenary 4a (Grand Ballroom)

Precision Agriculture. Chair: Mark Sweetingham

Plenary 4b (Astral 1)

Market Needs. Chair: Peter Metcalfe

Precision agriculture Variety performance and development

Climate and strategy Wheat breeding and classifi cations

Quick or commercial

Grand BallroomChair: Glen Reithmuller

Astral 1Chair: Peter Roberts

Astral 3Chair: Fran Hoyle

Astral 2Chair: Narelle Moore

Botanicals 1 & 2Chair: Alan Meldrum

1130 On how many paddocks

does PA pay?

Roger Lawes, CSIRO

Review of RR canola roll-

out and performance in

2010 season

Tom Breen, Monsanto

Strategic versus tactical

fallowing - does it pay?

Janette Drew, DAFWA

Australia’s wheat

breeding industry in

2010

Peter Reading, GRDC

CBH Group

Cargill Australia

Emerald


1210 Demonstration of

precision agriculture

principles in the Great

Southern of WA

Derk Bakker, DAFWA

Optimising OP and

hybrid canola plant

densities for yield

Mark Seymour, DAFWA

Justin Kudnig, Pacifi c Seeds

Statistical seasonal

rainfall forecasts for

south west Australia

Fiona Evans, DAFWA

Saudi Arabian wheat

quality requirements

Larisa Cato,DAFWA

Grain Growers

Curtin University

AqWorld


National changes to

spray application and

herbicide labelling

regulations

Rohan Rainbow, GRDC

National Working Party

for Pesticide Application

2010 National Variety Trial

results - canola

Michael Lamond, AgriSearch

Drought proofi ng the

low rainfall agricultural

zones of WA

Cameron Tubby, Nuffi eld Scholar

My experience in a

drought

Bill Crabtree,Agriculture Consulting

Lastest wheat

classifi cation actions

and varieties

Robert Sewell, Wheat

Classifi cation Council

AWB Seeds

Intergrain

Australian Grain Technologies

1320 Lunch sponsored by Emerald

Concurrent Sessions


iv

Pest and disease management

Profi table cropping systems

Rainfall, rotation, break crops

Barley issues and climate

Frost, weed mangement and the role of grazing in cropping systems

Astral 2Chair: Peter Bostock

Grand BallroomChair: Anna Butcher

Astral 1Chair: M. Carlshausen

Astral 3Chair: Steve Tilbrook

Botanicals 1 & 2Chair: Leecia Angus

1420 Control of insect and

mite pests in grains –

insecticide resistance

and IPM’

Paul Umina, CESAR/

Uni of Melbourne;

Laura Fagan, UWA

Svetlana Micic, DAFWA

VicFocus on

improving yields

in the HRZ. What

can be learnt

from Vic/SA/NSW

experiences?

Penny Riff kin, DPI Victoria

When is continuous

wheat or barley

sustainable?

Christine Zaicou-Kunesch and Rob Grima, DAFWA

Malting barley

opportunities in

China

Anne Wilkins, DAFWA

Where are we at with

managing frost?

Juan Juttner, Manager Gene

Discovery GRDC


1500 Infl uence of soil

amendments on soil

biology

Dan Murphy, UWA

Targeting inputs

for maximum

profi t

Steve Milroy, CSIRO

Cameron Weeks, Planfarm

Bridging the

Yield Gap: what’s

constraining grain

yield and what can

we do about it?

Peter White, DAFWA

National

accreditation of

malting barley

varieties.

New segregation

- Food Barley.

Discussion on

Barley Strategy for

WA

Andrew Gee, Barley Australia

Rob Dickie, CBH Grain

Blue lupins can now be

selectively controlled in

white lupins

Richard Quinlan, Planfarm

Harrington Seed

Destructor - Results

from 2010

Michael Walsh, AHRI


1540 Fungicide resistant

powdery mildew

discovered in WA in

2010 - implications for

coming seasons

Richard Oliver, Murdoch University

Is Yield Prophet

a useful tool in

Western Australia?

– an agribusiness

perspective

(Panel session)

Caroline Peek and Rob Grima,DAFWA

Ryan Pearce, ConsultAg

Rod Butcher, Landmark

Craig Topham, Agrarian

Richard Quinlan, Planfarm

Break crops - update

on crop sequencing

research at Wongan

Hills and Katanning

Bob French, DAFWA

How has a

changing climate

recently aff ected

Western Australia’s

capacity to increase

crop productivity

and water use

effi ciency?

David Stephens, DAFWA

Can livestock have a

long-term role in no-till

cropping systems?

James Fisher, Désirée Futures

Paddock scale crop

grazing trials

Jonathon England, DAFWA

1610 Afternoon tea and conference close Peter Metcalfe - Director, Grains Industry Development DAFWA

Afternoon Day 2

Concurrent Sessions


v

Table of Contents

Overview of the 2010 season .......................................................................................................................... 2

David Bowran

My experience in a drought as a farmer and consultant .................................................................................. 3

Bill Crabtree

Meeting the productivity and sustainability challenges to Australian agriculture until 2030............................. 6

Peter Carberry

New Crop Varieties

National Variety Trials wheat variety performance - captivity vs broadacre ..................................................... 10

Peter Burgess

WALAN2289 — a new lupin variety to replace Mandelup in the system ......................................................... 13

Bevan Buirchell

The strengths and pitfalls of different grades of new wheat varieties in Western Australia ............................. 16

Ben Curtis, Sarah Ellis, Brenda Shackley, Christine Zaicou

Yield performance of temperate and tropical rice varieties in the Ord River Irrigation Area ........................... 28

Siva Sivapalan, Penny Goldsmith and Gae Plunkett

Decision Support

The new phenology model of wheat ................................................................................................................ 34

Darshan Sharma, Mario D’Antuono, Brenda Shackley, Christine Zaicou, Ben Curtis

PestFax Map and the Weed Seed Wizard: tools to help with crop protection .................................................. 37

Art Diggle, Peter Mangano, Sally Peltzer, Michael Renton, Bill Macleod, Fumie Horiuchi and George Wyatt

Soil management calculator for predicting phosphorus losses under cropping systems in Western Australia ........................................................................................................................................... 41

Geoff Anderson, Richard Bell, Ross Brennan and Wen Chen

Tools to assist growers understand the impacts of management decisions in the high rainfall zone .............. 46

Penny Riff kin

Weeds and Herbicides55Herbicides for selective spot spraying application on winter weeds in chemical fallow ................................. 52

Grant Thompson

Management of emerging weeds within the Western Australian wheatbelt .................................................... 56

Abul Hashem and Catherine Borger

Integrated weed management — it’s all about early sowing of a big crop ....................................................... 61

Peter Newman

Increased water rates improve the performance of trifl uralin in minimum tillage systems ............................... 65

Catherine Borger, Mike Ashworth, Glen Riethmuller, David Minkey and Abul Hashem

Herbicide tolerance of new albus lupin WALAB2014 similar to or better than Andromeda ............................ 70

Harmohinder Dhammu and David Nicholson


vi

Pesticide application and spray drift management: recent developments ....................................................... 72

Nicholas Woods

Herbicide tolerance of new desi chickpea varieties ........................................................................................75

Harmohinder Dhammu and David Nicholson

Herbicide tolerance of oat varieties ................................................................................................................. 78

Harmohinder Dhammu

The case for seeking registration of metribuzin pre-seeding lupins ................................................................. 81

Peter Newman

Direct harvesting canola with desiccation or swathing to reduce ryegrass seed set ...................................... 84

Glen Riethmuller, Abul Hashem and Catherine Borger

Herbicides for selective spot spraying application on summer weeds ........................................................... 89

Grant Thompson

Development of the Harrington Seed Destructor ............................................................................................. 92

Michael Walsh and Ray Harrington

Pest and Diseases

Grains biosecurity – everyone’s business ........................................................................................................ 96

Jeff Russell

Control of insect and mite pests in grains — insecticide resistance and integrated pest management (IPM) 98

Paul Umina, Svetlana Micic and Laura Fagan

Effect of cropping rotations on pest mites of broadacre agriculture ............................................................... 101

Svetlana Micic, Mark Seymour, Tony Dore and Pam Burgess

Common bunt resistance in Western Australian wheat varieties ..................................................................... 104

John Majewski, Manisha Shankar and Rob Loughman

Balance® used in conventional cropping practice with half of the upfront fertiliser rate can sustain crop yield and build soil biological fertility ........................................................................................................................ 108

Deb Archdeacon, Andrew Gulliver and David Cullen

Effects of potassium supply on plant growth, potassium uptake and grain yield in wheat grown in grey sand ......................................................................................................................................................... 113

Qifu Ma, Richard Bell, Ross Brennan and Craig Scanlan

Improving fertiliser management: redefi ning the relationship between soil tests and crop responses for wheat in WA .................................................................................................................................................... 119

Wen Chen, Ross Brennan, Geoff Anderson, Richard Bell and Mike Bolland

Improved phosphorus and potassium fertiliser management: redefi ning the soil test and lupin response relationships in WA .......................................................................................................................................... 123

Wen Chen, Ross Brennan, Geoff Anderson, Richard Bell and Mike Bolland

Converting phosphorus retention index to phosphorus buffering index for Western Australian soils ................................................................................................................................................ 127

Peter Rees and Sandy Alexander

Variability of radiometric potassium and Colwell potassium relationships across the Great Southern............ 129

Frank D’Emden

Rotary spading and mouldboard ploughing of water-repellent sandplain soil fulfi ls promise .......................... 133

Stephen Davies, Craig Scanlan and Breanne Best


vii

Soil nitrous oxide fl uxes are low from a grain legume crop grown in a semi-arid climate ................................ 139

Louise Barton, Klaus Butterbach-Bahl, Ralph Kieseand Daniel Murphy

Mouldboard ploughing of sandplain soils — more grain, fewer weeds ............................................................ 143

Peter Newman

Precision Agriculture147What’s preventing growers from implementing precision agriculture? ............................................................. 148

Roger Mandel, Roger Lawes and Michael Robertson

On how many paddocks does precision agriculture deliver a return? ............................................................. 153

Roger Lawes, Michael Robertson and Roger Mandel

Demonstration of precision agriculture principles in the Great Southern, Western Australia .......................... 157

Derk Bakker, Jeremy Lemon, Alison Lacey, John Paul Collins, Roger Mandel, Frank D’Emden, Glen Riethmuller

Climate and Forecasting63Statistical seasonal rainfall forecasts for south west Australia ......................................................................... 164

Fiona H Evans

How has a changing climate recently affected Western Australia’s capacity to increase crop productivity and water use effi ciency? ................................................................................................................................ 168

David Stephens

Is Yield Prophet® a useful tool in Western Australia? — an agribusiness perspective ..................................... 169

Caroline Peek

A season of Yield Prophet® — how it saw the dry ........................................................................................... 173

Tim Scanlon and Caroline Peek

Farming Systems7Fallowing 50 per cent of the farm each year — does it pay? ........................................................................... 178

Janette Drew and Rob Grima

How crop sequences affect the productivity and resilience of cropping systems in two Western Australian environments ................................................................................................................................................... 181

Bob French, Raj Malik, Mark Seymour

When is continuous wheat or barley sustainable? .......................................................................................... 192

Christine Zaicou-Kunesch and Rob Grima

Identifying constraints to bridging the yield gap ............................................................................................... 196

Glenn McDonald

Land constraints limiting wheat yields in the Bridging the Yield Gap project area ........................................... 200

Brendan Nicholas and Dennis van Gool

Can livestock have a long-term role in no-till cropping systems? .................................................................... 204

James Fisher, Peter Tozer and Doug Abrecht

Pros and cons of dry seeding to counter variable seasonal breaks ................................................................ 208

Michael Robertson, Cameron Weeks, Michael O’Connor, Doug Abrecht, Rob Grima and Peter Newman

Defi ning economic optimum plant densities of open pollinated and hybrid canola in WA ............................... 213

Mark Seymour


viii

Alternative uses for unproductive soils examined in the North Eastern Agricultural Region .......................... 217

Mike Clarke and Andrew Blake

Markets1What the world wants from Australian wheat ................................................................................................... 222

Gordon MacAulay

Effect of lupin fl our incorporation on the physical and sensory quality of pasta ............................................. 229

Vijay Jayasena and Syed M. Nasar-Abbas

Wheat quality requirements for Saudi Arabia: baking quality and blending potential of some Australian exporting grades .............................................................................................................................................. 232

Larisa Cato, Robert Loughman and Ken Quail


ix

www.nvtonline.com.au

WHAT VARIETIES WILL YOU GROW IN 2011?Check out the NVT website with integrated Google map searching for independent trial results on how new varieties have performed.

Go to www.nvtonline.com.auPresents data on 10 crops and approximately 300 varieties with more than 630 trials conducted annually across all states.

10 CROPS, 300 VARIETIES, 630 TRIALS ANNUALLY

To compare yields of varieties in a specific region select Long Term Results from the trial options balloon. This example is for Main Season Wheat in N/W NSW. By scrolling through the report you can view the number of trials conducted for each variety to gain confidence in the result.

Click on the Current Trial Result button for a full report for the particular trial, or use the Statewide Tables of Yield & Grain Quality button to produce a Microsoft Excel table comparing all varieties in all trials in a particular state for both yield and grain quality.

Simply use the crop, sub-crop and postcode filters to find specific trial information, or use the zoom and scroll functions to see a broader range of trials.

Click on a trial marker to reveal and access all information for that trial including regional long term yield reports and individual trial data.


x

PASSIONATE ABOUT THE GRAINS INDUSTRY? WANT TO MAKE A DIFFERENCE?

BECOME A GRDC REGIONAL PANEL MEMBER“ If you want to challenge yourself, meet a diverse range of people and influence the future of the grains industry – become a GRDC panel member. As a panel member you operate across the GRDC’s programs – in Practices you see the latest agronomy and farming systems; in Varieties get exposure to the diversity of crop types and the science of plant breeding; and the New Products portfolio can take you anywhere.” JAMES CLARK, Northern Panel Chair

Across Australia there are three Grains Research and Development Corporation (GRDC) Regional Panels representing the principal cropping zones – northern, southern and western regions. The Panels work with GRDC management to develop the research, development and extension portfolio. Panel members provide a ‘face’ to the GRDC representing the corporation and promoting its regional investments.

Panel members’ combined skills and experience provide the Board with a valuable network to draw out local, regional and national grains industry issues. The GRDC Board considers the appointment of members to the Regional Panels as crucial to the GRDC’s success.

Who are we looking for?We are looking for grain growers, researchers, farm advisers and consultants as well as people from the broader grains community – marketers, bulk handlers, farm input suppliers, grain processing and food industries, finance and business management, economic evaluation of R&D, or natural resource management.

Candidates are to demonstrate: An understanding of the grains industry business environment, production issues and challenges Experience in liaising and working with grain growers Involvement in grains-industry-related R&D and the application and adoption of new technology and practices Extensive industry networks Good communication and language skills (verbal and written) Ability to work effectively in teams and with groups.

Panel members need to be able to commit approximately 40 days per year to GRDC panel activities. Panel members are compensated for their time spent on GRDC activities at rates set by the Remuneration Tribunal and agreed to by the GRDC Board. Appointments are for a three-year term, commencing 1 July 2011.

The GRDC is a statutory corporation funded by grain growers and the Australian Government.

The GRDC invests in developing better grain varieties, better agricultural practices, new grain-related products, and the building of Australian innovation and research capacity.

For a copy of the position description and details on how to apply visit the GRDC’s website (www.grdc.com.au/vacancies) or contact Noelia Grech on 02 6166 4500.

All applications are to be sent to:Panel Selection Committee Grains Research and Development Corporation PO Box 5367 KINGSTON ACT 2604

or electronically to email: [email protected]. Closing date for applications is 7 March 2011 AEDST.

Level 1, Tourism House | 40 Blackall Street, Barton ACT 2600PO Box 5367, Kingston ACT 2604 | t +61 2 6166 4500

f +61 2 6166 4599 | e [email protected] | w www.grdc.com.au

GRDC REGIONAL PANELS: APPLY NOW

AgribusinessCrop Updates 2011


2

Overview of the 2010 season

David BowranDirectorPractice and Systems InnovationDepartment of Agriculture and Food, WA

2010 turned out to be one of the most diffi cult to deal with from a weather point of view. Many parts of the

south west of WA received their lowest rainfall on record with growing-season defi cits of 150 to 300 mm

of rain. Overall, about 40% of the wheatbelt was in this category, with about 40% in the very much below

average category. The only areas with close to normal rainfall were in the Esperance area and along the coast

east of Esperance.

Late summer and autumn rainfall patterns were highly variable across the wheatbelt with some areas

receiving up to 70 mm of rain, but most of the region receiving much less than this. In general, suffi cient

rainfall was received across the wheatbelt for over 90% of the crop to have been planted by late May and

for most crops to germinate and emerge by mid June. Soil water was very low over approximately half the

wheatbelt at crop emergence.

Rainfall patterns for winter were, in general, dominated by four events that brought the majority of rain. Long

periods of no or low rainfall between these events were accompanied by very cold nights and warm sunny

days. Spring rainfall was extremely low for the majority of the wheatbelt, but was generally much better for

areas in the northern agricultural region.

Many crops faced ongoing water defi cits throughout the season, with these becoming severe in spring. The

combination of long periods of low rainfall, cold nights and warm days caused cereal fl owering to be delayed

with many crops being up to two weeks behind normal for the planting date. In the case of canola in the

eastern wheatbelt many crops fl owered but subsequently failed to fi ll pods.

While the rainfall defi cits contributed to low yields across the majority of the wheatbelt, the expected

large increase in screenings for wheat was generally not observed. The constant stress through winter and

subsequent low biomass of crops appears to have enabled wheat to adjust going into grain fi lling with fewer

grains set per ear. In contrast, barley had much higher levels of small grain.

Oats and canola were most aff ected by the season with very low grain yields and biomass for oats leading

to shortfalls in grain and hay production. While canola yields were lower than normal, the drier conditions

and lack of waterlogging appears to have helped off set lower yields from the poor rainfall in the traditionally

higher rainfall areas. The medium-to-low rainfall wheatbelt saw canola yields at less than 400 kg/ha with many

down to zero where rainfall was less than 100 mm for the growing season.

The global surprise this year was the drought in Russia, which saw a major price increase for wheat in spring,

while Argentina also had some weather related problems.

The wet conditions in the eastern states from the La Nina event have also supported grain prices as the quality

of many of these crops has been downgraded.


3

My experience in a drought as a farmer and consultant

Bill CrabtreeMorawa, Western Australia

Background

During December 2007, I purchased 2750 ha of arable land 38 km north-east of Morawa, Western Australia

with the assistance of Rabobank and my father James. The farmland borders the edge of the rangeland and

I estimate the long-term annual rainfall to be 305 mm. The farm had not been farmed much at all for the

previous eight years from the year 2000 and fi ve of these years were quite dry.

I believe that where I farm that drought is the main annual challenge. Drought has been a problem in all my

three years of farming despite two of these years (2008 and 2009) having ‘average‘ rainfall. The drought is for

three main reasons: the low-rainfall area (with spasmodic and irregular rainfall), the medium to heavy nature

of much of the soil and the strong evaporation rates of the region. Frontal rains have been generally weak or

non-existent before early May and from mid-August onwards.

The risk of frost is minimal. However, if wheat is sown in mid-April any subsequent warm weather during early

May, which is common, can cause the crop to bolt and fl ower during late June. This then predisposes the crop

to the most probable week of a slight frost, being during early July. Such mild frosts have occurred in all of my

three farming years.

The 2008 crop experience

We established our fi rst crop during 2008, after some good summer rain storms, and one very important

rain event at the end of April (24 mm on April 28). We were not able to capitalise fully on this important and

isolated rain event. This was due to:

1. No stubble cover to hold the water on sloping land and much of it ran off , as did a signifi cant proportion

of the summer rainfall.

2. The canola was sown before this heavy April rain and was unable to emerge properly as the soil had

sealed over (there was no stubble to reduce the raindrop impact).

3. The surface soil dried within a week and only crop planted before this rain or in the following seven days

emerged.

4. We had lots of rock heaps to shift, rocks to pick, fences to remove, cabling to do, and 2–4 m high shrubs

that had grown in the paddocks needed removing. All these were important distractions.

5. Many small trees and bluebush had grown across the farm and these took months to remove.

6. Attempts at night seeding did not work and always resulted in reseeding the next day.


4

There was no further rain for seven weeks. Some 75% of the farm emerged on this second rain. What was

sown during late April (wet or dry) yielded 2 t/ha and what was sown after May 6, 2008 did not emerge

until the rain on the June 9. This highlighted to me the value of dry seeding. Good soil nitrate levels meant

nitrogen (N) requirements were low. I used MAP fertiliser at 30 kg/ha and applied 13 L/ha of UAN. I didn’t use

trefl an, but I should have done so on at least 10% of the farm. Some broadleaf sprays were used.


Again, during 2009 we had good summer rains and summer weeds germinated everywhere, even on top of

the hills — unlike the previous year. I believe the no-till furrows and the full stubble cover held the water on

higher ground and gave it time to soak in evenly across all paddocks. A successful summer spray strategy was

implemented. On the May 20, 2009 it started raining, a total of 25 mm fell and with good summer rain stored,

measured at 50 mm, the season was off to a fl ying start. Good rains continued and then, in three weeks from

late July, 120 mm of rain fell.

This wet period was a lost opportunity for me. With such a tight budget I could only aff ord 15 kg/ha of DAP

and I was challenged to fi nd further funds to apply 40 kg/ha of urea and 10 kg/ha of ammonium sulphate. I

secured a contractor to do the spreading and he arrived three days late and then, as he arrived, so did my

biggest rain and he got bogged and left and then it stopped raining. The low rates of applied phosphorus (P)

and low nitrogen, the leaching rains and the yellowing crop was painful to watch.

What made things worse was the seeder bar that I was using gave poor seed placement. While 80% of the

programme emerged well, perhaps 20% was poor. In some soils the bar dug in too much and Wyalkatchem

wheat’s short coleoptiles could not emerge. On some areas I had only 20 plants/m2 of wheat and what few

ryegrass plants were there made the most of the space and no trefl an.

It is amazing how quickly things can go from looking and feeling very good during late July to nitrogen-

defi cient crops and weeds taking over in places by mid-August. Who would want to be a farmer . After

scrambling to get the urea on myself, there was little rain to wash the nitrogen into the soil and to fi nish the

crop. During the last fi ve rain events for the year, only 20 mm of rain fell. The crop yielded 1.2 t/ha and the

prices had fallen to about $220/t and noodle wheat was $200 — so I threw noodles out . I managed to pay

all my bills, but it was not the year it looked like it would be.


The drought of 2010 was my most nervous farming experience and, as it turned out, probably the one I

managed the best. My knowledge of practical farming has matured, many thanks to the great mentoring

from my oldest brother Geoff , who is a maintenance whiz and has an incredible work ethic. I secured lots of

DAP, at the right time, for $500/t from Ravensdown through an Emerald grain agreement. I applied 60 kg/ha

of DAP and 30 L/ha of UAN and the canola had 90 kg/ha of crystal AmSul.

The Perth storm, on March 22, 2010 dropped 38 mm of rain. I sprayed the whole farm and possibly stored

15 mm of this. Given my short history of low herbicide use and two years of healthy weed emergence, I now

have ryegrass and radish in low numbers on most paddocks. I fi xed my seeding depth problems with Agmore

boots — they gave aff ordable and reliable seeding depth control in all crops.

With minimal subsoil moisture and no rain in sight until late May and wheat predicted to drop to $180/t things

were not looking good. We kept dry seeding steadily from Anzac Day, despite one of my employees wanting

me to go hard and fast and through the night. There was no rain in sight until May 22, this small rain event of

6–8 mm, was enough encouragement to keep me seeding. Then on the June 1, I had just decided to fallow

my three heaviest paddocks if no more rain was probable. However, then there was more rain in sight so we

fi nished these on June 6.

The crops limped along through June and July with only 69 mm of rain falling for May, June and July and

mostly from small rain events. Then on August 13 and 31, two good events dropped 48 mm of rain. This

timing was good for the lighter soils, which had not yet experienced crop droughting. However, the earlier-

sown medium loams (my best soils) had already bolted and this extra rain made them put up late tillers that

only had 5–7 small grains in each tiller, which were sometimes barely harvestable as they only grew to half of

the height of the earlier tillers.


5

My wheat averaged 0.7 t/ha. One 300 ha paddock performed poorly as I had to plough it for tree control —

there were too many, too big and too tough for the cable technique. This paddock was sown last and with

lower fertiliser inputs also. On some sand areas I sowed triticale and it yielded 0.5 t/ha while the remaining

wheat went 0.35 t/ha.

I had 200 ha of canola, some of this went 300 kg/ha and some only 120 kg/ha. Slightly more stored moisture

gave the better result. The RR canola was a little better yielding than the TT (Cobbler) canola. A blocked

seeder head and no crop competition allowed silver grass to grow — I was not aware there was any in the

paddock as ryegrass was my focus. The ryegrass control was excellent, but I should have used trefl an in

patches as the plants were thick.

So what have I learnt about drought?

I have had drought experience in all my three farming years. Although each year has been a mind-twisting

challenge to learn from. Dry seeding is an important tool that needs to be used whenever possible. I have

learnt to not rely on follow-up rains, they may take six weeks to come and if you wait this long then it could

halve the crop yield. It is important to store summer rain, as everyone now knows. I remember coining the

phrase “summer spray to make your break early”, back during 1987 alongside Wayne Smith — as we learnt no-

till together.

Stubble is important for holding moisture evenly over the whole paddock in times of intense rainfall. I have

learnt to hold my nerve during dry periods at seeding and to be fl exible and consider chemical fallowing for

the most appropriate paddocks. Perhaps the most interesting thing I have learnt is the amount of thinking

that goes into a farming programme. There are so many options, limited dollars to work with and always lots

to do. I hope to share some more of these mind teasers in my verbal talk. I am glad to have a good knowledge

of crop agronomy, in particular soil texture and fertility to assist in decision making. I am hopeful of a wet year

to come and good crop prices and then who knows, I may sell . I hope these candid thoughts are useful.


6

Meeting the productivity and sustainability challenges to Australian agriculture until 2030

Peter CarberryCSIRO Sustainable Agriculture Flagship

Key Messages

• The challenge for Australian and International agriculture in the coming decades is to increase

productivity of agricultural lands, while adapting to new resource availability constraints, climate change

and greenhouse gas emissions.

• Current farming practices and their development through investment in science and technology have

helped sustain farming systems in Australia during the past 30 years.

• Productivity gains in the future need to come from improved system effi ciencies, better resource use

and novel technologies.

Global and Australian context

After two centuries of expanding food and fi bre production off the back of expanding land, water and energy

use, underpinned by innovation and technological change, Australian agriculture has reached a critical point.

Constraints are emerging in terms of resource availability and imperatives to reduce greenhouse gas emissions

and adapt to climate change. Hence the challenge for Australian agriculture is to maintain its productivity

in the face of such constraints. Meeting this challenge is essential both for the viability of Australian farming

communities as well as for Australia’s continued contribution to maintaining global food security.

Productivity growth in food and fi bre production has been fundamental to the past 50 years of agricultural

development both globally and in Australia. During this period, agricultural productivity growth in Australia

has been high relative to other sectors of the Australian economy and high relative to the agricultural sectors

in other OECD countries (Mullen, 2007). Australian farmers have outperformed the agricultural sectors in most

other countries, yet in contrast to these other regions, they farm, largely unsubsidised, on fragile soils and in

the most variable climate in the world. The impressive performance of Australian dryland agriculture has been

achieved via innovative research and development (R&D) leading to technology development and adoption.

Historically, such productivity growth has come both from improved farming practices and from breeding

better varieties. Australia clearly leads the world in technology development and innovation, particularly in

dryland farming systems.

Of real concern is the evidence of an emerging plateau in agricultural productivity both internationally and

in Australia, where the impressive annual productivity gains of the past 50 years are starting to slow. Clearly,

this represents a global challenge when demand for food production is projected to double by 2050 while, at

the same time, land and water resources will become increasingly constrained and there is likely to be limits

on greenhouse gas release to the atmosphere. These land, water, soil, energy and atmospheric constraints to

agriculture apply in Australia and represent a national challenge for farming systems during coming decades.

A return-risk framework

Dryland agriculture in Australia has adapted to an extremely variable climate. Keating et al. (2010) proposed

an approach to exploring returns on technology interventions relative to their riskiness. This return-risk

framework suggests that ’effi ciency frontiers‘ exist whereby the return on existing knowledge and technology

is maximised for diff erent levels of risk. The curves in Figure 1 are styled examples of such frontiers — the

lower curve is based on currently-known technologies and practices and the higher curve represents yet-to-

be adopted technologies, which create both new opportunities, and a new return-risk frontier. Figure 1 also

lists technologies that have or will in the future deliver productivity increases in Australian dryland agriculture

along three intervention pathways.

Firstly, system ineffi ciencies can be addressed to improve productivity with little or no additional risk (moving

from point B to point D in Figure 1). This pathway has been a signifi cant source of traditional productivity

improvement for industry over many years and leading Australian growers are now achieving yields that are

close to their attainable effi ciency frontiers. However, there is still likely room to move, especially in better


7

managing soil diseases. For instance, improved understanding of the biology of agricultural soils is a new

frontier, which is opened up by novel techniques such as functional genomics. Exciting research in this

domain promises the means of characterising the function of soil microbes, quantifying the consequences of

its poor management and pursuing opportunities to enhance agricultural performance.

Secondly, the effi ciency of resource use can be increased to maintain farm production at a constant level

while reducing risk (moving from D to C in Figure 1). In this context, managing climate risk in Australian

agriculture remains a key challenge. This can be achieved if growers can be fl exible and adjust their agronomic

and marketing management in order to avoid (in any one season) either over-investing in enterprises with

poor prospects or under-investing in enterprises with good prospects. Likewise, precision agriculture (PA) is

yet to have industry-wide impacts. Undoubtedly, to achieve increased resource use effi ciency in Australian

agriculture, improved management of spatial and temporal variation will require continued innovation in both

climate risk management and PA.

Thirdly, we must continue to invest in breakthrough technologies that can increase farm output without

increasing risk (moving from D to F in Figure 1). Gene technologies must be considered as one source of

‘breakthrough‘ innovations in agriculture particularly with the current signifi cant research investment into

genetically modifi ed (GM) crops. Also, matching the best crop and pasture cultivars or livestock breeds to

specifi c localities or soil types, and tailoring farm management practices to suit them, is being seen as a basis

for a genotype x environment x management (G x E x M) revolution that will push water use effi ciency and

enterprise performance beyond the current production frontier. Other emerging opportunities in Australian

agriculture will likely include new products or services, such as biofuels, forest-based carbon storage in

agricultural landscapes, bio-sequestration of carbon in agricultural soils, and environmental stewardship

schemes that would reward farmers for nature conservation and related non-production services from

farming land (Keating and Carberry, 2010).

Figure 1. Return-risk framework and technologies which either (a) impacted on Australian dryland agriculture from 1980–2010 or (b) are identifi ed as having potential to impact between 2010–2030. In both fi gures, A and D are representative points on the effi ciency frontier for the best technologies at a point in time ( ) and C and F are specifi c points on new effi ciency frontiers for hypothesised new technologies (- -). Point B represents a position below the current effi ciency frontier. (Taken from Carberry et al., 2010)

Discussion

The greatest emerging opportunity for Australian agriculture must be sought from productivity breakthroughs

in the face of current and emerging constraints. Such breakthroughs will likely emerge from continued

investment in agricultural R&D to produce new genetics and management practices. It is only through major

advances in the effi ciency with which limiting resources such as land, labour, water, energy and nutrients are

used in the production process that opportunities will be created to increase the supply of other outputs such

as carbon bio-sequestration and environmental services.


8

Key Words

Agricultural practices, return-risk framework

Acknowledgments

The basis of this paper is the publication Carberry P, Keating B, Bruce S and Walcott J (2010) Technological

innovation and productivity in dryland agriculture in Australia, A joint paper prepared by ABARE–BRS

and CSIRO, Canberra, July 2010, which can be sourced at http://adl.brs.gov.au/anrdl/metadata_fi les/pe_

abarebrs99000001.xml

Paper reviewed by: Allan Peake

References

Carberry PS, Bruce SE, Walcott JJ and Keating BA (2010) Innovation and productivity in dryland agriculture: a return-

risk analysis for Australia. Journal of Agricultural Science, Available on CJO December 22, 2010 doi:10.1017/

S0021859610

Keating BA and Carberry PS (2010) Emerging Opportunities and Challenges for Australian Broadacre Agriculture. Crop &

Pasture Science 61: 269–278.

Keating BA, Carberry PS, Bindraban PS, Asseng S, Meinke H and Dixon J (2010) Eco-effi cient agriculture: concepts,

challenges and opportunities. Crop Science 50: S–109–119.

Mullen JD (2007) Productivity growth and the returns from public investment in R&D in Australian broadacre agriculture.

Australian Journal of Agricultural and Resource Economics 51: 359–384

New Crop Varieties


10

National Variety Trials (NVT) wheat variety performance - captivity vs broadacre

Peter BurgessKalyx Agriculture

Key Messages

• Two years of National Variety Trial (NVT) data show Mace is a widely-adapted wheat variety, which

performs consistently across a range of soil types and environmental conditions in the Western

Australian wheatbelt.

• The shorter maturity of Wyalkatchem has been an advantage over the longer maturity of Magenta in the

hot dry fi nish of 2009 and the drought of 2010.

• Magenta is a variety that requires a longer growing season to reach yield potential and provide reduced

screening levels.

• Katana is a dark horse, which may require further evaluation and market appraisal to provide the variety

a position in the marketplace.

• Scout shows great adaptation in southern regions.

• The data suggest, and market signals indicate, that Fortune is a suitable replacement for Calingiri.

• Westonia is an eff ervescent variety and has little competition as yet in its quality and maturity group.

Background and Aims

The wheat National Variety Testing (NVT) is part of a multi-crop evaluation programme funded by the Grains

Research and Development Corporation (GRDC) and is designed to evaluate wheat varieties entering the market

that have gone through selection and evaluation within the various national breeding programmes. The NVT

wheat trials are essentially the shopfront for growers to select wheat varieties based on yield and quality.

To evaluate a number of wheat varieties across a range of soil types, rainfall zones and environmental

conditions in order to test their suitability and adaptability to the Western Australian wheatbelt.

Method

All trials are sown and harvested as close to or before district grower practice to ensure variety performance

is similar to that seen by growers on farm. The trials are treated with basal fertiliser and urea rates typically

and signifi cantly higher than growers would use. Weed-control rates and combinations of herbicide are also

typically higher than grower practise.

The wheat varieties are grown to their full yield potential and as a consequence yield is not limited by nutrition

or weeds. These trials are not grown with a view to carrying a gross margin analysis.

Results

The results are presented in terms of an average of variety ranking across sites within ‘Agzones’ rather than

absolute yields as it represents a much fairer assessment of variety performance. Results can be skewed when

high yields are achieved by a variety at one or two sites (usually ideal growing conditions) within an Agzone.

When using only yield fi gures, one or two high yields can increase a variety ranking, when in actual fact it was

not a consistent performer across all sites.

For the second year running Mace has topped the NVT across all Agzones and performs consistently across

all main soil types and a wide range of environmental conditions. It also shows greater adaptability in the

southern Agzones 3 and 5 compared with Wyalkatchem during the past two years.

The commercial release of Magenta has seen it tackle two less-than-favourable seasons. Its maturity length

requires a longer growing season with a cooler wet fi nish, neither of which has occurred during the past

two seasons. Although not shown here, Magenta has consistently higher screening levels compared with

Wyalkatchem, which is the industry benchmark for seed size and the new variety on the block — Mace.


11

Market signals during 2010 have seen Calingiri growers benefi t from retention of the variety. Before this,

market signals were such that Calingiri needed to be replaced. Fortune is a variety that may provide the

required replacement as indicated in the variety ranks of 2009 and 2010. It is now up to growers wishing to

stay in the noodle market to carry out their own wide-scale testing and get to understand the fi ner points of

Fortune agronomy.

It is a bit of a ‘toss of a coin’ requiring grower experience and comparing of disease resistance attributes as to

whether Arrino or Binnu is the shorter-maturity noodle variety of choice in Agzone 1, 2 or 4. Yandanooka is a

little off the pace compared with these varieties in these Agzones during the past two years. Not much to say

about this variety, other than grower adoption levels are very low compared with other mainstream varieties.

The data shows Katana has performed reasonably well in Agzones 1 to 5 during 2009 and 2010. Katana is a

dark horse, which may require further evaluation and market appraisal to provide the variety a place in the

market.

The LongReach APW variety Scout shows great adaptation in Agzones 3, 5, and 6 compared with Yitpi during

the past two seasons. This variety shows similar susceptibility to yellow spot as Yitpi and growers probably

should avoid wheat-on-wheat rotations with this Scout.

The data suggests, and market signals indicate, that Fortune is a suitable replacement for Calingiri and King

Rock will provide the same level of replacement for Bonnie Rock in specifi c areas of Agzones 1, 2 and 4.

Many coded Westonia type varieties from the various breeders have been presented to growers at the spring

fi eld days during the past couple of years. Westonia continues to be an eff ervescent variety performing

reasonably well across much of the State. There is yet to be a named variety to knock this variety off its perch

in this maturity group. Zippy’s maturity length is a little too short for most seasons, however it came to the

surface in some Agzones during the 2010 drought.

Key Words

NVT, wheat, variety trials, Agzone

Acknowledgments

The Grains Research and Development Corporation (GRDC), Australian Crop Accreditation System Limited

(ACAS), GGA, grower groups and grower co-operators.

Project No.: KAL00003

Paper reviewed by: Peter Carlton


12

Tabl

e 1.

Com

paris

on v

arie

ty ra

nkin

g fo

r yie

ld w

ithin

Agz

ones

Varie

ties

Stat

eAg

zone

1Ag

zone

2Ag

zone

3Ag

zone

4Ag

zone

5Ag

zone

6

2009

2010

2009

2010

2009

2010

2009

2010

2009

2010

2009

2010

2009

2010

Tota

l no

of

varie

ties

4242

2726

3534

3730

3031

3837

3432

Arr

ino

10

10

86

67

26

14

72

23

25

No

t

gro

wn

No

t

gro

wn

Bin

nu

51

64

92

17

17

23

41

22

22

65

21

Ca

ling

iri

17

23

11

17

19

22

10

72

12

52

41

57

19

Fort

un

e1

99

12

13

26

10

16

13

27

16

67

13

6

Yan

da

no

oka

27

22

18

15

28

13

35

14

26

18

19

28

No

t

gro

wn

No

t

gro

wn

Ma

ce1

12

13

13

41

11

83

14

Ma

ge

nta

81

83

19

71

67

17

10

17

21

25

14

7

Wya

lka

tch

em

36

64

43

13

17

51

11

32

16

23

AG

T K

ata

na

(RA

C 1

42

3)

11

48

31

21

19

11

36

81

22

41

6

EG

A B

on

nie

Ro

ck2

01

31

65

15

14

11

16

19

10

33

29

25

10

Kin

g R

ock

(IG

W 2

97

5)

18

15

15

81

32

02

21

71

51

32

81

92

91

2

Co

rre

ll2

23

12

6N

ot

gro

wn

24

No

t

gro

wn

17

No

t

gro

wn

21

No

t

gro

wn

92

19

9

Sco

ut

LPB

05

-11

64

)

16

24

27

No

t

gro

wn

27

27

53

16

No

t

gro

wn

21

11

5

Yit

pi1

21

17

24

18

20

15

14

21

25

19

16

17

12

7

We

sto

nia

45

15

81

27

12

72

09

11

13

Zip

py

15

72

12

10

93

31

91

23

17

22

No

t

gro

wn

No

t

gro

wn

Bu

mp

er

22

68

11

12

42

26

31

52

No

t

gro

wn

42

6

Gu

ard

ian

12

14

19

No

t

gro

wn

17

14

48

91

44

41

58


13

WALAN2289 — a new lupin variety to replace Mandelup in the system

Bevan Buirchell Department of Agriculture and Food, WA

Key Messages

• New lupin variety WALAN2289 will provide a suitable replacement for Mandelup throughout Western

Australia.

• The average yield of WALAN2289 is 102% of Mandelup — with a range of 98 –108%, with much less pod

shatter.

• The new lupin variety shows resistance to anthracnose and is equally as tolerant to metribuzin as

Mandelup.

• WALAN2298 shows resistance to phomopsis, bean yellow mosaic virus (BYMV) and seed transmission of

cucumber mosaic virus (CMV) is lower than Mandelup but still moderate.

• WALAN2298 is susceptible to grey spot.

Background and Aims

The national lupin breeding programme based at the Department of Food and Agriculture Western Australia

(DAFWA) and now under the umbrella of Pulse Breeding Australia (PBA) has successfully produced improved

lupin varieties to support the lupin industry. The breeding programme produces superior breeding lines,

which are tested Australia wide in the national variety trials (NVT) to identify lines suitable for release as

commercial varieties. This paper presents the results relating to the next line destined for release as a

commercial variety.

Method

The NVT trials are the fi nal stage of evaluation of breeding lines from the lupin breeding programme. These

trials occur at 16 sites throughout WA plus up to 22 sites covering South Australia, Victoria and New South

Wales. Approximately 30 new lines are promoted into the NVT trials every year with the equivalent number

eliminated from the trials based on poor performance against benchmarks such as: yield, disease resistance,

herbicide tolerance and quality.

Results

WALAN2289 (01A012R-65) comes from a complex cross but the main female parent was tested in the NVT as

WALAN2127.

Yield comparison

WALAN2289 produced competitive yields in most zones, with an overall performance of 102% of Mandelup.

It has performed best in the northern zones 1, 2 and 3 where it is 108%, 104% and 106% of Mandelup,

respectively (see Table 1). All these trials were harvested as soon as possible after maturity.


14

Table 1. Yield comparison of WALAN2289 in NVT trials across Western Australia during 2006–2009. The results are expressed as a % of Mandelup

Zone 1 2 3 4 5 6 7 8 Overall

Variety % n % n % n % n % n % n % n % n % n

Mandelup 100 7 100 11 100 6 100 7 100 10 100 6 100 7 100 4 100 58

Belara 91 7 90 10 88 4 91 7 84 10 94 6 87 8 97 3 90 55

Coromup 102 6 101 9 94 4 88 7 91 8 92 5 95 7 89 3 94 49

Danja 83 4 90 8 86 3 75 5 79 5 84 4 78 4 77 3 82 36

Jenabillup 107 7 99 10 105 4 108 7 96 9 100 5 100 7 103 3 102 52

Tanjil 96 7 94 10 93 4 88 11 85 10 95 6 95 9 85 3 91 60

WALAN2289 108 6 104 9 106 4 104 7 98 8 102 5 98 7 104 3 102 49

WALAN2325 103 3 104 5 109 2 88 1 97 3 108 1 102 2 95 1 101 18

WALAN2289 performed well across the years 2006 to 2009, all of which had reasonable fi nishes. During 2010

WALAN2289 did not perform as well as Mandelup in the north and this may be due to the slower pod setting

ability of WALAN2289, which would have been compromised during 2010 due to the lack of rain during pod

fi ll. WALAN2289 is related to Tanjil and has similar pod setting characteristics. It also seems to perform better

on deeper sands than on the red soils, which also is similar to Tanjil.

Quality parameters

WALAN2289 meets quality standards with seed alkaloid content similar to Mandelup and Coromup; seed

protein content similar to Tanjil and above Mandelup and Belara; seed size is similar to Tanjil (see Table 2).

Table 2. Comparison of 100 seed weight, alkaloid content and protein content of WALAN2289 with common lupin varieties

Variety 100 seed weight(mg) - 2009

Alkaloid content (% ar) - 2007–2009

Protein content(% ar) - 2009

Belara 140 0.009 30.8

Coromup 148 0.011 34.5

Danja 122 0.015 32.3

Jenabillup 146 0.009 31.9

Mandelup 142 0.012 31.2

Tanjil 126 0.014 32.9

WALAN2289 128 0.011 32.4

WALAN2325 132 0.011 30.2

Disease resistance

WALAN2289 is moderately resistant to anthracnose, which is similar to Mandelup, and would allow this variety

to be grown in most areas of the State except the coastal northern region (Zone 1) where anthracnose is

present in wild lupin populations. It has level of resistance to phomopsis stem blight similar to that of Tanjil.

It is not as resistant as Tanjil or Mandelup for seed transmission of cucumber mosaic virus (CMV) with its

resistance being equivalent to that of Kalya. Its resistance to bean yellow mosaic virus (BYMV) is moderate but

not as good as Jenabillup. WALAN2289 is susceptible to grey spot, but this is a disease not seen in WA since

the early 1980s, when lupin crops were grown in closer succession. Grey spot it is not considered a threat to

growing this new variety.


15

Non-shattering features

The pods of Mandelup sometimes split when the crop is left in the fi eld too long after maturity. The split

pods drop seeds, subsequently reducing the harvested yield. Since the release of Mandelup, the breeding

programme has been evaluating advanced lines left standing in the fi eld post maturity to gauge their ability

to resist pod splitting. Results will be presented to show that WALAN2289 experiences far less pod splitting

under these circumstances and should be able to be harvested in a fashion that fi ts in with normal farming

operations without signifi cant loss of yield.

WALAN2289 has the same tolerance to metribuzin as Mandelup.

Discussion

WALAN2289 has superior yields to Mandelup and, with the added advantage low pod splitting, makes this

new variety a better fi t in the farming system.

Currently there is 2.9 tonnes of pedigree seed of WALAN2289, which will go to a commercial partner for

bulking up during 2011. We expect some seed to be available to growers during 2012.

Key Words

Lupin, variety, WALAN2289, yield

Acknowledgments

This research has been supported by the Grains Research and Development Corporation (GRDC) and DAFWA.

Project No.: DAW00181

Paper reviewed by: Peter White


16

The strengths and pitfalls of different grades of new wheat varieties in Western Australia

Ben Curtis, Sarah Ellis, Brenda Shackley, Christine ZaicouDepartment of Agriculture and Food, WA

Key Messages

• Performance of Mace/Wyalkatchem during 2010 was exceptional despite the dry conditions.

• Magenta performance was variable in this diffi cult season. Magenta requires growing conditions

that suit its longer maturity. For early seeding, Magenta is a suitable option, but it appears to be quite

susceptible to sprouting.

• New imidazolinone-tolerant variety (RAC1683) shows promise.

• There is renewed interest in noodle wheat varieties after the past season’s high prices, but a conservative

approach is needed as the premiums received during 2011 could be lower.

• High-yielding mid-season varieties are still the most profi table ones to grow and provide growers with

higher yields if the season fi nishes strongly.

• Varieties Carnamah, Katana, Magenta and Axe had low falling numbers in the late harvest trial, despite

having no visual symptoms of sprouting.

• Phenology of diff erent varieties can change considerably depending on seasonal conditions bringing

forward or putting back fl owering times.

• New soft variety (Kunjil) has performed better than its parent line (2248).

• The wheat bulletin will be posted out to all WA growers and consultants during March 2011.

Aim

To assess the performance of recently-released wheat varieties during 2010, and where possible, provide

advice on reliability across recent successive seasons.

Method

Agronomy trials

Field-based time-of-sowing trials are carried at 11 sites across Western Australia each year. Twenty-four wheat

varieties, comprising known controls and recent release varieties in at least the second year of evaluation within

the national variety trials (NVT), are sown at three seeding times in a replicated, randomised split-plot design.

The full grain yield and quality results from 2010 are published in the Wheat Variety Guide 2011 Western

Australia. This publication will be posted to all growers in Western Australia during March 2011. Please refer to

the 2011 Variety Guide and previous guides in conjunction with this paper.

Phenology trials

Fifty wheat lines were sown in unreplicated, one-metre-long rows with three repeated checks on April 24,

2010, May 16, 2010, June 3, 2010 and June 20, 2010 at Northam, Geraldton and Katanning, WA to assess

phenology, or fl owering time response to seeding time. The proportion of heads showing anthesis (fl owering)

was recorded at 2–3 day intervals to calculate the fl owering date (50% of heads showing anthesis). These

same wheat varieties were also grown in a glasshouse in both increasing and degreasing day lengths with

vernalisation treatments and controls.

Falling numbers tests were carried out on varieties in the time-of-sowing trials at Esperance, Grass Patch and

Mt Barker during 2008 and at Mingenew during 2010.


17

Results and Discussion

Hard and APW wheat

Mace and Wyalkatchem yields were exceptional despite the dry conditions during 2010.

Magenta performance was variable, but it yielded very well in Mingenew. Magenta is a longer-season variety

and appears to perform best in early sowings and in locations with high potential yields.

Noodle wheat

The extremely high prices paid for noodle wheat during 2010 have put the spotlight back on this grade.

The shortage of noodle wheat was caused by signifi cantly lower plantings together with the poorer yields

achieved during the dry season.

Plantings of Calingiri wheat dropped from 9.7% of the total WA wheat crop during 2009–2010 to 5.5% in

2010–2011 (see Figure 1). Noodle plantings have been dropping due to the reduced premiums achieved

in this grade since 2007, however the extreme shortage last season caused a signifi cant turn-around in the

noodle price.

Growers should be cautious about committing to large increases in noodle production during 2011 because

large increases in overall State production could reduce the 2010–2011 premiums.

Percentage area sown to six wheat varieties grown in WA over the last five seasons (data from CBH)

0

5

10

15

20

25

30

35

Wyalka

tchem

Calingir

i

Arrino

Fortun

e

Magenta

Mace

% a

rea

sow

n 06/0707/0808/0909/1010/11

Figure 1. Percentage area sown to six wheat varieties grown in WA during the past fi ve seasons (data CBH).

Fortune wheat has a better end product quality than Calingiri. If premiums were paid for this variety, its

adoption may be more economic than Calingiri. Yields and screenings of Fortune were similar to Calingiri

during 2010, 2009 and 2008 at each seeding time in Mingenew, however this was not refl ected in the NVT

(2000–2009) where Calingiri was 3% higher yielding than Fortune in Agzone 1. The disease package for

Fortune is slightly better than for Calingiri, however sprouting risk is greater for Fortune than Calingiri. The

potential new noodle wheat (IGW 2944) performed similarly to Fortune and Calingiri.


18

Table 1. Yield and quality (protein and screenings*) of noodle wheats sown in Mingenew during 2010

Mingenew heavy land

Yield - (t/ha) Protein - (%) Screenings - (%)

May 15 June 2 May 15 June 2 May 15 June 2

Binnu 3.2 2.8 9.6 9.9 5.4 7.0

Fortune 3.1 2.6 10.8 11.2 5.9 4.8

IGW 2944 3.1 2.7 10.8 11.1 6.2 5.3

Calingiri 3.0 2.8 9.9 10.7 6.6 3.0

Wyalkatchem 3.0 2.9 10.5 11.1 3.3 3.3

Mace 2.9 2.7 10.9 10.6 3.8 5.2

%CV 5.6% 3.8 16.1

* Includes whole and cracked grain

Soft wheat

Kunjil (IGW3001) is a more rust-resistant derivate of EGA2248, which yielded well during 2010. Wedin

(IGW2873) is a non-club-head wheat similar in maturity to Bullaring. The longer-season varieties Wedin,

Bullaring and EGA Jitarning were not as competitive during 2010. However, EGA Jitarning was one of the

highest-yielding varieties at Frankland at all seeding times, indicating the late rain may have benefi tted this

variety. The varieties provide a range of maturities to select from, but soft wheats are more prone to excessive

screenings and tight protein requirements increase the risk of not meeting the grade. The tight protein

requirements were relaxed during the 2010 season, as soft wheat was accepted as ANW2 if the protein fell

between 9.5 and 11.5 %.

Imidazolinine-tolerant wheats

Two imidazolinine varieties were tested during the past season (AGT1683 and IGW 3097). AGT1683 has

consistently yielded better than IGW3097 across a range of sites and has been competitive with some of the

hard wheats.

Each of these lines contains two genes for imidazolinine resistance giving them extra crop safety for this group

of herbicides.

These wheats will potentially be used in weedy situations, such as after long pasture phases, or in situations

where populations of brome grass and silver grass are causing problems. Using these types of wheats might

also be considered if wheat is following Clearfi eld canola after a dry season, where some residual herbicide

might remain.

Phenology

DAFWA will soon release a web-based model that will ask the user to choose a variety, location and seeding

date allowing the model to predict a median fl owering date and demonstrate the variation in fl owering date

that might occur across diff erent seasons. Users will be able to compare varieties and their diff erent fl owering

dates in order to combine varieties that may help to reduce the risk of frost damage.

There are three main environmental infl uences that may aff ect the time a variety fl owers. These are: day

length, cold and heat (or the accumulation of temperature before a variety will fl ower — the basic vegetative

phase [BVP]). All three determinants must be met before a plant can fl ower, however, diff erent varieties have

diff erent reactions and dependencies on each of these factors.

Newly-released varieties are often assigned a maturity class of short, medium or long to help describe the

period of time it takes for the variety to fl ower. This may be convenient but not always accurate as fl owering

is determined by three main environmental factors. Wheat cultivars may be grouped into diff erent classes

according to their sensitivity to the controlling factors (see Table 2). The cultivars that appear in the same

group are likely to behave in a similar way, such as Spear, Stiletto and Yitpi.


19

The groupings may also help examine why varieties assigned a similar maturity can respond diff erently at

diff erent locations. Arrino and Binnu have a similar maturity, but Arrino tends to fl ower before Binnu in the

southern regions due to its medium response to BVP and Vernalisation VRN, while in the northern regions

there is less of an opportunity to satisfy Arrino’s VRN requirement so Binnu can fl ower earlier than Arrino.

There are some discrepancies to this inference (i.e. Arrino and Fortune are grouped similarly, but are assigned

diff erent maturity classes). However Table 2 provides a starting point to determine fl owering trends.

Scout has been assigned a similar maturity class as Yitpi by Long Reach, although it has a similar ‘preliminary’

grouping to Katana, except for a high vernalisation requirement, which explains why Scout can be quicker to

mature in the southern regions of WA (data not shown).

Table 2. Factors infl uencing the fl owering time of wheat varieties

Varieties Years BVP VRN Day-length sensitivity

Westonia 3 low low # low

Mace 2 low medium low

Wyalkatchem 3 low medium medium

Scout (LPB 05-1164) 1 low high low

Carnamah 3 medium low nil

Arrino 3 medium medium low #

Fortune 3 medium medium low

Magenta 3 medium very high medium

Calingiri 3 high medium low

Spear 3 very high nil medium

Stiletto 2 very high nil medium

Yitpi 3 very high nil medium

#: some variation in sensitivity between years

2010 Great Southern Regional Summary

The 2009 season was a tough year, but the 2010 season ended up even tougher with the growing season

rainfall (GSR) being well below average throughout the whole season. Between 15 mm to 35mm of rain fell

during mid-November - too late for much of the region and causing some problems with sprouting in areas

south of Katanning.

Unfortunately the trial at Lake Grace was not harvested as establishment problems would have made the

yields diffi cult to interpret.

During 2010 the average yields at Katanning declined by nearly 0.7 t/ha from May 27 to June 9 and then by

just above 0.4 t/ha on average for the June seedings. The yield penalty with delayed seeding at Frankland was

less due to the later seedings (June). The late rain had no eff ect on yield or quality as all seedings were still

green when the rain occurred.

Three varieties were released during 2010, two soft wheats (Kunjil and Wedin) and a preliminary APW Estoc.

(Kunjil) was the highest-yielding variety, or among the highest-yielding varieties, at Katanning (not examined

at Frankland). Estoc yielded similar to Calingiri at Katanning and Frankland, however Calingiri yields where well

below the highest-yielding varieties.

The season generally favoured the medium to shorter-maturing varieties. Mace and Wyalkatchem were

consistently the highest-yielding varieties at both sites. Magenta was among the high yielding-varieties at the

late May seeding time at Katanning, but its performance was disappointing elsewhere. During other years the


20

performance of Mace and Magenta have been comparable, with Magenta having an advantage over Mace

when sown during May.

Noodle wheat

The 2010 season saw extremely high prices being received by noodle wheat, putting the spotlight back

on this grade. Shortage of wheat for this grade was compounded by a strong movement of growers out of

growing Calingiri during 2010. Take care when considering the move back into the industry, as the premium

could be short-lived. Growers considering the move may be interested in Fortune, for which the Grain Pool

has exclusive marketing rights.

Fortune yielded slightly higher than Calingiri during 2010, previous results indicated the yields to be similar

but with Calingiri having the yield advantage when sown during May. Generally Fortune is slightly shorter in

maturity than Calingiri.

Soft wheat

Kunjil (IGW3001) is a more rust-resistant derivate of EGA2248, which yielded well during 2010. Wedin

(IGW2873) is a non-club-head wheat similar in maturity to Bullaring. The longer-season varieties Wedin,

Bullaring and EGA Jitarning were not as competitive during 2010. However, EGA Jitarning was one of the

highest-yielding varieties at Frankland at all seeding times, indicating the late rain may have benefi tted this

variety. The varieties provide a range of maturities to select from, but the soft wheats are more prone to

excessive screenings and tight protein requirements increase the risk of not meeting the grade. The tight

protein requirements where relaxed during 2010 as soft wheat was accepted as ANW2 if the protein fell

between 9.5 and 11.5%.

Grain quality

As the season was ‘tight’ all year, small grain screenings were not an issue in the Great Southern. Wyalkatchem

has the least risk of having problems with screenings while Fang was still more prone to higher levels of

screenings. Screenings for Mace and Magenta were both low. The soft wheat club head Bullaring was more

predisposed to screenings than the other soft wheat varieties.

Katanning Agzone 2/3: (see Table 3)

Paddock history: 2009 lupin; 2008 wheat

Soil description: Sandy duplex with clay at 25 cm

Rainfall (mm): GSR (May–October) 191 mm

Times of seeding: May 27, 2010, June 9, 2010, June 25, 2010

Comments: Establishment was excellent for all planting times, averaging 160 plants/m2. Weed control was

good. The site was stressed during October with only 6 mm of rain and a number of days at 30°C. A total of 15

mm of rain fell during mid-November, causing some sprouting.

Frankland Agzone 3: (see Table 4)

Paddock history: 2009 canola

Soil description: Sandy gravelly duplex with clay at 20 cm


Times of sowing: June 2, 2010, June 16, 2010 June 30, 2010

Comments: First seeding time was sown later than the crops in the surrounding area. Plant establishment was

excellent, averaging 190 plants/m2. October recorded a frost event and a number of days with temperature up

to 30°C.


21

Tabl

e 3.

Eff e

ct o

f see

ding

tim

e on

yie

ld, q

ualit

y (p

rote

in a

nd s

cree

ning

s) a

nd e

cono

mic

retu

rns

of w

heat

var

ietie

s at

Kat

anni

ng d

urin

g 20

10

Gra

in y

ield

- (t

/ha)

Prot

ein

- (%

)Sc

reen

ings

(who

le) -

(%)

Pric

e - (

$/ha

)

May

27

June

9Ju

ne 2

5 Av

.M

ay 2

7Ju

ne 9

June

25

Av.

May

27

June

9Ju

ne 2

5 Av

.M

ay 2

7 Ju

ne 9

25 Ju

ne

AH

Ca

rna

ma

h2

.84

2.5

02

.10

2.48

13

.61

5.1

14

.714

.40

.80

.40

.20.

51

14

91

01

18

52

Kin

g R

ock

3.3

22

.54

1.9

82.

611

3.1

16

.21

6.3

15.2

1.6

0.9

0.2

0.9

13

34

10

19

79

5

Ma

ce3

.65

2.8

62

.51

3.01

11

.11

3.7

13

.312

.70

.30

.90

.40.

51

24

71

15

01

00

9

Yit

pi

3.2

82

.38

2.1

22.

591

3.4

16

.11

5.1

14.9

0.3

0.4

0.3

0.3

13

27

96

08

58

APW

En

du

re2

.28

2.0

61

.45

1.93

13

.91

4.7

15

.014

.50

.40

.30

.30.

37

81

70

34

96

Esp

ad

a3

.27

2.4

82

.20

2.65

13

.11

5.9

13

.914

.30

.40

.80

.60.

61

12

18

50

75

4

Est

oc

(RA

C1

21

4)

3.1

92

.44

2.1

22.

581

3.5

15

.81

5.6

15.0

2.2

2.1

0.8

1.7

10

27

74

76

22

Fan

g3

.00

2.1

81

.82

2.34

12

.21

5.3

14

.714

.14

.32

.31

.02.

51

14

78

46

69

6

Ma

ge

nta

3.1

02

.24

1.8

52.

321

3.7

14

.81

5.1

14.5

0.4

0.5

0.6

0.5

11

03

93

77

31

Sco

ut

3.2

22

.74

2.1

42.

701

2.4

13

.81

5.2

13.8

2.2

2.1

0.9

1.7

10

04

*7

67

63

4

Wya

lka

tch

em

3.5

42

.97

2.1

92.

901

2.4

13

.31

4.3

13.3

0.2

0.4

0.2

0.2

10

92

83

37

25

Ka

tan

a#

3.3

52

.47

2.0

42.

621

3.3

15

.51

5.7

14.8

0.8

0.6

0.6

0.6

12

16

10

17

75

2

ASWN

Ca

ling

iri

3.1

32

.37

2.0

72.

521

2.3

14

.81

5.0

14.1

0.3

0.3

0.3

0.3

14

73

11

12

97

5

Fort

un

e3

.24

2.7

42

.32

2.77

13

.11

4.9

16

.114

.70

.70

.60

.40.

61

51

41

28

11

08

5

AS

FT

Bu

llari

ng

2.9

72

.29

1.8

92.

381

2.3

13

.51

3.7

13.2

2.3

4.8

4.5

3.8

13

88

10

72

88

5

EG

A2

24

83

.34

2.7

62

.37

2.82

11

.81

2.8

13

.112

.64

.71

.30

.82.

31

55

71

28

81

10

3

EG

A J

ita

rnin

g2

.89

2.2

31

.86

2.33

12

.01

4.0

14

.013

.30

.81

.50

.61.

01

35

11

04

38

69

Ku

njil

(IG

W3

00

1)

3.4

33

.00

2.7

03.

041

1.5

12

.61

2.4

12.2

3.2

2.3

1.2

2.2

16

02

13

99

12

60

We

din

(IG

W2

87

3)

3.0

42

.34

1.8

02.

391

2.3

13

.71

3.1

13.0

2.4

3.0

1.8

2.4

14

20

10

93

83

7

Ave

rag

e w

ith

in e

ach

TO

S3

.10

2.4

02

.00

2.50

13

.01

4.9

14

.914

.31

.41

.10

.61.

0

TOS

(ls

d)

0.6

1

.9

0.9

Va

r (l

sd)

0.2

0

.7

0.7

Va

r (l

sd)

be

twe

en

TO

S0

.6

2.0

1

.4

Va

r (l

sd)

wit

hin

TO

S0

.3C

V%

8

1.2

CV

%6

1

.2C

V%

68

# =

pe

nd

ing

cla

ssifi

ca

tio

n


22

Tabl

e 4.

Eff e

ct o

f see

ding

tim

e on

yie

ld, q

ualit

y (p

rote

in a

nd s

cree

ning

s) a

nd e

cono

mic

retu

rns

of w

heat

var

ietie

s at

Fra

nkla

nd d

urin

g 20

10

Gra

in y

ield

- (t

/ha)

Prot

ein

- (%

)Sc

reen

ings

(who

le) -

(%)

Pric

e - (

$/ha

)Ju

ne 2

June

16

June

30

Av.

June

2Ju

ne 1

6Ju

ne 3

0Av

.Ju

ne 2

June

16

June

30

AvJu

ne 2

Ju

ne 1

6Ju

ne 3

0

AH

Ca

rna

ma

h2

.64

2.0

61

.46

2.05

11

.71

1.9

12

.31

2.0

78

79

80

79

99

17

73

54

6

EG

A E

ag

le R

ock

2.2

01

.57

1.4

91.

751

3.6

14

.01

4.0

13

.97

97

98

07

98

87

63

05

99

Kin

g R

ock

2.6

12

.03

1.5

22.

051

2.5

12

.91

3.8

13

.17

98

18

38

19

69

75

46

11

Ma

ce2

.97

2.3

41

.92

2.41

10

.61

0.8

11

.01

0.6

79

81

83

81

10

14

80

16

56

Yit

pi

2.4

81

.56

1.4

11.

811

2.9

13

.61

4.0

13

.58

08

18

28

19

26

63

05

68

APW

Ca

rin

ya2

.67

1.9

81

.74

2.13

11

.31

2.0

12

.11

1.8

80

82

84

82

91

66

80

59

6

En

du

re2

.19

1.8

41

.44

1.82

11

.91

20

51

2.3

12

.28

38

48

58

47

48

62

84

94

Est

oc

(RA

C1

21

4)

2.3

91

.94

1.8

22.

051

1.5

12

.21

2.0

11

.98

08

18

48

27

00

62

34

85

Fan

g2

.05

1.8

21

.42

1.76

12

.61

3.3

13

.31

3.0

81

82

84

82

84

26

52

49

1

Ma

ge

nta

2.7

71

.92

1.5

62.

081

1.7

12

.01

2.1

11

.98

18

28

48

27

07

54

95

25

Sco

ut

2.0

71

.60

1.5

31.

731

2.4

13

.11

3.8

13

.18

08

38

48

29

48

65

65

33

Wya

lka

tch

em

3.0

22

.29

1.4

82.

261

2.4

13

.31

2.8

12

.88

08

18

38

18

16

66

56

21

Ka

tan

a#

2.4

61

.91

1.4

41.

941

0.7

11

.71

2.4

11

.67

98

08

28

01

03

57

86

50

7

ASWN

Ca

ling

iri

2.4

11

.96

1.5

71.

981

1.4

11

.51

2.3

11

.78

28

38

38

21

15

59

39

73

8

Fort

un

e2

.68

2.0

31

.89

2.20

11

.81

2.3

12

.41

2.2

80

81

83

81

12

50

95

08

84

AS

FT

EG

A J

ita

rnin

g2

.88

2.3

01

.71

2.29

10

.71

1.3

11

.31

1.1

78

80

81

80

13

44

10

73

79

8

We

din

(IG

W2

87

3)

2.6

92

.17

1.7

42.

201

2.2

12

.31

2.2

12

.27

77

98

07

91

25

71

01

48

13

FE

ED

Pre

sto

nA

#2

.25

1.7

11

.31.

751

1.5

12

.61

2.5

12

.27

87

87

97

87

58

57

64

40

Ave

rag

e w

ith

in e

ach

TO

S2

.55

1.9

91

.60

2.05

11

.91

2.6

12

.81

2.4

80

81

83

81

TOS

(ls

d)

0.1

0 .2

0.2

Va

r (l

sd)

0.3

0 .5

0.6

Va

r (l

sd)

be

twe

en

TO

S0

.5

0

.9

1

.1

Va

r (l

sd)

wit

hin

TO

SC

V%

15

C

V%

4.5

C

V%

0.8


23

2010 South Coast and Central Regions Summary

Dry seasonal conditions aff ected wheat variety performance across all sites in the south coast and central

agricultural regions during 2010.

At the high-yielding, high-rainfall Gibson site the dry, diffi cult start to the season caused poor establishment

of the earliest sown wheat (May 17, 2010 average 4.4 t/ha) whereas the later-sown June 8 planting averaged

signifi cantly higher 5.2 t/ha. The highest yields were from soft wheats. Bullaring, a club-headed wheat,

performed well at each seeding time and was highest yielding overall. Other varieties to perform well included

Yitpi, Magenta, Mace, Binnu and Wedin. Locally-popular Sapphire was among the lowest-yielding varieties.

Although harvest was generally dry, with minimal rainfall, a few varieties had a falling number below 300

(milling receival standard) despite showing no signs of sprouting. This may have been in part because of a

series of heat–cold shocks through grain fi ll during October and November causing enzymatic problems

in the grain. Varieties most aff ected were Carnamah, Katana, Magenta and Axe. Grain quality analysis is

continuing in order to sort out the diff erences between varieties in the fi eld.

Table 5. Average yields in trials in the central and southern regions

Yield - (t/ha)

Site TOS1 TOS2 TOS3 TOS4 lsd

EDRS Gibson 4.41 5.23 4.5 0.56

Grass Patch 2.78 2.57 2.08 0.35

Merredin* 1.46** 0.55 0.70 0.60 0.55

Quairading 0.84 0.57 0.49 0.20

Wongan Hills 1.53 1.23 1.02 0.05

* The earliest time of sowing (TOS) at Merredin is irrigated to simulate an early break due to thunderstorms. The three other TOS receive

natural rainfall only.

** Yields for the irrigated treatment are artifi cially high due to extra ~50 mm at seeding during late April.

Apart from the irrigated treatment at Merredin there were few notable diff erences between varieties. With

average yields around 0.5 t/ha there is not much diff erence to be found — all varieties were water limited

and few are showing any other useful diff erences, such as heat tolerance or better carbohydrate translocation

ability. Again, the longer-season varieties Yitpi, Calingiri, Magenta and Endure were particularly poorly suited,

but there were no stand-out short or mid-season varieties that were high yielding in this tough year.

At Grass Patch 125 mm of rain during May caused localised fl ooding on-site, however there was minimal

damage to the trial thanks to replication. Best-performing varieties were Mace, Carinya, Derrimut, Scout and

Estoc. Largely, these varieties have performed consistently well on the alkaline soil sites during the past several

years. The dry spring and tight fi nishing conditions did not suit longer-season varieties such as Eagle Rock,

Calingiri and Endure.

Quairading suff ered a dry season with diabolical weed control problems. The dry early start and patchy rainfall

events through the season meant poor annual ryegrass control, which competed heavily with the crop all

year. Yields were low, averaging 0.4 t/ha to 0.8 t/ha (range 0.3 –1.0) and it is probably unwise to conclude

much from such data.

Yields at Wongan Hills contrasted sharply with DAFWA data of previous years. Unexpectedly, short-season

varieties, such as Axe, Zippy and an AGT breeding line WAGT065, were among the highest yielders for all three

seeding times. This may have been because of the miserable dry season and relatively late seeding times (May

31, June 14, July 8). Consistent with other sites during 2010 long-season varieties Fang and Magenta were not

well suited and yielded poorly.


24

2010 Northern Regional Summary

The 2010 season in Western Australia highlights the benefi ts of preparation and preparedness for seeding as

close to the break-of-season possible in the low- and medium-rainfall areas. The yield penalty with delayed

seeding from May 15, 2010 to June 2, 2010 at the Mingenew seeding time trial was 15 kg/ha/day. At East

Maya the yield penalty with delayed seeding from May 25, 2101 to June 15, 2010 was 22 kg/ha/day. However,

in the seeding time trial on the non-wetting sandy gravel at Badgingarra, the average yields did not decline

signifi cantly when seeding moved from May 17, 2010 to June 4, 2010. The yield penalty was 30 kg/ha/day,

when seeding moved from June 4, 2010 to June 23, 2010. The likely cause was drought-induced copper (Cu)

defi ciency at the earlier seeding time on the non-wetting sandy gravel.

In the lower-rainfall areas, screenings were a problem for crops reliant on winter rainfall, with limited

fi nishing rains. The season generally favoured the medium- to shorter-maturing varieties (for example, Mace,

Wyalkatchem, EGA Bonnie Rock and King Rock). Magenta was among the high-yielding varieties in the higher-

rainfall areas, however sprouting was a risk.

Noodle wheat

Fortune wheat has a better end product quality than Calingiri. If premiums were paid for this variety its

adoption may be more economic than Calingiri. Yields and screenings of Fortune were similar to Calingiri

during 2010, 2009 and 2008 at each seeding time in Mingenew, however, this was not refl ected in the national

variety trials (NVT) (2000–2009) where Calingiri was 3% higher yielding than Fortune in Agzone 1. The disease

package for Fortune is slightly better than for Calingiri, however sprouting risk is greater for Fortune. The

potential new noodle wheat IGW 2944 performed similarly to Fortune and Calingiri.

Unreleased wheats

A number of unreleased cultivars were assessed in the northern agricultural region (NAR) during 2010. The

two IMI wheats in the trial (AGT1683 and IGW3097) yielded similarly to Wyalkatchem and had similar, or lower,

screenings on the loam at Mingenew. However at Badgingarra (sandy gravel) and East May (sandy loam),

AGT1683 yielded signifi cantly higher than IGW3097. In general, the potential APW and hard wheats (IGW 3119,

IGW 3186 and IGW 3167) yielded similarly to EGA Bonnie Rock and King Rock at Badgingarra and East Maya.

Badgingarra Agzone 2 (see Table NAR1)

Paddock history: 2009 canola; 2008 wheat; 2007 lupins

Soil description: sandy gravel (non wetting)


Times of seeding: May 17, June 4, June 23

Comments: The performance of wheat varieties sown at the fi rst seeding time was infl uenced by drought-

induced copper defi ciency (visual assessment). These symptoms were not observed with the other seeding

times.

Mingenew Agzone 1 (see Table NAR2)

Paddock history: 2009 pasture; 2008 wheat; 2007 wheat

Soil description: loam


Times of seeding: May 15, June 2

Comments: Production at this heavy land site was outstanding during 2010 with a GSR of 197mm. Yield

response of the varieties did not diff er signifi cantly when sown on the May 15 or June 2.

East Maya Agzone 4 (see Table NAR 3)

Paddock history: 2009 peas; 2008 wheat


25

Soil description: red sandy loam


Times of seeding: May 25, June 15

Comments: During 2010, a season based on very low rainfall, the water use effi ciencies of the crops sown

on May 25 ranged from 30–38 kg/mm of rain (Note: evaporation was calculated at 2/3 of GSR). Screenings

ranged from 3.7% (Wyalkatchem @ 1.37 t/ha) to 11.5% (Magenta @ 1.56 t/ha). Delaying seeding to June 15

dropped WUE to 22–29 kg/mm of rain and screenings ranged with 9.9% Calingiri @1.08t/ha) and 26% (Binnu

@1.29 t/ha).

Tabl

e N

AR1

. Eff

ect

of s

eedi

ng ti

me

on y

ield

, qua

lity

(pro

tein

and

scr

eeni

ngs)

and

eco

nom

ic re

turn

s of

whe

at v

arie

ties

at B

adgi

ngar

ra d

urin

g 20

10

Yiel

d (t

/ha)

Prot

ein

(%)

Scre

enin

gs (%

)G

ross

Inco

me

($/h

a)

Varie

ty17

/05

04/0

623

/06

Av.

17/0

504

/06

23/0

6Av

.17

/05

04/0

623

/06

Av.

17/0

504

/06

23/0

6

Ma

ge

nta

3.1

2.5

2.2

2.6

11

.21

1.8

12

.711

.95

.75

.93

.85.

11

03

08

37

74

8

Fort

un

e2

.92

.62

.32.

61

1.6

11

.61

2.2

11.8

3.3

3.6

3.5

3.5

13

55

12

39

10

78

RA

C 1

68

32

.82

.72

.12.

51

1.9

12

.21

1.7

11.9

3.0

4.4

3.7

3.7

IGW

29

44

2.8

2.9

2.3

2.7

11

.91

1.2

12

.211

.84

.33

.83

.63.

9

IGW

31

86

2.7

3.0

2.3

2.7

12

.41

1.3

11

.111

.62

.33

.64

.93.

6

Esp

ad

a2

.62

.72

.22.

51

2.1

11

.91

2.2

12.1

4.5

5.6

3.8

4.6

89

18

89

74

6

Ca

ling

iri

2.5

2.5

2.0

2.3

11

.21

1.6

12

.311

.74

.63

.92

.63.

71

21

21

18

99

32

Wya

lka

tch

em

2.5

2.3

1.9

2.2

12

.21

1.8

11

.411

.82

.42

.74

.03.

18

71

78

46

46

An

nu

ello

2.5

2.4

2.1

2.3

11

.61

1.9

12

.812

.13

.33

.72

.13.

08

69

81

37

35

EG

A E

ag

le R

ock

2.5

2.6

2.0

2.3

12

.31

2.4

12

.412

.42

.52

.42

.52.

59

37

96

37

34

Ma

ce2

.42

.42

.12.

31

1.1

12

.61

0.9

11.5

3.2

3.6

4.3

3.7

90

98

96

72

8

We

sto

nia

2.4

2.7

2.1

2.4

11

.51

1.4

12

.011

.65

.55

.24

.14.

97

99

88

97

08

Ca

rna

ma

h2

.42

.72

.02.

41

1.2

11

.81

1.9

11.6

5.8

4.2

3.5

4.5

79

31

01

27

58

IGW

31

67

2.4

2.6

2.0

2.3

12

.71

1.6

12

.312

.25

.74

.66

.05.

4

Gla

diu

s2

.32

.41

.72.

11

1.5

12

.11

2.6

12.1

4.6

5.3

6.3

5.4

80

27

85

57

6

IGW

31

19

2.3

3.1

2.1

2.5

11

.81

1.4

11

.311

.53

.43

.74

.94.

0

IGW

28

86

2.2

2.5

1.9

2.2

12

.11

2.1

13

.012

.46

.67

.85

.16.

5

EG

A B

on

nie

Ro

ck2

.02

.52

.12.

21

2.1

12

.81

2.4

12.4

2.7

4.0

4.3

3.7

74

49

31

78

5

GB

A S

ap

ph

ire

2.0

2.5

1.9

2.1

12

.41

1.6

12

.012

.03

.23

.84

.23.

77

38

94

77

30

KIN

G R

OC

K1

.72

.51

.92.

01

2.7

12

.71

2.3

12.6

3.1

3.6

5.2

4.0

63

79

23

67

2

IGW

30

97

1.4

1.8

2.0

1.7

13

.41

3.0

12

.112

.81

.41

.83

.92.

4

Ave

rag

e w

ith

in e

ach

TO

S2

.82

.92

.41

1.9

11

.91

2.0

4.0

99

4.3

07

4.2

8

TOS

(ls

d)

0.0

20

.33

0.8

07

0.7

0.8

89

1.2

75

3

Va

r (l

sd)

<.0

01

0.2

5<

.00

10

.6<

.00

10

.63

61

Va

r (l

sd)

be

twe

en

TO

S<

.00

10

.49

0.0

07

1.1

<.0

01

1.4

79

Va

r (l

sd)

wit

hin

TO

S0

.43

1.0

1.1

01

7

%C

V9

.9%

5.2

16

.1%

# =

pe

nd

ing

cla

ssifi

ca

tio

n


26

Table NAR2. Eff ect of seeding time on yield and quality (protein and screenings*) of wheat varieties at Mingenew during 2010

Yield - (t/ha) Protein - (%) Screenings - (%)

Variety May 15 June 2 Av. May 15 June 2 Av. May 15 June 2 Av.

IGW 3119 3.29 2.97 3.13 10.0 10.3 10.2 5.7 4.7 5.2

Westonia 3.29 3.03 3.16 10.4 11.3 10.9 7.0 5.9 6.5

Binnu 3.24 2.82 3.03 9.6 9.9 9.7 5.4 7.0 6.2

Magenta 3.21 2.81 3.01 10.8 11.3 11.1 6.1 5.0 5.6

IGW 3186 3.18 2.88 3.03 9.7 10.4 10.1 5.2 4.9 5.0

IGW 3167 3.13 2.79 2.96 10.7 11.5 11.1 7.0 7.8 7.4

Tammarin Rock 3.13 2.90 3.02 10.6 11.1 10.9 5.4 5.4 5.4

Fortune 3.07 2.64 2.85 10.8 11.2 11.0 5.9 4.8 5.4

IGW 2944 3.06 2.70 2.88 10.8 11.1 11.0 6.2 5.3 5.7

IGW 2886 3.04 2.68 2.86 11.1 11.4 11.3 7.2 6.8 7.0

Calingiri 3.03 2.82 2.93 9.9 10.7 10.3 6.6 3.0 4.8

Carnamah 3.03 2.62 2.82 10.1 10.9 10.5 7.3 4.2 5.7

Espada 3.01 2.77 2.89 11.0 11.4 11.2 5.3 5.7 5.5

Katana 3.01 2.60 2.81 10.4 11.6 11.0 4.0 4.3 4.2

Wyalkatchem 2.98 2.94 2.96 10.5 11.1 10.8 3.3 3.3 3.3

RAC 1683 2.95 2.41 2.68 10.6 11.3 10.9 3.9 4.0 3.9

Mace 2.89 2.74 2.82 10.9 10.6 10.8 3.8 5.2 4.5

King Rock 2.88 2.70 2.79 11.7 12.1 11.9 3.7 5.1 4.4

IGW 3097 2.86 2.60 2.73 11.4 12.1 11.7 1.5 1.9 1.7

EGA Bonnie Rock 2.84 2.77 2.81 11.2 12.0 11.6 3.9 4.8 4.4

Gladius 2.81 2.65 2.73 11.0 11.6 11.3 6.3 6.2 6.2

Average within each TOS 3.1 2.8 2.9 10.6 11.1 10.85 5.5 5.1 5.3

TOS (lsd) 0.001 (0.04) 0.016 0.3 0.378 1.3

Var (lsd) <.001 (0.19) <.001 0.5 <.001 1.0

Var (lsd) between TOS n.s 0.53 (0.26) 0.79 0.7 <.001 1.5

Var (lsd) within TOS (0.27) 0.7 1.4

%CV 5.6 3.8 16.1

* Includes wholes and cracked grains.


27

Table NAR3. Eff ect of seeding time on yield and quality (protein, screenings* and weight) of wheat varieties at East Maya during 2010

Yield - (t/ha) Protein - (%) Screenings (%) Test weight (kg/hL)

May 25 June 15 May 25 June 15 May 25 June 15 May 25 June 15

EGA Bonnie Rock 1.83 1.15 14.1 15.8 5.7 23.4 82.1 76

King Rock 1.82 1.34 14 15 6 17.5 81.4 77.1

IGW 3119 1.77 1.37 14.1 15.1 4.1 22.9 81.9 74.4

Espada 1.76 1.32 14 16.7 7.2 13.7 78.2 73.7

IGW 3186 1.74 1.17 14 15.8 4.4 23.4 82.1 74.8

Katana 1.74 1.17 15.1 16.6 5.3 23.4 82.1 76.8

Mace 1.74 1.32 14.1 15.2 4.3 25.8 79.8 75.2

Wyalkatchem 1.73 1.28 14.2 16.2 3.7 16.6 79.1 73.9

RAC 1683 1.72 1.23 13.7 16.3 6 18.9 76.3 71.5

IGW 3167 1.69 1.28 14.6 16.6 5 16 81.4 75

Westonia 1.68 1.18 14.1 15.6 6.9 12.5 77.7 73.3

Gladius 1.62 1.07 14.4 17.1 6.4 17.5 79.4 73.2

Fortune 1.59 1.06 14.9 16.2 9.9 14 75.6 73.5

Binnu 1.58 1.29 13.5 14.6 10.8 26.2 77.9 74.7

Magenta 1.56 1.08 14.2 16.6 11 15.5 75.8 74.6

Calingiri 1.55 1.08 14.8 16.7 11.5 9.9 75 75.9

Tammarin Rock 1.54 1.25 14.2 16 5.4 16.7 79.3 72.3

IGW 2944 1.52 1.14 15 17.3 9.8 14.9 74.6 71.9

Carnamah 1.51 1.08 13.8 15.9 8.6 11.1 76.1 75.1

IGW 2886 1.46 1.03 15.3 17.8 8.7 23.6 78.2 75.1

IGW 3097 1.39 1.3 15.6 15.8 2.3 13.6 81.1 74.5

Average within each TOS 1.66 1.2 14.26 16.18 6.75 18.25 78.8 74.3

TOS (lsd) 0.004 (0.12) 0.034 (0.4) 0.022 (7.5) 0.014 (2.3)

Var (lsd) <.001 (0.13) <.001 (0.4) <.001 (2.7) <.001 (1.1)

Var (lsd) between TOS 0.002 (0.19) 0.031 (0.7) <.001 (5.8) <.001 (2)

Var (lsd) within TOS (0.18) (0.6) (3.9) (1.6)

%CV 7.8 4.8 19.1 1.3

* Includes wholes and cracked grains.

Acknowledgments

Thanks to the Grains Research and Development Corporation (GRDC) for fi nancial support; Bruce Haig,

Melaine Kupsch, Anne Smith, Vicki Scanlon and DAFWA RSU throughout the State for technical support.

Mingenew Irwin Group, Liebe Group, NEFF and SEPWA

Project No.: DAW147

Paper reviewed by: Christine Zaicou


28

Yield performance of temperate and tropical rice varieties in the Ord River Irrigation Area (ORIA)

Siva Sivapalan, Penny Goldsmith and Gae PlunkettDepartment of Agriculture and Food, WA, Kununurra

Key Messages

• Several tropical and temperate rice varieties are showing potential for high yield in the Ord River

Irrigation Area (ORIA).

• Cold night temperatures during June caused high sterility in late-fl owering varieties.

• Three varieties were higher yielding in the raised-bed system, while another two varieties were higher

yielding in the fl ooded system.

Background and Aims

Rice has been demonstrated as a potentially suitable crop for the Ord River Irrigation Area (ORIA). Suitable soil

types, warmer climate and availability of irrigation water make the ORIA ideal for growing rice. The New South

Wales rice industry is looking for opportunities for quality rice production in northern Australia to meet the

demand of their export customers. The local industry group (ORIA Industry Development Committee) is keen

to explore the commercial viability of a rice industry in the region.

Small-scale rice trials carried out at the Department of Agriculture and Food Frank Wise Institute of Tropical

Agriculture (FWI) in Kununurra during 2009 demonstrated the potential for high yields (up to 13.6 t/ha) in this

environment.

In the ORIA, a gross margin analysis during 2010 indicated a 7.5 t/ha yield at the farm-gate value of $550/t

generates a gross margin of $2442/ha, which is very competitive compared with gross margins of many other

fi eld crops grown in this region. Trials carried out at FWI during 2010 aimed to evaluate the performance

of temperate and tropical rice varieties for diff erent planting dates and diff erent irrigation methods. Rice is

traditionally grown in a fl ooded system. However the aerobic system may be more suited by fi tting into the

fl ood/furrow irrigated farming system in the ORIA and reducing bird damage.

Method

Variety trial

Two temperate (Amaroo and Quest) and eight tropical (Lemont, Tachiminori, Vandana, Milyang 23, Muncul,

Takanari, Pandan Wangi No 7 and Pandan Wangi 1907412) rice varieties were evaluated for yield performance

when planted on February 22, 2010 and March 23, 2010, under a fl ooded system (due to limited supply of

seed, there were no replicates). Establishment counts, date of 50% fl owering and grain yield were measured.

Irrigation trial

Three temperate (Amaroo, Quest and Jarrah) and two tropical (Lemont and Tachiminori) varieties were

evaluated under three irrigation systems; raised-bed , fl ushed and fl ooded systems. In the raised-bed system,

rice was planted on beds and furrow irrigated whenever necessary (based on visual assessment of plants

and soil). In the fl ushed system, rice was planted on level topography and fl ushed with irrigation water

whenever necessary till crop maturity. In the fl ooded system, rice was fl ushed whenever necessary till panicle

initiation (PI) stage and then permanent water was applied. Each treatment had fi ve replicates arranged in

a randomised complete block design. Establishment counts, date of 50% fl owering, harvest index and grain

yield were measured.

Results

Variety trial

Despite grasshopper damage to the seedlings of early planted crop and poor establishment of Amaroo and

Lemont with early planting, the analysis of variance of establishment counts showed there is no signifi cant

diff erence between varieties (P=0.07) and between dates of planting (P=0.12).


29

Vandana was early fl owering and early maturing with lodging problems. Therefore, with late planting up to

late-April, Vandana can complete fl owering before the onset of cold night temperatures during June. Muncul

and Pandan Wangi 1907412 were late fl owering. In terms of days taken to reach 50% fl owering, the analysis

of variance showed there is signifi cant diff erence between varieties (P<0.001) but no signifi cant diff erence

between planting dates (P=0.22).

Grain yield data (see Table 1) shows Takanari with fi rst planting and Lemont, Tachiminori and Milyang 23

with second planting yielded >6 t/ha. Poor establishment of Amaroo, Lemont and Tachiminori with fi rst

planting resulted in low yields. Severe bird (fi nches) damage to Quest (fi rst planting) resulted in no grain being

harvested. Possible cold damage at early pollen microspore (EPM) stage occurred to Pandan Wangi 1907412,

Muncul and to some extent Takanari in the second planting. Although the water depth was 20 cm, it appears

insuffi cient to protect these tall varieties. The analysis of variance of yield data indicated there is no signifi cant

diff erence between varieties (P=0.73) and no signifi cant diff erence between planting dates (P=0.53).

Table 1. Grain yield of varieties planted on two dates

Variety Yield - (t/ha at 14% moisture)

First planting (February, 22, 2010)

Second planting (March 23, 2010)

Amaroo 0.38 2.28

Quest 0.00 2.61

Lemont 0.72 6.55*

Tachiminori 1.69 6.58*

Vandana 4.43* 4.36*

Milyang 23 4.27* 6.36*

Pandan Wangi No. 7 3.21* 4.61*

Pandan Wangi 1907412 5.51* 0.59

Muncul 4.64* 0.42

Takanari 6.50* 4.37*

Average 3.13 3.87

*Figures represent values greater than breakeven yield (3.01 t/ha) based on 2010 gross margin analysis.

Irrigation trial

Analysis of variance of establishment counts showed there is no signifi cant diff erence between varieties

(P=0.73) and irrigation methods (P=0.48). Seeding rate used in all systems was 150 kg/ha, the recommended

rate for drill sowing rice is 135–170 kg/ha. On average, establishment on a raised-bed system is lower than

the other systems. However, Quest and Jarrah had satisfactory establishment under a raised-bed system.

Both fl ushed and fl ooded systems were initially managed in a similar manner. Hence the diff erence in

establishment between these two systems may be due to factors other than irrigation method.

Flowering information from the raised-bed system showed Lemont and Tachiminori took 3 - 4 weeks longer

to complete fl owering and suff ered possible cold damage at the EPM stage. Night temperatures lower than

17–19ºC can cause sterility. The minimum air temperature during June 2010 was below 17 ºC for most days.

In the fl ushed system, Quest was early fl owering, Jarrah was later than Amaroo, and Lemont and Tachiminori

were considerably later. Possible cold damage occurred in all varieties. In the fl ooded system, Jarrah took bit

longer to mature than in NSW where it is four weeks shorter in maturity than Amaroo. Possible cold damage

occurred to Tachiminori, a tall variety for which 20 cm water depth may not be suffi cient to protect the crop

from cold damage.

It is also noted Amaroo, Quest and Jarrah matured about 40 days earlier compared with NSW conditions. With

a shorter growing season, too much nitrogen fertiliser may have been applied (200 kg urea/ha at planting and


30

200 kg urea/ha at panicle initiation stage). High nitrogen availability can often lead to more fl oret sterility. High

nitrogen also increases the impact of low temperatures, further increasing fl oret sterility.

Harvest index is a useful measure, indicating how eff ective the crop is at converting growth into yield. High-

yielding short-season varieties commonly have a value of 0.55. Amaroo has a harvest index of 0.45 - 0.55 in

south-eastern Australia. Harvest index provides a more sensitive indicator of stresses during reproduction and

grain fi lling. Stresses such as low temperatures, high temperatures, water defi cit and salinity will aff ect yield

potential without necessarily reducing biomass production. The low harvest index values (varying from 0.01 to

0.39) obtained from these trials indicated problems with high sterility, weeds and birds.

Table 2. Grain yield of varieties grown under diff erent irrigation systems

Variety Yield - (t/ha at 14% moisture)

Raised-bed system Flushed system Flooded system

Amaroo 2.24 0.19 1.27

Jarrah 2.63 0.40 5.62

Quest 3.80 1.31 2.47

Lemont 1.31 0.14 4.82

Tachiminori 4.48 1.15 1.53

Mean 2.89 0.64 3.14

lsd (α=0.05) 0.65 0.32 0.64

CV% 17 37 15

The analysis of variance of grain yield data showed signifi cant diff erences (P< 0.001) between the varieties

and between the irrigation systems and signifi cant interaction also existed between irrigation systems and

varieties. Grain yield data in Table 2 shows Tachiminori is the highest-yielding variety under the raised-bed

conditions and Quest performed better than Amaroo and Jarrah. The fl ushed system performed poorly

compared with the other two systems, which showed similar mean (average) yields and variation.

Discussion

Variety trial

Most varieties are showing potential for high yield. Problems such as bird damage, minor stem borer attack,

brown plant hoppers and sterility in heads were encountered. Further research is required to establish the

ideal planting time for each variety.

A dry-season crop could be planted during February-March or April-May to ensure PI, EPM and fl owering

occur at optimum temperatures.

Wet-season crops could make use of the longer day length during summer.

Optimum seeding rate and fertiliser application also need to be established.

Among the tropical varieties, only Lemont, Tachiminori and Vandana are recommended for the dry season.

Therefore it is necessary to test all varieties for their performance during the wet season.

Irrigation trial

Raised-bed and fl ooded systems yielded better than the fl ushed system for all varieties. Jarrah and Lemont

performed better under fl ooded conditions. Amaroo, Quest and Tachiminori performed better in the raised-

bed system. Overall, the yields were far lower than the industry expectations.

Identifi cation of varieties better suited for raised-bed (aerobic) conditions needs further research.

An ideal seeding time to avoid cold damage during June-July and to maximise yield potential must be

identifi ed.


31

A nitrogen application strategy suited for the growing conditions in the tropical environment also needs to be

established.

Key Words

Rice varieties, planting date, irrigation method, grain yield

Acknowledgments

Assistance provided by Dr Peter Snell (Rice Breeder, NSW Industry and Investment) and Russell Ford (Manager,

Rice Research Australia Pty Ltd) is gratefully acknowledged. Financial support for the research project was

provided by Rice Research Australia Pty Ltd, Australian Centre for International Agricultural Research (ACIAR)

and Department of Agriculture and Food, Western Australia (DAFWA).

Paper reviewed by: Noel Wilson


32

Decision Support


34

A new phenology model (DM) for wheat

Darshan Sharma, Mario D’Antuono, Brenda Shackley, Christine Zaicou, Ben CurtisDepartment of Agriculture and Food, WA

Key Messages

• A new phenology model (DM) for predicting fl owering dates in wheat is now available.

• Predictions will be updated regularly on the DAFWA website.

• DM has superior predictability that its predecessor throughout Western Australia, particularly for the

colder and more southern locations.

• DM recognises seasonal diff erences and can display median points as well as percentile distributions.

• The existing phenology model (the Flowering Calculator) may still be useful in the northern, warmer

locations.

Background and Aims

Flowering date predictions are important for risk aversion from frost and terminal stresses of heat and water

stress. A new, improved model has been developed to predict fl owering dates of wheat in Western Australia.

The aim of this paper is to display the usefulness of the new model compared with the existing ‘Flowering

Calculator’ and to indicate where the related information may be sought.

Method

A new phenology model has been developed, to take into account that wheat-growing locations in WA diff er

not only for the mean (average) temperature and day length but also for the extent of low temperatures, and the

rate at which heat and cold accumulate. Details of the model can be found at Sharma and D’Antuono, (2011).

Predictions were developed at a range of locations in WA where hourly temperature data were available.

For validation and comparison with the existing model (Flowering Calculator), an independent data set from

six variety x time of sowing trials (two presented in Figure 1) were used. To ensure validity, the coeffi cients of

both models were calculated using the same temperature profi les. Predictions from Flowering Calculator were

drawn using Model-4 (temperature, day length, interaction between temperature and day length).

Results

The new model (DM) has already been developed, validated and peer reviewed. The predictions will soon

be available in the public domain through the DAFWA website. Meanwhile, predictions using DM can be

obtained from authors of this paper. Current available locations are shown in Table 1.

Table 1. Locations currently available for DM fl owering predictions

Northern agricultural region (NAR)

Central agricultural region (CAR)

Great Southern South Coast

Binnu Bonnie Rock Jerramungup Cascade

Badgingarra Cunderdin Katanning Esperance

Eradu East Beverley Mt Barker Lake King

Chapman Meckering Newdegate Salmon Gum

Geraldton Merredin Ravensthorpe Scaddan

Kalannie Muresk

Mingenew Northam

Moora Wickepin

Morawa

Mullewa

Wongan Hills


35

A comparative summary of the two models is given in Table 2. An example of the comparison of predicted

fl owering dates from the two models is shown in Figure 1. This comparison reveals three points: i) deviations

from modelled to observed dates with DM are much smaller at the southern site of Mount Barker (see Figure 1b);

ii) deviations in the northern site at Mullewa (see Figure 1a) are low with both models; iii) deviations are relatively

greater at the earlier seeding times. This fi gure along with some more validations (not shown here) demonstrates

that the new model predictions are more reliable at a range of locations and seeding times. Larger deviations at

earlier seeding times probably refl ect the erratic seed bed and plant growth conditions generally associated with

greater variation of temperature, rainfall and evaporation under early-sown conditions.

Which model is good for me?

Although DM is suitable for all locations in WA and the model also highlights the seasonal sensitivity of

fl owering date, some people might still like to follow Flowering Calculator especially for the benefi t of its off -

line availability. DM has an inbuilt component to account for periods of low temperature during early stages

of crop growth (vernalisation). This means, if you are located at a place experiencing minimum temperatures

of less than 10oC, there is a chance some cultivars will respond; and if your location often gets 5oC or less,

sensitive cultivars are sure to satisfy some of their vernalisation requirements, thereby altering their rate of

development. Therefore, unless the seasonal temperatures generally remain above 10 degrees, Flowering

Calculator is unlikely to be the best model to use.

Table 2. Summary of the features of DM phenology model vs. the Flowering Calculator

‘Flowering Calculator’ ‘DM’ phenology model

Reliability Good in the northern wheatbelt

(warmer conditions)

Throughout the wheatbelt

Model choice Confusing (diffi cult to decide which of

the four models to choose)

Automatic (variety specifi c)

Seasonal distribution Infl exible Flexible to include season related temperature

responses. Can produce percentile/deciles graphs

Information layers Fixed but includes frost probability, high

temperature event

Flexible (layers will be added to display after

collating feedback)

Available as CD Online; bulletin

Weather data restriction

Maximum and minimum temperature Hourly temperature

Future plan No plans at the moment Annual updating; new varieties; additional sites

Contact Meredith Fairbanks

[email protected]

Brenda Shackley

[email protected]

Mario D’Antuono

[email protected]


36

a) Mullewa 2008

-15-10-505

1015202530

08/Jun 13/Jun 18/Jun 23/Jun 28/Jun

Sowing date

Dev

iatio

n (d

ays)

of p

redi

ctio

nfr

om o

bser

ved

date

New model (DM)Flowering Calculator

b) Mount Barker 2008

-15-10-505

1015202530

09/May 19/May 29/May 08/Jun 18/Jun

Sowing date

Dev

iatio

n (d

ays)

of p

redi

ctio

nfr

om o

bser

ved

date

New model (DM)Flowering Calculator

Figure 1. Deviation of predicted fl owering date from the observed fl owering date during 2008 at a) Mullewa and b) Mount Barker. The varieties tested at Mullewa were Arrino, Binnu, EGA Wentworth, Wyalkatchem and those at Mount Barker were Carnamah, EGA Jitarning, EGA Wentworth, Yitpi and Wyalkatchem.

Relevant information

Relevant information can be requested from authors. The following wheat phenology information will be

made available before the next crop season:

• Actual fl owering dates of wheat varieties during 2010 at Geraldton, Northam and Katanning; updated

annually in DAFWA’s Wheat Variety Guide.

• Predicted median and distribution of fl owering dates over seasons; updated annually on the DAWFA

web site

• A farmnote outlining the concept of fl owering window and determinants of fl owering date.

Discussion

The newly-developed wheat phenology model (DM) is superior to the existing Flowering Calculator in terms

of location, season and seeding date. It recognises seasonal variability rather than averaging temperature

across seasons. The new model accounts for vernalisation response and the location characterisation in terms

of both the low and high temperatures.

Key Words

Wheat, phenology, anthesis date, heading date, frost, screenings, fl owering window, optimum seeding time

Acknowledgments

The authors would like to thank Bruce Haig, Vicki Scanlan, Melaine Kupsch and Anne Smith for technical

support in implementing the experiments.

Project No.: DAW 00147

Paper reviewed by: Glenn McDonald

References

Sharma, D. and D’Antuono, M., 2011. Agronomy Journal 103: 221-229.


37

PestFax Map and the Weed Seed Wizard: tools to help with crop protection

Art Diggle1, Peter Mangano1, Sally Peltzer1, Michael Renton2, Bill Macleod1, Fumie Horiuchi1, George Wyatt1

1Department of Agriculture and Food, WA, 2University of Western Australia

Key Messages

Use the PestFax Map to keep tabs on pest and disease reports as the season progresses. It is available at

http://www.agric.wa.gov.au/pestfaxmap.

Use the Weed Seed Wizard to keep track of your weed seed bank. The Wizard allows you to test the long-and

short-term eff ectiveness of your weed control strategies.

Aims

PestFax Map aims to allow its subscribers (farmers, consultants and agricultural specialists) to keep track of the

locations and movements of pests and diseases. PestFax Map users will be able to track reports of key pests

and diseases as the season progresses, and they will be able to compare the current season to past seasons.

The Weed Seed Wizard aims to predict the seed banks of any weed species for any cropping paddock in

Australia. The Wizard is currently being tested against long-term weed control experiments across Australia.

Method

PestFax Map

PestFax Map is a web-based tool. It shows a map of the occurrences of insects, crop diseases and abiotic

disorders that are reported to the PestFax newsletter. Users can pick any time period, any host plant, and

any disorder, or can view multiple disorders at the same time. Users can go straight to the map for up to

the minute information and they will be able to link to the map from the PestFax newsletter. Examples are

presented here for in-season dynamics of diamondback moth infestations and the whole-of-season pattern

of stripe rust infection in wheat for two contrasting years.

Weed Seed Wizard

The Weed Seed Wizard uses paddock management information to predict weed emergence, and crop losses

in current year and future years. The Wizard can deal with multiple weed species and multiple crops. The

Wizard uses actual rainfall to calculate germination and accounts for the eff ects of foliar and residual herbicides,

seed burial, crop competition, seed catching and destruction, seed death and predation and season-to-season

variability in weed seed production. The Wizard can be tuned to fi t any paddock. Examples are presented here

for seed-bank size through time for ryegrass and crop seed for a fi ve year crop sequence (wheat / lupin / wheat /

canola / wheat) at Geraldton. A conventional herbicide based weed management regime is compared with the

same conventional regime plus catching of the ryegrass seed each year at harvest.

Results and Discussion

PestFax Map

Figure 1 shows the pattern of reports of diamondback moth in canola as the season progressed in 2001. In

September of that year there were several report of diamondback moth in the Northern Agricultural Region

of Western Australia, and a few reports in the Central region. In the fi rst half of August infestations began to

be reported south of the Great Eastern Highway, and in the last half of August there were many reports across

the Southern canola growing area. In seasons where there is an outbreak of a highly mobile pest or disease,

users will be able to use the PestFax Map to get an early warning for their area.


38

Figure 1. Reports of Diamondback moth on Canola in September and October 2001.

Figure 2. Reports of wheat stripe rust during the 2004 and 2005 growing seasons.


39

Figure 2 shows all of the reports of stripe rust in wheat for the 2004 and 2005 growing seasons. In 2004 there

was a high level of reporting of stripe rust, particularly in the Eastern regions of the wheatbelt. In the summer

leading up to that season there were repeated rainfall events along the Eastern edge of the wheatbelt and

in the Esperance region, and there was substantial greenness in those areas in March and April. In 2005

there were less reports of stripe rust and a more even spread of reports. In the summer leading up to that

season there was substantial rain across the wheatbelt in late March and April, particularly in the South-West.

Very little greenness had developed by the end of March, but substantial greenness developed across the

wheatbelt in April. By monitoring summer conditions and checking the PestFax Map for the pest and disease

patterns that developed in similar years in the past, users will be better able to asses their risk and be prepared.

Weed Seed Wizard

Figure 3 shows a time-series for ryegrass and crop seed numbers in the soil where a conventional, herbicide

based weed management regime has been used. Weed seed numbers fl uctuate from year to year but remain

at moderate levels. In each year there is a slow decline in seed numbers through summer as a result of death

and predation. Weed seed numbers drop early in each growing season as the seeds germinate. Weed seed

numbers then jump sharply at harvest when the newly produced seeds fall to the ground. Spikes in crop seed

numbers occur each year at sowing and to a lesser extent at harvest because of spilled grain.

Figure 3. Weed and crop seed numbers for a fi ve year cropping sequence in Geraldton using conventional weed management practices. Ryegrass is shown in black and crop seeds are shown in feint grey.

Figure 4 shows the same time-series for the case where seed catching has been used each year as well as

conventional, herbicide based weed management. In this case, the seed bank of ryegrass falls steadily from

year to year, reaching very low levels by the end of the fi fth year. For a comprehensive discussion of weed

management options in this system please refer to the paper by Peter Newman in these proceedings.


40

Figure 4. Weed and crop seed numbers for a fi ve year cropping sequence in Geraldton using conventional weed management practices plus seed catching at harvest in each year. Ryegrass is shown in black and crop seeds are shown in feint grey.

Availability and Future Plans

The PestFax Map can be found at http://www.agric.wa.gov.au/pestfaxmap. The current PestFax service will

continue in its existing newsletter format during 2011 with the added advantage of links to the new PestFax

Map. Additional features will be added over the next couple of years. Users will be able to link to PestFax

Map to get access to more information and to make pest and disease reports. Users will be able to get SMS

or email alerts to tell them when specifi ed pests or diseases are reported. Logged on users will be able to

customise the PestFax Map to show the particular pests and diseases that interest them and to home in on

their region. Users will be able to search and comment on PestFax newsletter articles and make contact with

other PestFax users. Please give the PestFax Map a try and let us know what you think. Contact Art Diggle

on [email protected] or Peter Mangano on [email protected] for help or for further

information.

Testing and calibration of the Weed Seed Wizard will continue for the coming year and the Wizard will then

be made freely available. If you would like to try the Wizard for your situation this season please contact Art

Diggle, [email protected].

Key Words

Crop disorders, weed demographics, simulation, spatial information, decision support

Acknowledgments

PestFax is a DAFWA publication. Ongoing production of PestFax is jointly funded by DAFWA and GRDC. The

PestFax Map web interface to PestFax is being developed by DAFWA and UWA with GRDC funding. The Weed

Seed Wizard is being developed in a joint DAFWA, UWA project with support from GRDC.

Paper reviewed by: Dusty Severtson, John Moore


41

Soil management calculator for predicting phosphorus losses under cropping systems in Western Australia

Geoff Anderson1, Richard Bell2, Ross Brennan1 and Wen Chen2 1Department of Agriculture and Food, WA, 2School of Environmental Science, Murdoch University

Key Messages

• Large summer fallow rainfall events and wet growing seasons can result in water run-off in the wheat

belt of Western Australia.

• A model has been developed to assess the impact of these events on phosphorus (P) run-off losses. The

phosphorus-loss routines have been included in the previously-developed nutrient and lime model, soil

management calculator (SMCAL).

• The model illustrates how water run-off and resulting phosphorus run-off can be managed by retaining

wheat stubble and banding phosphorus fertiliser.

Background and Aims

Agriculture in many parts of the world is coming under increasing pressure to develop management

practices that will minimise phosphorus (P) loss to the environment. Water and phosphorus run-off have been

monitored in a catchment studied near Jacup (Jerramungup) in the south-coast region of Western Australia

(Wong, 2011 pers. comm.). The amount of phosphorus run-off was signifi cant and resulted in phosphorus

concentrations in stream water greater than the ANZECC trigger values for water quality.

A strategy to reduce phosphorus loss is to improve phosphorus fertiliser recommendations with the use of

models, such as NUlogic by CSBP, used in WA. However, this model does not contain routines that allow for

prediction of water and phosphorus run-off .

Work has recently been undertaken to include these routines in the nutrient and lime model, soil

management calculator (SMCAL). These routines were derived from models developed in the United States

(Neitsch et al., 2005; Vadas et al., 2008, 2009).

This paper applies the developed water and phosphorus run-off routines to make an assessment of the

amount of water and phosphorus run-off from a shallow sandy duplex located on a 1% slope within the Jacup

catchment.

Method

Model

The approach used to model water and phosphorus run-off has been described by Anderson et al., (2010).

This modelling approach has been included in the previously-developed nutrient and lime model, SMCAL.

In brief, the water run-off routines come from the soil water assessment tool (SWAT) used widely throughout

the world (Neitsch et al., 2005) while, the phosphorus run-off model comes from Vadas et al., (2008, 2009).

The phosphorus run-off model relies on empirical relationships developed and has been observed to reliably

predict fertiliser phosphorus run-off in the US using only a few input parameters.

Soil phosphorus in run-off is divided into dissolved or labile phosphorus and particulate phosphorus based on

fraction size. Dissolved phosphorus is associated with fractions < 0.45 μm, whereas particulate phosphorus is

associated with fractions > 0.45 μm.

This phosphorus run-off model was adopted because it addresses the following key issues:

• The behaviour of recently-applied phosphorus (fertiliser or manures) or recycled phosphorus (crop

residues) has been noted to be diff erent than the phosphorus already incorporated within the soil pools.

• Recently-applied fertiliser can dominate phosphorus run-off with the soil phosphorus having a relatively

minor role.

• No-till crop systems have less particulate soil phosphorus loss, but greater dissolved or labile phosphorus

loss derived from surface applications of manure and fertiliser compared with conventional tillage systems.


42

A schematic depiction of the model is shown in Figure 1. In general it separates the applied phosphorus

(fertiliser, manure crop residues) and soil phosphorus into diff erent pools, which can have varying impacts on

the amount of phosphorus run-off .

The soil type used in the study was a shallow sandy duplex with a curve number of 88. This curve number

defi nes the relationship between rainfall and run-off . It is an empirical relationship developed in the US. Slope

of the study sites was set to 1%. The impact of soil phosphorus was assessed by varying the models’ input soil

test values. Rainfall data was obtained from the meteorological site located at Jerramungup. Rainfall for the

January 2006 rainfall event was adjusted to the values reported by (Wong, 2011 pers. comm.).

Figure 1. Schematic depiction of applied phosphorus (fertiliser, manure crop residues) and soil phosphorus pools, and pathway of phosphorus transformation between pools.

Experimental site

The study area is an ~1000 km2 catchment mostly under crop and pasture located near Jacup (Jerramungup)

in the south-coast region of WA (Wong, 2011 pers. comm.). Phosphorus concentrations were continuously

monitored during a three-year period (2005–2007) at fi ve stream locations across the catchment. Phosphorus

concentrations were consistently above 10 μg P/L (Australian and New Zealand Environment Conservation

Council [ANZECC] trigger values for management response for upland rivers) throughout the monitoring

period, illustrating the importance of being able to predict the amount of phosphorus run-off from these soils.

Results

The south-west region of Australia has a Mediterranean-type climate. Cropping mainly occurs in the zone

that receives < 450 mm of annual rainfall and as a result there tends to be little water run-off on average. The

exceptions occur when growing season rainfall (GSR) is greater than average, or when there is a large summer

fallow rainfall event. The model developed can be used to assess the impact of these rainfall patterns on water

and phosphorus run-off . This was done for the relatively wet growing season that occurred at Jacup during

2005 and the large summer fallow rainfall event (89 mm) that occurred at Jacup during January 2006 resulting

in large amounts of water run-off .

Applied P Soil P

Cropuptake

Stablephosphorus

Water-extractablephosphorus

Labilephosphorus

Organicphosphorus

Active and stable

inorganicphosphorus

Immobilisation

Mineralisation

Adsorption

Desorption

Run-off


43

Growing season rainfall events

Growing season rainfall greater than average can result in phosphorus run-off , as occurred at Jerramungup

during 2005. These rainfall events are illustrated in Figure 2. During 2005 there were no signifi cant summer

fallow rainfall events. However, the remainder of the year was characterised by a relatively wet growing season,

annual rainfall of 582 mm and GSR (April-October) of 475 mm.

2005

Time (Month)

Dai

ly ra

infa

ll (m

m)

0

20

40

60

80

100

Jan Mar May Jul Sept Nov

Figure 2. Daily rainfall (mm) events that resulted in an annual rainfall of 582 mm measured at Jerramungup during 2005.

Under this rainfall pattern the model predicted the following amounts of phosphorus run-off . In the presence

of soil cover (2.1 t wheat straw/ha) only 1 mm of water run-off was predicted and no phosphorus run-off

(graph not presented). In the absence of soil cover predicted water run-off was 16 mm with predicted

phosphorus run-off increasing with level of soil phosphorus (see Figure 3). The increase in phosphorus run-off

occurred from both the particulate and labile soil phosphorus pools. For the level of soil phosphorus at which

most growers operate, Colwell P between 20 and 40 mg/kg, total phosphorus run-off was in the order of 0.06

to 0.10 kg/ha of phosphorus.

10 20 40 80 160

P ru

noff

(kg

P/h

a)

0.0

0.2

0.4

0.6

0.8

1.0

Particulate soil P Labile soil P Fertiliser P

Figure 3. Growing season phosphorus run-off (kg/ha) predicted by SMCAL at various levels of Colwell P (mg/kg soil) when there was no soil surface cover. Predictions were based on a shallow sandy duplex with a curve number of 88 and slope of 1%.


44

Phosphorus fertiliser (5–15 kg/ha of phosphorus) is applied when crops are sown during May to June. When

10 kg/ha was top-dressed on May 13, SMCAL predicted that 0.11 kg/ha of phosphorus would be loss in the

run-off (see Figure 3). At the level of soil phosphorus maintained by most growers (20 mg/kg), the applied

fertiliser phosphorus accounts for 65 % of total phosphorus run-off . Thus the model predictions illustrate the

relatively large impact fertiliser phosphorus input has on phosphorus run-off when phosphorus is applied to

the soil surface. In contrast, when 10 kg/ha of phosphorus was banded on May 13, no fertiliser phosphorus

run-off was predicted.

Summer fallow rainfall events

Time (Month)

Dai

ly R

ainf

all (

mm

)

0

20

40

60

80

100

Jan Mar May Jul Sept Nov

Figure 4. Daily rainfall (mm) events that resulted in an annual rainfall of 435 mm measured at Jerramungup during 2006.

(a)

Colwell P (mg P/kg soil)

10 20 40 80 160

P ru

noff

(kg

P/h

a)

0.00

0.25

0.50

0.75

1.00

Particulate soil P Labile soil P

(b)

10 20 40 80 160

Figure 5. Summer fallow phosphorus run-off (kg/ha of phosphorus) predicted by SMCAL when soil surface cover was set at (a) 2.1 t wheat straw/ha and (b) 0.0 t wheat straw/ha for various levels of Colwell P (mg/kg soil). Predictions were based on a shallow sandy duplex with a curve number of 88 and slope of 1%.

A large summer fallow rainfall event (89 mm over two days) occurred at Jerramungup during January 2006

(see Figure 4). This rainfall event resulted in large volume of water run-off . The remainder of the year was

characterised by a relatively-dry growing season (191 mm), giving an annual rainfall of 435 mm.


45

Management of soil cover by retaining crop residues is an important practice to prevent water run-off (see

Figure 5). When the soil surface was covered with 2.1 t of cereal straw/ha the model predicted 26 mm of run-

off . In the absence of this soil cover the model predicted 50 mm of water run-off . In the presence or absence

of soil cover, phosphorus run-off increased with increasing levels of Colwell soil P. The increase in phosphorus

loss occurred for both the particulate and the labile phosphorus pools. For a typical level of soil Colwell P

(20–40 mg/ha), total phosphorus run-off was predicted to be in the range 0.10 to 0.32 kg/ha of phosphorus.

Discussion

A model that takes into account both water and phosphorus run-off can be used to predict the impact

of stubble management and phosphorus fertiliser rate and placement method on phosphorus run-off .

Predictions by the model in relation to a catchment study near Jerramungup suggests that water and

phosphorus run-off can be managed by retaining cereal straw and the banding phosphorus fertilisers. The

routines used in the model were derived from models developed in the US. Hence, experimental validation,

by carrying out run-off experiments, of these routines in agricultural regions in WA is required before they are

adopted in fertiliser recommendation models used in WA.

Key Words

Phosphorus, run-off

Acknowledgments

The studies were funded by the Grains Research and Development Corporation (GRDC), Department of

Agriculture and Food Western Australia (DAFWA) and Murdoch University.

Project No.: UMU 00030

Paper reviewed by: Dr Mike Wong

References

Anderson GC, Chen W, Bell R, Brennan R (2010) Modelling of water, sediment and phosphorus runoff : implications for grain

cropping in southwest Australia. In: ‘Proceedings of the 19th World Congress of Soil Science, Soil Solutions for

a Changing World’, (Eds. Gilkes RJ, Prakongkep N) ISBN 978-0-646-53783-2, Published on DVD, http://www.iuss.

org, Symposium 4.1.2 Management and protection of receiving environments, August 1–6, 2010. Brisbane,

Australia: IUSS, pp.114–117.

Neitsch SL, Arnold JG, Kiniry JR, Williams JR (2005) Soil and Water Assessment Tool theoretical documentation version 2005.

Available at //www.brc.tamus.edu/swat/doc.html.

Vadas PA, Owens LB, Sharpley AN (2008) An empirical model for dissolved phosphorus in run-off from surface-applied

fertilisers. Agriculture Ecosystems and the Environment, 127, 59-65.

Vadas PA, Good LW, Moore PA, Widman N (2009) Estimating Phosphorus Loss in Run-off from Manure and Fertiliser for a

Phosphorus Loss Quantifi cation Tool. Journal of Environmental Quality 38, 1–9.


46

Tools to assist growers understand the impacts of management decisions in the high rainfall zone

Penny RiffkinDepartment of Primary Industries, Victoria, Hamilton

Key Messages

• Crop models can be used as a tool to help growers understand the impact of their management

decisions on crop yields and profi t.

• Simulated yields were close to actual yields obtained from the on-farm case-study sites in the high

rainfall zone (HRZ).

• Confi dence in the model outputs enabled the exploration of diff erent management strategies at various

locations and across a range of seasons in the HRZ at low cost and economic risk to growers.

Aims

The aim of this project was to assist growers to improve crop production through more targeted management

practices by providing tools that help them better understand the impact of their management decisions on

crops yields and profi ts.

Method

Crop models, long-term historical climate data and site specifi c information were used to help growers and

advisers explore the impacts of a wide range of management practices across a wide range of seasons during

a short period of time and with little expense or personal risk.

Selection of strategies

A ‘participatory action research’ approach was adopted involving close collaboration between growers,

agronomists and modellers. Growers and advisers identifi ed management strategies of interest at three

workshops held in Victoria, Tasmania and South Australia at the start of the project during 2007. More than

1700 strategies were run in total relating to time of seeding, nitrogen (N) fertiliser, stubble management

(carbon [C] and nitrogen), opportunity cropping, grazing, irrigation and climate change. Final topics and

strategies were developed based on model capabilities, project requirements and the amount and quality of

available data.

Model parameters and validation

At the initial workshops, locations for on-farm case-study sites considered to be representative of the wider

high rainfall zone (HRZ) were identifi ed. Data including soil parameters, climate and crop management were

collected from the case-study sites at Campbell Town and Perth in Tasmania, Millicent and Frances in South

Australia and Meredith, Mininera and Dunkeld in Victoria across the 2008 and 2009 seasons. This information

was used to parameterise and validate the models. The crop models used included APSIM for the time of

seeding, nitrogen fertiliser, opportunity cropping and stubble management (nitrogen) strategies, RothC for

the stubble management (carbon) strategies and CAT for strategies relating to climate change. Weather data

was collected from weather stations placed at the case-study sites and long-term climate data was sourced

from the SILO database (www.bom.gov.au/silo). Cultivar parameters in APSIM were modifi ed using phenology

data from experiments carried out in a previous project.

Time of seeding strategy

The project produced 27 fact sheets and a report of model performance. However for this paper, only

simulations of the time of seeding at Mininera, Victoria will be discussed as an example of the applied

methods. Results of the simulation of other management variables and locations are available on the Southern

Farming Systems and Mackellar Farm Management Group websites: http://www.sfs.org.au/cb_pages/hrz_

factsheets_2010.php and www.mackillopgroup.com.au.

The eff ect of seeding time on grain yield and exposure to climatic stress at fl owering (frost; minimum daily

temperature less than 0°C and heat; maximum daily temperature greater than 30°C) was determined for three


47

cultivars with short, mid and long-season maturities. Varieties were sown on the fi rst and fi fteenth of each

month. All simulations of yield and fl owering time were based on site-specifi c data from Mininera, Victoria

including 120 years of climate data.

Results

Model performance

The models predicted grain yields and fl owering dates close to actual values obtained from the case-study

sites. Across all sites, the coeffi cients of determination (R2) between observed and simulated values were 0.71

and 0.69 for wheat and barley grain yields respectively and 0.74 and 0.95 for wheat and barley fl owering dates

respectively. Root mean (average) squared error values were within the error reported for the model in lower-

rainfall regions. This gave a reasonable level of confi dence in the ability of the model to predict grain yield in

the HRZ of south-eastern Australia for the strategies investigated.

Time of seeding

The optimum seeding time is a balance between maximising resource capture (sunlight, water and

temperature) to achieve high grain yields and minimising potential yield losses due to climatic stresses

including frost and heat stress around fl owering and drought during grain fi ll.

Data from this project showed grain yields and fl owering times diff ered, both within and between seeding

times across the years due to variations in rainfall, evaporation, temperature and radiation (sunlight). Yield

potential and optimum seeding time also diff ered for cultivars with diff erent maturities (see Figure 1). Grain

yields ranged from less than 1 kg/ha for the long-season variety sown on November 15, to more than 8700 kg/

ha for the same variety sown on April 15, (see Figure 1). Signifi cant yield reductions and therefore economic

penalties can occur if varieties of a given maturity group are sown on an inappropriate date. For example, a

yield reduction of 50% occurred when the short-season variety was sown on the optimum date for a long-

season variety (April 1). Understanding the maturity of a variety is therefore essential in choosing the best

seeding date.

Yields from Figure 1 are the average potential yields for the varieties at this location in the absence of stresses

including disease, frost, heat, nutrient defi ciencies or toxicities (with the exception of drought). Yield losses

from climatic stresses can be signifi cant and therefore need to be considered when deciding on the optimum

seeding date. The probability of a crop encountering frost and heat stress during fl owering can be determined

by observing historical climate data. At Mininera, the greatest risk of frost occurs in mid-July but diminishes to

zero per cent by early November (see Figure 2). The risk of the maximum temperature exceeding 30°C starts

during late September and by mid-November has reached a more than 50% chance on any given day.

For all cultivars the earlier seeding dates that achieved the greatest yields (90–100 per cent of the maximum)

generally coincided with the seeding dates that gave the minimum risks for frost and heat stress around

fl owering. However, crops sown later but still within the maximum yield range were often exposed to greater

risks of temperatures exceeding 30°C around fl owering thus increasing the risk of yield reductions due to

heat stress. At other sites in the study, the optimum seeding times to achieve maximum potential yields did

not coincide with the dates of lowest climatic stress. Under such circumstances growers may experience

lower yields due to having to select a sub optimal seeding time to either achieve the full yield potential or to

minimise climatic risk at fl owering.


48

Short Season Varieties

0

2000

4000

6000

8000

10000

1-Ja

n

15-J

an

1-Fe

b

15-F

eb

1-M

ar

15-M

ar

1-A

pr

15-A

pr

1-M

ay

15-M

ay

1-Ju

n

15-J

un

1-Ju

l

15-J

ul

1-A

ug

15-A

ug

1-S

ep

15-S

ep

1-O

ct

15-O

ct

1-N

ov

15-N

ov

1-D

ec

15-D

ec

Mid Season Varieties

0

2000

4000

6000

8000

10000

1-Ja

n

15-J

an

1-Fe

b

15-F

eb

1-M

ar

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pr

15-A

pr

1-M

ay

15-M

ay

1-Ju

n

15-J

un

1-Ju

l

15-J

ul

1-A

ug

15-A

ug

1-S

ep

15-S

ep

1-O

ct

15-O

ct

1-N

ov

15-N

ov

1-D

ec

15-D

ec

Long Season Varieties

0

2000

4000

6000

8000

10000

1-Ja

n15

-Jan

1-Fe

b15

-Feb

1-M

ar15

-Mar

1-Ap

r15

-Apr

1-M

ay15

-May

1-Ju

n15

-Jun

1-Ju

l15

-Jul

1-Au

g15

-Aug

1-Se

p15

-Sep

1-O

ct15

-Oct

1-N

ov15

-Nov

1-D

ec15

-Dec

Sowing Date

Gra

in Y

ield

(kg/

ha)

Short Season Varieties

0

2000

4000

6000

8000

10000

1-Ja

n

15-J

an

1-Fe

b

15-F

eb

1-M

ar

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1-M

ay

15-M

ay

1-Ju

n

15-J

un

1-Ju

l

15-J

ul

1-A

ug

15-A

ug

1-S

ep

15-S

ep

1-O

ct

15-O

ct

1-N

ov

15-N

ov

1-D

ec

15-D

ec

Mid Season Varieties

0

2000

4000

6000

8000

10000

1-Ja

n

15-J

an

1-Fe

b

15-F

eb

1-M

ar

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1-M

ay

15-M

ay

1-Ju

n

15-J

un

1-Ju

l

15-J

ul

1-A

ug

15-A

ug

1-S

ep

15-S

ep

1-O

ct

15-O

ct

1-N

ov

15-N

ov

1-D

ec

15-D

ec

Long Season Varieties

0

2000

4000

6000

8000

10000

1-Ja

n15

-Jan

1-Fe

b15

-Feb

1-M

ar15

-Mar

1-Ap

r15

-Apr

1-M

ay15

-May

1-Ju

n15

-Jun

1-Ju

l15

-Jul

1-Au

g15

-Aug

1-Se

p15

-Sep

1-O

ct15

-Oct

1-N

ov15

-Nov

1-D

ec15

-Dec

Sowing Date

Gra

in Y

ield

(kg/

ha)

Figure 1. Grain yields for three maturity groups of wheat, short, mid and long-season varieties sown on the 1st and 15th of each month. Simulations were run using 120 years of climate data with black bars representing yields at 90-100 per cent of the maximum, white bars 80 to 89 per cent of the maximum and diagonally-striped bars less than 80 per cent of the maximum. Climatic risks have not been accounted for and the optimum sowing date needs to be considered in conjunction with Figure 2.


49

80

110

140

170

200

230

260

290

2-Jul 2-Aug 2-Sep 3-Oct 3-Nov 4-Dec 4-Jan

Short Season VarietiesMid Season VarietiesLong Season Varieties

��

��

��

��

��

� �

1

1

1

1

1

115

15

15

15

15

15

0

20

40

60

80

100

% C

hanc

e fro

st o

r hea

t stre

ss

Sow

ing

Dat

e

Flowering Date

80

110

140

170

200

230

260

290

2-Jul 2-Aug 2-Sep 3-Oct 3-Nov 4-Dec 4-Jan

Short Season VarietiesMid Season VarietiesLong Season Varieties

��

��

��

��

��

� �

1

1

1

1

1

115

15

15

15

15

15

0

20

40

60

80

100

% C

hanc

e fro

st o

r hea

t stre

ss

Sow

ing

Dat

e

Flowering Date

Figure 2. Flowering times for three maturity groups of wheat, short, mid and long-season varieties sown on the 1st and 15th of each month. Simulations were run using 120 years of climate data. The circles represent median values and the bars show the range. Climatic risk at fl owering is shown by the grey line (frost) and black line (heat).

Discussion

Crop models provide useful tools to assist growers to explore various management strategies across diff erent

seasons. This can be especially useful in areas new to cropping, such as the HRZ where there may be limited

knowledge and understanding of how a crop behaves in a particular environment. Although it is not possible to

predict how any one season may progress, the use of historical climate data for a location can help determine the

probability of certain events occurring and thus provide a guide for future seasons. The ability of the model to

accurately predict grain yields will depend on the quality of the input data. Simulated data should be compared

with actual results from the fi eld to check that the model parameters have been set correctly.

Key Words

Crop models, participatory action research

Acknowledgments

Rob Harris, Angela Clough, Garry O’Leary, Irma Grimmer and Jamie Smith from DPI Victoria, Trent Potter from

SARDI and Geoff Dean and Tina Acuna from TIAR are acknowledged for their considerable contribution to the

project. Thanks go to the Grains Research and Development Corporation (GRDC), DPI Victoria, TIAR and SARDI

for their fi nancial contribution.

Project No.: DAV00083

Paper reviewed by: Angela Clough


50

crop updates 2011 - cereals - research library

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