spaa summer 2005 · understanding guidance days at longerenong victoria & roseworthy sa in...

65S A N T F A March / April 2003

© SANTFA 2001

— SPAA RESEARCH & COMMUNICATION PARTNERS — Page 65

The Southern Precision Agri-culture Association (SPAA), ex-ists to promote the develop-ment and adoption of preci-sion agriculture technologiesin the:

grainswine grapeshorticultureother Ag industries

Southern PrecisionAgriculture AssociationPO Box 1060Clare SA 5453Ph: 08 8842 1568Fax: 08 8842 1875email: [email protected] www.spaa.com.au

PrecisionAgNewsT H E M A G A Z I N E O F T H E S O U T H E R N P R E C I S I O N A G R I C U L T U R E A S S O C I A T I O N

SPAA DisclaimerThis publication has been prepared by SPAA on the basis of informationavailable at the time of publication. Neither SPAA nor any contributor tothis publication represent that the contents of this publication areaccurate or complete; nor do we accept any omissions in the contents,however they may arise. Readers who act on the information do so attheir risk. SPAA may identify products by proprietary names to helpreaders identify particular types of products. We do not endorse orrecommend the products of any manufacturer referred to. Other productsmay perform as well or better than those specifically referred to.

© SPAA 2005 ISSN 1449-3705Volume 2 Issue 4 Summer 2005 Pages 65-92

C O N T E N T SC O N T E N T SC O N T E N T SC O N T E N T SC O N T E N T S

Presidents Report ....................................................................... 66

From the Exec Officers Desk .................. 66

Autosteer & Variable Rate EXPO for PA 67

SPAA website update ............................. 67

Coming Events ........................................ 67

SPAA training courses 2006 ................. 67

KEE & Farmscan VR controller training ... 68

Omnistar release XP ............................. 68

Using satellites in livestock production ..... 70

Variable rate nitrogen using an N-sensor .. 72

Monitoring wheat protein on harvesters ... 76

Precision Agriculture in low rainfall .......... 81

Remote sensing for vineyard management 88

SPAA PA equipment survey .................... 91

Understanding Guidance Days at Longerenong Victoria &Roseworthy SA in February 2003 attracted over 200 farmers.

Guidance systems and auto-steer are now attracting widespread interest

Crop sampling using a GPS enabled Pocket PC at a SPAA trial site on theTurner family property at Snowtown South Australia.

Left to right: Allan Mayfield, Michael Wells, Peter Hooper, Peter Cousins.

Autosteer &Variable Ratefor Precision AgricultureEXPO

Friday 24th February 2006Gawler Starplex - Page 67

SPAA

2005 - 06

SPAA Committee

PresidentBRIAN TILLER(08) 8634 [email protected]

Vice PresidentALLEN BUCKLEY(08) 85 41 2869

TreasurerPETER COUSINS(08) 8636 [email protected]

Research CoordinatorALLAN MAYFIELD(08) 8842 [email protected]

Research OfficerMICHAEL WELLS(08) 8636 2474

CommitteeMARK BRANSONROB BRAMLEYBRENDAN FRISCHKECRAIG HUMPHRISJOHN HEAPMALCOLM SARGENTMATT McCALLUMASHLEY WAKEFIELDGRANT YATES

Executive OfficerROHAN RAINBOWSPAA PO Box 1060Clare SA 5453ph (08) 8842 1568Fax (08) 8842 1875Mobile 0418 422 482email [email protected]

To Contact SPAAwrite to

SPAA PO Box 1060 Clare SA 5453

Phone: (08) 8842 1568Fax: (08) 8842 1875

Email: [email protected] www.spaa.com.au

Presidents Report

From The Executive Officers Desk

PrecAgNewsSummer 2005 Page 66

Welcome to another edition of PrecisionAgNews. Ithas been a little while since the last edition howeverthe SPAA committee have continued to run an num-ber of events for members during 2005 and havecontinued the SPAA research program.

We had a very good day with Brett Whelan from theAustralian Centre for Precision Agriculture on variablerate application at Crystal Brook in September. Wewould have liked to see more members attend thismeeting which also included our AGM . I would liketo welcome our new committee member AshleyWakefield from Urania on Yorke Peninsula, and thankyou to Richard Hamilton of Fosters Wines for hiscontribution on the committee over several years.

SPAA attended the Birchip Farming Expo in July and we had good feedback on what SPAAis doing in the area including some research in this region. A number of SPAA membersand committee traveled to Perth in August to attend the 9th Annual Symposium on PrecisionAgriculture Research & Application in Australia. ACPA, SPAA and others put a great programtogether and the day was excellent.

The committee is currently looking at future directions for SPAA through strategic planning.This will give increased attention to training directions in PA with manufacturing compa-nies, agents, rural advisors and farmers. We have to get all areas of agriculture and thefunding organizations to work together to make this work.

I look forward to seeing you at a SPAA event in 2006 which starts with the Autosteer andVariable Rate EXPO on the 24th February.

Brian Tiller SPAA [email protected]

The last year has been a very busy one for SPAA. Aconsiderable amount of effort has been put intopreparing SPAA for future training and events. A keypart of this has been the need for training materialsand manuals. There has also been significant de-mand from growers for support in operating variablerate controllers.

During 2006 there will be a couple of key publica-tions on precision agriculture published. One will bea PA manual for the grains industry to be published byGRDC and the other ins a book on Precision Viticultureto be published by wine titles. SPAA has made somecontribution to both and they are now in the finalproofing stages. Both these publications will beextremely useful for further development and train-ing in precision agriculture.

There continues to be strong interest in autosteer systems and a number of manufacturerswill be releasing a number of new products in early 2006. A number of these products haveenhanced capacity for variable rate control of seeders and spray equipment. Due to thisinterest the next event I will see members at is the Autosteer & Variable Rate EXPO forprecision agriculture in February 2006 at Gawler.

I look forward to seeing you at this event or later in 2006.

Rohan Rainbow SPAA Executive [email protected]


If you wish to haveinput into the pri-orities and develop-ment of standardswithin SPAA, wewould welcomeyour comment.

SPAA Autosteer & Guidance EXPO

SPAA Membership is$55 (inc GST)

for the 2005/06Financial year

New Membershiprenewals will be for12 months due at

1 July 2006

SPAA www.spaa.com.au website update

Autosteer &Variable Ratefor Precision Agriculture

SPAAEXPO

SPAA will be hosting a Autosteer & Variable Rate EXPO for Precision Agriculture on Friday the 24thFebruary 2006 at the Gawler Starplex (Adjacent to Trinity College at the southern end of theGawler Bypass). Registration will take place from 8.30am - $20 SPAA members $40 Non-members.

Come & Hear about:DGPS options, RTK beacon placement Autosteer & visual guidance options.Test drive GPS Guidance & Autosteer systems on the day.Variable Rate Precision Agriculture technologies, EM Mapping, Software, Crop Imagery.

Friday 24th February 2006Gawler Starplex

9.00 am - 5.00 pmSeminars, Demo’s& Trade Diplays

The SPAA website was launced over a year ago andthe content of this site has continued to be up-graded and can be found at www.spaa.com.au.

The site includes downloads of useful informationsuch as PrecisionAgNews, seminar notes and con-ference proceedings. Membership and registrationforms for SPAA events can also be downloaded.There are a significant number of links added to keyPA manufacturers websites and information on GPSsystems. If you would like to make comment on thiswebsite, please email us at [email protected].

Coming EventsGRDC Advisor Cropping Systems Research Update - 8th -9th February 2006 Adelaide

Convention Centre. Ph (08) 8362 5417 for further information.ABB Grain 8th SANTFA Annual No-Till Conference - No-Till - Our farming future 10th

February 2006 -Barrossa Arts & Convention Centre Tanunda see www.santfa.com.auSPAA Autosteer & Variable Rate EXPO for Precision Agriculture - 24th February 2006

Gawler Starplex. Registration & Trade Enquiries to (08) 8842 1568 or www.spaa.com.au

SPAA Training Courses 2006

Farmers who wish toimpliment variablerate technology on

their farm should notmiss these SPAA

Courses

Further courses inother regions will

begin later in 2006

The next SPAA Precision Agriculture Training Events will be held in Victoria & SA in March 2006.The full course program are being finalised. Full details and registration forms will be available toSPAA members from the 1 February 2006 and at the SPAA website www.spaa.com.au.

- Precision Agriculture—An Introduction to concepts, analysis & Interpretation6th March 2006 - Location Birchip Victoria - A one day introduction course for farmers new to PA.This course will be delivered by Dr Brett Whelan of the Australian Centre for Precision Agriculture.The cost is likely to be $120 inc GST (subject to Farmbis approval). Places are limited - book early.

- On farm implementation of precision agriculture and variable rate technologyStarting 7th-8th March 2006 through to February 2007 - Location Birchip VictoriaStarting 9th-10th March 2006 through to February 2007- Location Cleve Eyre Peninsula SA

This is a 5 day course held over a 12 month period. Growers participating in this excellent coursewill implement a variable rate trial on one paddock on their own farm. Growers will be assistedthrough a step by step approach to achieve a result of the yield benefits and economics ofimplementing a variable rate program on their property. This course will be delivered by Dr BrettWhelan of the Australian Centre for Precision Agriculture and Michael Wells of Precision CroppingTechnologies, with additional support from ACPA SPAA research and communication officers.

The cost of the 5 day course is likely to be $1,200 inc GST (subject to Farmbis approval) whichincludes significant data support and analysis. Places are limited to12 participants in each course.See page 68 for full course details. For further information contact SPAA on (08) 8842 1568.


KEE & Farmscan variable rate controller trainingA large number SPAA members have expressed interest in receiving training on programming theirvariable rate KEE Zynx and Farmscan controllers on their airseeders to implement test strips or trialson their properties. SPAA has discussed this with both KEE and Farmscan and they have bothagreed to support this training in both SA and Victoria.

Growers who attend the SPAA course - On farm implementation of precision agriculture andvariable rate technology will be attending the first of these days in each region. This is a free courseavailable to all SPAA members.

If you are interested in attending any of these one day workshops run by KEE and Farmscan andsupported by SPAA please register your interest by contacting the numbers below:

KEE Zynx productsBCG Office Birchip Victoria – To register contact Beverly Dowker (08) 8203 330028th March 200629th March 2006Ramsey Bros Cleve – To register contact Beverly Dowker (08) 8203 33006th April 20067th April 2006

Farmscan productsBCG Office Birchip Victoria – To register contact Ian Giles Ph 0418 394 13716th March 200617th March 2006Cleve Field Day Site – To register contact Gavin Wheatcroft Ph 0427 877 59722nd March 200623rd March 2006

OmniSTAR, a subsidiary of the world wideFugro group, has released an enhancement tothe traditional OmniSTAR product. The en-hancement allows the use of new generationdual frequency receivers with the OmniSTARservice. “We have introduced the new serviceto meet OmniSTAR customers’ requests formore precision at an economical price,” saidOmniSTAR’s, Geoff Glazier. “XP is an economi-cal alternative to OmniSTAR’s high performance(HP) service, which continues to be availablefor applications that demand the higher accu-racy. It will be available in all agricultural areasof Australia.”

The XP product does not rely on local referencestations for its signal, but utilizes a globalsatellite monitoring network and fully mannednetwork control centre in Perth, 24 hours aday, 7 days a week. While many currentdifferential GPS systems are accurate to withina metre or so, OmniSTAR with XP is sub half-metre.

Omnistar release XP +/-0.5m serviceWith the recent release of dual frequency GPSreceivers into the guidance and autosteer mar-ket, the XP service will enable farmers to takeadvantage of this technology. “The use of thelatest auto steer and GPS assisted steer systemsthat are currently on the market significantlyreduces stress on farm machinery operators,”said Mr Glazier. “The XP technology has beendeveloped to work with these systems and takesthe pressure off those operators.” The new dualfrequency auto steer systems in Australia can belicensed to utilize the new OmniSTAR XP dualfrequency service.

XP will be available from all major Australiansuppliers of auto steer systems and OmniSTARretailers. Users interested in upgrading theircurrent receiver should contact their dealer tosee if they can utilise the new system. OmnistarXP compatible equipment is available from thereciever manufacturers Trimble, Novatel andTopcon. For more information see the Omnistarwebsite www.omnistar.com.au

CANBus ISO11783 or ISOBus compatibility continues to create widespread debate in the PAindustry. It appears that the CANBus ISO11783 standard, which is still continuing to evolve, willgain greater industry recognition with the introduction of ISOBus standards approval stickersbeing introduced on compatible equipment. The CANBus ISO 11783 appears to becoming thepredominant standard in agricultural tractor controller systems, particularly in the OEM market,however there continues to be many proprietary CANBus standards used by a number ofmanufacturers. Go to www.isobus.net for further information.

CANBus ISO11783 Update


The outcome of this program will be that farmers have a clear understanding of the various waysprecision agriculture can be used in their farm management and will have implemented a VR orPA trial on their farm with follow-up and technical support within the course.

Prerequisites for this course include:At least 2 years of yield maps,Prepared to complete an electromagnetic image and collect soil tests of the trial siteHave a access to a variable rate controller on a seeder or spreaderHave a laptop computerParticipants must attend all training daysIn addition growers will need an electromagnetic image and soil tests at extra cost.This is available by contacting Michael Wells PCT on 0428 362 474 by the 10th February 2006

This is a 5 day course held over a 12 month period.

Starting 7th-8th March 2006 through to February 2007 - Location Birchip VictoriaStarting 9th-10th March 2006 through to February 2007- Location Cleve Eyre Peninsula SA

Day 1 – Using PA in farm ManagementMorning - Precision Agriculture – Course Introduction.1. Why do we want to use PA.2. PA systems – Grid management, zone management, sensor systems.Starting the PA Process – Collecting Yield data1. Setting up and operating yield mapping systems2. Getting files out of JD Office and Case IH AFS software3. Data management for PA – Data cleaning, interpolation (kriging) and storage.4. Inserting META dataAfternoon - Collecting imagery and soils data1. How do use EM38 and how does this compare to other tools and methods2. Understanding remote sensing and how we can use it3. Soil sampling strategies for PA - Ground truthing EM and satellite imagery4. Creating soil management zones – How this is done & Software

Day 2 - Setting up on farm PA trialsMorning - Planning for variable rate application1. The next steps – what are the options2. Can we use VR to manage paddock variability?Afternoon - Implementing variable rate application1. Managing and understanding paddock variability2. Setting up on farm PA trials3. Setting up a VR controller (Basics)

Post workshop follow up (Mid-April 2006)– Data management and specific paddock sampling requirements

Day 3 - Programming your variable rate controller - see dates page 681. Specific Training on use of VR controllers (Specific brand session eg KEE Zynx, Farmscan

programs are planned as per dates above) John Deere, Flexi-Coil, Morris training will beorganised based on demand and availability)

Day 4 (September/October 2006) - Assessment of VR controller trials1. Group Discussion - follow up on issues, problems with operating VR controllers and

implementation of PA trials.2. Preparation for Harvest of trials (Basics)3. Additional Yield Mapping Training from John Deere, Case IH etc

Day 5 ( Feb 2007) - Post harvest PA discussion and training meeting1. Group Discussion – Follow up on issues, problems with yield mapping and measurement

of PA trials.2. Opportunity for sharing of results and outcomes from on-farm PA trials3. Where to next with PA on farm.

Further details on this training program and registration forms can be down-loaded from the SPAA website www.spaa.com.au from the 1st February 2006.

- Places are limited to 12 participants per course -

On farm implementation of precision agriculture andvariable rate technology - Course program


Farmers use satellites to boostlivestock production

Richard Stovold & Matt Adams, Department of Land Information WAe-mail: [email protected]

Kojonup farmer Bill Webb who has been apioneer in the use of PGR said “we haveincreased our overall sheep gross margin by$25/hectare by using feed lots to increasesheep production and pasture utilisationper hectare. The satellite derived PGR datawhich I am using (figure 3) as part of myproduction risk management can detectdegrees of pasture growth rates not detect-able by the eye and gives me 2-3 weeks leadtime and improves my confidence level instock management decisions”.

“I also use the information to decide on mygrazing rotations,stocking rates, feed bud-geting and fertiliser applications.”

The Department of Land Information whoprocess the satellite information to PGRmeasurements based on the CSIRO Live-stock Industries PGR model and Depart-ment of Agriculture ground data, have setup a new web site within the Farm Channelof their Landgate service with free publiclyviewable Pastures From Space information.The site has had unprecedented use with30% more web site visits from producersand agronomic consultants in 2005.

DLI contribution to the development of thePasture Growth Rate and Feed On Offersatellite based maps is an exciting step for-ward to help the grazing and livestockindustries increase profitability and gainbetter utilisation of their pastures.

Consortium partner Department of Agricul-ture is working with a group of around 50collaborating producers who are evaluat-ing the satellite-derived pasture growth rate(PGR) and feed on offer (FOO) technologieson farm. Case studies undertaken show thatthe use of PGR and FOO information im-proved the profitability of the producers’sheep enterprise.

The increase in profit ranged from a grossmargin of AUD$23 to AUD$90/wintergrazed hectare. The increased profit re-sulted from better utilisation of pasturethrough more effective feed budgeting andthe introduction of new management tech-niques into the farming system. The produc-ers recognised PGR as a valuable tool whenapplied to decisions about the use of arange of management techniques such asincreasing stocking rates, feedlotting ofwethers, whether or not to agist livestock,application of fertilisers and conservation offodder during spring. The information on

New and improved satellite images are now beingused by farmers to give a weekly measurement oftheir pasture growth rate (PGR) within paddocks.The PGR information is delivered every week as asubscription service over the internet. The informa-tion is being delivered through Fairport Technolo-gies Pasture Watch software to producers in south-ern Australia. Farmers in Western Australia and theEastern States are already using this new technol-ogy to assist them improve their managementdecisions resulting in higher profitability. Farmersare achieving increased pasture utilization usingPasture Growth Rate and Feed On Offer mapsresulting in more wool and profit per hectare.

Figures 1 and 2 above indicate current Pastures From Space coveragein Western Australia and the Eastern states

Richard Stovold

Matt Adams

PrecAgNewsSummer 2005 1

PGR and FOO was also found toimprove producers’ confidence in de-cision-making and helped reduce theirlevels of stress.

Currently the Pastures From Spaceconsortium is delivering the follow-ing products to clients every week aspart of an annual subscription servicethrough it’s commercial partnerFairport Technologies:

Weekly Pasture Growth Rates (PGR)Forecasted Pasture Growth Rates

Testing of a 10year Historical PGRproduct is presently being tested withfarmer groups and consultants. Thishistorical information will allow farm-ers to view and implement manage-ment strategies based on the seasontrends and assist in whole farm bud-geting.

Figure 4: A 10 year weekly trace of Pasture Growth Rates for a property in WA.

Fiqure 3. A Pasture growth rate map of a farm property delivered weeklyto the farmers computer and viewable in Fairports PastureWatch software.

To view the Pastures From Space information visit:http://www.pasturesfromspace.csiro.au

To visit the Landgate website visit:http://www.landgate.com.au(go to the Farm channel)

For information on the Fairport subscription servicevisit: http://www.fairport.com.au/pasturewatch


Fitted to the roof of the tractor, it scans cropsand automatically regulates the rate of nitrogenfertiliser spread according to the greenness ofthe crop.

This multispectral scanner measures the lightreflectance properties of the crop canopy. Thisis in the range of 450 to 900nm. In the visiblewavelength range (400-700nm) the reflectanceis indicative of leaf chlorophyll content andhence, the crop nitrogen status. In the near-infrared region (700-900nm) higher reflectance

Variable rate nitrogen in cropsusing an N-Sensor

Allan Mayfield, SPAA Research Coordinatore-mail: [email protected]

Allan Mayfield

Does the N-Sensor have a place?• Paddocks are now much bigger and variable

rate inputs are likely to be of more value.• More N later post-emergence and less at

sowing is becoming more popular.• An automatic operation has a lot of appeal.

The Southern Precision Agriculture Associationis trialling an N-Sensor to see if a variable rate ofnitrogen produces any higher yield than aconstant rate when used post emergence incereal crops. This is part of the SIP09 programfunded by GRDC.

This N-Sensor, developed by the European com-pany Yara, is now used commercially in Europeby 350 growers and contractors, but is not yetavailable for sale in Australia.

Will variable rate N be more profitablethan a fixed rate?

These differences are used to derive aspectral index for each crop

Reflectance of a crop shows atypical shape

A crop with high N-supply shows adifferent reflectance

The unit consists of two diode array spectrom-eters: One spectrometer collects the cropreflectance data on both sides of the tractor.

is indicative of greater crop biomass.

This researchhas been

funded by the


The second spectrometer is used to measurethe irradiance conditions at the same time inorder to correct the reflectance signal due tochanges in sun angle and cloud cover. Normaloperating time is from 10am to 4pm. Thesystem is controlled through a terminal thatdisplays current system information and logscrop and GPS data on a chip card.

The N-Sensor also assesses the crop biomass.There is a low biomass “cut-off” setting whichprevents excessive amounts of fertiliser beingapplied to parts of the crop which may be thindue to other factors, such as poor emergenceor pest damage.

A pre-determined rate of fertiliser is set in thecontrol box after scanning a small part of thecrop. Thereafter the fertiliser rate will varyaround this value. Where the crop is palergreen a higher rate is applied and where thecrop is darker green a lower rate is applied. Thiscan also be reset to apply more nitrogen fertiliserto darker green areas and less to paler greenareas. Alternatively, crops can be scannedearlier, for example when spraying herbicide.Crops can then be checked to identify causes ofyellowing before applying the fertiliser.

The research question is which if any is the rightdecision? This will depend on the cause(s) ofthe crop yellowing and the ability of differentparts of the crop to respond economically tomore nitrogen fertiliser.

Other limitations such as trace element deficiency as well as nitrogen can occur. Urania Yorke Peninsula 2004


To test this concept the N-Sensor has been used in 2005to apply strips of nitrogen fertiliser at a variable rate andthen at a constant rate alongside (using the same totalamount of fertiliser). These trials have been carried outacross a range of soil types and crop conditions. Plantsamples were also taken from different areas of the cropto check whether or not nitrogen is the main limitingfactor or whether the yellowing is due to other causessuch as those detailed in the results shown left. Crop yieldsof the variable and constant fertiliser strips will be assessedfrom yield maps. Grain samples will also be taken from thedifferent treatments and zones to compare grain proteins.

These trials will be repeated in 2006. In preliminary trialsat three sites in South Australia in 2004 yield increases withvariable compared with a constant rate in wheat rangedbetween 0% and 4% (see results below and next page).The average increase in trials in Europe is approximately3%. Grain protein in these European trials was alsoslightly higher with variable rate application.

The N-Sensor is also being used to map variation acrosscrops in New South Wales, Victoria and South Australia inthe SIP09 research program. This information is used withother crop and soil details to better define zones fordifferential management across paddocks.

Mapping N status in wheat, Yeelanna EP 2004.

Will variable rate N be more profitable than a fixed rate?

N-Sensor grain yield results Hilltown Mid-North SAUrea applied to Chara wheat 2nd September 2004

The N-Sensor mounted on a utility was used formuch of the crop scanning program

PrecAgNewsSummer 2005 Page75

Other possible uses of the N-Sen-sor being trialled in Europe in-clude variable rate desiccation ofcrops with herbicides and variablerate application of fungicides ac-cording to differences in the cropbiomass across the paddock. Thatis, higher rates are being appliedto thicker parts of the crop andlower rates to thinner parts.

N-Sensor grain yield results Urania Yorke Peninsula SAUrea applied to wheat 10th September 2004

N-Sensor researchIn 2004 trials were conducted withfarmers in northern NSW and theVictorian Wimmera-Mallee. In2004, 4 variable rate trials wereconducted in SA. In 2005 SPAAestablished 15 research sites usingthe Yara – N-Sensor for variablerate post emergent N applicationand crop density scanning acrossSA & Victoria. These trials com-pared variable rate N applicationcompared to constant N applica-tion. The results of these trials isstill being analysed. These trialswill be repeated again in 2006.

Variable rate versus a constant rate of urea N Urania Yorke Peninsula SA 2004

Allan Mayfield pictured with the N-Sensor mountedon a tractor hooked to a urea air-boom system

Further information contactDr Allan MayfieldAllan Mayfield ConultingSPAA Research CoordinatorPh (08) 8842 3230email [email protected]


Monitoring wheat protein content on harvestersJames Taylor1, Brett Whelan1, Lars Thylén2, Mikael Gilbertsson2 and

James Hassall3

E-mail: [email protected] [email protected] Centre for Precision Agriculture University of Sydney

2 Swedish Institute of Agricultural and Environmental Engineering Uppsala3 "Kiewa", Gilgandra, NSW

A Zeltex AccuHarvest®on-harvester protein sensor has been tested for twoseasons on a commercial combine harvester in Australia. Output from the ZeltexNIT protein sensor was coherent and often strongly correlated to yield response,giving a good indication that the observed protein patterns are real. Absoluteprotein values however appeared suppressed and a new calibration curve for

Australia has been developed for the sensor.

Figure 1: The sensor and sampling systemmounted on the clean grain elevator (left)and a close-up of the sensor and sampling

system (right)

IntroductionProtein content is an important considerationin grain sale price, particularly wheat varieties.A bonus/discount payment is made on a 0.1%sliding scale beyond the base rate for eachgrade. Knowledge of the variability in proteincontent prior to marketing could be used inmany tactical ways to optimise farm gate re-turns. However, while the opportunity to raiseprofits does exist, the actual return to thegrower is dependent on market forces (Long etal. 2002) and the cost/effort required for differ-ential harvest, which may deter contract har-vesters from the practice. Information on nitro-gen use and removal, in conjunction with yielddata, would also be useful in the strategicmanagement of nitrogen fertiliser and the de-velopment of more accurate site-specific grossmargin analysis. This may be of greater benefitto growers in the short term due to tangiblesavings in fertiliser cost, which may be upwardsof 30% of production costs.

The potential benefits of protein maps, particu-larly for nitrogen management, have prompteda great deal of interest in the development ofboth on-the-go and remote-sensing based pro-tein measurement in Australia, as well as NorthAmerica (Long et al. 1998). For the 2001, 2003and 2004 winter cropping seasons, the Austra-lian Centre for Precision Agriculture (ACPA), inconjunction with growers in Conservation Farm-ers Incorporated (CFI), has been collaboratingwith Zeltex and the Swedish Institute of Agricul-tural and Environmental Engineering (JTI) totest a prototype Near-Infrared Transmission(NIT) on-harvester grain protein and moisturesensor. This paper reports on some of ourexperiences with the sensor and the develop-ment of a calibration for Australian conditions.

Sensor Mounting and OperationGrain tends to be harvested at a lower moisturecontent (generally <13%) to avoid post-harvestdrying. Climatic conditions at harvest are gen-erally dry and dusty with temperatures oftenabove 40ºC. In 2001, dust and light contami-nation created problems with sensor opera-tion. As a result very little useful data wasrecorded. The sampling system was subse-quently redesigned to minimise dust and lightcontamination.

The sampling system hasbeen designed to mounton the side of the cleangrain elevator housing.Grain is sampled from theup elevator shaft and de-posited into the down el-evator shaft. The inletand outlet are controlledby two trapdoors drivenby windscreen wipermotors. The trapdoorsclose tightly to seal thechamber and avoid con-tamination in the sensor.Figure 1 illustrates themounting and samplingmechanism. The trap-doors are activated by LEDfill sensors at the top and

James Taylor

Brett Whelan


bottom of the NIT sensor measurement cham-ber. When the top fill sensor is triggered the topdoor closes and the NIT sensing protocol isinitiated. Once the NIT sensing is complete thebottom trapdoor opens to purge the NIT sensorof grain. The bottom trapdoor closes once thelower fill sensor is activated and the top trap-door opens completing the cycle. If the cyclegets stuck at a particular stage for >30s, thesensor has an override function to open thebottom trapdoor and restart the cycle. In initialtesting this option was not available and thesensor had to be manually restarted if it stoppedfunctioning. The sensor takes a reading atapproximately 12s intervals, which equates to65-70 points/hectare at normal harvestingspeeds. The actual NIT sensor is a 14-band NearInfrared Transmission whole grain analyser(Zeltex AccuHarvest®) operating 14 wave-lengths between 893 and 1045nm.

The data from the sensor is currently beinglogged onto a laptop computer installed in thecabin of the harvester. The software is writtenin LabView. The software is easy to use andprovides a graphical and numerical indicationof how grain protein and moisture is varyingover a 3-4 minute window. The growers hadno problem interacting with the software andthe only drawback was the current use of alaptop to log the data. The cabin environmentin combine harvesters is not particular suited tolaptops and a more robust, simpler data loggerwill be required for any commercial release.

At the time of writing the second full harvest ofprotein data has been collected with the Zeltexsensor. The same system has now been usedfor 2 Australian and 2 European harvests. Forthe 2004 harvest in Australia, the sensor wasrun at two locations over a period of 6 weeks.The sampling system that was used is an earlyprototype that has not been updated. As aresult some hardware fatigue issues were iden-tified from overuse that will be addressed infuture models. In general, however, the systemworked well and for the second year running alarge amount of data has been collected. Bothgrowers that operated the sensor had no problems apart from the hardware fa-tigue. Without having analysed,visualised and discussed the datafrom 2004, the information dis-played in real-time on the softwareinterface generally concurred withthe growers' knowledge of the field.

Sensor CalibrationThe Zeltex NIT sensor is currentlycalibrated using data from the North-ern Hemisphere (North America andEurope). One of the aims of thisstudy was to determine if the cali-bration is applicable to Australianconditions. This was initially testedin the field and later in the labora-tory.

Field TestingFor the field situation, two transects in a wheatfield near Gilgandra, NSW, were used. As thecombine harvester harvested the two transects,the Zeltex sensor was used to measure grainprotein on-harvester. At the same time 15samples were manually collected from thebubble-up auger near the top of the clean grainelevator. These samples were taken at approxi-mately the same recording interval (12s) as theon-harvester protein sensor. The manuallysampled grain was analysed using desktop NITspectrophotometers at the Gilgandra silo andthe Australian Bread Research Institute (BRI)using the FOSS Infratec 1229 (Global calibra-tion No. WH000003). The mean protein valuesof the two transects from the different measure-ments are given in Table 1.

The comparison of the desktop results with theon-harvester sensor indicated that the on-har-vester sensor was underestimating both grainprotein and grain moisture content. The meanprotein difference between the desktop sensors(at the Gilgandra Silo and BRI) and the Zeltexwas 0.94%. The mean moisture difference was0.62%. There may be some error in this ap-proach as it was not possible to manually collectthe same grain that was sampled by the Zeltexsensor. It is hypothesized that this underestima-tion is a bias from the use of the NorthernHemisphere calibration curve. To test this alaboratory experiment was conducted.

Table 1: Comparison of protein results from samples taken along two transectsand analysed with three different NIT sensors. (NB. The Gilgandra silo and BRI

sensors analysed the same grain samples. *The adjusted Zeltex response isdiscussed in the following section)

Zeltex computerinterface


Figure 2: Plots of measured vs predicted protein (left) and moisture (right) using derived calibration equations.

Laboratory ExperimentThe results from the field trial indicated that anew calibration would be required for Austra-lian conditions. This was not unexpected giventhe different climate conditions, wheat varietiesand moisture content at harvest in Australia.The new Australian calibration for the Zeltexsensor was derived using 99 Australian grainsamples sourced from different regions of theAustralian grain belt, including North-West NSW,the Riverine district on the NSW/Victoria borderand the Yorke Penisula in South Australia.

The grain samples were analysed using theFOSS Infratec 1229 protein content under stan-dard conditions (25ºC) at the Australian BreadResearch Institute (BRI) at North Ryde, NSW.The FOSS Infratec 1229 analyses the grain at2nm intervals between 850 and 1048nm. Thespectra were extracted and a protein and mois-ture value determined using the standard cali-bration (WH000003) for Australian wheat de-veloped for the FOSS Infratec 1229.

The same samples were then run through theZeltex sensor, mounted in a laboratory at theUniversity of Sydney, at two temperatures, 25°Cand 40°C. The two temperatures were selectedas temperature has a known effect on NIT andit was desirable for the calibration to encom-pass the probable temperature ranges at har-vest. The raw output from the sensor (14wavelengths) was extracted. From this analysis5 readings gave strange values and were dis-carded. This left 193 readings (from the 99samples at two temperatures). A Multiple LinearRegression (MLR) was performed to predict theBRI protein % using the wavelength responsefrom the Zeltex sensor. Similarly the moisture %was also predicted. Alternative regression mod-els, Multiple Stepwise Linear Regression (MSLR)and Partial Least Squares Regression (PLS) werealso tried with no additional benefit.Results and DiscussionThe protein and moisture calibration resultingfrom the MLR is shown in Figure 2. The r2 andstandard error of prediction (SEP) are given on

the graphs. The SEP value for protein is similarto those derived using the Northern Hemi-sphere data set (Thylén and Algerbo, 2001),however the moisture SEP is higher. This maybe due to the lower moisture contents at har-vest or the different grain varieties. The proteinshows a strong 1:1 linear response over a largerange of protein values (9-17%).

For the general calibration curve the transectdata from the within field transects was used.The transect data was excluded from the datasetand a new calibration curve derived (n=134).The new calibration curve was then applied tothe transect data to predict protein and mois-ture for the transect data above. The meanresults are shown in Table 1 (Zeltex adj.). Aftertransformation the absolute mean differencein percent protein measurement between thestandard laboratory measurements and theZeltex instrument decreased from 0.94% to0.14%. For moisture the absolute mean differ-ence was slightly increased from 0.29% to0.41%. The Australian calibration curve ap-pears to be giving a better protein predictionthan the Northern Hemisphere calibration forthe data from these two transects.

For the 2004 harvest, field samples were againtaken to help validate the accuracy of theprotein sensor. These data were not analyzedat the time of this writing and cannot bepresented here.

Nitrogen Budgeting.One of the principal benefits of a protein moni-tor identified by Australian growers is the abilityto better identify nitrogen use within fields andvariably replenish nitrogen. The amount ofnitrogen removed from a system is a function ofthe amount of grain (yield) and the amount ofnitrogen in the grain. For Australian conditionsthe relationship between protein, yield andnitrogen removed in wheat has been quanti-fied by Kelly et. al. (2003) as;

N removal (kg/ha) = Grain Yield (kg/ha) x Grain protein (%) X 0.00175 (1)


not unusual in Australia and generally reflects either insufficient nitrogen or soil moisture to achieve yield potential. Thenitrogen removed map is shown in Figure 4. As well as calculating the amount of nitrogen removed a site-specific nitrogenbudget can be determined using Equation 2.

N budget = N present + N input - N removed (2)

This is similar to the approach of Long et al. (1998) except that the inherent soil nitrogen pre-sowing is considered. InAustralia this is important as the variable rainfall means that crop failure is quite possible and in drought situations theremay be a large amount of residual nitrogen stored in the soil.

The relationship inNorth America has alsobeen quantified (seeLong et al. 1998) but isnot used here due todifferent varieties andgrowing conditions.Since both yield andprotein data have beencollected on-the-go thedata can be interpo-lated (block kriged us-ing local variograms)onto a common gridand the nitrogen re-moved from the crop-ping system calculatedusing Equation 1.

The interpolated grainyield and protein mapsare shown in Figure 3.Both maps show simi-lar spatial patterns witha negative response be-tween grain and pro-tein (highlighted by theboxed areas). Thisnegative relationship is

For Field 3, the pre-sow-ing soil nitrogen levelswere only available asa field average of60kgN/ha. A pre-sow-ing application of 80kg/ha Monoammoniumphosphate (MAP)(12%N) was applied.The majority of the field,except for the pan-handle in the southeastcorner, was also top-dressed with 50kg/haurea (46% N). Thismeans that the major-ity of the field received32.6kg N/ha (assumingan even distribution)and the panhandle re-ceived 9.6kg N/ha. Thepanhandle was not topdressed due to thespreader running outof fertiliser. The cropresponse to this missedapplication is clearlyevident with grain pro-

Figure 4: Map of Nitrogen removed (left) and the Nitrogen Budget (right) for Field 3derived from the interpolated yield and protein maps.

Figure 3: Interpolated maps of Grain Yield (Mg/ha) (left) and Grain Protein (%) right.


tein suppressed in the panhandle althoughgrain yield was not (Figure 3).

Figure 4 shows a continuous nitrogen budgetmap for Field 3. In reality, field management,including fertiliser, is being managed at a zonelevel. To facilitate adoption the ACPA intends todevelop a protocol to incorporate this informa-tion into management class response functionsas proposed by Whelan et al. (2005). Thenitrogen budget is currently limited by the useof a mean response for initial soil N. Withoutreal-time soil N-sensors, it is an expensive soilsampling exercise to obtain an accurate map ofsoil available N prior to sowing. Managementzones represent an approach that allows thegrower to determine the mean zone 'N present'in a cost and time effective manner at a similarresolution to which management is being ap-plied (Whelan et al. 2002).

While Equation 2 allows for the calculation of anitrogen budget, the actual level of nitrogenapplied will be dependent on the availability ofsoil moisture. Determining rainfall and soilmoisture availability is difficult, however, inSouthern Australia where top dressing (withinseason fertilising) is common, earlier seasonrainfall can be a strong indicator of total sea-sonal rainfall (Peter Stone, CSIRO Land andWater, pers. comm.)

ConclusionsThe output from the protein sensor shows strongspatial patterns that are consistent with whatthe grower expects, observed yield variationsand management decisions. Growers are en-thused about the quality of data being gener-ated by the sensor while combine operators arehappy with the ease of performance of thesensor and data collection software on-har-vester. There seems little reason from an engi-neering perspective not to commercially re-lease a limited number of units for the nextharvest.

Preliminary investigations into deriving an Aus-tralian based protein and moisture calibrationcurve appear to give better results, in Australianconditions, than the current global calibrationcurves. However further validation is neededover a wider distribution of grain samples.Accurate site-specific determination of proteincontent will provide growers with confidencein calculating site-specific or zonal nitrogenbudgets as well as trying to determine thereasons for spatial patterns in their crop produc-tion.

AcknowledgementsThe authors would like to acknowledge theassistance and in-kind support given to thisproject by Todd Rosenthal and the staff atZeltex Inc. Maryland, USA.

ReferencesKelly, R., Strong, W., Jensen, T., Butler, D.,Town, B. and Adams, M. 2003 Recurrence ofyield and protein variation in the northerngrains region. Proceedings of the 11th Austra-lian Agronomy Conference, Australian Societyof Agronomy, Geelong, February, 2003 (http://www.regional.org.au/au/asa/2003/c/15/kelly.htm)

Long, D.S., Carlson, G.R. & Engel, R.E. 1998Grain protein mapping for precisionmanangement of dryland wheat. In P.C.Robert, R.H. Rust & W.E. Larson (eds) PrecisionAgriculture, Proceedings of the 4th Interna-tional Conference on Precision AgricultureASA/CSSA/SSSA, Madison, WI, USA pp787-796

Long, D.S., Carlson, G.R. & Engel, R.E. 2002Gross value of spring wheat under precisionnitrogen management as influenced by grainprotein. In P.C. Robert, R.H. Rust & W.E.Larson (eds) Precision Agriculture, Proceed-ings of the 6th International Conference onPrecision Agriculture, ASA/CSSA/SSSA, Madi-son, WI, USA, CD-ROM

Thylén, L. and Algerbo, P.A. 2001 Develop-ment of a protein sensor for combine harvest-ers. In G. Grenier & S. Blackmore (eds) ECPA2001, Proceedings of the 3rd European Con-ference on Precision Agriculture, Montpellier,June, 2001, pp869-873

Whelan, B.M., Cupitt, J. & McBratney, A.B.2002. Practical definition and interpretationof potential management zones in Australiandryland cropping. In P.C. Robert, R.H. Rust &W.E. Larson (eds) Precision Agriculture, Pro-ceedings of the 6th International Conferenceon Precision Agriculture, ASA/CSSA/SSSA, Madi-son, Wisconsin, pp325-329

Whelan, B.M. and Taylor, J.A. 2005. Local re-sponse to inputs: advancing SSCM in Australia.In Proceedings of the 5th European Confer-ence on Precision Agriculture. Ed J.V. Stafford,Wageningen Academic Publishers, TheNetetherlands

Further information on this research is avail-able at the Australian Centre for Precision Agri-culture website: www.usyd.edu.au/su/agric/acpa/papers/On-harvester_Protein_web.pdf

This article is taken from the the followingpaper and should be referenced as:Taylor, J., Whelan, B.M., Thylen, L., Gilbertsson,M. & Hassall, J. (2005). Monitoring wheatprotein on-harvester - Australian experiences.In: J.V.Stafford (ed) Precision Agriculture ’05,Proceedings of the 5th European Conferenceon Precision Agriculture, Uppsala, Sweden,Wageningen Academic Publishers, The Neth-erlands, pp 369-375.

Further information on the ZeltexAccuharvest grain protein monitor is

available from www.zeltex.com


Using precision agriculture in low rainfall farmingMichael Wells, Precision Cropping Technologies

John Heap, Research Scientist SARDIRohan Rainbow, SPAA Executive Officer

e-mail: [email protected]

A summary of the Australian Government National Landcare Program – NaturalResource Innovation Grant project - Demonstration of advantages of precision

agriculture technologies in lower rainfall farming systems.

IntroductionPrecision Agriculture (PA) is developing rapidlyin USA and Europe, driven by both economicand environmental pressures. Improved tech-nology and increasing research effort has re-sulted in increased adoption overseas, but inAustralia the rate of adoption remains relativelyslow. In the future PA and guidance systemswill be a major innovation on many Australianfarms, with potential for a quantum increase inproduction efficiency. In the interim demon-stration is required in the development robustPA systems which can be applied to a range ofAustralian farming systems.

This project aimed to demonstrate of advan-tages of Precision Agriculture Technologies inlower rainfall farming systems and to increasethe use of precision agriculture and guidancesystems by grain growers in low rainfall envi-ronments in southern Australia. The projectalso aimed to measure and publicise the eco-nomic value of using variable rate inputs tograin crops in low rainfall environments andimprove the flow of information and developthe farmer and advisor skills base in PA tech-nologies. The planned outcome of this projectwas to increase returns to growers by improvedunderstanding and management of within-paddock variability, and validation of PA sys-tems under low rainfall conditions using large-scale demonstration trials.

This project had linkages with other researchand communication groups, such as at theAustralian Centre for Precision Agriculture atthe University of Sydney, and the South Austra-lian Research and Development Insitute to usethe best expertise available for training andresearch. Training was provided at workshopsand field days held in the low rainfall Malleeand Upper Eyre Peninsula regions to improvethe skills of farmers and advisors to use preci-sion agriculture measuring and interpretingtools. These include use of GPS equipment,yield and protein monitors on harvesters, print-ing yield maps, zoning and testing soil to inter-pret yield maps, and making use of other sens-ing systems, such as satellite imagery of cropsand electromagnetic mapping of soils.

Case studies of farmers fields using the datacollected in this project were presented at theseworkshops, field site visits and field days todemonstrate how precision agriculture tech-

Michael Wells

John Heap

Rohan Rainbow

niques can be used in low rainfall farmingbusinesses to improve profitability.

In 2004/5 SPAA expanded it’s field demonstra-tion program. To complement the existingtraining program, investigations are now be-ing conducted to look for practical and eco-nomic benefits of precision agriculture in lowrainfall areas of South Australia. SPAA is con-ducting some applied demonstration researchto validate and demonstrate the economicviability of PA systems under local conditions.The demonstration sites are incorporating vari-ous measurement techniques such as yieldmapping, EM surveys, Airborne imagery andsoil testing to establish potential managementzones. Various variable rate application tech-niques are then being applied over these pad-docks.

Investigations have been carried out on se-lected fields in both the Upper Eyre Peninsulaand Murray Mallee districts of SA. These sitestypically had a history of yield monitor datahaving been collected for several seasons. Mapscreated from the yield monitor data allowed aninitial visual assessment of the extent of varia-tion in yield within each paddock and its influ-ence on gross margin. Similar patterns could attimes be observed between yield maps fromdifferent seasons with the shapes in yield vari-ability appearing to be strongly influenced bythe underlying broad soil zones of the dune/swale environment.

Discussing paddock management zones at Ade and ColinStoeckle’s property During a workshop at Swan Reach SA.


Murray Mallee - Waikerie - Grower: Allen BuckleyFarm: “Glenrae” Field: “Kroehns Corner”.Data Collected: Soil ECa (EM38 Vertical Dipole Mode) collectedApril 2005, Actual Crop Yield 2000, 2000, 2003 & 2004, RTKElevation, Soil Analysis, Airborne Multi Spectral Imagery.

This site is located 12km south of Waikerie in the Murray Malleedistrict of SA and in a field with a dune/swale soil environment typicalof this farming area. Yield monitor data has been collected since2000. Seasonal conditions have been varied over these years withquite different wheat yield outcomes. This makes it a little difficult tocompare the yield maps between seasons. To enable a comparisonto be made between yield maps the data for each season can benormalised. This puts each wheat yield map on the same scale andshows how the yield has varied above and below the mean in eachseason.

Other Data Collected for Investigating causes to YieldVariabilityIn the Mallee areas, subsoil chemical properties of sodicity or high pHthat are often associated high salts and boron, can restrict water useefficiency. The presence of subsoil constraints both physical andchemical in the soil profile can restrict root growth of a croppreventing it from extracting all the apparent available water andtherefore limit yield. Electromagnetic induction technology utilizingthe EM38 is proving useful for mapping areas of a field affected bysubsoil constraints.

An EM38 coupled with an RTK GPS were used to collect apparentelectrical conductivity and high quality elevation data over the fieldin April 2005. The EM38 was operated in vertical dipole. Theresultant map infers variation in soil profile conditions over the field.The low EM values are associated with the tops of sand rises gradingto the highest values mostly in the low lying, depressions in the field.Soil samples were taken to interpret the EM map and establish thenature of the indicated soil profile variation. This is an essential stepin determining what soil properties are varying and to what extent.Sample locations were selected with consideration to the range anddistribution of EM38 values over the site.

The analysis EM38 measurement against soil test results revealedsome important relationships. Generally as the EM value increasedover the field there was an increase in the sub soil of EC 1:5 (r2 0.67),sodicity (r2 0.72), chloride (r2 0.73) and boron (r2 0.81) although soilanalysis results indicated boron concentrations did not attain acritical level. Exchangeable sodium levels in the 30-60cm depthexceeded 30% at high EM value sites. Analysis of the EM map withyield maps from various seasons suggested that for the majority ofthe field the wheat yield generally declined as the EM value in-creased.

Airborne Multi Spectral ImagerySpecTerra Services from WA were commissioned to capture AirborneDigital Multi Spectral Imagery. This system measures on-groundreflectance across visible and infrared wavelengths. The productmost commonly applied in precision agriculture is Plant Cell DensityIndex which is a ratio of the Infrared and Red bands.

2000-2004 yield maps - Waikerie

In order to explore opportunities to manage thevariability depicted in the yield maps it is neces-sary to build an understanding as to the majorcauses of this variability. Focus so far has beenon the physical components of the growingenvironment including specific soil propertiesand the topography as these will have a largeinfluence on availability of water, the mostlimiting resource in these dry-land areas. Twofields in each of the Murray Mallee and UpperEyre Peneinsula were investigated. The follow-ing details progress to date with some keyfindings and description of the demonstrationsbeing conducted in 2005.

Plant Cell Density imagery (See page 83) was captured in earlySeptember 2004 when the crop was already suffering moisturestress. This field was used at a field day held by the Mallee SustainableFarming systems project at Waikerie in a workshop session con-ducted by SPAA in September 2004. The presentation increasedgrower awareness of the benefits of precision agriculture technolo-gies in low rainfall farming. Plant Cell Density index captured inSeptember 2004 showing relative difference in vegetation groundcover. Red is depicting less dense/green crop cover through Bluebeing denser, healthier crop. Mallee Sustainable Inc trial sites andscrub areas can be clearly observed.


‘Normalised’ yield maps - Waikerie

Potential Management ZonesThe management of within field variability is likelyto be more practically and logistically achievableif the paddock is divided into potential manage-ment zones. These could be described as smallfenceless areas within which there is a relativelyuniform agronomic environment.

There are various methods for creating manage-ment zones for variable rate experimentation.Initial SPAA trial sites have been ‘zoned’ using amethod developed by the Australian Centre forPrecision Agriculture’s Dr Brett Whelan. Dataelements of yield, elevation and an EM38 datawere combined in a statistical process, to classifythe paddock into a predetermined number ofclasses. This was typically 2 or 3 classes whichwere determined to be statistically and signifi-cantly different in yield and physical environmentto justify being treated differently.

This process was applied to the Waikerie demon-stration site. Three management classes appearto be more suitable than two initially, given thatwhen segregated into two classes the low lyingflats associated with heavier soil (and predisposi-tion to subsoil constraints) were grouped withthe tops of the sand rises. Yield in these areas arelikely to be limited for very different reasons. Asresults from variable treatment experiments be-come available in addition to other spatial infor-mation, the number of and boundaries to zonescan be refined.

The highest yielding zone 1 (green) is dominatedby the low EM38, lighter textured soil areas of thepaddock with lower water holding capacity. Atthe time of sampling zone 1 had lower storednitrogen and available phosphorus but low chemi-cal subsoil constraint properties. Similarly, zone 2(blue) has lower nutrient levels and low subsoilconstraints. Zone 3 (red) has heavier texturedsubsoil, high subsoil constraints and higher accu-mulated nutrients in particular nitrogen and sul-phur. Zone 3 has highest mean EM value andlowest elevation.

Trials 2005Areas of fields with similar characteristics as asso-ciated with zone 3 (red) are generally a problemwhen growing Sloop barley. Dry springs com-bined with chemical subsoil constraints and shal-low soil over limestone greatly increase the riskfor higher protein and increased screenings,breeching quality specifications and reducinggross margin. When too much of an individualfield comprises this high risk barley growing areaone management response has been to sow adifferent crop in the hostile soil zones. Triticalehas been used due to high protein being anobjective with feed grain. This is the basis for oneof two differential treatment trials which will beconducted concurrently in 2005.

In collaboration with the Mallee Sustainable Farm-ing Systems Project, SPAA funded by the GrainsResearch and Development Corporation con-ducted a trial to investigate options for paddock

variation using crop and variety selectionand variable rate phosphorus management.Sloop SA barley was the intended crop for2005. Both Sloop SA and Tahara Triticalewere sown across soil zones to assess grossmargin benefits of Triticale in hostile soilzones and to better define the boundary toany benefit. In addition MAP was applied at0, 15 and 50 kg/ha to assess variable ratefertilizer response within soil zones.

Additional MeasurementsOther measurements taken during the courseof this season included leaf tissue testing, NSensor scanning at GS 30-39 and grainsamples pre harvest and at harvest for pro-tein and screenings.

EM38 image - Waikerie

Plant Cell Density - Waikerie


Potential Management Zones - Waikerie

Murray Mallee - Swan ReachGrower: Ade & Colin StoeckelFarm & Field: “Swan Reach”.Data Colletced: Soil ECa (EM38 VerticalDipole Mode) April 2004, Actual Crop Yield2003, RTK Elevation, Soil Analysis, AirborneMulti Spectral Imagery.

An EM38 in vertical dipole mode and RTK GPSwere used in April 2004 to collect apparentelectrical conductivity and elevation data.Soil samples were collected from targetedsites to assist in interpreting the soil profilevariation inferred by the EM map. As with theWaikerie site, the low EM values are associ-ated with the rising sandy a regions withhigher EM measurements dominating in theless elevated parts of the field. Not all sitescould be cored to the desired depth of 60cmdue to the closeness to the surface of alimestone. This was within 15cm of the soilsurface at site 8 and in itself an obviousconstraint to yield. As future yield maps be-come available further field investigation willbe required to better define the very variablesoil profile evident in this field in particularthe influence of and boundaries to the shal-low soil restriction to yield caused by nearsurface limestone.

John Heap of the SARDIPathology unit utilizedthe Swan Reach site tosee if Rhizoctonia solanibehaved differently be-tween PA zones. Smallmicro plots (1.5m x1.5m) were fumigatedbefore sowing. Crop es-tablishment was mea-sured, and Rhizoctoniaroot damage, early shootdry-weight, harvestshoot dry-weight, andgrain yield (harvest in-dex was calculated).There were 3 manage-ment zones identified,rocky flats (Z1), sand hills(Z2) and slopes (Z3) de-rived from yield maps,EM, and elevation.

The results of this work indicated that cropestablishment was affected by fumigation.Soil Rhizoctonia DNA levels were fairly highin Z1 and Z3, but low in Z2. Fumigationreduced Rhizoctonia root damage to lowlevels, and resulted in large shoot dry-weightincreases. Increased shoot growth trans-lated to higher harvest index and yield in Z2and Z3, but not Z1. It is likely that in Z1 (rockyflats) the soil volume (ie water supply) wasnot available to the roots to utilise the in-creased shoot growth. This data is still beingfully analysed. A full report on this study willbe made available at a later date.

Yield map andEM38 imageSwan Reach


Claying, one of the accepted solutions to the challenge of non-wetting soil, can reduce brome grass problems.

The trustees are assisted in project allocation decisions by SAFF nominees John McEvoy of Warookaand Simon Ballinger of Wolseley

Secretariat: Anthony Francis c/- Deloitte – SA Grain Industry Trust Phone (08) 8407 7234 www.sagit.com.au

Targeted Research for SA GrowersThe SA Grain Industry Trust invests more than $1 million a year in researchcrucial to the advancement of the SA grain industry with funds coming froma 15c a tonne contribution on all grain delivered by SA grain growers.

In 2005/06 the SAGIT is supporting 29 projects including:

OTHER PRIORITIESSeasonal climate forecasts for SA grainsNo-Till Farming support – for the SA No-Till Farmers AssociationHigher Returns – Using Precision Agriculture to increase returns - Southern Precision Agriculture Assoc

CEREALSFast Tracking – Wheat breeding with combined disease resistances Molecular Plant Breeding CRC

PULSES AND PASTURESPastures – Improving Pratylenchus tolerance in annual legumes SARDI

Trustees of the SA Grain Industry TrustChairmanMalcolm Sargent, Crystal Brook

MembersJim Heaslip, Appila, Peter Kuhlmann, Mudamuckla,and Linda Eldredge, Clare

Plant Cell Density imag-ery was captured inearly September 2004when the wheat cropwas already sufferingmoisture stress. Thisfield was used in a work-shop conducted bySPAA at Swan Reach inOctober 2004. Theworkshop was orga-nized to assist farmersand advisors improveskills in PA.

Plant CellDensity ImageSwan Reach

Field discussions at the Swan Reach workshop

Upper Eyre Peninsula - BucklebooGrower: Graeme Baldock Farm: “Karinya”Field: “Berkshires”.Data Collected: Soil ECa (EM38 Vertical Dipole Mode)collected April 2004, Actual Crop Yield 2003 & 2004,RTK Elevation, Soil Analysis, Airborne Multi SpectralImagery.

This trial site is located at Buckleboo approximately50km NW of Kimba on the Upper Eyre Peninsula ofSouth Australia. The long term annual rainfall is 304mm.Two seasons yield monitor data have been collectedwith barley averaging 1.41 t/ha in 2003 and wheat1.07 t/ha in 2004. These seasons were below averagewhen it is usual that higher yields are achieved on therising sandy soil environment and lower yields gener-ally in the less elevated heavier soil regions.

Normalising the yield data creates maps on the samescale and allows a comparison between the yield mapsfrom the two seasons. Electromagnetic and highquality elevation data were collected from the field inApril 2004 using an EM38 in vertical dipole mode andRTK GPS. Soil samples were collected to 60cm and

segmented in 3 depths at strategic sitesto interpret the nature of the soil profilevariation that the EM38 map was infer-ring.

Low EM38 measurements coincide withthe rising sandy soil areas and also ahistorical water course which transectsthe paddock in the SE corner. The EMmeasurement generally increases spa-tially from these lighter textured areastoward the heavier texture profiles in thelow regions of the field. Some strongrelationships were apparent from theanalysis of EM38 measurement againstsoil analysis results. As the EM38 mea-surement increases over this field thereis a tendency for an increase in chemical


subsoil properties. Exchangeable sodium % (r2 0.83), EC 1:5 (r2 0.81)and chloride (r2 0.81) generally increased in the subsoil as the EM valueincreased. All but 2 sample sites revealed ESP >6% in the 30-60cm layerwith ESP levels >25% at high EM value sites. Chloride concentrationswere >1000 ppm at 30-60cm at sites with high EM38 measurement.In addition pH (water) exceeded 9.0 in the subsoil.

These subsoil properties combine to reducewater use efficiency by increasing the energyrequired by the crop to extract water andpreventing roots from exploring more of theprofile to access available water. How much ofthe available water the crop can access fromthe subsoil is important late in the season as theprofile dries out from the top down. If the cropis restricted in extracting moisture by chemicalsubsoil properties, ‘haying off’ is likely to occur.There is some evidence of this in the last twoseasons yield maps where low yields are asso-ciated with higher EM areas of the field withinferred subsoil constraints.

Trials 2005In collaboration with the Buckleboo Farm Im-provement Group SPAA funded by the GrainsResearch and Development Corporation con-ducted a trial to investigate options for manag-ing subsoil constraints. One management re-sponse would be to simply reduce nutrientinputs to these zones. The trial implemented in2005 however aimed at exploring opportuni-ties to manage these hostile soil zones andimprove productivity by increasing the depthof soil profile the crop has to access water.

Trial treatments involved deep ripping at a30cm row spacing to a depth of 25cm, rippingwith deep placed gypsum at 1.0 t/ha andripping with deep placed fertilizer of 17:19 Zn2.5% at 55kg/ha. The field was sown toWyalkatchem wheat and 60 kg/ha 17:19 Zn2.5%. The trail site was established in a locationthat places treatments over a soil zone withhigh potential for subsoil constraints and thenextending into the rising sandy soil which theEM and soil test analysis inferred had lowchemical subsoil properties.

Upper Eyre Peninsula - BucklebooGrower: Michael Schaefer Farm: “Altback”Field: “Power Pole”.Data Collected: Soil ECa (EM38 Vertical Di-pole Mode) collected April 2004, Actual CropYield 2004, RTK Elevation, Soil Analysis, Air-borne Multi Spectral Imagery.

This trial site is also located at Buckleboo ap-proximately 35 km NW of Kimba on the UpperEyre Peninsula of South Australia and has adune/swale type soil environment. Yield moni-tor data was collected for the first time in 2004with a wheat crop averaging 0.75 t/ha.

Electromagnetic and high quality elevation datawas collected in April 2004 and soil sampleswere collected to 60cm and segmented atstrategic sites.

Analysis of the EM map with soil test resultsrevealed similar soil characteristics to the otherBuckleboo site with chemical subsoil constraintsquite evident. Again as the EM measurementincreased over the paddock there was an in-crease in sodicity, particularly in the subsoil,and an increase in chloride and boron concen-

2003-2004 yield maps - Baldock farm Buckleboo

‘Normalised’ yield maps - Baldock farm Buckleboo

EM38 image - Baldock farm Buckleboo


trations. Chloride levels at some hig EM siteswere >1000ppm and pH (water) up to 9.5.

ConclusionsThis project has highlighted the opportunity forprecision agriculture to provide improved man-agement of crop inputs and has clearly demon-strated that precision agriculture may poten-tially have greater immediate application in lowrainfall environments, particularly in a dune-swale environment due to the cost saving ben-efits. This project has greatly increased growerinterest in precision agriculture in low rainfallenvironments in SA. The farming systems groupsin these regions have sought SPAA’s input intofurther application of PA technologies in theirenvironments. The project demonstrated theuse of remote and terestrial sensing usinghyperspectral digital imagery, real time NIRSensors and Electromagnetic mapping of soilsfor improved identification of managementzones in low rainfall farming systems. This datacollected was used in training and field demon-stration for farmers and advisors in the Malleeand Upper Eyre Peninsula regions of SouthAustralia.

This work has identified the significant impactof hostile sub-soils has on grain production onupper Eyre Peninsula. As a result of this project,precision agriculture techniques have been uti-lized in ongoing work by SPAA funded by GRDCin collaboration with the Eyre Peninsula Farm-ing Systems Project and also the BucklebooFarm Improvement Group. The principles ofprecision agriculture and the cost saving ben-efits to farmers have been recognized throughthis project. Through this project it was recog-nized that the issues restricting grain produc-tion in low rainfall farming systems were ingeneral more complex than in the high rainfallfarming systems regions. The time taken toclearly identify these problems, particularly as-sociated with high electrical conductivity anddeep soil sodicity has been longer than experi-enced in the high rainfall areas, mainly due tothe more complex chemical interactions andthe impact of this on available soil water to thecrop.

Through this project it was recognized that atleast one full season of crop growth should beset aside to identify these issues through soiltesting and crop testing, before variable ratetreatments or subsoil amelioration treatmentsare imposed. This will have some impact onadoption as the payback period from time andexpenditure cannot be recouped in one sea-son. It is because of this that the industry mustcapitalize on communication of precision agri-culture techniques following an above averageseason or period of above average seasons toenable farmers to amortize the costs of imple-menting this technology over several years. Theresearch and demonstration work in precisionagriculture in low rainfall regions in SA hasincreased the awareness of the potential ben-

efits of this technology. The project has success-fully attracted sufficient grower interest to con-tinue this work, utilizing all the data and infor-mation collected from the project sites and alsogiving opportunity to continue grower groupinvolvement through funding from the GRDCin the continued development and promotionof this technology.

AcknowledgementsSPAA would like to thank the Australian Govern-ment National Landcare Program – NaturalResource Innovation Fund for supporting thisproject. SPAA would also like to thank thefarmers who collaborated in this project. Thesefarmers include; Allen Buckley (Waikerie - Mallee)Ade and Colin Stoeckle (Swan Reach-Mallee),Graeme Baldock (Buckleboo –upper Eyre Pen-insula), and Michael and Ken Schaefer(Buckleboo –upper Eyre Peninsula).

EM38 image - Schaefer farm Buckleboo

Plant Cell Density Image - Schaefer farm Buckleboo

This projecthas been

supported by


Using airborne remote sensing to improve vineyardperformance through zonal management

Tony Proffitt1 and Andrew Malcolm2

1AHA Viticulture, Dunsborough, WA 2SpecTerra Services, Perth, WAe-mail: [email protected]

Irrigation waterCorrelations betweenPCD and canopy surfacearea, trunk circumfer-ence and pruningweights (indices of vinevigour) were establishedduring the 2003 and2004 growing seasonsacross a 9 ha block ofCabernet Sauvignon ata vineyard located in theMargaret River region.The linear regressions foreach index of vigour

The use of precision agriculture technologieswithin the grape and wine industry is com-monly referred to as Precision Viticulture (PV).Following the introduction of PV tools such asglobal positioning systems (GPS), grape yieldmonitors, airborne remote sensing, and soilsensing instrumentation to the industry in thelate 1990’s and associated research during theintervening years, grapegrowers andwinemakers are now recognising the magni-tude of within-vineyard variation and the causesof that variation.

Vineyard variability results in inefficiencies inthe management of inputs to the productionsystem (eg. water, fertiliser, labour and ma-chinery), and uncertainties in both the fore-casting of the potential crop yield and thedelivery of fruit parcels of uniform quality. Oneapproach for managing variable yield andquality is to use PV tools to identify differentzones of characteristic performance within in-dividual vineyard blocks and to manage themaccordingly (zonal management). This paperdescribes some recent experiences in the com-mercial application of this approach to improvevineyard management by using airborne re-mote sensing. Some of these experiences haverealised financial benefits.

Experience has shown that veraison is an ap-propriate time for image acquisition. SpecTerraServices based in Perth are a commercial pro-vider of airborne Digital Multi-Spectral Imagery(DMSI). The DMSI sensor collects data in fourwavebands corresponding to the infra-red, red,green and blue wavelengths from which ‘im-ages’ of the ratio of infra-red to red reflectanceare then produced. This ratio is generally re-ferred to as the ‘plant cell density’ (PCD) index.Such images are now commonly used to iden-tify and map zones of different vine productivityin vineyards.

Applying inputs differentiallyThe inefficient use of inputs in a vineyard maycompromise the productivity and subsequentprofitability of that vineyard, as well as increas-ing the risk of causing undesirable environmen-tal impacts both on and off site. Obtaininginformation on vine parameters across a wholevineyard in order to understand where andhow much of a certain input to apply hastraditionally been difficult and expensive. Air-borne remote sensing provides a means bywhich information on vine characteristics cannow be easily collected. In this case study, DMSIdata was processed to generate images ofvarious vigour related vine descriptors derived

from correlations thathave been found to ex-ist between PCD and on-the-ground measuredvine attributes. The es-tablishment of such rela-tionships now makes itpossible to quantifychanges in vine perfor-mance over time and tosubsequently assess thebenefits or otherwise ofzonal management.

Figure 1: Canopy surface area across the Cabernet Sauvignon block in (a) 2003 and (b)2004 determined from correlations between plant cell density and canopy surface area.The change in canopy surface area between the two years as a consequence of different

irrigation management practices within the three zones is shown in (c).

Tony Proffitt

Andrew Malcolm

An abstract of thispaper was presented

at the 9th AnnualSymposium on

Precision AgricultureResearch & Applica-tion in Australasia


Table 1: Piece rates and total pruning costs in a 8.3 ha block of Shirazusing both zonal viticulture and uniform management methods.

Table 2: Vine yield, components of yield, and vine numbers usedto estimate crop yield in a 2.54 ha block of Cabernet Sauvignonusing both zonal viticulture and random sampling methods.

were similar for the two years suggesting thatthese correlations may be stable over time. Usingthe imagery and visual assessments during 2003,vines within certain zones of the block wereidentified as being either excessively vigorous ortoo weak. Mindful that changes in the applicationof water via the drip irrigation system could onlybe done within the constraints of the irrigationdesign, three different zones (A, B and C) wereidentified. In 2003, irrigation water had beenapplied uniformly across the block. During the2004 growing season, the amount of irrigationwater applied was reduced in a 6 ha vigorouszone and increased in a 3 ha weaker zone in orderto better manipulate vegetative growth. A com-parison of the images (Figure 1) derived for thetwo years shows that the application of less watergenerally reduced vegetative growth whilst theapplication of more water generally increasedvegetative growth, thereby making the wholeblock more uniform. Costs associated with canopyand fruit manipulation in the 6 ha vigorous zonewere reduced in 2004 compared with 2003 (ie.less machine leaf plucking at $250/ha, machineshoot trimming at $140/ha and hand crop thin-ning at $300/ha). In addition, the smaller canopyin the vigorous zone improved aeration and spraypenetration which reduced the risk of botrytiswhich had been a significant problem in previousyears, and the improved fruit exposure to sunlighthastened the rate of ripening so that fruit qualityacross the whole vineyard block was more uni-form.

Labour at pruningFor the same vineyard, the2003 PCD imagery was usedto identify zones of high, me-dium and low vine vigour in a8.3 ha block of Shiraz in anattempt to reduce pruningcosts and to ensure that allstaff pruned an equal numberof vines of varying vigour andhence degree of difficulty.Piece rates per vine were de-termined for each zone ac-cording to the amount of timeallocated to work on the vineswithin that zone. As an ex-ample of the outcome of thisapproach, it is estimated thata saving of approximately$2,400 (11.6%) was made(Table 1). All the pruning staffmade similar amounts ofmoney and endorsed the ap-proach.

Forecasting crop yieldThe uncertainty in predictingcrop yield costs the industrymillions of dollars each yeardue to discrepancies betweenthe forecast tonnage and theactual tonnage of fruit deliv-

ered to wineries. Surveys have shown thatnationally, yield forecasts differ from actualyields by ±33%. Crop forecasting is oftenbased on a random sampling approachwhereby samples are taken at random fromwithin whole vineyard blocks regardless ofthe spatial variation in vine performance.Whilst this approach to crop forecasting hasimproved in recent years, the strong spatialstructure of variation commonly seen in vine-yards suggests that an alternative samplingapproach is worthwhile exploring.

In this study, crop yield was estimated for a2.54 ha block of Cabernet Sauvignon locatedin McLaren Vale 2 weeks before the expectedharvest date using both a random samplingapproach and a zonal viticulture approach.For the random sampling method, 30 vineswere selected across the block using a com-puter ‘random number generator’. The num-ber of samples was not determined statisti-cally to satisfy a pre-determined degree oferror, but was based on the amount of timethat could be allocated to the task of provid-ing a crop estimate. For the zonal viticulturemethod, 3 zones of characteristic vine perfor-mance within the block were identified fromPCD images. These were identified as havinghigh (0.71 ha), medium (1.8 ha) and low(0.03 ha) vine vigour. 10 vines were thenselected from within each zone using the


computer random number generator. For bothmethods, crop yield for each of the 30 selectedvines was determined by removing, countingand weighing all the bunches.

In the random sampling method, crop yield forthe block was estimated using the mean yieldper vine (mean number of bunches per vinemultiplied by the mean bunch weight per vine)and the total number of vines within the block.In the zonal viticulture method, crop yield withineach zone was estimated using the mean yieldper vine for each zone and the number of vineswithin each zone. Crop yield for the block wasdetermined by summing the estimated yields foreach zone (Table 2).

Using the random sampling method the blockyield was estimated to be 26.26 t compared to23.57 t using the zonal viticulture method. Theactual tonnage delivered to the winery was21.3t. This represents an overestimate of 4.96 t(23.3% difference) using the random samplingapproach and an overestimate of 2.28 t (10.7%difference) using the zonal viticulture approach.The random sampling method when comparedwith the zonal viticulture method predicted a12.2% greater mean number of bunches pervine and a 7.9% greater mean bunch weight.

Since the area (and hence the number of vines)associated with the medium vigour zone repre-sents 71% of the total block, it is not surprisingthat the mean yield per vine determined for thatzone is similar to the mean yield determinedfrom the 3 zones together (Table 2). In otherwords, 10 samples taken from the mediumvigour zone alone in order to determine yieldper vine would have given a block estimate veryclose to the actual tonnage delivered (ie. 21.6 tpredicted compared to 21.3 t delivered). Thisobservation highlights the benefit of getting asgood an estimate of the mean as possible (ie.removing both high and low extremes from theestimate results in an improved estimate).

A few other points emerge from this study.Firstly, it is worth questioning whether the lowyielding zone warranted separate delineationgiven that it represents only about 1% of thetotal number of vines in the block. Secondly, inallocating the 30 vines equally between thethree zones, bias was introduced into the meanestimate since a 10 vine sample in each of the 3zones represents a sample size equivalent to 1%,0.4% and 21% of the total number of vines in thehigh, medium and low vigour zones respec-tively. Thus, whilst, the results point to the meritof zonal-based sampling, they also suggest thatthe number of samples allocated to each zoneshould be proportionate to the zone area (orvine number), relative to the total for the block.If this had been done, then there would havebeen 8 sample vines in the high vigour zone, 21sample vines in the mediumvigour zone and 1sample vine in the low vigour zone. Therefore,

when using zonal-based sampling, it is recom-mended that this proportional allocation ofsamples to the different zones is adopted.

Selective harvestingVariation in fruit quality delivered to the winerycan result in ‘average’ quality from whole vine-yards. This limits the options available towinemakers for maximising the production ofhigh quality wines and producing wines that fitmarket demand. The selective harvesting ofvineyard blocks using a combination of PCDimages and harvester generated yield maps hasbeen demonstrated to improve the uniformityof fruit parcels delivered to the winery. A num-ber of commercial examples of selective har-vesting have been reported in the literature andconference proceedings (eg. Bramley et al. 2005;Proffitt and Pearse 2004). In order to reiteratethe potential benefits of this approach to har-vesting, a case study from a vineyard in Marga-ret River is briefly described.

In 2002, airborne DMSI data was acquired for a3.3 ha section of a Cabernet Sauvignon blockand then processed in order to produce imagesof PCD. Two weeks prior to the expected har-vest date, vines in areas of low and high PCDwere assessed on the ground for vine vigour,and fruit samples assessed for sugar, pH, titrat-able acidity and sensory characteristics. Theresults obtained confirmed that differences inPCD translated into real differences on theground. The section of vines was subsequentlydivided into a northern zone with high vinevigour (ie. high PCD) and a southern zone withlow vine vigour (ie. low PCD), and selectivelyharvested by keeping fruit from the two zonesseparate. This strategy has been repeated for 3consecutive vintages. In some years, harvestingthe two zones has not occurred on the sameday, but parcels of fruit from the two zones havealways been processed separately in the win-ery. For both the 2002 and 2003 vintages,differences in quality between the wines madefrom the two zones have been significantenough to justify allocation to different endproducts. If the section had been harvested asa single unit, the resulting wines would havebeen allocated to the lower end-use product.This strategy has improved profitability quitesignificantly.

ReferencesBramley, R.G.V, Proffitt, A.P.B, Hinze, C.J. Pearse,B. and Hamilton, R.P. (2005). Generating ben-efits from Precision Viticulture through selectiveharvesting. In: Stafford, J.V. (Ed). Proceedingsof 5th European Conf. Prec. Agric., WageningenAcademic Publishers, The Netherlands. (pp.891-898).

Proffitt, A.P.B. and Pearse. B. (2004). Addingvalue to the wine business precisely: usingprecision viticulture technology in MargaretRiver. Aust. NZ Grapegrower Winemaker. 491:40-44.


SPAA PA Equipment surveyRohan Rainbow, Executive Officer SPAA

e-mail: [email protected]

SPAA PA Equipment SurveySPAA have recently completed a detailed surveyof PA equipment to all SPAA & SANTFA membersin SA receiving surveys on 92 different items ofprecision agriculture equipment, predominantlyguidance and auto steer equipment. This surveyfunded by the SA Grain Industry Trust was con-ducted by Scott Boyle, formerly of Regional SkillsTraining. The survey documented farmers expe-riences on equipment reliability, ease of use andtechnical support. All but six surveys wherereturned from South Australian farmers.

The average size of the property that PA equip-ment was used was over was 2,490 hectares andthe grower produced on average 3,659 tonnesof grain. The average number of years surveyrespondents had been involved with PA was 2.78years. Almost 18% of respondents where practic-ing some form of controlled traffic.

Following this survey, it has become evident thatthere is a need for broadening the survey to otherstates outside SA, particularly WA, Victoria & NSWto get a better total aggregate of single models ofPA equipment. SPAA would like to seek additionalfunding to broaden this survey.PA Equipment Survey FindingsThere are several main areas of issues and prob-lems the PA equipment industry needs to addressthat emerged from this survey.Signal accuracy and reliability – 56% of allsurvey respondents had some form of signalproblem. 25% specifically indicated signal lossoccurring.Software and data removal and storage –With more than 40% of all survey respondentshaving software problems of some sort and someof the lower ratings.Screens – The predominant screen problemsrelated to glare and reflection on the screens.Operators manual and fitting instructions– As the lowest rated feature in the survey and hassignificant OH&S considerations.

Many thanks to all the respondents who contrib-uted to this survey. Many thanks also to the SAGrain Industry Trust who funded this survey.

The survey showedthat four manufactur-ers are dominating

the market in terms ofprecision agriculture

equipment.

Auto steering andguidance made up

74% of the total useof PA equipment.

A distant 9% usedyield mapping.

Most PA equipmentusers where usingsub-metre or sub-

10cm signals.

Most respondents sufferedsome form of signal

problems with their differ-ential GPS signal. Survey

comments and the surveydata generally indicatedthat they where mostly

minor or of short duration,

Half of the farmers usedsatellite differential

correction signal fol-lowed by 31% that

relied on marine naviga-tion beacon

Congratulations toRyan Dubois of Wudinna EyrePeninsula SA who has won aGarmin GPS72 personal navi-gator for submitting his sur-

vey form. His name was ran-domly selected by SPAA presi-

dent Brian Tiller from thesurveys recieved.

spaa summer 2005 · understanding guidance days at longerenong victoria & roseworthy sa in...

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