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SPAA, a non-profit, independent membership organisation - promoting the development and adoption of precision technologies in agriculture, viticulture and horticulture

Precision Ag News

www.spaa.com.au

T 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

FeaturesActive sensors

Views from USA

High resolution imagery

PA in sugar

Volume 5 Issue 1 Spring/Summer 2008

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Precision Ag News www.spaa.com.au 3

ContentsPA on the up . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

MGA Crop Insurance – members offer . . . . . . . 5

SPAA in the USA . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Exploring the PA possibilities . . . . . . . . . . . . . . . 8

Actively responding to the season . . . . . . . . 10

NDVI imagery determines harvest strategies . . . . . . . . . . . . . . . . . . . . . . . . 12

Forensic agronomy . . . . . . . . . . . . . . . . . . . . . . . .15

Remote sensing for crop variability in peanuts . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

Cuban technology backs sugar harvest breakthrough . . . . . . . . . . . . . . . . . . . . 21

Precision Ag News is published by Southern Precision Agriculture Association© 2008 ISSN1449-3705SPAAPO Box 83, Strathalbyn, South Australia 5255Ph 08 8536 3958 Fax 08 8536 3734 Email [email protected]

Precision Ag News is edited and produced for SPAA by AgriKnowHow with design by Lightning Designs.

SPAA DISCLAIMERSPAA has prepared this publication, on the basis of information available at the time of publication without any independent verification. Neither SPAA and its editors nor any contributor to this publication represent that the contents of this publication are accurate or complete; nor do we accept any omissions in the contents, however they may arise. Readers who act on the information in this publication do so at their risk. The contributors may identify particular types of products. We do not endorse or recommend the products of any manufacturer referred to. Other products may perform as well or better than those specifically referred to.

SPAA is supported by

Advertising contact Hyde Media 03 9870 4161 [email protected]

4 Precision Ag News www.spaa.com.au

If the demand for copies of the SPAA publication ‘PA in Practice’ is anything to go

by, the interest in adopting PA is increasing dramatically. As Malcolm Sargent noted at the 2008 AGM, the dramatic changes in input and commodity prices are in part fuelling this interest. However, improved knowledge and understanding of PA, technological developments and more accessible pricing are all likely to be playing a part.

In this issue of Precision Ag News we report on some of the papers that were presented at the SPAA Crop Scanning Forum and AGM, and at the 12th Annual Symposium on PA Research and Application in Australasia, held in Sydney in October 2008. If you missed attending either of these events, papers and presentations can be found on the web. For the SPAA Crop Scanning Forum visit www.spaa.com.au and for the Sydney symposium visit the Australian Centre for Precision Agriculture’s website at www.usyd.edu.au/su/agric/acpa.

For the first time data generated by a SPAA research project supported

by the SA Grains Industry Trust was presented at the International Conference on Precision Agriculture, held in Denver, USA, in July 2008. The Grains Research and Development Corporation supported two SPAA grower members to attend the conference. In addition to presenting the paper, SPAA committee members Malcolm Sargent and Ashley Wakefield met with farmers, agronomists and researchers using and developing PA technologies in the USA (see page 6).

AGM 2008

At the 2008 AGM five long-standing committee members retired, Brian Tiller, Peter Cousins, Allan Mayfield, Matthew McCallum and Richard Turner. Our appreciation is extended to all of them, as they have been instrumental in steering the direction of SPAA and increasing the adoption of PA. Mark Branson was elected as SPAA’s new President, replacing Malcolm Sargent who has done a great job leading SPAA for the past two years. You can learn about how Mark is using PA and his hopes for the industry’s future, in the article on page 8. A big thankyou must go to

Pam Pilkington for her past efforts. She has decided not to continue as the Administration Officer, but is instead taking the opportunity to spend more time with her growing family. Three new members have joined the committee: viticulturist Hans Loder, agronomist Sam Trengove and grain grower Grant Pontifex. We look forward to their involvement (Table 1).

SPAA News

PA on the up The SPAA Expos and Forums provide a great place to exchange ideas on PA.

Chris Slade (L), Rinex and Lameroo grian grower Gary Flohr.Kirstie Murphy, SPAA Executive Officer

Ivan Di Federico, Topcon with the Crop Spec™ sensor that will be launched in 2009.


Electronic communications

I want to make sure that SPAA has your correct email address, as during the coming year more use will be made of electronic communications to keep you up-to-date with the latest events and developments in PA. If you have changed your email address recently or are unsure if it is in the database please let SPAA know by emailing [email protected].

Precision Ag News will now be published three times per year, and continue to feature a broad range of articles about PA research and adoption.

2009 European Conference on Precision Ag - 6 to 8 July 2009

A joint international conference that brings together the European

Conference on Precision Agriculture, the European Conference on Precision Livestock Farming and the European Federation for Information Technology in Agriculture, Food and the Environment will be held at the campus site in Wageningen University, Netherlands,in July 2009. There will also be some pre- and post conference activities. One of them will be the international Field Robot Event. http://www.jiac2009.nl/Organization/Program/tabid/387/Default.aspx

If you are interested in attending please let me know as SPAA will considerer applying to GRDC for a travel grant.

Kirstie Murphy, SPAA Executive Officer. 08 8536 3958, 0408 088 624 [email protected]

SPAA has negotiated a crop insurance package on behalf of its members with MGA Insurance Brokers Pty Ltd. The major feature of this policy for SPAA members is the After Harvest Declaration where the crop insurance premiums are based on the actual crop yield at harvest, as recorded by a yield monitor. A traditional pre-harvest final estimate is also available upon request.

Other benefits of this offer include:

• Anagreedvaluepertonne

• Seedandgrainintransit

• Seedandgraininstorage

• Chemicaloverspray

• Strayinglivestock

This crop insurance package offers SPAA members the opportunity to: access competitive insurance rates, have their premiums based on actual yields and support SPAA.

For more information contact Chris Noonan at MGA Insurance Brokers on 08 8632 5588 or [email protected].

SPAA News

MGA Crop Insurance – members offer

Table 1: SPAA Committee and Officers 2008/09.

Mark Branson - Grain Grower, Stockport SAPresident [email protected] 0417 832 776

Vice President Randall Wilksch - Grain Grower, Yeelanna SA

Treasurer Ed Cay - Technician gps-Ag, Adelaide SA

Immediate Malcolm Sargent - Grain Grower, Crystal Brook SA Past President

Committee Members

Sam Trengove Agricultural Consultant, Clare SA

Rob Bramley Principal Research Scientist - CSIRO, Adelaide SA

John Heap Senior Research Scientist - SARDI, Adelaide SA

Hans Loder Viticulturist, Wingara Wine Group, Coonawarra SA

Colin Hinze Viticulturist, Taylors Wines, Auburn SA

Grant Pontifex Grain Grower, Kadina SA

Ashley Wakefield Grain Grower, Urania SA

Leighton Wilksch Product Development Agronomist, Landmark, Paskeville SA

Ben Mitchel (L), Taylors Wine and Colin Booth, Fairport.


It is always valuable to look over the fence and take the time to share information. This was very

much the objective of Malcolm Sargent and Ashley Wakefield’s trip to the USA in July 2008. In addition to presenting the results from the SPAA research on the ‘Economics of Adopting PA on Australian Farms’, they took the opportunity to talk to farmers, agronomists, service providers and researchers using or developing PA technologies. They also took the opportunity to present the Australian perspective to a few of the machinery manufacturers.

“The objectives of the trip were four fold,” explained Malcolm Sargent. “Presenting the paper was the catalyst but we wanted to gain a better perspective and understanding of the adoption of PA in North America; to understand how barriers to PA adoption have been overcome in the USA; and to identify opportunities to extend PA adoption in Australia”.

Attending the 9th International Conference on Precision Agriculture provided and excellent platform to learn about new and emerging PA technologies and their application.

the adoption of PA in the USA is at a similar

stage to Australia

The conference, in Denver, Colarado, was attended by over 450 participants from 43 countries and 250 papers on Precision Agriculture were presented.

As Ashley points out, “over the two and half days there were four rooms running concurrent 20 minute sessions, so at best you could only attend 25 per cent of the presentations.”

From the conference Ashley reports the following observations:

• Therewasanemphasisoncropscanning research using real time scanning, airborne imagery and satellite imagery to target variable rate application of nitrogen fertilisers.

• Therewereseveralpresentationson real time protein measurements, including using this technology to predict test weight in cereals.

• Researchisbeingcarriedoutusingcrop scanning (NDVI) to determine whether crops are suffering from water stress or lack of nitrogen, before applying in-crop nitrogen.

• Variouson-the-gosoilsamplingtechniques for a range of soil properties are being developed. For example a group in Korea are developing a mobile motorised digital cone penetrometer for measuring soil strength and compaction.

• Weedrecognitiontoguideprecision weeding robots is being developed.

Prior to the conference Malcolm and Ashley visited Case IH and John Deere, major manufacturers of farm equipment with PA systems and met with organisers and members of organisations that are similar to SPAA in Nebraska and Kansas.

They emphasised to the manufacturers the need for equipment compatibility and for calibrations etc that are suitable for use in Australia.

Malcolm reports that, “achieving this will be an on-going challenge

SPAA News

Emma Leonard, AgriKnowHow

A recent trip to the USA by two SPAA committee members provided a valuable platform for two-way dialogue to share and learn about PA in both countries.

SPAA in the USA

Malcolm Sargent (L) and Ashley Wakefield (C) with Nebraskan farmer Arnie Hinkson, who is showing them his liquid fertilise system that has variable rate control. In the background are some of the thousands of hectares of irrigated corn they saw on their trip through Wisconsin, Nebraska, Kansas and Colorado.


A shock for weeds

SPAA Newsbecause their questions to us suggested that many of the people we met in the USA had little or no concept of how we farm in Australia.”

These visits and attending the conference highlighted that the adoption of PA in the USA is at a similar stage to that in Australia. Some farmers have fully integrated PA into their operation, while others are still using a summer fallow/wheat rotation and little new technology.

However, at the University of Nebraska, every agricultural course offered contains a PA component. Education is consdered an important part in achieving the adoption of PA technology.

Groups such as the Nebraska Agricultural Technology Association (NeATA) and the Kansas Agricultural Research Association (KARA) have been formed by innovative people (growers, researchers and industry) to make agiculture more productive. It is hoped that SPAA can maintain and build on the contacts made with these groups.

This trip was partly funded by a travel grant from the GRDC and by SPAA. More information about the International Conference on Precision Agriculture is located at www.icpaonline.org and the next conference will be held in the USA in 2010.

Malcolm’s list of interesting web sites.www.mapshots.com

www.agmanager.info – search for Terry Kastens

www.notilltalk.org

www.talk.newagtalk.com

www.unibots.com

www.futurefarm.com – precision irrigation

www.precisioncropmanagement.com

www.rapideye.de

http://precisionagriculture.unl.edu – go to publications

http://bse.unl.edu/adamchuk

http://plantsci.sdstate.edu/precisionfarm

First there was Greenseeker® now there is GreenWeeder an autonomous system designed to detect and destroy weeds without the use of herbicides.

Still in development, this lightweight robot is equipped with a GPS and a laser scanner with a 240 degree rotation for in row guidance, stereo imaging cameras to assess distance and a long range communication system.

Under the supervision of Dr Jay Katupitiya, University of New South Wales student Kim Son Dang has developed the software for the GreenWeeder and is currently experimenting with the use of electric shock treatment to kill weeds.

Basically any material that closes the circuit will receive an electric shock. This way the GreenWeeder does not have to be fitted

with sensors that identify weeds or their location. Electric shock treatment is most successful on weeds with a single tap root.

In future the team may mount other non-chemical weed control tools on the robot and assess their performance.

The GreenWeeder was just one of the autonomous agricultural tools demonstrated during the post Symposium tour to the Centre for Autonomous Systems at the University of NSW.


PA in practice

When I started yield monitoring in 1997 a two megabyte data card

cost $500; this figure is burnt on my brain, as my first card and its precious data were lost after falling from my top pocket into a water trough.

In the intervening 11 years we have seen the price of PA equipment and peripherals dramatically decrease. Over the same period our understanding of their application and potential applications continues to increase.

Like many I have seen big savings from the use of autosteer in time and inputs. I estimate autosteer has helped reduce overlap by five per cent. I have also converted to controlled traffic farming (CTF), with implement widths matched and run on 2.2m wheel spacing. On our heavy black cracking clays and red brown earth soils the reduction in compaction and improvements in water infiltration brought about by CTF and autosteer have resulted in estimated yield improvements of between two and seven per cent.

Having adopted these changes, further soil improvements will take a very long time to express themselves fully. This is not the case for input management, the possibilities of which I believe we have only just started exploring.

For the past few years I have used PA data to support variable rate (VR) applications of phosphorus at seeding, in-crop nitrogen management and more recently weed control.

Variable rate PSoil tests indicated adequate levels of phosphorus (P) across all soil types. However, the yield maps indicated in-paddock variation. So, I decided to use a replacement rate of P based on the previous year’s crop yield, rather than apply a blanket rate of 22kg P/ha across a paddock.

Replacement rate maps are calculated on a crop related replacement rate plus a blanket rate of 2kg P per tonne of grain removed to account for P tied-up in straw and the soil.

For example:

• 3.5kgPisreplacedforevery 1t/ha of cereal grain removed;

• 4.4kgPreplacedforevery1t/haof legume grain removed;

• 7.5kgPreplacedforevery1t/haof canola grain removed.

On average, I estimate that moving to a replacement fertiliser policy is reducing expenditure on P by about 15 per cent, with no detrimental affects on the soil test.

Biomass sensing for NFor several years I have been experimenting with biomass sensing as a method of determining in-crop nitrogen requirements. The objective is for the crop to indicate its nitrogen requirement for that growing season rather than using a pre-season soil test.

At seeding, mono ammonium phosphate fertiliser is the only source of nitrogen. Liquid urea (UAN 42 per cent N) is applied, if required, at about growth stage 31 (GS31).

Mark BransonMark Branson, SPAA’s incoming President shares his experience of and vision for PA.

PA possibilities

Mark Branson, incoming President of SPAA demonstrates the use of his GreenSeeker® for making in-crop nitrogen decisions.

Farm details

Location: Stockport, SA

Annual Rainfall: 425 to 525mm

Area: 1200 hectares, 80 per cent annually cropped, remainder grazed.

Cropping system: dryland, no-till cropping with wool and prime lamb enterprises

PA equipment: Case AFS yield monitor, Kee Zynx controller with VR capacity, Kee Zynx 2cm autosteer, GreenSeeker® handheld biomass scanner.

PA software: CASE IH AFS (SMS), ZYNX Maplink.


All post seeding N is applied as a liquid because it is not possible to achieve an even spread of granular fertiliser across 40m, (this width is determined by the CTF set-up).

While UAN is expensive I have calculated that running over more of the crop and achieving an uneven spread of granular fertiliser would cost me more in yield loss.

I have had about 25 per cent of paddocks zoned professionally using a range of data, while I have roughly divided the remaining paddocks into high, medium and low yield areas based on personal experience and yield data. The remainder will be properly zoned in the coming year.

Urea or UAN is applied in strips (20 by 100m) in each production zone in a paddock at the two leaf, crop growth stage. These N rich strips are used to provide the biomass scanner with a reference crop that is unlimited by nitrogen. I use a GreenSeeker®, for biomass scanning.

At about the mid-tillering (GS25), I start to scan the N rich strips and the crop adjacent to the strip. If there is a large difference at mid tillering, I apply a low blanket rate of N to stop the crop becoming more deficient. If there is no difference at this stage then I do not apply N.

I continue to scan crops on a weekly basis. The next and most critical stage is at about first node stage (GS31). If there is a difference at this stage then I use the NDVI readings fed directly into the sensor software to produce a fertiliser rate for each zone in the crop. I assess this rate based on available soil moisture and future rainfall predictions and apply the prescribed or a modified rate.

Up to GS31 there is a good relationship between the readings from the nitrogen rich strip and the crop NDVI readings. Using the GreenSeeker® has certainly given me the confidence not to apply N in wheat if there is no NDVI or visual difference.

At later growth stages the accuracy of scanning can reduce because with a dense green canopy the NDVI values may saturate - that is, there may be too many green leaves to see if there is a difference. In less dense canopies and if the season looks

good and I have good soil moisture levels, I am happy to scan up to GS39 and use the recommended rate for a top-up late N application. If the crop has saturated I use many methods to calculate my N rate including ‘gut feel’.

Currently each zone receives a fixed rate of N but in future I hope to purchase a tractor mounted biomass sensor that will enable me to do on-the-go variable rate with the boomspray.

When using UAN, care must be taken to avoid burning leaves, especially late in crop development. UAN can be applied through flat fans, diluted or neat, and through streaming nozzles or dribble bars. When using flat fans avoid: applications at above 18°C, rates above 100L/ha and wet leaves. If these conditions occur then streaming nozzles or dribble bars should be used. UAN can be diluted 50:50 with water to lessen the potential for leaf burning.

In future, I hope Australian calibration data for the Greenseeker® will be further developed for canola, pulses and barley, as I believe that this technology can have application in all crop types, not just for nutrition but also for desiccation and growth regulants.

Weed mappingThe biomass sensor is also enabling me to map ryegrass patches, which I then treat differently in the following cropping season. I estimate about 25 to 30 per cent of a paddock can be covered with high density ryegrass patches. By scanning crops at early post emergence these patches can be identified and seeding rates in the following year can be modified appropriately.

For example, where I would have usually sown wheat at a blanket rate 100kg/ha, I have now established three seeding rates depending on the density of ryegrass in the previous crop.

• Verylowdensityryegrass, 70kg/ha;

• Mediumdensityryegrass, 120kg/ha;

• Highdensityryegrass,150kg/ha.

I have been really pleased with the results this has achieved. The high seeding rates provided good competition and the plants do not tiller as much as those in the low seeding rate areas. So, haying off has not been experienced. The reduced tillering is likely to be due to the lack of nitrogen applied at seeding. By head emergence the crop looks pretty even and so far I have not seen an impact on yield.

From my experience this control method has been as successful as competitive crops and grazing but allows me to grow wheat in a paddock with high levels of herbicide resistant ryegrass.

Methods of variable rate weed control will provide a range of benefits and I look forward to seeing more research and development in this area.

I have already mentioned some of the aspects of PA that I hope will be available to the industry soon, including more NDVI calibrations for Australian conditions. I also would like to be able to map soil moisture accurately, as this is the real driver of the cropping system.

I believe that software and hardware need to be simplified further, to include plug and play hardware. Oh for the day when you add a piece of hardware onto the agricultural vehicle and push a button and it works, and for software that only requires a minimum of buttons to be pushed to achieve the desired result. At the moment everything is too complicated for most farmers to become excited about.

In the past 11 years I have learnt much about PA and not just to button down my top pocket when it contains a data card. Using PA is making me a better farmer; I am now more able to match inputs to production potential, which makes sense financially and environmentally. Overall PA makes me a better agronomist.

It is great to be a part of this exciting period in agriculture.

For more information

Mark Branson, 08 8528 2412 [email protected]

PA in practice


Active sensors

Until recently PA has been based around the use of historical data to manage

soils and crops. This works well for the management of factors that change slowly over time but is not as useful for reacting to the season. Active sensors, such as CropCircle™, Yara N-Sensor® and GreenSeeker®, are able to identify variation in characteristics of a growing crop.

Active crop sensors use an inbuilt light source to illuminate the crop and measure the crop’s reflectance in several specific wavelengths. While the human eye is a crucial active crop sensor, it cannot see the infrared wavelength. The sensors currently on the market measure the reflectance of red light and the infrared spectrum by the plant.

Plants use most of the blue and red light for photosynthesis, while most of the green light is reflected; that is why we see plants as green. Virtually no infrared wavelengths are used

for photosynthesis, so they are also reflected. Therefore, a stressed plant has a lower reflectance of red and infrared light (Figure 1). It is these differences that the active sensors are able to quantify.

Reflectance of the infrared wavelengths has been found to be closely related to crop biomass, while the red reflectance is connected with the level of chlorophyll, which the sensors can detect changes in before they are seen with the human eye.

Different weather patterns cause crops to grow and respond differently to inputs on different soil types. In-crop management needs to respond to these differences if the objective is to generate a more even return across the whole paddock. Active sensors provide the ideal tool to identify these differences.

Having its own light source means that an active sensor can be used in all light conditions and the

readings are more stable as the light conditions are the same for every scan. This makes imagery from sensors more replicable or useful for measuring changes over a period of time. The reflectance recorded in

Jim Wilson, Soilessentials

Active crop sensors allow crop scouting and real-time management of nitrogen and agrichemicals.

Actively responding to the season At the SPAA Forum, Jim Wilson suggested that

the best strategy for mid-season N fertilizer was to apply it only to the responsive areas.

Biography

Jim Wilson was a keynote speaker at the SPAA Crop Scanning Forum and joined several of the PA Group Crop walks in August. He is a cereal and potato grower from Scotland. Jim has gained broad experience using in-crop scanning and satellite imagery in his own crops and those of farmers for which his business, Soilessentials, provides agronomic services based on PA technology. Soilessentials is also an agent for the sensing technology CropCircle™ and for Mojo RTK.


satellite images can be distorted by atmospheric conditions.

Scans can be carried out in real time, providing direct feedback to the controller to vary inputs such as nitrogen or growth regulators on-the-go. Alternatively the scan can be conducted during another operation, e.g. spraying, and the information assessed in the farm office where an application map is produced. This map is then used by the variable rate controller to modify input rates by location.

Both techniques allow growers to respond to crop variability introduced by current weather patterns. What an active scanner cannot do is predict the future or identify what is actually limiting crop growth. Therefore, the farmer and agronomist still need to make decisions on what treatment, if any, is appropriate and if all other limiting factors have been eliminated to determine nitrogen rates.

new roles are developing for active sensors

Currently the main job of an active sensor is to redistribute nitrogen to the locations in the paddock where it will be best used. New roles are developing for active sensors to identify where inputs such as herbicides, growth regulators or modified seeding rates are most required.

In the UK we have found the easiest way to improve nitrogen use efficiency, and consequently return, is to apply nitrogen only to responsive areas. The CropCircle™ calibrations are based on the Home Grown Cereals Authority’s Wheat Growth Guide. Therefore, it provides a map of the amount of nitrogen in the crop at the time of scanning. In the UK there has been very good correlation between the

CropCircle™ active sensor and the identification of the crops nitrogen status.

The results from applying this form of variable rate nitrogen management in the UK have recorded a yield increase of three percent, compared to uniform applications of nitrogen. This figure is inline with results from similar trials in South Australia.

Calibrations are currently being developed under Australian conditions for CropCirle™.

More information on active sensors can be found in Precision Ag News Volume 3 Issue 1.


Jim Wilson, Director, Soilessentials. 00 11 44 1 356 650 307 [email protected] www.soilessentials.com

Figure 1. The changes in crop reflectance between a healthy and stressed plant. (Source Jim Schepers, USDA).

Active sensors

Scans can be carried out in real time, providing direct feedback to the controller to

vary inputs such as nitrogen or growth regulators on-the-go. Alternatively the scan can be conducted during another operation, e.g. spraying, and the information

assessed in the farm office where an application map is produced. This map is then

used by the variable rate controller to modify input rates by location.

Both techniques allow growers to respond to crop variability introduced by current

weather patterns. What an active scanner cannot do is predict the future or identify

what is actually limiting crop growth. Therefore, the farmer and agronomist still need to make decisions on what treatment, if any, is appropriate and if all other limiting

factors have been eliminated to determine nitrogen rates.

Figure 1. The changes in crop reflectance between a healthy and stressed plant.

(Source Jim Schepers, USDA).

Currently the main job of an active sensor is to redistribute nitrogen to the locations in

the paddock where it will be best used. New roles are developing for active sensors

to identify where inputs such as herbicides, growth regulators or modified seeding rates are most required.

In the UK we have found the easiest way to improve nitrogen use efficiency, and consequently return, is to apply nitrogen only to responsive areas. The CropCircle™

calibrations are based on the Home Grown Cereals Authority’s Wheat Growth Guide.

Therefore, it provides a map of the amount of nitrogen in the crop at the time of

scanning. In the UK there has been very good correlation between the CropCircle™ active sensor and the identification of the crops nitrogen status.

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Amberreceiver

IR reciever Healthy Plant

StressedPlant


For a long time significant variation across vineyard blocks has been recognised to impact

on the final quality of the wine. However, these differences in vine canopy and fruit formation, which have formed the basis of harvesting decisions, were only being identified visually. The use of new technologies allows variation to be quantified and managed, resulting in targeted pest and disease control and improved fruit quality and increased dollar value per tonne.

Mission Estate Winery is located in the Hawke’s Bay region of New Zealand’s North Island. Precision agriculture (PA) applications were introduced to the vineyard management systems in 2006 to improve knowledge of the vineyard and quality of the fruit supply.

Biomass scanning

One tool that has been used with great success to help determine vine variation is biomass measurement with the Normalized Difference Vegetation Index (NDVI).

A CropCircle™ sensor is mounted on a quad bike (Figure 1). As the bike is driven up and down the vine rows, the CropCircle™ sensor takes five readings of the canopy biomass (vine vigour) every second. Each reading is GPS positioned and the data is stored on a logging device. Once the vine vigour data is recorded it is downloaded into a Geographic Information System (GIS) and overlaid onto a satellite image of

Figure 1. The CropCircle™ senor is mounted on the rear of a quad bike at a sufficient height to scan the biomass of the whole canopy.

the block. The GIS software makes it possible to interpolate the data and produce images of NDVI that are split into defined zones, representing areas of variation in vigour. At Mission Estate Winery, a number of blocks were identified to have significant variation but visually this was difficult to quantify.

This biomass image (Figure 2) was used as the basis of the 2007 vintage harvesting plan. Having defined the biomass zones it was possible to sample fruit from these areas and to provide an indication of differences in phenological and maturity ripeness between the zones. Vast differences in maturity were found

Active sensors

Caine Thompson, Mission Estates

PA tools are helping introduce micro-management in NZ vineyards resulting in improved grape production, quality and product value.

NDVI imagery determines harvest strategies

Table 1. Differences in maturity analysis of grape juice by zone, after NDVI mapping Mere Road vineyard.

Syrah Maturity parameters

Titratable Date Zone Brix pH acidity (TA)

9/04/2007 A (low vigour) 24 8.8 3.15

B (high vigour) 23.3 8.6 3.11

11/04/2007 A HARVEST 24.6 7.1 3.33

18/04/2007 B HARVEST 25.2 6.4 3.35

Merlot Maturity parameters

Date Zone Brix TA pH

14/03/2007 A (low vigour) 21.8 8.06 3.17

B (high vigour) 20.2 10.5 2.95

4/04/2007 A (low vigour) 23.4 6.5 3.36

B (high vigour) 22.8 9 3.17

7/04/2007 A HARVEST 24 6.4 3.43

14/04/2007 B HARVEST 23.4 6.8 3.29


Figure 2. Mission Estate – Mere Road vineyard on the Gimblett Gravels was the first block to be NDVI mapped. To the left of the red line is Merlot and to the right Syrah. The yellow and green areas are low vigour and the blue high vigour.

from areas of low NDVI compared to areas of high NDVI (Table 1).

In consultation with Mission Estate’s Chief Winemaker Paul Mooney, it was decided to separate the fruit from these vigour zones. The goal was to produce premium fruit from the low vigour zones (Zone A) for ‘Jewelstone’, Mission Estate’s most exclusive label.

An extremely high input management model was introduced within the boundaries of these low vigour zones. This included bunch thinning clusters down to one bunch per shoot, removing apical and wing bunches, lateral thinning, and bunch and shoot positioning. This resulted in vines that were very well balanced and provided the basis for even fruit ripening and consistent flavour development. The fruit from these low/medium vigour zones was ready for harvest seven days earlier than the remainder of the block and had

ripe flavours and soft silky tannins.

The fruit from the higher vigour zones (Zone B) was left to ‘hang’ for longer, allowing the sugar levels to increase to a desired level as vintage conditions remained settled. The performance of these grapes will be monitored in the barrel.

The second property mapped for NDVI was a block of Cabernet Sauvignon. Before

the CropCircle™ Sensor was used on this property the block was thought to be fairly uniform. It had been agreed that this parcel of fruit (25t) would be picked as one block and used for the entry level estate Cabernet Sauvignon. Figure 3 contains the NDVI image, which clearly defined two zones.

The zones were sampled for fruit maturity and substantial differences in the maturity of the fruit between these vigour zones were found (Table 2).

It was decided that the variation was enough to warrant selective harvesting of these zones. Zone A was significantly more advanced than Zone B. The quality in Zone A was to a level that meant that this parcel of fruit was upgraded to reserve status, thus giving the grower an increased return of $200 per tonne. The fruit from Zone A was picked eight days earlier than Zone B. The major advantage of this, when growing in a cool climate conditions, is that a reserve quality Cabernet Sauvignon was achieved significantly earlier than expected, reducing the risk of vintage rains and cooling temperatures.

Figure 3. This image shows clearly variation in biomass (Zone A, green lower NDVI and Zone B blue higher NDVI) that had not been observed visually. This image resulted in selective management of the two areas.

Targeted pest control The second PA tool used for improved vineyard management at Mission Estate is a hand held GPS unit. This is used for marking, recording and tracking the spread of Leaf Roll Virus (LRV). This data is then mapped over a satellite image of the block using a GIS. LRV delays fruit ripening, causes increased acidity, slows development in flavour expression and results in yield reductions. Once the vine is infected with LRV, the incidence and level within the vine will increase over time and the described effects will become more and more evident. LRV spread is mainly from the vector mealy bug that transmits the virus to vines after feeding on other virus-infected vines. With GPS tracking, ‘hotspots’ of virus and potential high populations of mealy bug can be identified. These technologies help determine the zones of high mealy bug populations to spray or which infected vines to remove. In the coming years this form of micro-management that is facilitated by PA is anticipated to expand to all areas of vineyard management.


Caine Thompson, Viticulturist/vineyards manager, Mission Estates. [email protected]

Table 2. Differences in maturity analysis of grapes by zone after NDVI mapping.

Cabernet Sauvignon Maturity parameters

Titratable Date Zone Brix pH acidity (TA)

23/03/2007 A 22 8.25 3.31

23/03/2007 B 21.8 8.1 3.32

31/03/2007 A 22.6 7.5 3.38

31/03/2007 B 21.8 7.8 3.36

12/04/2007 A HARVEST 24 5.25 3.78

20/04/2007 B HARVEST 25 5.6 3.81

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There has been much focus on understanding the causes of in paddock variation.

Queensland agronomist Tim Neale, CTF Solutions, has taken his investigation to the next level using high resolution satellite imagery. He acknowledges that it is not feasible to manage variability at a 1m resolution but this level of detail is required to understand the causes. In many cases he has found the variability relates to management rather than underlying soil or topographic causes.

Much satellite data used in precision agriculture has been based on coarse data. That is, each pixel that makes up the image represents large areas. For example, 25 metre pixel (625m2) for a satellite image gathered from the LANDSAT or 10 metre (100m2) from SPOT. At this resolution much of the variability is averaged out in each pixel and consequently masked (Figure 1).

High resolution satellite imagery provides pixel sizes of less than 2.5m

it is not feasible to manage variability at a 1m resolution but this level of detail is required

to understand the causes

(6.25m2) and much more variability is seen.

Tim has been using high resolution satellite data with his clients for several years and has been amazed at how often the variation in a paddock is related to management or to factors not identified by other forms of imagery. From his experience the timing of data capture during the growing season is not crucial, as poor areas generally appear poor throughout the season.

Using data from satellites that provide 1m and 0.6m resolution images CTF Solutions has now captured over 850,000ha of

high resolution satellite images across Australia.

Four wavelength bands are captured allowing true colour analysis, so images can be delivered in a range of formats including looking like aerial photos or NDVI, within about a week of capture. At about $0.50/ha high resolution imagery has become cost effective (minimum areas are required).

The causes of variation being identified include poor calibration of fertiliser spreaders resulting in up to 50 per cent of the paddock being under fertilised, soil compaction caused by random traffic and poor plant vigour caused by uneven seeding depth/poor seeder set-up. Spray damage, variety differences, disease and insect damage have also been recorded. Paddock history and previous management such as header rows also clearly show-up in this high resolution data, and all have considerable effects on crop productivity.

Disease has also been observed using these images. An NDVI analysis of a

Forensic agronomyHigh resolution satellite images have high-

lighted that in-paddock variability is often the result of previous management practices.

Emma Leonard, AgriKnowHow

In many situations management practices are the main cause of in-paddock yield variability.

Satellite Imagery


high resolution satellite image, which indicates the biomass production of an area, identified small areas of very poor growth in a barley crop in Victoria. On the ground these areas were found to be between three and four metres diameter and were hotspots of the root disease Rhizoctonia. Prior to the analysis these areas had not been identified and the information was used to modify future rotations.

CTF Solutions has found high resolution images are valuable when identifying areas suffering from poor drainage. In 2004, a high resolution image of a 400ha paddock in

Central Queensland was converted to NDVI, which highlighted substantial variability (Figure 2a).

Ground truthing confirmed that much of the variation related to water logging. The image was combined with a high definition topography map and the two data sets were used to identify the best options to drain the paddock. Yield variability was substantially reduced and total paddock yield increased (Figure 2b). The benefits of $5000 invested in drainage work were returned in 2006, which experienced a very wet winter, when yield income increased by $53,000.

Tim acknowledges that proximal sensing allows a grower to gather data and use data from a paddock at a specific time. However, until systems cover a greater proportion of the paddock he believes there is great value to be obtained from the high resolution satellite imagery. As with all remotely or proximally sensed data, on-ground truthing is essential.


Tim Neale, Director, CTF Solutions. 0428 157 208 [email protected]

Figure 1. The level of detail that can be obtained from satellite images gathered at different resolutions a) 25m pixel (625m2) LANDSAT, b) 10m (100m2) SPOT, c) 1m pixel (1m2).

Figure 2. High resolution images converted to NDVI highlighted considerable paddock variation (a) that was substantially reduced following drainage (b).

Satellite Imagery

a)

a) b)

b) c)


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Growers, generally have a good understanding of where consistently poor

performing regions of a crop occur. However, multispectral satellite imagery and field sampling guided by global positioning systems (GPS) has been shown to be an effective technology for predicting the spatial variability of crop vigour, maturation and yield within individual peanut crops. Determining the yield deficit produced by a limiting growth factor, combined with the area of crop affected, allows accurate predictions on total economic losses to be made.

Up to 60% of infrared (IR) radiation in sunlight is reflected upward (reflected energy) or downwards (transmitted energy) by the growing leaves of non-stressed vegetation. Any limitation on plant health reduces this percentage to a degree that can be measured by a number of remote sensing technologies, including high resolution multi-spectral satellite and aerial infrared (IR) imagery.

The spatial variability of plant vigour across individual peanut crops has been identified with satellite imagery, which in turn has been accurately correlated to pod yield and maturity in both dryland and irrigated crops. This information has enabled growers to formulate better harvest regimes in order to maximise quality and yield, whilst minimising the risk of aflatoxin (a toxin produced by soil-borne fungi under drought conditions at the end of the season).

Acquisition and analysis of satellite and aerial imagery

Aerial images of a disease-affected irrigated pivot where taken on 30 April 2003, using a Sony digital camcorder mounted in the door of a Cessna 185. Digital images were geo-referenced using ground control points collected with a handheld Global Positioning System (GPS) at strategic locations around the site. This camera system only outputs one digital reflectance data value for

each pixel, so is unable to be used for band ratios or specific vegetation indices. However, images can be classified into regions of differing IR reflectance.

For satellite imagery, the American owned QuickBird satellite was selected due to its high pixel resolution of 0.6m and its multi-spectral format (blue 450- 520nm, green 520- 600nm, red 630- 690nm and near infra-red (NIR) 760- 900nm).

Imagery of the centre pivot monitored for maturity timing was acquired on 17 March 2006 near the S.E. Queensland township of Wooroolin, while the pivot displaying inefficient irrigation was acquired on 20 February 2007 near the township of Texas, Queensland. Imagery was used to develop a Normalised Differential Vegetation Index (NDVI) to remove noise errors such as those associated with shading and crop geometry.

Satellite Imagery

Remote sensing for crop variability in peanutsAndrew Robson1 and Stuart Phinn2

Satellite imagery is proving a useful tool for predicting crop vigour, maturation and yield in peanuts.

On ground differences in peanut biomass between highest yielding zones – above – and the lowest yielding areas – right- matched the zones

identified by the vegetation index generated from the high resolution satellite images. The pink dots represent ground sampling points.


Both the aerial IR image and the NDVI transformed satellite images were segregated into five classes of IR reflectance. The classes were then colour coded with Red indicating a high reflectance value and therefore larger crop vigour, followed by Yellow, Green, Blue and then Black indicating low vigour or bare soil.

Field validation of aerial IR and QuickBird satellite images

From the classified images, pod sampling locations were selected to represent each colour class and were located on the ground with a non-differential GPS. To compensate for the GPS accuracy of 5m, each sample location was selected within a 20m2 area of homogenous colour zone. Three replicate samples of intact peanut bushes and pods were collected from two adjacent 1m lengths of peanut row.

For the harvest timing trial the grower left test strip areas unharvested around the sample locations, so that hand samples could be collected after the commercial harvest. The samples were dried and threshed to

determine pod yields. A 200g pod sub-sample was shelled and the percentage of pods having a black (i.e. mature) pericarp was used as an index of crop maturity. The maturity and yield values from each sample location were then correlated against the corresponding IR and NDVI values.

Impacts of inefficient irrigation and soil type on peanut yield and economic gains

The true colour high resolution satellite image of the Texas pivot (cv. Holt) provided useful paddock information, such as the location of wheel tracks and contours etc. However, the addition of the infrared (IR) spectral band and subsequent vegetation index (NDVI) clearly identified the spatial variation in crop vigour. A clear separation in plant vigour was observed within the area of the second irrigator wheel track where smaller plants were located, compared to surrounding irrigator runs that produced predominantly high vigour plants This was later identified to be the result of the incorrect installation of irrigator nozzles.

Replicated ground sampling of this peanut crop, within the classified zones, produced a highly significant correlation between yield and NDVI with higher IR reflectance or crop vigour (Red) zones producing a higher yield, in this case over 12t/ha compared to 4t/ha in the Blue zones (Table 1).

Data in Table 1 shows that only 39 per cent of the crop grew at an optimum level (Red zones). At an estimated yield of 12.68t/ha this zone would have produced 107.8 tonnes. This production nearly equalled the sum of the other three zones that encompassed 61 per cent of the pivot and produced 139.8 tonnes.

Had the entire crop achieved optimum growth (Red) then the predicted total pivot yield would have been 278 tonnes or 50 tonnes more than the total predicted yield based on the measured variation within each zone. In monetary terms, this represents a potential loss of $50,000 (at $1000 per tonne).

While impacts resulting from the irrigator are easily corrected, other

Satellite Imagery


poor performing regions were likely to be the result of a poorer soil type. By locating, sampling and identifying the soil deficiency with this technology, an agronomist could determine whether remedial action, such as earth works, liming etc., would be a cost effective management option based on the estimate of lost production within this area.

Impacts of harvest timing on peanut yield and lost economic production

The classified NDVI image of the Wooroolin pivot identified both a large region of low crop vigour, a result of a gravely soil type, and a similar area of high vigour,which was attributed to a heavier soil. Replicated ground samples were collected within these regions on three separate occasions, the first corresponded with the actual crop harvest (20 April 06), the second 13 days later (3 May 06) and the last 22 days later (12 May 06).

A strong relationship between NDVI value and yield was again identified, with larger more vigorous plants producing a greater yield (3.75t/ha) than the low vigour areas (2.28t/ha). The yield measured from the high vigour zone increased from 3.75t/ha to 5.3t/ha and the low vigour from 2.28t/ha to 3.11t/ha over the 22 days following actual harvest time. This was attributed to pod maturity, with high crop vigour zones in particular demonstrating a 46 per cent increase in mature pods over that time period.

determining the yield deficit produced by a limiting growth factor, combined with the area of

crop affected, allows accurate predictions on total economic losses to be made

The estimated yield gain of 20.05t between actual harvest timing to 22 days later, equates to $20,000 (at $1000/t) and could be further increased by an additional $23,000 if the pivot achieved uniform optimum growth (Red zones) rather than cause the regions of reduced growth potential.

Impacts of foliar disease on peanut yield and lost economic production

The temporal imaging of a Wooroolin irrigated pivot identified that the spread of Net Blotch (Didymosphaeria arachidicola) spores over a 51 day period resulted in nearly the entire crop being exposed to some level of infection.

The IR imagery was able to distinguish the impacts of the foliar fungal disease, by reduced IR reflectance, in some cases when no visible effects could be seen by the grower.

Hand samples taken within varying crop vigour regions, caused by disease, produced a strong correlation between pod yield and IR reflectance or in this case brightness

values, with the worst effected plants yielding less than 4t/ha in comparison to up to 8t/ha produced in the optimum Red zones..

In monetary terms, the lost production resulting from this foliar disease could be estimated at nearly $12,000. By using this technology to determine the potential yield loss, a grower could estimate whether the application of additional fungicide treatments at $50/ ha or $750 for the pivot, would be a cost effective option.

The results presented indicate a number of possible applications that remote sensing and subsequent image analysis offers to cropping industries, using peanut crops as an example. These include the accurate prediction of maturity and yield variability across individual crops, a cost analysis of possible lost production from under performing areas; the in-season identification of irrigation deficiencies and other limiting constraints such as foliar diseases.

This research has been part of ongoing Grains Research and Development Corporation (GRDC) and Australian Centre for International Agricultural Research (ACIAR) projects.

1 Queensland Department of Primary Industries and Fisheries.

2 University of Queensland.


Dr Andrew Robson, 07 4160 0735 [email protected]

Satellite Imagery

Table 1. Average pod yield (t/ha) measured from the replicated hand samples, the area encompassed by each colour zone and the calculated yield (t/ha) produced by each colour zone.

Red Yellow Green Blue Black Total

Area (%) of pivot of each zone 38.3 31.5 20.5 7.8 0.3 100.0

Area (ha) encompased by each zone 8.5 6.9 4.5 1.7 1.4 21.9

Yld (t/ha) (calculated from hand samples) 12.68 10.31 9.18 4.31 n/a

Total yield (t) per zone 107.79 71.17 41.33 7.34 n/a 227.64(area of each zone* hand sample yield)

Note: Black zones were not sampled as these mainly represented irrigator wheel tracks.


Precision cane farming and harvesting in the Herbert River district took an

exciting leap forward this year, with harvesters using state-of-the-art yield monitoring and tracking technology as part of an ambitious program designed to ensure district profitability and sustainability.

In addition to the harvesting initiative, an increasing number of tractors and other farm machinery will have access to a co-ordinated district-wide GPS base station network, allowing growers to cut costs, improve efficiency and potentially increase cane/sugar yields and financial returns.

Herbert River district’s commitment to securing its sugar future was

evident at the recent Sugar Research and Development Corporation’s (SRDC) annual innovation awards where the Herbert Information Resource Centre won top honours for its GIS knowledge sharing enterprise.

Industry stakeholders are collaborating at various levels to exploit opportunities for developing better risk management and industry sustainability.

The systems approach has positive implications for other regions through streamlined harvest management and better communications and decision-making.

Ron Kerkwyk, Manager, Herbert Cane Productivity Services Ltd

(HCPSL), sees considerable potential to increase total sugar production, Commercial Cane Sugar (CCS – approximately equal to content of sucrose), sugar yields per hectare and grower profitability through better management of harvest scheduling and decision-making based on regional variations in CCS, soils and climatic conditions.

Selecting optimum times for harvest start/finish in different areas and even particular blocks on individual farms can substantially influence sugar produced and an enterprise’s profitability.

HCPSL’s initiative has greatly reduced the cost to individuals of adopting new technology. Farmers and CSR Sugar are each paying 2.5c/t to

PA in sugar

Cuban technology backs sugar harvest breakthroughBill Kerr The sugar industry is taking a slightly different approach to the adoption of PA, which may offer some new ideas to other industry sectors.

Where’s that harvester? In the Herbert River district a harvester tracking system is being used

to relate yield to paddock area and to improve management of cane transport and processing.


establish the $380,000 GPS network but the Federal Government is paying the full $620,000 cost for on-board computers and yield monitors. The Government will share with cane harvesting contractors the $144,000 cost for automatic base-cutters and auto-steering of harvesters.

HCPSL has negotiated an agreement with Cuban R&D company Techagro Pacific to implement much of the new technology. The initial focus is on yield monitoring and data collection and distribution, but

automatic base-cutter systems and harvester performance reporting is also in the wings.

Last year five Techagro units on harvesters mapped about 400ha and 30 AgGuide units mapped approximately 10,000ha. Data gathered was used to produce yield maps that can be used for precision agriculture and to determine why parts of blocks planted with the same cane variety may yield differently. Precision agriculture can help growers contain and reduce input costs through variable

rate fertiliser application, adding lime and gypsum, and other best management practices.

Lawrence Di Bella, who was with the Bureau of Sugar Expereiment Stations (BSES) for 17 years before joining HCPSL, says paddock yields can vary from 20 to140t/ha. He stresses that yield monitoring data should not be used in isolation from other information such as soil and plant tissue analysis data, soil and topography maps, aerial photos and remote sensing data.

This year 78 Herbert harvesters will be fitted with Techagro on-board computers and Next G™ modems and 20 equipped with the Techagro yield monitors. Another 40 will be fitted with AgGuide yield monitors.

Eight machines will be fitted with the Techagro automatic base-cutter systems. The BSES harvester at Ingham will also be fitted with the two yield monitors to compare the performance of each system.

Field position of individual harvesters will be recorded every 10 seconds and HCPSL staff will be able to communicate with machine operators. A dedicated Techagro computer server at HCPSL will also have access to accurate weighbridge information from CSR and GIS data through the Herbert Information Resource Centre.

HCPSL’s Mike Sefton, who will oversee the program, says the new technology will allow harvesting groups to track their harvesting “to the nearest drill” as well as giving mill management better control over transport and processing of cane.

He says the challenge for the industry now is to convert available data into usable information/applications that growers and millers can use to make practical, profitable business decisions.

He expects even bigger payoffs as the harvester system evolves e.g. if automatic base-cutter height sensors could pick up an extra 2 to 3t/ha of high value cane they would generate in excess of $1m for the district.

How is it that technologists from a small Caribbean country are

PA in sugar

Lawrence Di Bella (L), HCPSL Agricultural Systems Information Officer, discusses the harvester monitoring device that will be used to track sugarcane harvesters in the Herbert River District with (L to R) Santiago Marrero, General Manager of

Techagro Pacific and his colleagues Angel Luis and Enrique Caballero.


working at the cutting edge of Australian harvesting innovation? Although Cuba was once a global force in sugar production, its output plummeted from 7Mt to 1.2Mt after the former USSR scrapped its sugar-for-oil preferential trade arrangements. Faced with a domestic industry in decline, Cuban researchers began developing integrated control systems for mills and plantations in booming Brazil and other South American countries.

CSIRO scientist Robert Bramley learned about the breakthrough work Cubans were doing in Brazil when he attended an international conference.

This led to a visit here by specialists from Techagro, commercial arm of a consortium of Cuban and Brazilian universities and research bodies.

They visited the Herbert, Burdekin and Mackay to assess opportunities and they trialled equipment on several harvesters including the Ingham machine owned by Caneharvesters Chairman Robert Lyon. This aroused interest among growers who were keen to reduce their harvesting costs and improve productivity, but were frustrated by lack of suitable equipment. Interest was particularly strong at Ingham, where Techagro has now based its Pacific regional operation.

In 2006 SRDC helped fund a visit to Cuba and Brazil, to see Techagro

systems in action, by a group including Lawrence Di Bella and Ron Kerkwyk, Burdekin grower Ian Haigh, John Powell of Caneharvesters Mackay and Gary Sandell, a Mackay-based harvesting consultant.

In Brazil, large numbers of harvesters have been fitted with on-board computers, electronic logbooks, base-cutter height sensor kits, yield monitors and automatic constant flow systems.

Seven Cuban technologists (some with their families) have made Ingham their temporary home while they work closely with HCPSL to adapt their equipment to suit the local system of small farms and faster harvesting rates.

Ingham was chosen because of the district’s innovative, progressive culture and its standout enthusiasm for innovation and achieving best practice.

The community is delighted to have overseas experts living locally, close

to where things are happening on the ground. This is a wonderful bonus, said Ron Kerkwyk. “The partnership is a good marriage of Cuban harvest management technology with our industry experience and skills”.

“The stakeholders share a vision for a more efficient and profitable industry and, importantly, Techagro does not have to work directly with every stakeholder because HCPSL coordinates the entire operation.”

This article was supplied by CANEGROWERS. It was originally published in the 26 May 2008 edition of the Australian Canegrower magazine.

Bill Kerr, is the CANEGROWERS consultant journalist.

For more information www.canegrowers.com.au

PA in sugar

HCPSL Agricultural Systems Information Officer Lawrence Di Bella (L) and Techagro Pacific engineer Angel Luis inspect one of the monitors that will be fitted in the cab of the cane harvesters to track movement and record yield.

HCPSL Harvest Management Officer Mike Seaton (seated), Techagro Pacific engineer Enrique Caballero and HCPSL Manager Ron Kerkwyk (R), prepare to fire-up the Techagro server that will be used by HCPSL to track cane harvesters in the Herbert River district.

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