Being profitable precisely - a case study of precision viticulture from Margaret River
Rob Bramley Bruce Pearse CSIRO Land and Water and Cooperative Research Centre for Viticulture Vasse Felix PMB No.2, PO Box 32, Glen Osmond, South Australia 5064 Cowaramup, Western Australia 6284 Corresponding author e-mail: [email protected] Phil Chamberlain Vasse Felix
Introduction Precision Viticulture (PV) is an all- Supplementary information encompassing term given to the use of a eg Remote sensing, Digital range of information technologies that elevation model, Soil and tissue enable grapegrowers and winemakers to testing, Soil mapping (Grid ? Observation γ better see and understand variability in their EM38 ? -radiometrics ?), Crop production systems, and to use this assessment Interpretation understanding to better match the inputs to production to desired or expected outputs. At least, that is the claim, but is it true? This GIS paper describes a small case study How precision undertaken in part of a block of Cabernet Sauvignon owned by Vasse Felix, in viticulture works Margaret River, Western Australia; the study demonstrates that adoption of PV can realise Yield map immediate economic benefits. The adoption and implementation of a Evaluation Precision Viticulture approach to vineyard Implementation management is a continual cyclical process (Figure 1) that begins with observation of vineyard performance and associated Targeted vineyard attributes, followed by management plan interpretation and evaluation of the collected data, leading to implementation of targeted Fig. 1. The process of precision viticulture. The process begins with yield (and/or quality) mapping and the management. Here, ‘targeted management’ acquisition of complementary information (e.g., a soil map) followed by interpretation and evaluation of the can mean the timing and rate of application information leading to implementation of targeted management. This is followed by further observation (was of water, fertiliser or spray, or the use of the targeted strategy useful?) etc… The process of data acquisition and use is, therefore, continuous, and improvements to management, incremental. Over time, data collected during the observation stage take on a machinery and labour for operations such as predictive value. harvesting, pruning or just about any aspect of vineyard management. The key technologies involved in PV, Conventional wisdom from broadacre agriculture, for which aside from the ubiquitous desk computer, are the global positioning precision agriculture has been available since the early 1990s, system (GPS), grape yield monitors that might be regarded as suggests that farmers would be wise to collect around five years of primary observation tools and have now been commercially data before implementing targeted management. In the example available in Australia for five vintages, and geographical used to illustrate Figure 1, a 7.3ha vineyard in Coonawarra information system software (GIS). Also invaluable is access to a (Bramley and Proffitt, 1999; Bramley, 2001), the pattern of yield range of sources of ‘supplementary information’ that may be useful variation has been shown to be temporally stable over a three-year in helping explain the observed variation in vineyard productivity. period, with the wines produced from fruit harvested from the These might be regarded as secondary observation tools, and different ‘zones’ producing wines of differing characteristics include soil-sensing technologies such as the EM38 sensor, more (Bramley, 2002). Given the perenniality of grapevines, one might traditional methods of soil inspection, plant tissue analysis and expect spatial variation in vineyard productivity to be reasonably remote sensing (Lamb and Bramley, 2001; 2002); as we temporally stable. Indeed, in the vineyard shown in Figure 1, yield demonstrate in this paper, remote sensing may also be regarded as variation in any given year has been shown to be driven primarily a source of primary observations. by variation in the amount of plant-available water which, in this
84 The Australian & New Zealand Grapegrower & Winemaker Annual Technical Issue 2003 Table 1. Analysis of fruit sampled two weeks prior to vintage from areas identified as being of ‘low’ or ‘high’ plant cell density from imagery collected at veraison. Plant cell density Baumé pH TA Quality
10.4 3.20 8.40 Medium High 10.8 3.24 8.35 Medium 10.9 3.42 8.25 Low
11.9 3.33 5.77 Good Low 12.3 3.37 6.53 Very Good 11.7 3.29 7.87 Good veraison +/- two weeks is the optimal time for image acquisition (Lamb and Bramley, 2002). Accordingly, Vasse Felix engaged the services of a commercial provider of airborne digital multispectral video (DMSV) imagery who acquired imagery of the site on 6 February, 2002. The DMSV system used collected images in four separate wavebands (e.g., Hall, 2002) corresponding to the infra- red, red, green and blue wavelengths. For this study, the so-called ‘plant cell density’ index (i.e., the ratio of infra-red to red reflectance) was used to generate the image shown in Figure 2. Variation in this index is thought to give an indication of variation in vine vigour. Two weeks prior to the expected date of harvest, the imagery collected at veraison was used as the basis for targeted fruit sampling in 27 rows (3.3ha) of a block of Cabernet Sauvignon. Areas of apparently low and high ‘plant cell density’ were sampled and the fruit analysed for maturity indices; an assessment of fruit quality was also made (Table 1). In light of the differences shown in Table 1, a targeted harvesting strategy was employed at harvest (19 March, 2002). The crop was harvested by a ‘tow-behind’ Gregoire G65HD mechanical harvester fitted with a Farmscan grape yield monitor and differential GPS. On the basis of the imagery and subsequent Fig. 2. Plant cell density (infra-red/red) image of the Vasse Felix study area (delineated by the white rectangle) taken on 6 February, 2002. analysis (Table 1), the study area was split into a northern and instance, is predominantly controlled by variation in soil depth (Bramley et al., 2000; Bramley and Lanyon, 2002); of course, soil depth is unlikely to vary over time! BOOTH The vineyard shown in Figure 1 is the subject of a large study of T R A N S P O R T vineyard variability being conducted by the Cooperative Research Centre for Viticulture (CRCV: www.crcv.com.au/research/ programs/one/project1.1.1.asp). Whilst this research seeks to assist grapegrowers and winemakers wishing to adopt PV by identifying the key drivers of vineyard variation, the fact is that PV is available now, with many early adopters looking to target management sooner rather than later, and avoid at least some of the waiting associated with the early phase of data collection that Figure 1 and the preceding discussion implies. Certainly, this was the intention of Vasse Felix, early adopters of PV from Margaret River. On the other hand, like others interested in adopting this technology, Vasse Felix needed to be sure that targeting its management was going to deliver an economic benefit. Precision viticulture at Vasse Felix – Vintage 2002 Carriers of Wine During 2001, Vasse Felix saw that PV offered an opportunity for better managing a recently-planted property it had acquired for over 60 Years towards the northern end of the Margaret River region. Block boundaries were georeferenced using differentially corrected GPS HEAD OFFICE: (accurate in the x and y planes to about 50cm), and a high spatial CNR BRIAN ROAD & LINDSAY ROAD, resolution soil and elevation survey was conducted by local LONSDALE, SA 5160 geotechnical engineers using real-time kinematic GPS (accurate to PO BOX 66, LONSDALE, SA 5160 about 2cm in the x, y and z planes) and a range of soil sensors of PHONE 08 8381 3077 FAX 08 8381 3888 which -radiometrics proved to be the most useful (the use of steel posts in the vineyard mitigated against the utility of EM38 soil BAROSSA - Ph 08 8563 2802 Fax 08 8563 2536 sensing). The data so collected were used as the basis for a GIS in BRISBANE - Ph 07 3271 5321 Fax 07 3271 4744 which all spatial data are stored, analysed and displayed. SYDNEY - Ph 02 9892 4422 Fax 02 9892 4229 MELBOURNE - Ph 03 9689 3177 Fax 03 9689 3512 The use of remotely-sensed imagery in viticulture has been the subject of much recent research (e.g., Hall et al., 2002; Lamb et al., Servicing All Wine Producing Areas 2001; Lamb and Bramley, 2002) with early indications being that ACN 007 678 622
Annual Technical Issue 2003 The Australian & New Zealand Grapegrower & Winemaker 85 results of analysis of bulk samples delivered to the winery. As can be seen, the differences in fruit character noted two weeks prior to harvest for samples taken from the areas identified in the imagery collected at veraison (Figure 2, Table 1) carried through to harvest (Table 2) and were large enough to warrant allocation of the different batches to different end products. Thus, fruit from the higher yielding northern area (higher plant cell density) was deemed suitable for the Vasse Felix ‘Classic Dry Red’ (retail price of approximately $19/bottle), whilst that from the lower yielding area was assigned to the Cabernet Sauvignon varietal (retail price of approximately $30/bottle); had the block been harvested as a single unit, it would have all been assigned to the lower value wine.
Precision viticulture is profitable A total of 12.68t fruit were harvested from the higher quality southern portion of the block. Assuming a simple conversion of 1t fruit producing 750L wine, we estimate that the gross retail value of production from this area was approximately $285,300. The lower quality northern portion produced a total of 25.5t with a gross retail value of $363,375. Thus, the total gross retail value of production using the targeted harvesting strategy based on remotely-sensed imagery was approximately $648,675. Had the block been harvested into single bins and the fruit used to make the cheaper ‘Classic Dry Red’, the 38.18t would have produced wine with a gross retail value of $544,065 – that is, a PV approach to harvesting of this 3.3ha block has yielded an increase of $101,610 in the estimated gross retail value of production, equivalent to $2661/t fruit harvested or $30,791/ha. It is recognised that wine retail pricing is a less satisfactory basis for assessing the merits of adopting PV than would be provided by the true costs and value of production of grapes and wine. However, for reasons of commercial confidentiality, this is the only indicator of the benefit:cost that we can provide. Further, Fig. 3. Yield of Cabernet Sauvignon from an area of 3.3ha (27 rows) within a we have assumed that the costs of winemaking for the two larger block in Margaret River harvested on 19 March 2002. The dashed horizontal line delineates the areas of low and high plant cell density (Figure 2) products are comparable. With respect to viticultural operations, that were harvested separately. Mean yield in northern section was 16t/ha whilst since the block was managed uniformly, the costs of grape in the southern section, the mean yield was 8t/ha; Mean yield for the whole production for the two products were the same, although the block was 13t/ha. See text for further explanation. targeted harvesting incurred the additional cost associated with southern section (Figure 3). Two chaser bins were used such that running the second chaser bin that enabled segregation of the the fruit from the northern, higher vigour, area went into one bin, fruit. Thus, in spite of its obvious shortcomings, we suggest that with the fruit from the southern section going into the other. this analysis provides an indication of the level of increase in Operationally, this required the two sections to be delineated by revenue that might accrue to a grapegrowing and winemaking flagging tape, with the appropriate chaser bin then moving business through the adoption of PV. alongside the harvester for each section; the other bin could move The cost of a grape yield monitor with supporting software is out of the way by either moving ahead, or dropping behind the bin approximately $9050 excluding GST. Grape yield monitoring collecting the fruit. However, a system is currently being tested in requires the use of a differentially corrected GPS of which there which the ‘boundary’ between the sections is delineated on a are a range of models available; purchasers may also choose harvest plan and identified automatically by the GPS. whether to access the differential correction from a commercial Following harvest, the data collected by the yield monitor were provider to whom an annual subscription is payable, or the signal mapped using the protocol of Bramley and Williams (2001). As that is available free of charge from the chain of marine beacons can be seen from Figure 3, the yield map bears a strong operated by the Australian Maritime Safety Authority resemblance to the remotely-sensed image collected close to (www.amsa.gov.au/ns/dgps/dgps.htm) which, depending on the veraison (Figure 2). The mean yield for the whole study area was location and intended application of the user, may or may not be 13t/ha, but the higher and lower vigour areas had substantially suitable. A GPS unit similar to that used by Vasse Felix costs different yields (mean yields of 16 and 8t/ha, respectively). Of approximately $9000 and the annual subscription to differential greater significance, however, was the quality of the fruit correction is $2500. If these costs were spread over five years, the harvested from the two areas, and the implications of this quality cost of yield monitoring amounts to $6110/year. If we assume that difference with respect to final product. Table 2 presents the average grape yields in Australia are of the order of 10t/ha (note that on average, the block at Vasse Felix Table 2. Analysis of fruit delivered to the winery from areas harvested separately on the basis of ‘plant cell was higher yielding than this), and that density’ at veraison. during a vintage, a harvester covers about Plant cell density Mean yield Baumé pH TA Quality Winemaker comments 0.4ha/hour for a vintage total of 450 hours (t/ha) (a total of 180ha or 1800t), the cost of yield High 16 12.35 3.56 6.23 Medium Light in colour, some simple berry fruits, greener leaf edges, tobacco, herbal, monitoring amounts to about $3.40/t. This medium intensity with stalky finish. Acid equates to about $13.60/hour of harvester balance not too bad. Greener palate than operation. Of course, for harvesters low vigour/yield. operating at faster speeds (i.e., covering Low 8 13.0 3.55 5.40 Very good Darker red colour, rhubarb, smokey, dark cherry nose, shows more intensity of larger areas per hour), this cost will go flavour and riper notes than higher down. vigour/yield.
86 The Australian & New Zealand Grapegrower & Winemaker Annual Technical Issue 2003 Remote sensing services are now available in Australia for Overall, the simple study detailed here suggests that PV offers about $25/ha, equivalent to $2.50/t fruit harvested. The costs of grapegrowers and winemakers the ability to acquire valuable the sort of high resolution soil survey conducted at Vasse Felix, information about their production system, the cost of which is which is not required on a repetitive basis, are of the order of far outweighed by its value. only $1/t when spread over five years. Thus, the total costs of the data acquisition elements of PV amount to approximately Acknowledegments $6.90/t. If a consultant were employed to construct the GIS and We are most grateful to Susie Williams (CSIRO Land and carry out the sort of data analysis required in this study, which is Water / CRCV) for her assistance with the map production and probably the most appropriate way for early adopters to gain a spatial analysis in this work. benefit from PV rather than trying to learn the necessary spatial References statistical, image analysis and associated techniques themselves, Bramley, R.G.V. (2001) Progress in the development of precision viticulture - the costs of PV would increase to around $11/t. Clearly, this is a Variation in yield, quality and soil properties in contrasting Australian vineyards. In: ‘Precision tools for improving land management’. (Eds, L.D. Currie and P. trivial expense in relation to the increase in the gross retail value Loganathan). Occasional report No. 14. Fertilizer and Lime Research Centre, of production achieved in the Vasse Felix study simply by Massey University, Palmerston North. pp.25-43. Also available at: targeting harvesting based on aerial imagery. It should also be www.crcv.com.au/research/programs/one/bramley1.pdf noted that the targeted harvesting employed in this study was a Bramley, R.G.V. (2002) Towards optimal resource management for grape and simple straight-line delineation of the block into two zones wine production. In: Blair, R.J., Williams, P.J. and Hoj, P.B. (Eds) ‘Proceedings of the 11th Australian Wine Industry Technical Conference’. Winetitles, Adelaide, (Figure 3). A more sophisticated approach could have involved a pp.274-275. more complicated zonation, not necessarily based on straight Bramley, R.G.V. and Lanyon, D.M. (2002) Evidence in support of the view that lines, and with greater differentiation in terms of target product; vineyards are leaky Ð Indirect evidence and food for thought from precision note that the top of the range ‘Heytesbury’ wine, which the very viticulture research. In: Bramley, R.G.V. and Lanyon, D.M. (Eds) ‘Vineyard ‘leakiness’’ Proceedings of a workshop held at the Waite Campus, Adelaide, 24- best fruit in this block may have been suitable for, retails for 25 January, 2002, to scope the potential threat to the sustainability of Australian about $65/bottle. viticulture through excessive drainage below the root zone. Final Report on The success of this example from Vasse Felix might lead GWRDC Project No. GWR01/04. CSIRO Land and Water/Grape and Wine Research and Development Corporation, Adelaide. Also available at: some readers to wonder why yield monitoring was used; surely www.clw.csiro.au/publications/consultancy/2002/Vineyard_leakiness_high_res. the same result could have been obtained more cheaply through pdf use of a GPS and the remotely-sensed imagery alone? On the Bramley, R.G.V. and Proffitt, A.P.B. (1999) Managing variability in viticultural face of it, this is true. However, as Figure 1 infers, the adoption production. The Australian Grapegrower & Winemaker 427:11-16. and use of PV involves a continuous cyclical process of data Bramley, R.G.V., Proffitt, A.P.B., Corner, R.J. and Evans, T.D. (2000) Variation in acquisition and use, each data layer building on those already grape yield and soil depth in two contrasting Australian vineyards. In: ‘Soil 2000: New Horizons for a New Century. Australian and New Zealand Second Joint Soils collected. Such an approach allows the merits of targeted Conference’. Volume 2: Oral papers (Eds. Adams, J.A. and Metherell, A.K.) 3-8 management to be evaluated and, if necessary, for the December 2000, Lincoln University. New Zealand Society of Soil Science. 29-30. ‘management zones’ to be modified and the differences between Bramley, R.G.V and Williams, S.K. (2001) A protocol for the construction of yield them understood – “you can’t manage what you can’t measure” maps from data collected using commercially available grape yield monitors. is an old, but very true adage! Importantly, and assuming www.crcv.com.au/CRCVProtocolBkfinal.pdf Cooperative Research Centre for Viticulture, Adelaide. temporal stability in the patterns of vineyard variation, data collected annually will acquire a predictive value. Thus, Hall, A., Lamb, D.W., Holzapfel, B. and Louis, J. (2002) Optical remote sensing applications in viticulture Ð a review. Australian Journal of Grape and Wine managers will be able to tune their management in the increased Research, 8:36-47. expectation that any given decision will indeed deliver the Lamb, D.W. and Bramley, R.G.V. (2001) Managing and monitoring spatial desired outcome, leading to increased control over the whole variability in vineyard variability. Natural Resource Management, 4:25-30 production and supply chain. Importantly to Vasse Felix, the PV Lamb, D.W. and Bramley, R.G.V. (2002) Precision viticulture Ð tools, techniques approach also ensures continuity and retention of information and benefits. In: Blair, R.J., Williams, P.J. and Hoj, P.B. (Eds) ‘Proceedings of the and knowledge about the production system; the departure of key 11th Australian Wine Industry Technical Conference’. Winetitles, Adelaide, pp.91- staff certainly leads to a loss of experience, but given the data 97. storage implicit in the use of PV and GIS, it need not lead to a Lamb, D., Hall, A. and Louis, J. (2001) Airborne remote sensing of vines for canopy variability and productivity. The Australian Grapegrower & Winemaker, loss of expertise. 449a:89-92.
From May 2003, Master Winemakers will offer state-of-the-art bottling services to our valued contract clients and to external wine producers. Winemaker in charge of the bottling line is Peter Florance. For enquiries contact Senior Winemaker, Scott McCarthy on 03 9876 5885 or 0425 766 382; fax: 03 9876 4752; e-mail: scottm@master- After vintage comes bottling. winemakers.com.au
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