GiESCO 2019 banner
IVES 9 IVES Conference Series 9 GiESCO 9 Digitising the vineyard: developing new technologies for viticulture in Australia 

Digitising the vineyard: developing new technologies for viticulture in Australia 

Abstract

Context and purpose of the study – New and developing technologies, that provide sensors and the software systems for using and interpreting them, are becoming pervasive through our lives and society. From smart phones to cars to farm machinery, all contain a range of sensors that are monitored automatically with intelligent software, providing us with the information we need, when we need it. This technological revolution has the potential to monitor all aspects of vineyard activity, assisting growers to make the management choices they need to achieve the outcomes they want. For example, a future vineyard may possess automated imaging that generates a three dimensional model of the vine canopy, highlighting differences from the desired structure and how to use canopy management to improve fruit composition, or generates maps with yield estimates and measurements of berry composition throughout the growing season. That same imaging may also provide whole of vineyard data on vine nutrition or early warning of disease, allowing proactive management on a rapid timescale. We are working with a range of technologies to develop such capabilities for Australian viticulture.
Material and methods – A variety of technologies are being deployed at the whole block scale to address a number of management questions. Early indicators of yield variation are being assessed shortly after budburst, using video imaging with consumer video cameras and machine learning, to determine inflorescence numbers. Canopy growth and structure are being monitored using (i) photogrammetry with drones imagery, (ii) video imaging from vehicles and (iii) a spinning LiDAR system using Simultaneous Localisation and Mapping (SLAM) to register the data. The latter is also being used to develop novel indices of canopy structure. Hyperspectral imaging is being used to segment vine images into their constituent parts and analyse them for fruit and canopy composition and presence of disease. Finally, yield estimation from veraison onwards is being developed using (i) video imaging in daylight, (ii) digital imaging with depth perception and (iii) foliage penetrating (FOPEN) technology. These technologies are being trialed at commercial vineyards in multiple winegrape growing regions of South Australia, concentrating on vines grown with the locally common ‘Australian sprawl’ trellis type, where the fruit are typically highly occluded by leaves, compared to vertical shoot position trellis types.
Results – The technologies described are at various stages of development, from the lab to field application at vineyard scale, but all have produced results with potential commercial application. Initial imaging work with inflorescence counts produced 94% accuracy; a preliminary pipeline to analyse drone imagery with depth data from photogrammetry for estimating vine cover irrespective of cover crop has been developed; a preliminary pipeline to analyse video imagery from the ground and map canopy gap fraction and leaf area index has been developed; the ability to accurately register 3D LiDAR data using SLAM and only basic GPS data has been demonstrated and use the results to develop models of seasonal light interception and indices of canopy light penetration; further, the ability of the FOPEN to determine the presence of fruit within a ‘sprawl’ canopy has been demonstrated.We are continuing to develop these technologies and apply them at the whole block scale in order to produce accurate yield estimates that do not rely on point measurements and spatial maps to allow fine-grained vineyard management decisions.

DOI:

Publication date: September 28, 2023

Issue: GiESCO 2019

Type: Poster

Authors

Everard J. EDWARDS1*, Mark R. THOMAS1, Stephen GENSEMER2, Peyman MOGHADAM3, Thomas LOWE3, Dadong WANG4, Ryan LAGERSTROM4, Chad HARGRAVE5, Jonathon RALSTON5

CSIRO Agriculture & Food, Locked Bag 2, Glen Osmond, SA 5064, Australia
CSIRO Manufacturing, Locked Bag 2, Glen Osmond, SA 5064, Australia
CSIRO Data61, PO BOX 883, Kenmore, QLD 4069, Australia
CSIRO Data61, PO BOX 76, Epping, NSW 1710, Australia
CSIRO Energy, PO BOX 883, Kenmore, QLD 4069, Australia

Contact the author

Keywords

digital technologies, FOPEN, LiDAR, photogrammetry, proximal sensing, RGB imaging, viticulture

Tags

GiESCO | GiESCO 2019 | IVES Conference Series

Citation

Related articles…

Spatial variability of temperature is linked to grape composition variability in the Saint-Emilion winegrowing area

Elevated temperature during the grape maturation period is a major threat for grape quality and thus wine quality. Therefore, characterizing the grape composition response to temperature at a larger scale would represent a crucial step towards adaptation to climate change. In response to changes in temperature, various physiological mechanisms regulate grape composition. Primary and secondary metabolisms are both involved in this response, with well-known effects, for example on anthocyanins, and lesser known effects, for example on aromas or aroma precursors. At the field scale or at the regional scale, however, numerous environmental or plant-specific factors intervene to make the effects of temperature difficult to distinguish from overall variability. In this study, it was attempted to overcome this difficulty by selecting well-characterized situations with differing temperatures. A long-term study of air temperature variability across several Merlot vineyards in the Saint-Emilion and Pomerol wine producing area found significant temperature differences and gradients at various time scales linked to environmental factors. From this study area, a few sites were selected with similar age, soil and training system conditions, and with repeated and contrasted temperature differences during the maturation period. The average temperature difference during the maturation period was about 2°C between cooler and warmer sites, a difference similar to that expected under future climate change scenarios. In close vicinity to the temperature sensors at each site, grape berries were sampled at different times until full maturity during 2019 and 2020. Also, berries from bunches on either side of the row were analyzed separately, allowing an investigation of bunch exposure effect associated with the coupling of berry temperature and solar radiation. Four replicates of pooled berries for each time – site – bunch exposure combination were obtained and analyzed for biochemical composition. Analyses of variance of the biochemical composition data collected at different sampling times reveal significant effects associated with temperature, site, and bunch azimuth. For instance, anthocyanins in grape skins are clearly influenced by temperature and solar radiation exposure, with up to 30% reduction in warmer conditions.

Optimizing stomatal traits for future climates

Stomatal traits determine grapevine water use, carbon supply, and water stress, which directly impact yield and berry chemistry. Breeding for stomatal traits has the strong potential to improve grapevine performance under future, drier conditions, but the trait values that breeders should target are unknown. We used a functional-structural plant model developed for grapevine (HydroShoot) to determine how stomatal traits impact canopy gas exchange, water potential, and temperature under historical and future conditions in high-quality and hot-climate California wine regions (Napa and the Central Valley). Historical climate (1990-2010) was collected from weather stations and future climate (2079-99) was projected from 4 representative climate models for California, assuming medium- and high-emissions (RCP 4.5 and 8.5). Five trait parameterizations, representing mean and extreme values for the maximum stomatal conductance (gmax) and leaf water potential threshold for stomatal closure (Ψsc), were defined from meta-analyses. Compared to mean trait values, the water-spending extremes (highest gmax or most negative Ysc) had negligible benefits for carbon gain and canopy cooling, but exacerbated vine water use and stress, for both sites and climate scenarios. These traits increased cumulative transpiration by 8 – 17%, changed cumulative carbon gain by -4 – 3%, and reduced minimum water potentials by 10 – 18%. Conversely, the water-saving extremes (lowest gmax or least negative Ψsc) strongly reduced water use and stress, but potentially compromised the carbon supply for ripening. Under RCP 8.5 conditions, these traits reduced transpiration by 22 – 35% and carbon gain by 9 – 16% and increased minimum water potentials by 20 – 28%, compared to mean values. Overall, selecting for more water-saving stomatal traits could improve water-use efficiency and avoid the detrimental effects of highly negative canopy water potentials on yield and quality, but more work is needed to evaluate whether these benefits outweigh the consequences of minor declines in carbon gain for fruit production.

Grapevine yield estimation in a context of climate change: the GraY model

Grapevine yield is a key indicator to assess the impacts of climate change and the relevance of adaptation strategies in a vineyard landscape. At this scale, a yield model should use a number of parameters and input data in relation to the information available and be able to reproduce vineyard management decisions (e.g. soil and canopy management, irrigation). In this study, we used data from six experimental sites in Southern France (cv. Syrah) to calibrate a model of grapevine yield limited by water constraint (GraY). Each yield component (bud fertility, number of berries per bunch, berry weight) was calculated as a function of the soil water availability simulated by the WaLIS water balance model at critical phenological phases. The model was then evaluated in 10 grapegrowers’ plots, covering a diversity of biophysical and technical contexts (soil type, canopy size, irrigation, cover crop). We identified three critical periods for yield formation: after flowering on the previous year for the number of bunches and berries, around pre-veraison and post-veraison of the same year for mean berry weight. Yields were simulated with a model efficiency (EF) of 0.62 (NRMSE = 0.28). Bud fertility and number of berries per bunch were more accurately simulated (EF = 0.90 and 0.77, NRMSE = 0.06 and 0.10, respectively) than berry weight (EF = -0.31, NRMSE = 0.17). Model efficiency on the on-farm plots reached 0.71 (NRMSE = 0.37) simulating yields from 1 to 8 kg/plant. The GraY model is an original model estimating grapevine yield evolution on the basis of water availability under future climatic conditions.  It allows to evaluate the effects of various adaptation levers such as planting density, cover crop management, fruit/leaf ratio, shading and irrigation, in various production contexts.

Use of a new, miniaturized, low-cost spectral sensor to estimate and map the vineyard water status from a mobile 

Optimizing the use of water and improving irrigation strategies has become increasingly important in most winegrowing countries due to the consequences of climate change, which are leading to more frequent droughts, heat waves, or alteration of precipitation patterns. Optimized irrigation scheduling can only be based on a reliable knowledge of the vineyard water status.

In this context, this work aims at the development of a novel methodology, using a contactless, miniaturized, low-cost NIR spectral tool to monitor (on-the-go) the vineyard water status variability. On-the-go spectral measurements were acquired in the vineyard using a NIR micro spectrometer, operating in the 900–1900 nm spectral range, from a ground vehicle moving at 3 km/h. Spectral measurements were collected on the northeast side of the canopy across four different dates (July 8th, 14th, 21st and August 12th) during 2021 season in a commercial vineyard (3 ha). Grapevines of Vitis vinifera L. Graciano planted on a VSP trellis were monitored at solar noon using stem water potential (Ψs) as reference indicators of plant water status. In total, 108 measurements of Ψs were taken (27 vines per date).

Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r2cv) of 0.67 and a root mean square error of cross-validation (RMSEcv) of 0.131 MPa. This predictive model was employed to map the spatial variability of the vineyard water status and provided useful, practical information towards the implementation of appropriate irrigation strategies. The outcomes presented in this work show the great potential of this low-cost methodology to assess the vineyard stem water potential and its spatial variability in a commercial vineyard.

From a local to an international scale: sensory benchmarking of PDO wines. Quincy and Reuilly PDO wines (Sauvignon blanc) as a case study (France)

In a collective marketing strategy, the Protected Designation of Origin (PDO) can be used as a quality indicator. To highlight terroir specificities, it is useful to know how the wines are positioned on the local, national or international market from a sensory point of view. This is especially true for a comparison of varietal wines (e.g. Sauvignon blanc). We focus on the case of two closed Loire Valley PDO (France): Quincy and Reuilly. Three distinct tastings were organized. Firstly, at the local level comparing the 2 PDO (11 and 9 wines, 17 professional assessors); secondly at a regional level adding 3 closed PDO: Menetou-Salon, Sancerre and Pouilly-Fumé (3 wines per PDO, 16 assessors) and thirdly at an international level comparing these 5 PDO with Sauvignon Blanc wines coming from South Africa, New Zealand and Chile (1 to 3 wines per PDO, 19 assessors). All the wines were from the 2019 vintage and were considered to have a traditional elaboration process without contact with oak. A sensory descriptive analysis was performed using an aroma wheel allowing to combine a Check-All-That-Apply methodology, often used in sensory benchmarking, with a hierarchical structuration of the attributes. The aim is to facilitate data acquisition in a professional context without common training, to consider the hierarchical relationships among the attributes during the data analysis and to be able to characterize wines with a large range of sensorial variability. We use univariate, multivariate and clustering analyses. Similarities and differences between Quincy and Reuilly PDO wines and other Sauvignon blanc wines were identified. Specific attributes can distinguish the two PDO and different proximities exist with other local PDO, while clear differences were observed compared to international wines. Our study contributes to propose and discuss a method to do a wine sensory benchmarking highlighting sensory specificities linked to origin.