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…

Comparison of imputation methods in long and varied phenological series. Application to the Conegliano dataset, including observations from 1964 over 400 grape varieties

A large varietal collection including over 1700 varieties was maintained in Conegliano, ITA, since the 1950s. Phenological data on a subset of 400 grape varieties including wine grapes, table grapes, and raisins were acquired at bud break, flowering, veraison, and ripening since 1964. Despite the efforts in maintaining and acquiring data over such an extensive collection, the data set has varying degrees of missing cases depending on the variety and the year. This is ubiquitous in phenology datasets with significant size and length. In this work, we evaluated four state-of-the-art methods to estimate missing values in this phenological series: k-Nearest Neighbour (kNN), Multivariate Imputation by Chained Equations (mice), MissForest, and Bidirectional Recurrent Imputation for Time Series (BRITS). For each phenological stage, we evaluated the performance of the methods in two ways. 1) On the full dataset, we randomly hold-out 10% of the true values for use as a test set and repeated the process 1000 times (Monte Carlo cross-validation). 2) On a reduced and almost complete subset of varieties, we varied the percentage of missing values from 10% to 70% by random deletion. In all cases, we evaluated the performance on the original values using normalized root mean squared error. For the full dataset we also obtained performance statistics by variety and by year. MissForest provided average errors of 17% (3 days) at budbreak, 14% (4 days) at flowering, 14.5% (7 days) at veraison, and 17% (3 days) at maturity. We completed the imputations of the Conegliano dataset, one of the world’s most extensive and varied phenological time series and a steppingstone for future climate change studies in grapes. The dataset is now ready for further analysis, and a rigorous evaluation of imputation errors is included.

A spatial explicit inventory of EU wine protected designation of origin to support decision making in a changing climate

Winemaking areas recognized as protected designations of origin (PDOs) shape important economic, environmental and cultural values that are tied to closely defined geographic locations. To preserve wine products and wine-growing practices adopted in different PDOs these areas are strictly regulated by legal specifications. However, quality viticulture is increasingly under pressure from climate change, which is altering the local conditions of many winegrowing areas. Therefore, maintaining traditional wine products will require the adoption of tailored adaptation strategies, including possible changes in the legal regulation of protected wines. To this end, it is necessary to have a comprehensive knowledge on PDOs including their extension, products and allowed practices. While there have been efforts to build databases that summarize the characteristics for individual wine PDO areas and to quantify the related effects of climate change, much information is still included only in the official documentation of the EU geographical indication register and has never been collected in a comprehensive manner. With this study we aim at filling this gap by building a spatial inventory of European wine PDOs that supports decision making in viticulture in the context of climate change. To map and characterize European wine PDOs, we analysed their legal documents and extracted relevant information useful for climate change adaptation. The output consists of a comprehensive geographical dataset that identifies the boundaries of all 1200 European wine PDOs at unprecedented spatial resolution and includes a set of legally binding regulations, such as authorized vine varieties, maximum yields and planting density. The inventory will allow researchers to analyse the impacts of climate change on European wine PDOs and support decision makers in developing tailored adaptation strategies. This includes, among others, the evaluation of new vineyard site selection, the expansion of cultivated varieties or the authorization of irrigation in vineyards.

Estimating bulk stomatal conductance of grapevine canopies

In response to changes in their environment, grapevines regulate transpiration using various physiological mechanisms that alter conductance of water through the soil-plant-atmosphere continuum. Expressed as bulk stomatal conductance at the canopy scale, it varies diurnally in response to changes in vapor pressure deficit and net radiation, and over the season to changes in soil water deficits and hydraulic conductivity of both soil and plant. It is necessary to characterize the response of conductance to these variables to better model how vine transpiration also responds to these variables. Furthermore, to be relevant for vineyard-scale modeling, conductance is best characterized using data collected in a vineyard setting. Applying a crop canopy energy flux model developed by Shuttleworth and Wallace, bulk stomatal conductance was estimated using measurements of individual vine sap flow, temperature and humidity within the vine canopy, and estimates of net radiation absorbed by the vine canopy. These measurements were taken on several vines in a non-irrigated vineyard in Bordeaux France, using equipment that did not interfere with ongoing vineyard operations. An inverted Penman-Monteith equation was then used to calculate bulk stomatal conductance on 15-minute intervals from July to mid-September 2020. Time-series plots show significant diurnal variation and seasonal decreases in conductance, with overall values similar to those in the literature. Global sensitivity analysis using non-parametric regression found transpiration flux and vapor pressure deficit to be the most important input variables to the calculation of bulk stomatal conductance, with absorbed net radiation and bulk boundary layer conductance being much less important. Conversely, bulk stomatal conductance was one of the most important inputs when calculating vine transpiration, further emphasizing the need for characterizing its response to environmental changes for use in vineyard water use modeling.

Grape berry size is a key factor in determining New Zealand Pinot noir wine composition

Making high quality but affordable Pinot noir (PN) wine is challenging in most terroirs and New Zealand’s (NZ) situation is no exception. To increase the probability of making highly typical PN wines producers choose to grow grapes in cool climates on lower fertility soils while adopting labour intensive practices. Stringent yield targets and higher input costs necessarily mean that PN wine cost is high, and profitability lower, in line-priced varietal wine ranges. To understand the reasons why higher yielding vines are perceived to produce wines of lower quality we have undertaken an extensive study of PN in NZ. Since 2018, we established a network of twelve trial sites in three NZ regions to find individual vines that produced acceptable commercial yields (above 2.5kg per vine) and wines of composition comparable to “Icon” labels. Approximately 20% of 660 grape lots (N = 135) were selected from within a narrow juice Total Soluble Solids (TSS) range and made into single vine wines under controlled conditions. Principal Component Analysis of the vine, berry, juice and wine parameters from three vintages found grape berry mass to be most effective clustering variable. As berry mass category decreased there was a systematic increase in the probability of higher berry red colour and total phenolics with a parallel increase in wine phenolics, changed aroma fraction and decreased juice amino acids. The influence of berry size on wine composition would appear stronger than the individual effects of vintage, region, vineyard or vine yield. Our observations support the hypothesis that it is possible to produce PN wines that fall within an “Icon” benchmark composition range at yields above 2.5kg per vine provided that the Leaf Area:Fruit Weight ratio is above 12cm2 per g, mean berry mass is below 1.2g and juice TSS is above 22°Brix.

Effects of graft quality on growth and grapevine-water relations

Climate change is challenging viticulture worldwide compromising its sustainability due to warmer temperatures and the increased frequency of extreme events. Grafting Vitis vinifera L.