GiESCO 2019 banner
IVES 9 IVES Conference Series 9 GiESCO 9 Evaluation of intra-vineyard spatial and temporal variability of leaf area index using multispectral images obtained by satellite (Landsat 8, Sentinel-2) and unmanned aerial vehicle platforms

Evaluation of intra-vineyard spatial and temporal variability of leaf area index using multispectral images obtained by satellite (Landsat 8, Sentinel-2) and unmanned aerial vehicle platforms

Abstract

Context and purpose of the study – Estimation of vineyard leaf area index (LAI) is an important aspect for the winegrowers. However, tracking and monitoring are difficult tasks due to time constraints. Satellite and unmanned aerial vehicle (UAV) imaging have become a practical monitoring method for LAI. Nevertheless, for a proper LAI determination, the image’s spatial resolution is a key factor, since low-resolution images are incapable of distinguishing between adjacent vines due to the large area covered in each pixel, this leads to misinterpretation or generalisation of vineyard information. The objective of this study was to evaluate the effect of spatial resolution on the accuracy of LAI estimation using different spatial resolutions: Landsat8 (30 m), Sentinel-2 (10 m) and UAV Multispectral images (0.05 m).

Material and methods – This study was carried out in a dryland vineyard cv. Pinotage situated in Stellenbosch, at the Welgevallen experimental farm (33°57’8” S, 18°52’26” E). The block (1.9 ha) has a North-South orientation and was planted on a West-South-West slope. The vines are trained on a sevenwire (moveable) hedge trellis, VSP (vertical shoot positioning) system. Three sources of remote sensing data, with different spatial resolutions, were chosen: i) Multispectral images acquired by a multi-rotor unmanned aerial vehicle (UAV) (spatial resolution 0.052 m); ii) Landsat 8 images (spatial resolution of 30 m) and iii) Sentinel-2A images (spatial resolution of 30 m). Images from these three sources were used to calculate the normalised difference vegetation index (NDVI) from the experimental site, and these values were compared with field measurements (empirical LAI model).

Results – Results obtained from low-resolution satellite images show a poor accuracy in the estimation of LAI on a plant scale. The image resolution of Landsat 8 and Sentinel-2 was not high enough to differentiate between adjacent groups of vines. The UAV multispectral images obtained the best agreement with the field LAI measurements, due to the high resolution (0.052 m pixel size). It is evident with the results obtained that UAV imaging is the most appropriate and accurate monitoring methodology since this technology providing enough information to estimate LAI per plant.

DOI:

Publication date: September 27, 2023

Issue: GiESCO 2019

Type: Poster

Authors

Yolandi BARNARD1, Guillermo OLMEDO2, Albert STREVER1, Carlos POBLETE-ECHEVERRÍA1*

1 Department of Viticulture and Oenology, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa
2 EEA Mendoza, Instituto Nacional de Tecnología Agropecuaria, Mendoza M5507EVY, Argentina

Contact the author

Keywords

Normalised Difference Vegetation Index (NDVI), Unmanned Aerial Vehicle (UAV), grid analysis, spatial variability

Tags

GiESCO | GiESCO 2019 | IVES Conference Series

Citation

Related articles…

Modeling the suitability of Pinot Noir in Oregon’s Willamette Valley in a changing climate

Air temperature is the key driver of grapevine phenology and a significant environmental factor impacting yield and quality for a winegrape growing region. In this study the optimal downscaled CMIP5 ensemble for computing thegrowing season average temperature (GST) viticulture climate classification index was determined to spatially compute on a decadal basis predictions of the GST climate index and the grapevine sugar ripeness (GSR) model for Pinot Noir throughout the Willamette Valley (WV) American Viticultural Area (AVA). Forecasts for average temperature and a 220 g/L target sugar concentration level were computed using daily Localized Constructed Analogs (LOCA) downscaled CMIP5 historic and Representative Concentration Pathways (RCP) future climate projections of minimum and maximum daily temperature. We explore spatiotemporal trends of the GST climate classification index and Pinot Noir specific applications of the GSR phenology model for the WV AVA. Spatiotemporal computations of the GST climate index and Pinot Noir specific applications of the GSR model enable the opportunity to explore relationships between their computed values with one intent being to provide updated GST ranges that better align with current temperature-based modeling understanding of Pinot Noir grapevine phenology and the viticultural application of LOCA CMIP5 climate projections for the WV AVA. The Pinot Noir specific applications of the GSR model or the GST index with updated bounds indicate that the percent of the WV AVA area suitable for Pinot Noir production is currently at or near its peak value in the upper 80s to lower 90s of this century.

Grapevine sugar concentration model in the Douro Superior, Portugal

Increasingly warm and dry climate conditions are challenging the viticulture and winemaking sector. Digital technologies and crop modelling bear the promise to provide practical answers to those challenges. As viticultural activities strongly depend on harvest date, its early prediction is particularly important, since the success of winemaking practices largely depends upon this key event, which should be based on an accurate and advanced plan of the annual cycle. Herein, we demonstrate the creation of modelling tools to assess grape ripeness, through sugar concentration monitoring. The study area, the Portuguese Côa valley wine region, represents an important terroir in the “Douro Superior” subregion. Two varieties (cv. Touriga Nacional and Touriga Franca) grown in five locations across the Côa Region were considered. Sugar accumulation in grapes, with concentrations between 170 and 230 g l-1, was used from 2014 to 2020 as an indicator of technological maturity conditioned by meteorological factors. The climatic time series were retrieved from the EU Copernicus Service, while sugar data were collected by a non-profit organization, ADVID, and by Sogrape, a leading wine company. The software for calibrating and validating this model framework was the Phenology Modeling Platform (PMP), version 5.5, using Sigmoid and growing degree-day (GDD) models for predictions. The performance was assessed through two metrics: Roots Mean Square Error (RMSE) and efficiency coefficient (EFF), while validation was undertaken using leave-one-out cross-validation. Our findings demonstrate that sugar content is mainly dependent on temperature and air humidity. The models achieved a performance of 0.65

Effect of regulated deficit irrigation regime on amino acids content of Monastrell (Vitis vinifera L.) grapes

Irrigation is an important practice to influence vine quality, especially in Mediterranean regions, characterized by hot summers and severe droughts during the growing season. This study focused on deficit irrigation regime influence on amino acids composition of Monastrell grapevines under semiarid conditions (Albacete, Southeastern of Spain). In 2019, two treatments were applied: non-irrigation (NI) and regulated deficit irrigation (RDI), watered at 30% of the estimated crop evapotranspiration from fruit set to onset of veraison. Grape amino acids content was analyzed by HPLC. Berries from non-irrigated vines showed higher concentration of several amino acids, such as tryptophan (73%), arginine (70%), lysine (36%), isoleucine (27%), and leucine (21%), compared to RDI grapes. Arginine is, together with ammonium ion, the principal nitrogen source for yeasts during the alcoholic fermentation; while isoleucine, tryptophan, and leucine are precursors of fermentative volatile compounds, key compounds for wine quality. Moreover, NI treatment increased in a 14% the total amino acids content in grapes compared to RDI treatment. The reported effects might be because yield was 70% higher in RDI vines than in the NI ones and, therefore, the sink demand was increased in the irrigated vines. In addition, NI vines suffered more severe water stress and it is known that the amino acids synthesis and accumulation can be influenced by the plant response to stress. According to the results, the irrigation regime showed effect on amino acids concentration in Monastrell grapes under semiarid conditions. Grapes from non-irrigated vines showed a higher content of several amino acids relevant to the fermentative process and to the wine aroma compounds formation. It is demonstrated that the final content of nitrogen-related components in grapes is influenced by the irrigation regime. The convenience of the irrigation strategy to suggest will depend on the desired wine style and the target yield levels.

Terroir analysis and its complexity

Terroir is not only a geographical site, but it is a more complex concept able to express the “collective knowledge of the interactions” between the environment and the vines mediated through human action and “providing distinctive characteristics” to the final product (OIV 2010). It is often treated and accepted as a “black box”, in which the relationships between wine and its origin have not been clearly explained. Nevertheless, it is well known that terroir expression is strongly dependent on the physical environment, and in particular on the interaction between soil-plant and atmosphere system, which influences the grapevine responses, grapes composition and wine quality. The Terroir studying and mapping are based on viticultural zoning procedures, obtained with different levels of know-how, at different spatial and temporal scales, empiricism and complexity in the description of involved bio-physical processes, and integrating or not the multidisciplinary nature of the terroir. The scientific understanding of the mechanisms ruling both the vineyard variability and the quality of grapes is one of the most important scientific focuses of terroir research. In fact, this know-how is crucial for supporting the analysis of climate change impacts on terroir resilience, identifying new promised lands for viticulture, and driving vineyard management toward a target oenological goal. In this contribution, an overview of the last findings in terroir studies and approaches will be shown with special attention to the terroir resilience analysis to climate change, facing the use and abuse of terroir concept and new technology able to support it and identifying the terroir zones.

Soil, vine, climate change – what is observed – what is expected

To evaluate the current and future impact of climate change on Viticulture requires an integrated view on a complex interacting system within the soil-plant-atmospheric continuum under continuous change. Aside of the globally observed increase in temperature in basically all viticulture regions for at least four decades, we observe several clear trends at the regional level in the ratio of precipitation to potential evapotranspiration. Additionally the recently published 6th assessment report of the IPCC (The physical science basis) shows case-dependent further expected shifts in climate patterns which will have substantial impacts on the way we will conduct viticulture in the decades to come.
Looking beyond climate developments, we observe rising temperatures in the upper soil layers which will have an impact on the distribution of microbial populations, the decay rate of organic matter or the storage capacity for carbon, thus affecting the emission of greenhouse gases (GHGs) and the viscosity of water in the soil-plant pathway, altering the transport of water. If the upper soil layers dry out faster due to less rainfall and/or increased evapotranspiration driven by higher temperatures, the spectral reflection properties of bare soil change and the transport of latent heat into the fruiting zone is increased putting a higher temperature load on the fruit. Interactions between micro-organisms in the rhizosphere and the grapevine root system are poorly understood but respond to environmental factors (such as increased soil temperatures) and the plant material (rootstock for instance), respectively the cultivation system (for example bio-organic versus conventional). This adds to an extremely complex system to manage in terms of increased resilience, adaptation to and even mitigation of climate change. Nevertheless, taken as a whole, effects on the individual expressions of wines with a given origin, seem highly likely to become more apparent.