GiESCO 2019 banner
IVES 9 IVES Conference Series 9 GiESCO 9 Assessing bunch architecture for grapevine yield forecasting by image analysis 

Assessing bunch architecture for grapevine yield forecasting by image analysis 

Abstract

Context and purpose of the study – It is fundamental for wineries to know the potential yield of their vineyards as soon as possible for future planning of winery logistics. As such, non-invasive image-based methods are being investigated for early yield prediction. Many of these techniques have limitations that make it difficult to implement for practical use commercially. The aim of this study was to assess whether yield can be estimated using images taken in-field with a smartphone at different phenological stages. The accuracy of the method for predicting bunch weight at different phenological stages was assessed for seven different varieties.

Material and methods – During the 2017-18 growing season in the Coombe Vineyard at the Waite Campus of the University of Adelaide seven different varieties were chosen for this study: Semillon, Grenache, Shiraz, Merlot, Sauvignon Blanc, Tempranillo and Cabernet Franc. After fruitset, 30 vines per variety were selected and two shoots were flagged on each vine. Images of bunches were taken five times from EL stage 30-31 to EL stage 37-38 using a smartphone. Bunch volumes were estimated from images. At harvest bunches were collected, weighed and imaged in the laboratory to compare with field images.

Results – This new approach using a smartphone to forecast the yield showed promising results. Accurate weight forecast models could be obtained by taking bunch images at veraison (R2 ranging from 0.71 to 0.84). As the bunch architecture of different varieties can vary further studies are required to improve the accuracy of this method. The tools used for this study are inexpensive, in common use, and do not need a high level of expertise to use them, furthermore, the labour required to obtain data, is not time-consuming.

DOI:

Publication date: September 28, 2023

Issue: GiESCO 2019

Type: Poster

Authors

Marco ZITO*1, Massimiliano COCCO2, Roberta DE BEI3, Cassandra COLLINS3

1 Istituto di Scienze della Vita, Scuola Superiore Sant’Anna, Pisa, Italy 56127
2 Dipartimento di Agraria, Università degli Studi di Sassari, Sassari, Italy 07100
3 School of Agriculture, Food and Wine, Waite Research Precinct, The University of Adelaide, PMB I, Glen Osmond, SA 5064, Australia

Contact the author

Keywords

bunch architecture, yield prediction, image analysis, non-destructive method

Tags

GiESCO | GiESCO 2019 | IVES Conference Series

Citation

Related articles…

Towards a regional mapping of vine water status based on crowdsourcing observations

Monitoring vine water status is a major challenge for vineyard management because it influences both yield and harvest quality. It is also a challenge at the territorial scale for identifying periods of high water restriction or zones regularly impacted by water stress. This information is of major importance for defining collective strategies, anticipating harvest logistic or applying for irrigation authorisation. At this spatial scale, existing tools and methods for monitoring vine water status are few and often require strong assumptions (e.g. water balance model). This paper proposes to consider a collaborative collection of observations by winegrowers and wine industry stakeholders (crowdsourcing) as an interesting alternative. Indeed, it allows the collection of a large number of field observations while pooling the collection effort. However, the feasibility of such a project and its interest in monitoring vine water status at regional scale has never been tested. The objective of this article is to explore the possibility of making a regional map of vine water status based on crowdsourcing observations. It is based on the study of the free mobile application ApeX-Vigne, which allows the collection of observations about vine shoot growth. This information is easy to collect and can be considered, under certain conditions, as a proxy for vine water status. This article presents the first results obtained from the nearly 18,000 observations collected by winegrowers and wine industry stakeholders during 2019, 2020 and 2021 seasons. It presents the vine shoot growth maps obtained at regional scale and their evolution over the three vintages studied. It also proposes an analysis of the factors that favoured the number of observations collected and those that favoured their quality. These results open up new perspectives for monitoring vine water status at a regional scale but above they provide references for other crowdsourcing projects in viticulture.

Analysis of some environmental factors and cultural practices that affect the production and quality of the Manto Negro, Callet and Prensal Blanc varieties

45 non irrigated vineyards distributed in the DO (Denomination) Pla i Llevant de Mallorca and the DO Binissalem Mallorca were used to investigate the characteristics of production and quality and their relationships certain environmental factors and cultural practices. The grape varieties investigated are autochthonous to the island of Mallorca, Manto Negro and Callet as red and Prensal Blanc as white. All plants were measured for four consecutive years in the main production and quality parameters. Among the environmental factors, the type of soil has been studied, more specifically its water retention capacity, the planting density, the age of the vineyard and the level of viral infection. The presence or absence of virus seems to have no effect on any component studied in the varieties studied. For the white variety Prensal Blanc age is negatively correlated with production and the number of bunches, nevertheless it does not cause any effect on the required quality parameters. However, for the red varieties Callet and Manto Negro, the age of the plantation is the variable that best correlates with the quality parameters, therefore the old vines should be the object of preservation by the viticulturists and winemakers in order to guarantee its contribution to the quality of the wines made with these varieties.

1H-NMR-based Metabolomics to assess the impact of soil type on the chemical composition of Mediterranean red wines

The aim of this study was to evaluate the effects of different soil types on the chemical composition of Mediterranean red wines, through untargeted and targeted 1H-NMR metabolomics. One milliliter of raw wine was analyzed by means of a Bruker Avance II 400 spectrometer operating at 400.15 MHz. The spectra were recorded by applying the NOESYGPPS1D pulse sequency, to achieve water and ethanol signals suppression. No modification of the pH was performed to avoid any chemical alteration of the matrix. The generation of input variables for untargeted analysis was done via bucketing the spectra. The resulting dataset was preprocessed prior to perform unsupervised PCA, by means of MetaboAnalyst web-based tool suite. The identification of compounds for the targeted analysis was performed by comparison to pure compounds spectra by means of SMA plug-in of MNova 14.2.3 software. The dataset containing the concentrations (%) of identified compounds was subjected to one-way analysis of variance (ANOVA) to highlight significant differences among the wines. The untargeted analysis, carried out through the PCA, revealed a clear differentiation among the wines. The fragments of the spectra contributing mostly to the separation were attributed to flavonoids, aroma compounds and amino acids. The targeted analysis leaded to the identification of 68 compounds, whose concentrations were significant different among the wines. The results were related to soils physical-chemical analysis and showed that: 1) high concentrations of flavan-3-ols and flavonols are correlated with high clay content in soils; 2) high concentrations of anthocyanins, amino acids, and aroma compounds are correlated with neutral and moderately alkaline soil pH; 3) low concentrations of flavonoids and aroma compounds are correlated with high soil organic matter content and acidic pH. The 1H-NMR metabolomic analysis proved to be an excellent tool to discriminate between wines originating from grapes grown on different soil types and revealed that soils in the Mediterranean area exert a strong impact on the chemical composition of the wines.

Adaptation to soil and climate through the choice of plant material

Choosing the rootstock, the scion variety and the training system best suited to the local soil and climate are the key elements for an economically sustainable production of wine. The choice of the rootstock/scion variety best adapted to the characteristics of the soil is essential but, by changing climatic conditions, ongoing climate change disrupts the fine-tuned local equilibrium. Higher temperatures induce shifts in developmental stages, with on the one hand increasing fears of spring frost damages and, on the other hand, ripening during the warmest periods in summer. Expected higher water demand and longer and more frequent drought events are also major concerns. The genetic control of the phenotypes, by genomic information but also by the epigenetic control of gene expression, offers a lot of opportunities for adapting the plant material to the future. For complex traits, genomic selection is also a promising method for predicting phenotypes. However, ecophysiological modelling is necessary to better anticipate the phenotypes in unexplored climatic conditions Genetic approaches applied on parameters of ecophysiological models rather than raw observed data are more than ever the basis for finding, or building, the ideal varieties of the future.

Simulating climate change impact on viticultural systems in historical and emergent vineyards

Global climate change affects regional climates and hold implications for wine growing regions worldwide. Although winegrowers are constantly adapting to internal and external factors, it seems relevant to develop tools, which will allow them to better define actual and future agro-climatic potentials. Within this context, we develop a modelling approach, able to simulate the impact of environmental conditions and constraints on vine behaviour and to highlight potential adaptation strategies according to different climate change scenarios. Our modeling approach, named SEVE (Simulating Environmental impacts on Viticultural Ecosystems), provides a generic modeling framework for simulating grapevine growth and berry ripening under different conditions and constraints (slope, aspect, soil type, climate variability…) as well as production strategies and adaptation rules according to climate change scenarios. Each activity is represented by an autonomous agent able to react and adapt its reaction to the variability of environmental constraints. Using this model, we have recently analyzed the evolution of vineyards’ exposure to climatic risks (frost, pathogen risk, heat wave) and the adaptation strategies potentially implemented by the winegrowers. This approach, implemented for two climate change scenarios, has been initiated in France on traditional (Loire Valley) and emerging (Brittany) vineyards. The objective is to identify the time horizons of adaptations and new opportunities in these two regions. Carried out in collaboration with wine growers, this approach aims to better understand the variability of climate change impacts at local scale in the medium and long term.