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 26, 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…

AOC valorization of terroir nuances at plot scale in Burgundy

In the highly competitive global wine market, Burgundy has a long-established reputation to maintain. The vine and wine sector in Burgundy is based on a five-level ranking of AOC (Appellation d’Origine Contrôlée) wines and of the plots where the grapes are grown.

Different yield regulation strategies in semi-minimal-pruned hedge (SMPH) and impact on bunch architecture

Yields in the novel viticulture training system Semi-Minimal-Pruned Hedge (SMPH) are generally higher compared to the traditional Vertical Shoot Positioning (VSP). Excessive yields have a negative impact on the vine and wine quality, which can result in substantial losses in yield in subsequent vintages (alternate bearing) or penalties in fruit quality. Therefore yield regulation is essential. The bunch architecture in SMPH differs from VSP. Generally there is a higher amount but smaller bunches with lower single berry weights in SMPH compared to VSP.

Effectiveness of carboxymethyl cellulose (CMC) on tartaric stabilization of cava base wine

Recent EU regulations allow the use of carboxymethylcellulose (CMC) as a stabilization agent in wine. We tested CMC in bases for sparkling wines, which must be stabilized before the second fermentation that raises alcohol concentration by 1,5%.

Tracking the origin of Tempranillo Tinto through whole genome resequencing and high-throughput genotyping  

Grapevine cultivars are vegetatively propagated to maintain their varietal characteristics. This process of multiplication leads to spontaneous somatic mutations that can eventually generate a variant phenotype, of potential interest for cultivar improvement and innovation. However, regardless their phenotypic effect, somatic mutations stack in the genome, and they can be used to reveal the origin and dissemination history of ancient cultivars. Here, a stringent somatic variant calling over whole genome resequencing data from 35 ‘Tempranillo Tinto’ clones or old vines from seven Iberian winemaking regions revealed 135 single nucleotide variations (SNVs) shared by some of the clonal lines.

Rootstock effect on Cabernet Sauvignon aromatic and chemical composition

Grape quality potential for wine production is strongly influenced by environmental parameters and agronomic factors. Several studies underline the rootstock effect on scions vegetative growth and berry composition [1] with an impact on wine quality. Rootstocks are promising agronomic tools for climate change adaptation and in most grape-growing regions the potential diversity of rootstocks is not fully used and only a few genotypes are planted. Moreover, little is known about the effect of rootstock genetic variability on the aromatic composition in wines.