terclim by ICS banner
IVES 9 IVES Conference Series 9 International Congress on Grapevine and Wine Sciences 9 2ICGWS-2023 9 Evaluation of the effects of pruning methodology on the development of young vines 

Evaluation of the effects of pruning methodology on the development of young vines 

Abstract

Grapevine pruning is one of the most important practices in the vineyards. Winegrowers use it to provide the vines the shape needed, or to maintain it once achieved, and also to balance vegetative growth and fruit production. In the last decades, careless pruning has been blamed, among other factors, as responsible of the vineyard decay that is been observed even in young vines. However, to our knowledge, there is a lack of systematic research trying to elucidate to which extent the pruning method used affects plant development or its susceptibility to grapevine trunk diseases (GTD). Within this context, the aim of this work is to study the influence of different pruning method strategies on the development of field-planted young vines. Two trials were carried out in commercial vineyards planted in 2019 in La Rioja and Navarra, where three pruning criteria were applied: i) control pruning, following the criteria of the winegrowers in the area (CONT); ii) respectful pruning, paying attention to the preferential sap flow pathway and leaving protective wood in the cuts (RESP); and iii) aggressive pruning, not paying attention to sap flow pathways and not leaving protective wood (AGGR). In general, RESP pruning tended to increase shoot growth compared to CONT and AGGR pruning, obtaining higher values of pruning wood weight in winter, and reaching greater yield in the first harvest. In conclusion, the different pruning strategies applied have a significant effect on growth, even though more years of experimentation would be necessary to evaluate their impact on the agronomic behavior and general performance and longevity of the vineyard.

The project (EFA324/19 VITES QUALITAS) has been 65% cofinanced by the European Regional Development Fund (ERDF) through the Interreg V-A Spain-France-Andorra programme (POCTEFA 2014-2020).

DOI:

Publication date: October 5, 2023

Issue: ICGWS 2023

Type: Article

Authors

Mónica Galar1*, Nazareth Torres1-2, Bárbara Sebastián3, Julián Palacios3, Nahiara Juanena1, Ana Villa-Llop1-4, C. Dewasme5, J.P. Roby5, L. Gonzaga Santesteban1-2

1Dpt. of Agronomy, Biotechnology and Food, Public University of Navarre (UPNA), Pamplona, Navarra.
2Institute for Multidisciplinary Research in Applied Biology (IMAB), Pamplona, Navarra.
3Viticultura Viva, S. Martín de Unx, Navarra.
4Vitis Navarra, Road NA132, km. 18, 31251 Larraga, Navarra.
5ISVV, UMR EGFV, 210 Chemin de Leysotte CS50008 33 882 Villenave d’Ornon

Contact the author*

Keywords

grapevine pruning, grapevine trunk disease, longevity

Tags

2ICGWS | ICGWS | ICGWS 2023 | IVES Conference Series

Citation

Related articles…

Dynamics of Saccharomyces cerevisiae population in spontaneous fermentations from Granxa D’Outeiro terroir (DOP Ribeiro, NW Spain)

Granxa D’Outeiro is a recovered ancient vineyard located in the heart of DOP Ribeiro, where traditional white grapevine varieties are growing under sustainable management. Spontaneous fermentations using grape must from Treixadura, Albariño, Lado, Godello, and Loureira varieties were carried out at experimental winery of Evega. Yeasts were isolated from must and at different stages of fermentation. Those colonies belonging to Saccharomyces cerevisiae were characterized at strain level by mDNA-RFLPs.

Analysis of volatile composition of interaction between the pathogen E. necator and two grapevine varieties

Volatile organic compounds (VOCs) are emitted by nearly all plant organs of the plants, including leaves. They play a key role in the communication with other organisms, therefore they are involved in plant defence against phytopathogens. In this study VOCs from grapevine leaves of two varieties of Vitis vinifera infected by Erysiphe necator were analysed. The varieties were selected based on their susceptibility to pathogen, Kishmish Vatkana has the Ren1 resistance gene and Zamarrica showed high susceptibility in previous trials.

Selecting green cover species in the under-trellis zone of Lower Austrian vineyards

The under-trellis zone of vineyards is a sensitive area through which vines cover a significant portion of their nutrient and water needs. Mechanical and chemical methods are applied to suppress competing and tall-growing weeds to ensure optimal vine growth conditions. In addition to higher operating costs and depending on the soil conditions, these practices might lead to a long-term reduction in soil fertility and biodiversity. The presented study aims to analyse the suitability and interspecies competition of a selected green cover mixture of five local herbaceous species as potential green cover mixture in the under-trellis area of Lower Austrian vineyards.

Atypical aging and hydric stress: insights on an exceptionally dry year

Atypical aging (ATA) is a white wine fault characterized by the appearance of notes of wet rag, acacia blossoms and naphthalene, along with the vanishing of varietal aromas. 2-aminoacetophenone (AAP) – a degradation compound of indole-3-acetic acid (IAA) – is regarded as the main sensorial and chemical marker responsible for this defect. About the origin of ATA, a stress reaction occurring in the vineyard has been looked as the leading cause of this defect. Agronomic, climatic and pedological factors are the main triggers and among them, drought stress seems to play a crucial role.[1]

Applicability of spectrofluorometry and voltammetry in combination with machine learning approaches for authentication of DOCa Rioja Tempranillo wines

The main objective of the work was to develop a simple, robust and selective analytical tool that allows predicting the authenticity of Tempranillo wines from DOCa Rioja. The techniques of voltammetry and absorbance-transmission and fluorescence excitation emission matrix (A-TEEM) spectroscopy have been applied in combination with machine learning (ML) algorithms to classify red wines from DOCa Rioja according to region (Alavesa, Alta or Oriental) and category (young, crianza or reserva).