Deficit irrigation in table grape: eco-physiological basis and potential use to save water and improve quality

Permanhani, Miquéias; Costa, J.M.; Conceição, M. A. F.; Souza, R. T. de; Vasconcellos, Marco Antônio da Silva; Chaves, M. M.

doi:10.1007/s40626-016-0063-9

Cited by 44 publications

(20 citation statements)

References 147 publications

(208 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Hence, there is a direct link between the seasonal weather characteristics, which are mainly temperature expressed in thermal time (degree days) accumulated over 10 • C and phenological stages occurrence and duration [13], berry cell death, wine quality, and aroma profiles [11,12]. Furthermore, these berry quality traits can be manipulated using different irrigation techniques, such as regulated deficit irrigation (RDI) [14][15][16][17][18][19][20] and partial rootzone drying (PRD) [21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

Modeling Pinot Noir Aroma Profiles Based on Weather and Water Management Information Using Machine Learning Algorithms: A Vertical Vintage Analysis Using Artificial Intelligence

Fuentes

Tongson

Torrico

et al. 2019

Foods

View full text Add to dashboard Cite

Wine aroma profiles are determinant for the specific style and quality characteristics of final wines. These are dependent on the seasonality, mainly weather conditions, such as solar exposure and temperatures and water management strategies from veraison to harvest. This paper presents machine learning modeling strategies using weather and water management information from a Pinot noir vineyard from 2008 to 2016 vintages as inputs and aroma profiles from wines from the same vintages assessed using gas chromatography and chemometric analyses of wines as targets. The results showed that artificial neural network (ANN) models rendered the high accuracy in the prediction of aroma profiles (Model 1; R = 0.99) and chemometric wine parameters (Model 2; R = 0.94) with no indication of overfitting. These models could offer powerful tools to winemakers to assess the aroma profiles of wines before winemaking, which could help adjust some techniques to maintain/increase the quality of wines or wine styles that are characteristic of specific vineyards or regions. These models can be modified for different cultivars and regions by including more data from vertical vintages to implement artificial intelligence in winemaking.

show abstract

Section: Introductionmentioning

confidence: 99%

Modeling Pinot Noir Aroma Profiles Based on Weather and Water Management Information Using Machine Learning Algorithms: A Vertical Vintage Analysis Using Artificial Intelligence

Fuentes

Tongson

Torrico

et al. 2019

Foods

View full text Add to dashboard Cite

show abstract

“…Stem water potential and leaf gas exchange indicated anisohydric behaviour, good capacity to recover, and high physiological performances of Vermentino after severe water deficit [16,17]. Stomatal conductance was more sensitive to water stress than net assimilation.…”

Section: Physiological Performance and Productivitymentioning

confidence: 96%

Effects of pre and post-veraison water deficit on Vermentino cluster microclimate and berry composition

et al. 2019

View full text Add to dashboard Cite

The influence of light and thermal microclimate on berry quality of a Vermentino vineyard, managed with deficit irrigation strategies in north-western Sardinia, was analyzed. Two water deficit, pre- (ED) and post-veraison (LD), an irrigation (IC) and a non-irrigation (NC) control treatments were compared during berry development. Grapevine performances were evaluated by analyzing leaf gas exchange, source-sink balance, light and thermal microclimate effects on berry composition. Early and/or late deficit irrigation following a mild to moderate water stress threshold enabled high leaf physiological performances. Though with high stomatal conductance sensitivity to water deficit and anisohydric behavior, this variety exhibited high assimilation rate and quick recovery capacity after enduring moderate and severe water stress. All treatments achieved satisfactory sugar and acidic levels. Berry phenols were higher in LD due to lower canopy coverage and better light conditions compared to IC. Up to mid-ripening, cluster exposure to elevated temperatures negatively influenced phenolic accumulation, mostly in NC and to a lower extent in ED. In the last ripening weeks, total phenols was majorly influenced by light interception.

show abstract

“…Grapevines require optimum temperatures and sufficient solar radiation throughout its growth cycle (Failla et al, 2004;Sadras and Moran, 2013). Furthermore, water availability is crucial during certain stages of grapevine development (Tramontini et al, 2013;Permanhani et al, 2016;Fraga et al, 2018), while excessive dryness may lead to detrimental water stress impacts (Pavlousek, 2011;Webb et al, 2012). To assess these two terroir elements, high-resolution datasets, produced by the WorldClim project (Hijmans et al, 2005) at ca.…”

Section: Terroir Elementsmentioning

confidence: 99%

Multivariate clustering of viticultural terroirs in the Douro winemaking region

Fraga

Costa

Santos

2017

Ciência Téc. Vitiv.

View full text Add to dashboard Cite

SUMMARYThe Douro Demarcated Region (DDR) is one of the most important winemaking regions in Portugal. Viticulture is historically and culturally tied to the DDR, having a strong impact on the local economy. This mountainous region, characterized by the steep slopes of the Douro Valley, provides a wide range of environmental characteristics for grapevine growth. Different climatic conditions, soil profiles, topography, grapevine varieties and management practices comprise the DDR terroir, resulting in the distinctiveness of the wines produced. In the present study, an assessment of the homogeneous zones of interest for viticultural activities is proposed for the DDR, by integrating different terroir elements (thermal, hydric, soils, topography and vegetation), using state-of-the-art high resolution datasets (1 km) and a large number of variables/indices. A multivariate zoning was carried out using a principal component analysis and a subsequent clustering methodology. A geospatial assessment of the terroir elements was also performed separately for each type of vegetation covering the DDR. The inter-connections of the different terroir elements that exist at a given location, were also innovatively assessed. The zoning may promote a more appropriate selection of vineyard sites, the selection of more locally-adapted varieties and rootstocks and the adoption of appropriate viticultural practices and management planning. After assessing the terroir conditions that exist at the current vineyard locations, possible expansion zones within the DDR were also evaluated. The present study may also be used as an archetypal methodology that can be applied to other winemaking regions worldwide. RESUMOA Região Demarcada do Douro (RDD) é uma das regiões vitivinícolas mais importantes de Portugal. A viticultura está historicamente e culturalmente ligada à RDD, tendo uma importância vital para a economia local. Esta região montanhosa, caracterizada pelas encostas íngremes do vale do Douro, proporciona uma ampla gama de características edafoclimáticas para o crescimento da vinha. Diferentes condições climáticas, perfis de solo, topografia, castas e práticas culturais fazem parte do terroir da RDD, resultando no carácter distintivo dos vinhos aí produzidos. No presente estudo, propõe-se uma avaliação de zonas homogéneas com interesse para as atividades vitivinícolas na RDD, integrando diferentes elementos do terroir (térmico, hídrico, solos, topografia e vegetação), utilizando-se conjuntos de dados de alta resolução (1 km) e um elevado número de variáveis/índices. Foi realizada uma zonagem multivariada com recurso à análise em componentes principais e a uma metodologia de clustering. A avaliação geoespacial dos elementos do terroir foi também realizada separadamente para cada tipo de vegetação existente na RDD. As interconexões entre os diferentes elementos do terroir de um determinado local também foram avaliadas de forma inovadora. Esta zonagem poderá potenciar uma seleção mais adequada de áreas vitícolas, a seleção de castas e p...

show abstract

Deficit irrigation in table grape: eco-physiological basis and potential use to save water and improve quality

Cited by 44 publications

References 147 publications

Modeling Pinot Noir Aroma Profiles Based on Weather and Water Management Information Using Machine Learning Algorithms: A Vertical Vintage Analysis Using Artificial Intelligence

Modeling Pinot Noir Aroma Profiles Based on Weather and Water Management Information Using Machine Learning Algorithms: A Vertical Vintage Analysis Using Artificial Intelligence

Effects of pre and post-veraison water deficit on Vermentino cluster microclimate and berry composition

Multivariate clustering of viticultural terroirs in the Douro winemaking region

Contact Info

Product

Resources

About