Journal International des Sciences de la Vigne et du Vin (J INT SCI VIGNE VIN )

Journal description

Discontinued in 1999.

Current impact factor: 0.80

Impact Factor Rankings

2015 Impact Factor Available summer 2015
2013 / 2014 Impact Factor 0.804
2012 Impact Factor 0.83
2011 Impact Factor 1.022
2010 Impact Factor 0.913
2009 Impact Factor 0.771
2008 Impact Factor 0.917
2007 Impact Factor 0.696
2006 Impact Factor 0.404
2005 Impact Factor 0.393
2004 Impact Factor 0.333
2003 Impact Factor 0.432

Impact factor over time

Impact factor
Year

Additional details

5-year impact 1.27
Cited half-life 6.80
Immediacy index 0.15
Eigenfactor 0.00
Article influence 0.38
Website Journal International des Sciences de la Vigne et du Vin website
Other titles Journal international des sciences de la vigne et du vin
ISSN 1151-0285
OCLC 27137513
Material type Periodical
Document type Journal / Magazine / Newspaper

Publications in this journal

  • [Show abstract] [Hide abstract]
    ABSTRACT: Aim: To compare grape yield prediction methods to determine which provides best results with an acceptable error earliest in the growing season. Methods and results: The grape yields predicted by six models - one for use at fruit set (FS), two for use at veraison (V1 and V2), and three for use during the lag phase (LP40, LP50 and LP60) – were compared to field-measured yields. Regressions for the yield predicted by each model were constructed. The V1 and V2 models returned the highest R2 (0.75), efficiency index (EF; 0.67-0.70) and lowest RMSE values (±16-17%, or <0.5 kg per m. of row). The FS model returned the same or similar R2 (59%), EF (0.06) and RMSE (±30%, or <0.83 kg per m. of row) values as the LP models, but allowed yield predictions to be made one month earlier. Conclusion: The validated FS, V1 and V2 models are all useful in predicting grape yields, and could be used to accurately forecast (with different errors) grape yields sooner or later according to winery needs. These models could be improved as further data become available in following seasons. Significance and impact of the study: Few validated models are available for predicting grapevine yields at fruitset and veraison. This study provides predictive models that can be used at these different times of the growth cycle.
    Journal International des Sciences de la Vigne et du Vin 01/2015; 49(1).
  • [Show abstract] [Hide abstract]
    ABSTRACT: Aim: To use Remote Sensing imagery and techniques to differentiate categories of Burgundian vineyards. Methods and results : A sample of 201 vine plots or “climats” from the Côte d’Or region in Burgundy was selected, consisting of three vineyard categories (28 Grand Cru, 74 Premier Cru, and 99 Communale) and two grape varieties (Pinot noir and Chardonnay). A mask formed by the polygons of these vine plots was made and projected on four satellite images acquired by the ASTER sensor, covering the Côte d’Or region in years 2002, 2003 (winter image), 2004 and 2006. Mean reflectances were extracted from pixels within each polygon for each of the nine spectral bands (visible and infrared) covered by ASTER. The database had a total of 797 reflectance spectra assembled over the four images. Statistical discriminant analysis of percentage classification accuracy was made separately for Côte de Nuits and Côte de Beaune, and for each year. Results showed that for individual years and Côtes, classification accuracy for vineyard category was as high as 73.7 % (Beaune 2002) and as low as 66.7 % (Beaune 2003). There were no significant differences in accuracy between spring, summer and winter images. Classification accuracy for grape variety in Côte de Beaune over the four study years was between 73.5 % for Pinot noir climats in 2004 and 91.9 % for Chardonnay climats in 2006, including the winter image. Concerning the vegetation index NDVI, there were no significant differences between vineyard categories. Conclusions : Satellite data is shown to be functional to reveal vineyard quality. Spectral differences between categories of Burgundian vineyards are at least partially due to terroir characteristics, which are transmitted to vine and vine canopy. Significance and impact of the study : This work indicates that Remote Sensing techniques can be used as an auxiliary tool for the monitoring of vineyard quality in established viticultural regions and for the study of quality potential in new regions. Key words : Burgundian climats, Remote Sensing, vineyards spectra, leaf reflectance, satellite images
    Journal International des Sciences de la Vigne et du Vin 12/2014; 48:247.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Aims: To determine the anthocyanin composition in Carignan and Grenache grapes and wines as affected by vintage, plant vigor and bunch uniformity. Methods and results: Anthocyanin composition of Carignan and Grenache grapes and wines were analysed by chromatographic techniques considering the influence of two different vigor levels over two vintages. The heterogeneity in the distal parts of the bunch was also taken into account. Warm vintage was better for the accumulation of anthocyanins. However, each variety responsed differently according to vine vigor. Grenache anthocyanin synthesis decreased in low vigor (weak) vines, whereas Carignan anthocyanin content depended on vigor, berry size, rootstock and vintage. In both varieties, but more significantly in Carignan, there was a tendency to accumulate acylated anthocyanins in bottom berries. Conclusion : Carignan anthocyanin concentration was increased in low vigor plants, where clusters received greater sun exposure, unlike Grenache, where better canopy management in the fruit zone is necessary. Avoiding the poor growing conditions for Grenache in the region and improving the canopy/fruit ratio deserves careful consideration in order to reach optimal anthocyanin content. Significance and impact of the study : Knowledge of anthocyanin accumulation according to both plant vigor and bunch ripeness is of major importance to determine the optimal harvest date for each cultivar and thus improve the quality of wine.
    Journal International des Sciences de la Vigne et du Vin 09/2014; 48(3):201.
  • Journal International des Sciences de la Vigne et du Vin 01/2014;
  • Journal International des Sciences de la Vigne et du Vin 01/2014; 48(4):269-292.
  • [Show abstract] [Hide abstract]
    ABSTRACT: Aims: A water stress index based on a water balance model was tested as a tool for classifying the water stress paths experienced by grapevines in various French Mediterranean vineyards. The relations between the index value and grapevine yield and berry quality (sugars, organic acids, anthocyanins) at harvest were investigated. Methods and results : A data set of 102 situations, each combining one location, one variety, one vintage and one water regime (irrigation or, most often, no irrigation), was collected for the study. The Fraction of Transpirable Soil Water (FTSW) was simulated by a unique-soil-reservoir water balance model at a daily time step. Five classes of water deficit were delimited from specific decreasing thresholds of FTSW over four periods between flowering and harvest. These thresholds were derived from predawn leaf water potential values because over decades, grapegrowers and researchers have shared references and built expertise by using this variable throughout the Mediterranean region. A water stress index resulting from the levels of water deficit reached at each of the four periods of the cycle was calculated. This index was correlated with yield per vine, berry weight, and berry sugar and organic acid contents but not with berry anthocyanin content. Conclusion : A simple water stress index, based on the water balance model, exhibited significant correlations with yield and berry quality for various cultivars and pedo-climatic conditions in Mediterranean vineyards. Significance and impact of the study : This water stress index is a valuable tool for explaining the variations in grape yield and quality of grape among various locations and years because it reflects the vineyard water stress history, in relation to rainfall regime and soil conditions. Improvement would come from the simulation of FTSW during winter, notably for soils of high Total Transpirable Soil Water. One potential application is the quantification of water stress change brought by irrigation in Mediterranean vineyards, and its relation to grapevine production.
    Journal International des Sciences de la Vigne et du Vin 01/2014; 48(1):1-9.