The biochemical composition of grape berries depends on the cultivar genome and is influenced by environmental conditions and growing practices, which vary according to origin and "terroir" (French word accounting for the factors of climate, soil, and cultural practices on grape and wine quality). The components currently measured to determine the potential quality of grapes for wine-making at harvest are sugars, acidity, pH, and total phenolics, referred to as "classic analysis". The aim of this work was to establish metabolic profiles using both conventional physicochemical analyses and 1H NMR spectrometry of the skin and pulp of mature berry extracts in order in four appellations situated in different locations in southern-western France (Bordeaux). Principal component analysis was applied to the physiochemical and 1H NMR data to investigate the variability of the grape composition and to characterize groups of samples. A significant clustering of the metabolic profile of pulps or skins in relation to their terroir was observed. Physicochemical analyses were more discriminant than 1H NMR data, but NMR spectroscopy allowed metabolic finger-printings using identified metabolites and some still nonattributed resonances.

Following our previous review on Pinus spp. seed fatty acid (FA) compositions, we recapitulate here the seed FA compositions of Larix (larch), Picea (spruce), and Pseudotsuga (Douglas fir) spp. Numerous seed FA compositions not described earlier are included. Approximately 40% of all Picea taxa and one-third of Larix taxa have been analyzed so far for their seed FA compositions. Qualitatively, the seed FA compositions in the three genera studied here are the same as in Pinus spp., including in particular the same delta5-olefinic acids. However, they display a considerably lower variability in Larix and Picea spp. than in Pinus spp. An assessment of geographical variations in the seed FA composition of P. abies was made, and intraspecific dissimilarities in this species were found to be of considerably smaller amplitude than interspecific dissimilarities among other Picea species. This observation supports the use of seed FA compositions as chemotaxonomic markers, as they practically do not depend on edaphic or climatic conditions. This also shows that Picea spp. are coherently united as a group by their seed FA compositions. This also holds for Larix spp. Despite a close resemblance between Picea and Larix spp. seed FA compositions, principal component analysis indicates that the minor differences in seed FA compositions between the two genera are sufficient to allow a clear-cut individualization of the two genera. In both cases, the main FA is linoleic acid (slightly less than one-half of total FA), followed by pinolenic (5,9,12-18:3) and oleic acids. A maximum of 34% of total delta5-olefinic acids is reached in L. sibirica seeds, which appears to be the highest value found in Pinaceae seed FA. This apparent limit is discussed in terms of regio- and stereospecific distribution of delta5-olefinic acids in seed triacylglycerols. Regarding the single species of Pseudotsuga analyzed so far (P. menziesii), its seed FA composition is quite distinct from that of the other two genera, and in particular, it contains 1.2% of 14-methylhexadecanoic (anteiso-17:0) acid. In the three genera studied here, as well as in most Pinus spp., the C18 delta5-olefinic acids (5,9-18:2 and 5,9,12-18:3 acids) are present in considerably higher amounts than the C20 delta5-olefinic acids (5,11-20:2 and 5,11,14-20:3 acids).

No abstract

No abstract

Field delineation is an essential preliminary step for the design of management maps for grape production. In this paper, we propose a new algorithm for the segmentation of vine fields based on high-resolution remote sensed images. This algorithm takes into account the textural properties of vine images. It leads to the computation of a textural attribute on which a simple thresholding operation allows to discriminate between vine field and non-vine field pixels. The feasibility of the automatic delineation is illustrated on a range of vineyard images with various inter-row distances, grass covers, perspective distortions and side perturbations. In most cases it produces precise delineation of field borders while the parcel under consideration remains separate from the rest of the image.

The seed fatty acid (FA) compositions of Abietoids (Abies, Cedrus, Hesperopeuce, Keteleeria, Pseudolarix, and Tsuga) are reviewed in the present study in conclusion to our survey of Pinaceae seed FA compositions. Many unpublished data are given. Abietoids and Pinoids (Pinus, Larix, Picea, and Pseudotsuga)-constituting the family Pinaceae-are united by the presence of several delta5-olefinic acids, taxoleic (5,9-18:2), pinolenic (5,9,12-18:3), coniferonic (5,9,12,15-1 8:4), keteleeronic (5,11-20:2), and sciadonic (5,11,14-20:3) acids, and of 14-methyl hexadecanoic (anteiso-17:0) acid. These acids seldom occur in angiosperm seeds. The proportions of individual delta5-olefinic acids, however, differ between Pinoids and Abietoids. In the first group, pinolenic acid is much greater than taxoleic acid, whereas in the second group, pinolenic acid is greater than or equal to taxoleic acid. Moreover, taxoleic acid in Abietoids is much greater than taxoleic acid in Pinoids, an apparent limit between the two subfamilies being about 4.5% of that acid relative to total FA. Tsuga spp. appear to be a major exception, as their seed FA compositions are much like those of species from the Pinoid group. In this respect, Hesperopeuce mertensiana, also known as Tsuga mertensiana, has little in common with Abietoids and fits the general FA pattern of Pinoids well. Tsuga spp. and H. mertensiana, from their seed FA compositions, should perhaps be separated from the Abietoid group and their taxonomic position revised. It is suggested that a "Tsugoid" subfamily be created, with seed FA in compliance with the Pinoid pattern and other botanical and immunological criteria of the Abietoid type. All Pinaceae genera, with the exception of Pinus, are quite homogeneous when considering their overall seed FA compositions, including delta5-olefinic acids. In all cases but one (Pinus), variations from one species to another inside a given genus are of small amplitude. Pinus spp., on the other hand, have highly variable levels of delta5-olefinic acids in their FA compositions, particularly when sections (e.g., Cembroides vs. Pinus sections) or subsections (e.g., Flexiles and Cembrae subsections from the section Strobus) are compared, although they show qualitatively the same FA patterns characteristic of Pinoids. Multicomponent analysis of Abietoid seed FA allowed grouping of individual species into genera that coincide with the same genera otherwise characterized by more classical botanical criteria. Our studies exemplify how seed FA compositions, particularly owing to the presence of delta5-olefinic acids, may be useful in sustaining and adding some precision to existing taxonomy of the major family of gymnosperms, Pinaceae.

In the last decades, orientation estimation has often been investigated for instance in the domain of still image analysis for feature extraction [5] or in the context of video stream processing for motion analysis [10] [20] [27]. Applications of orientation estimation vary, for example, from the enhancement of ancient engravings to the analysis of fingerprint images or seismic data [8]. Orientation relates to the direction of the apparent structures in the observed area. At a given location in an image, orientation depends on the size of the observation window, which corresponds to the scale of analysis. Statistical techniques applied to orientation vectors (as for instance PCA [8], Rao's algorithm [5][22] or the tensor-based framework proposed by Knutsson [14]) allow to compute orientations at a large scale from orientations at a local scale. Given the capabilities of such techniques, we focus specifically on local orientation estimation. Local orientation estimation is often based on the computation of local derivatives [6][7][8][17] [22], assuming that orientation is orthogonal to the gradient vector. Nevertheless, gradient based approaches rely on the unicity of orientation at a given point and are not suitable if several orientations occur at a given location. As an illustration, the texture in Fig. 1.a shows two components with different orientations, one at 20° the other one at 60°. The spatial period of both components is 10 pixels. A structure tensor with a computing support size of 55 pixels estimates the main orientation of the texture at approximately 32° (Fig. 1.b). Indeed, this Fig.1

No abstract