Olivier Lavialle

Bio: Olivier Lavialle is an academic researcher from University of Bordeaux. The author has contributed to research in topics: Anisotropic diffusion & Filter (signal processing). The author has an hindex of 17, co-authored 85 publications receiving 960 citations. Previous affiliations of Olivier Lavialle include Total S.A. & Centre national de la recherche scientifique.

1H NMR and chemometrics to characterize mature grape berries in four wine-growing areas in Bordeaux, France.

Abstract: 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 winemaking 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 southernwestern 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 th...

Fatty acid composition of Pinaceae as taxonomic markers.

Abstract: 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 Δ5-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 Δ5-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 Δ5-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 C18Δ5-olefinic acids (5,9-18:2 and 5,9,12-18:3 acids) are present in considerably higher amounts than the C20Δ5-olefinic acids (5,11-20:2 and 5,11,14-20:3 acids).

Delineation of Vine Parcels by Segmentation of High Resolution Remote Sensed Images

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.

Microbial biogeography of wine grapes is conditioned by cultivar, vintage, and climate

Abstract: Wine grapes present a unique biogeography model, wherein microbial biodiversity patterns across viticultural zones not only answer questions of dispersal and community maintenance, they are also an inherent component of the quality, consumer acceptance, and economic appreciation of a culturally important food product. On their journey from the vineyard to the wine bottle, grapes are transformed to wine through microbial activity, with indisputable consequences for wine quality parameters. Wine grapes harbor a wide range of microbes originating from the surrounding environment, many of which are recognized for their role in grapevine health and wine quality. However, determinants of regional wine characteristics have not been identified, but are frequently assumed to stem from viticultural or geological factors alone. This study used a high-throughput, short-amplicon sequencing approach to demonstrate that regional, site-specific, and grape-variety factors shape the fungal and bacterial consortia inhabiting wine-grape surfaces. Furthermore, these microbial assemblages are correlated to specific climatic features, suggesting a link between vineyard environmental conditions and microbial inhabitation patterns. Taken together, these factors shape the unique microbial inputs to regional wine fermentations, posing the existence of nonrandom “microbial terroir” as a determining factor in regional variation among wine grapes.

Path Planning for Autonomous Underwater Vehicles

Abstract: Efficient path-planning algorithms are a crucial issue for modern autonomous underwater vehicles. Classical path-planning algorithms in artificial intelligence are not designed to deal with wide continuous environments prone to currents. We present a novel Fast Marching (FM)-based approach to address the following issues. First, we develop an algorithm we call FM* to efficiently extract a 2-D continuous path from a discrete representation of the environment. Second, we take underwater currents into account thanks to an anisotropic extension of the original FM algorithm. Third, the vehicle turning radius is introduced as a constraint on the optimal path curvature for both isotropic and anisotropic media. Finally, a multiresolution method is introduced to speed up the overall path-planning process

On the stability of linear systems with fractional-order elements

Abstract: Linear integer-order circuits are a narrow subset of rational-order circuits which are in turn a subset of fractional-order. Here, we study the stability of circuits having one fractional element, two fractional elements of the same order or two fractional elements of different order. A general procedure for studying the stability of a system with many fractional elements is also given. It is worth noting that a fractional element is one whose impedance in the complex frequency s-domain is proportional to sα and α is a positive or negative fractional-order. Different transformations and methods will be illustrated via examples.

Associations among Wine Grape Microbiome, Metabolome, and Fermentation Behavior Suggest Microbial Contribution to Regional Wine Characteristics

Abstract: Regionally distinct wine characteristics (terroir) are an important aspect of wine production and consumer appreciation. Microbial activity is an integral part of wine production, and grape and wine microbiota present regionally defined patterns associated with vineyard and climatic conditions, but the degree to which these microbial patterns associate with the chemical composition of wine is unclear. Through a longitudinal survey of over 200 commercial wine fermentations, we demonstrate that both grape microbiota and wine metabolite profiles distinguish viticultural area designations and individual vineyards within Napa and Sonoma Counties, California. Associations among wine microbiota and fermentation characteristics suggest new links between microbiota, fermentation performance, and wine properties. The bacterial and fungal consortia of wine fermentations, composed from vineyard and winery sources, correlate with the chemical composition of the finished wines and predict metabolite abundances in finished wines using machine learning models. The use of postharvest microbiota as an early predictor of wine chemical composition is unprecedented and potentially poses a new paradigm for quality control of agricultural products. These findings add further evidence that microbial activity is associated with wine terroir. IMPORTANCE Wine production is a multi-billion-dollar global industry for which microbial control and wine chemical composition are crucial aspects of quality. Terroir is an important feature of consumer appreciation and wine culture, but the many factors that contribute to terroir are nebulous. We show that grape and wine microbiota exhibit regional patterns that correlate with wine chemical composition, suggesting that the grape microbiome may influence terroir. In addition to enriching our understanding of how growing region and wine properties interact, this may provide further economic incentive for agricultural and enological practices that maintain regional microbial biodiversity.

Weed detection for site-specific weed management: mapping and real-time approaches

Abstract: This work was partially financed by the Spanish Minister of Science and Innovation by project AGL2008-04670-CO3-03 (FEDER).