Euclidean Supersymmetry, Twisting and Topological Sigma Models

We discuss two dimensional N-extended supersymmetry in Euclidean signature and its R-symmetry. For N=2, the R-symmetry is SO(2)\times SO(1,1), so that only an A-twist is possible. To formulate a B-twist, or to construct Euclidean N=2 models with H-flux so that the target geometry is generalised Kahler, it is necessary to work with a complexification of the sigma models. These issues are related to the obstructions to the existence of non-trivial twisted chiral superfields in Euclidean superspace.Comment: 8 page

Leaf morphoanatomy of four red grapevine cultivars grown under the same terroir

XII Congreso Internacional TerroirThis study compare leaf morphoanatomical characteristics of four red cultivars - ‘Touriga Nacional’, ‘Trindadeira’, ‘Cabernet Sauvignon’ and ‘Syrah’ -, grown side by side at the same terroir. The analyzed leaf traits, under light and scanning electron microscopy, showed large variability among genotypes. ‘Trincadeira’ has the biggest single leaf area and ‘Cabernet Sauvignon’ the smallest one. ‘Touriga Nacional’ showed the lowest leaf dry weight and ‘Trincadeira’ the highest one, nonetheless there was no significantly differences in leaf dry mass per area and in leaf density. Leaf dry mass per area was positively correlated with leaf density but showed no correlation with leaf thickness. The French genotypes presented higher thickness of the leaf anatomical traits than the two Portuguese ones. ‘Trincadeira’ showed significantly highest stomata density while the other cultivars showed no significant differences among them. The analyses of the three types of stomata revealed that ‘Trincadeira’ has the lower percentage of raised above and the highest percentage of sunken stomata while ‘Cabernet Sauvignon’ showed the opposite behaviour. The hairs on the lower surface presented a similar woolly aspect in all cultivars. The possible role of leaf morphoanatomical characteristics in determining the cultivars adaptation to abiotic stresses is suggested and discussedinfo:eu-repo/semantics/publishedVersio

Anatomia da folha de cultivares brancas de videira com distinta origem geográfica

This study aims to compare the leaf morphoanatomical characteristics of seven Vitis vinifera subsp. vinifera white cultivars with different geographical origin, grown side by side at the same “terroir”. The leaf morphoanatomical traits analyzed under light and scanning electron microscopy (SEM) showed large variability among genotypes. Significant differences between cultivars were observed in single leaf area, specific leaf area, leaf density and in the thickness of cuticle, upper and lower epidermal cells and mesophyll. Leaf dry mass per area presented a significant positive correlation with leaf density but showed no correlation with leaf thickness, results that can be explained by the quite different mesophyll structure, epidermal cells and cuticle thickness. ‘Alvarinho’, ‘Encruzado’, ‘Macabeu’ and ‘Viosinho’ were the cultivars with the highest thickness of cuticle and mesophyll tissues. Under SEM magnification three types of stomata were identified: sunken, at the same level and raised above, with the same level type presenting the higher percentage in all cultivars. Stomata density presented significant differences between cultivars, with ‘Macabeu’ showing the highest value and ‘Alvarinho’ and ‘Arinto’ the lowest ones. The hairs on the lower surface presented a similar woolly aspect in all cultivars. Calcium oxalate crystals, raphids and druses were visible and widely distributed in the parenchyma tissues. The observed differences in leaf traits among genotypes suggest a major role of leaf anatomy in determining grapevine capacity for coping with different environmental conditionsinfo:eu-repo/semantics/publishedVersio

Overcoming the challenge of bunch occlusion by leaves for vineyard yield estimation using image analysis

Accurate yield estimation is of utmost importance for the entire grape and wine production chain, yet it remains an extremely challenging process due to high spatial and temporal variability in vineyards. Recent research has focused on using image analysis for vineyard yield estimation, with one of the major obstacles being the high degree of occlusion of bunches by leaves. This work uses canopy features obtained from 2D images (canopy porosity and visible bunch area) as proxies for estimating the proportion of occluded bunches by leaves to enable automatic yield estimation on non-disturbed canopies. Data was collected from three grapevine varieties, and images were captured from 1 m segments at two phenological stages (veraison and full maturation) in non-defoliated and partially defoliated vines. Visible bunches (bunch exposure; BE) varied between 16 and 64 %. This percentage was estimated using a multiple regression model that includes canopy porosity and visible bunch area as predictors, yielding a R2 between 0.70 and 0.84 on a training set composed of 70 % of all data, showing an explanatory power 10 to 43 % higher than when using the predictors individually. A model based on the combined data set (all varieties and phenological stages) was selected for BE estimation, achieving a R2 = 0.80 on the validation set. This model did not show validation metrics differences when applied on data collected at veraison or full maturation, suggesting that BE can be accurately estimated at any stage. Bunch exposure was then used to estimate total bunch area (tBA), showing low errors (< 10 %) except for the variety Arinto, which presents specific morphological traits such as large leaves and bunches. Finally, yield estimation computed from estimated tBA presented a very low error (0.2 %) on the validation data set with pooled data. However, when performed on every single variety, the simplified approach of area-to-mass conversion was less accurate for the variety Syrah. The method demonstrated in this work is an important step towards a fully automated non-invasive yield estimation approach, as it offers a solution to estimate bunches that are not visible to imaging sensorsinfo:eu-repo/semantics/publishedVersio

Yield components detection and image-based indicators for non-invasive grapevine yield prediction at different phenological phases

Forecasting vineyard yield with accuracy is one of the most important trends of research in viticulture today. Conventional methods for yield forecasting are manual, require a lot of labour and resources and are often destructive. Recently, image-analysis approaches have been explored to address this issue. Many of these approaches encompass cameras deployed on ground platforms that collect images in proximal range, on-the-go. As the platform moves, yield components and other image-based indicators are detected and counted to perform yield estimations. However, in most situations, when image acquisition is done in non-disturbed canopies, a high fraction of yield components is occluded. The present work’s goal is twofold. Firstly, to evaluate yield components’ visibility in natural conditions throughout the grapevine’s phenological stages. Secondly, to explore single bunch images taken in lab conditions to obtain the best visible bunch attributes to use as yield indicators. In three vineyard plots of red (Syrah) and white varieties (Arinto and Encruzado), several canopy 1 m segments were imaged using the robotic platform Vinbot. Images were collected from winter bud stage until harvest and yield components were counted in the images as well as in the field. At pea-sized berries, veraison and full maturation stages, a bunch sample was collected and brought to lab conditions for detailed assessments at a bunch scale. At early stages, all varieties showed good visibility of spurs and shoots, however, the number of shoots was only highly and significantly correlated with the yield for the variety Syrah. Inflorescence and bunch occlusion reached high percentages, above 50 %. In lab conditions, among the several bunch attributes studied, bunch volume and bunch projected area showed the highest correlation coefficients with yield. In field conditions, using non-defoliated vines, the bunch projected area of visible bunches presented high and significant correlation coefficients with yield, regardless of the fruit’s occlusion. Our results show that counting yield components with image analysis in non-defoliated vines may be insufficient for accurate yield estimation. On the other hand, using bunch projected area as a predictor can be the best option to achieve that goal, even with high levels of occlusioninfo:eu-repo/semantics/publishedVersio

Nonlinear atom optics and bright gap soliton generation in finite optical lattices

We theoretically investigate the transmission dynamics of coherent matter wave pulses across finite optical lattices in both the linear and the nonlinear regimes. The shape and the intensity of the transmitted pulse are found to strongly depend on the parameters of the incident pulse, in particular its velocity and density: a clear physical picture for the main features observed in the numerical simulations is given in terms of the atomic band dispersion in the periodic potential of the optical lattice. Signatures of nonlinear effects due the atom-atom interaction are discussed in detail, such as atom optical limiting and atom optical bistability. For positive scattering lengths, matter waves propagating close to the top of the valence band are shown to be subject to modulational instability. A new scheme for the experimental generation of narrow bright gap solitons from a wide Bose-Einstein condensate is proposed: the modulational instability is seeded in a controlled way starting from the strongly modulated density profile of a standing matter wave and the solitonic nature of the generated pulses is checked from their shape and their collisional properties

Tempranillo physiological and agronomical responses to heat and drought stress – perspectives on its vulnerability under climate change scenarios

With the aim to characterize the ability of Tempranillo grapevines, one of the most widely used varieties in Spain and Portugal, to withstand drought and heat stress, ecophysiological and agronomical data from irrigation experiments conducted in the hot and dry region of Alentejo, south of Portugal, are presented. The impact of different irrigation treatments on physiological parameters (leaf water potential, photosynthesis, and stomatal conductance) and water use efficiency are showed. Leaf senescence observed in non-irrigated and deficit irrigated plants and its consequences on cluster exposure and berry temperature are compared with those of fully irrigated plants. The consequences on berry ripening and juice composition are discussed in order to evaluate the vulnerability of Tempranillo to the expected global climatic changeinfo:eu-repo/semantics/publishedVersio