Monitoring and Mapping Vineyard Water Status Using Non-Invasive Technologies by a Ground Robot

[EN] There is a growing need to provide support and applicable tools to farmers and the agro-industry in order to move from their traditional water status monitoring and high-water-demand cropping and irrigation practices to modern, more precise, reduced-demand systems and technologies. In precision viticulture, very few approaches with ground robots have served as moving platforms for carrying non-invasive sensors to deliver field maps that help growers in decision making. The goal of this work is to demonstrate the capability of the VineScout (developed in the context of a H2020 EU project), a ground robot designed to assess and map vineyard water status using thermal infrared radiometry in commercial vineyards. The trials were carried out in Douro Superior (Portugal) under different irrigation treatments during seasons 2019 and 2020. Grapevines of Vitis vinifera L. Touriga Nacional were monitored at different timings of the day using leaf water potential (psi(l)) as reference indicators of plant water status. Grapevines' canopy temperature (T-c) values, recorded with an infrared radiometer, as well as data acquired with an environmental sensor (T-air, RH, and AP) and NDVI measurements collected with a multispectral sensor were automatically saved in the computer of the autonomous robot to assess and map the spatial variability of a commercial vineyard water status. Calibration and prediction models were performed using Partial Least Squares (PLS) regression. The best prediction models for grapevine water status yielded a determination coefficient of cross-validation (r(cv)(2)) of 0.57 in the morning time and a r(cv)(2) of 0.42 in the midday. The root mean square error of cross-validation (RMSEcv) was 0.191 MPa and 0.139 MPa at morning and midday, respectively. Spatial-temporal variation maps were developed at two different times of the day to illustrate the capability to monitor the grapevine water status in order to reduce the consumption of water, implementing appropriate irrigation strategies and increase the efficiency in the real time vineyard management. The promising outcomes gathered with the VineScout using different sensors based on thermography, multispectral imaging and environmental data disclose the need for further studies considering new variables related with the plant water status, and more grapevine cultivars, seasons and locations to improve the accuracy, robustness and reliability of the predictive models, in the context of precision and sustainable viticulture.This research was funded by the European Union under grant agreement number 737669 (Vinescout project).Fernández-Novales, J.; Saiz Rubio, V.; Barrio, I.; Rovira Más, F.; Cuenca-Cuenca, A.; Alves, FS.; Valente, J.... (2021). Monitoring and Mapping Vineyard Water Status Using Non-Invasive Technologies by a Ground Robot. Remote Sensing. 13(14):1-20. https://doi.org/10.3390/rs13142830120131

La Universidad de Burgos a la Catedral de Burgos en su VIII Centenario

La Universidad de Burgos se ha sumado a la celebración del VIII Centenario de la Catedral de Burgos con esta monografía sobre la investigación, la gestión y la difusión que, desde nuestra institución y hasta la fecha, se ha hecho en torno a dicha basílica. Así, se aúnan los testimonios científicos y/o personales de personal docente e investigador, de administración y servicios y de estudiantes y compendia la producción bibliográfica de quienes, a lo largo de la historia de la UBU, han contribuido al conocimiento de la seo. Todo ello es fruto de la participación voluntaria de quienes han querido contribuir a esta edición

Dietary inflammatory index and all-cause mortality in large cohorts: The SUN and PREDIMED studies

[Background]: Inflammation is known to be related to the leading causes of death including cardiovascular disease, several types of cancer, obesity, type 2 diabetes, depression-suicide and other chronic diseases. In the context of whole dietary patterns, the Dietary Inflammatory Index (DII®) was developed to appraise the inflammatory potential of the diet. [Objective]: We prospectively assessed the association between DII scores and all-cause mortality in two large Spanish cohorts and valuated the consistency of findings across these two cohorts and results published based on other cohorts.[Design]: We assessed 18,566 participants in the “Seguimiento Universidad de Navarra” (SUN) cohort followed-up during 188,891 person-years and 6790 participants in the “PREvencion con DIeta MEDiterránea” (PREDIMED) randomized trial representing 30,233 person-years of follow-up. DII scores were calculated in both cohorts from validated FFQs. Higher DII scores corresponded to more proinflammatory diets. A total of 230 and 302 deaths occurred in SUN and PREDIMED, respectively. In a random-effect meta-analysis we included 12 prospective studies (SUN, PREDIMED and 10 additional studies) that assessed the association between DII scores and all-cause mortality.[Results]: After adjusting for a wide array of potential confounders, the comparison between extreme quartiles of the DII showed a positive and significant association with all-cause mortality in both the SUN (hazard ratio [HR] = 1.85; 95% CI: 1.15, 2.98; P-trend = 0.004) and the PREDIMED cohort (HR = 1.42; 95% CI: 1.00, 2.02; P-trend = 0.009). In the meta-analysis of 12 cohorts, the DII was significantly associated with an increase of 23% in all-cause mortality (95% CI: 16%–32%, for the highest vs lowest category of DII).[Conclusion]: Our results provide strong and consistent support for the hypothesis that a pro-inflammatory diet is associated with increased all-cause mortality. The SUN cohort and PREDIMED trial were registered at clinicaltrials.gov as NCT02669602 and at isrctn.com as ISRCTN35739639, respectively.Supported by the official funding agency for biomedical research of the Spanish Government, Instituto de Salud Carlos III (ISCIII), through grants provided to research networks specifically developed for the trial (RTIC G03/140, to R.E.; RTIC RD 06/0045, to Miguel A. Martínez-González) and through Centro de Investigación Biomédica en Red de Fisiopatología de la Obesidad y Nutrición (CIBERobn), and by grants from Centro Nacional de Investigaciones Cardiovasculares (CNIC 06/2007), Fondo de Investigación Sanitaria–Fondo Europeo de Desarrollo Regional (Proyecto de Investigación (PI) 04-2239, PI 05/2584, CP06/00100, PI07/0240, PI07/1138, PI07/0954, PI 07/0473, PI10/01407, PI10/02658, PI11/01647, P11/02505, PI13/00462, PI13/00615, PI13/01090, PI14/01668, PI14/01798, PI14/01764), Ministerio de Ciencia e Innovación (Recursos y teconologia agroalimentarias(AGL)-2009-13906-C02 and AGL2010-22319-C03 and AGL2013-49083-C3-1- R), Fundación Mapfre 2010, the Consejería de Salud de la Junta de Andalucía (PI0105/2007), the Public Health Division of the Department of Health of the Autonomous Government of Catalonia, Generalitat Valenciana (Generalitat Valenciana Ayuda Complementaria (GVACOMP) 06109, GVACOMP2010-181, GVACOMP2011-151), Conselleria de Sanitat y, PI14/01764 AP; Atención Primaria (CS) 2010-AP-111, and CS2011-AP-042), and Regional Government of Navarra (P27/2011).). Drs. Shivappa and Hébert were supported by grant number R44DK103377 from the United States National Institute of Diabetes and Digestive and Kidney Diseases