Televitis is a R+D+i group of the Institute of Grapevine and Wine Sciences and the University of La Rioja (http://televitis.unirioja.es/en/). Its research activity is focused on precision viticulture and the application of new technologies to vineyard monitoring and plant phenotyping.
Televitis is working on the development of new, non-invasive sensors to monitor key aspects in grapegrowing, such as the yield, grape composition and water status, among others, in fast and non-destructive way.
Among the different non-invasive sensors and technologies used for plant phenotyping and vineyard monitoring, studied and applied by Televitis, can be listed:
• Machine vision
• Multi and hyperspectral sensors
• Chlorophyll-fluorescence sensors
• Thermography
These non-destructive technologies are applied either manual or on-the-go, by installing them in terrestrial and/or aerial vehicles, for vineyard monitoring. In this context it is worth highlighting that Televitis coordinates an European project called VineRobot (www.vinerobot.eu), aimed at developing an autonomous robot with embebed non-invasive sensors, to monitor key parameters of the vineyard.
DIAGO, M.P., FERNANDEZ-NOVALES J., FERNANDES A., MELO-PINTO P., TARDAGUILA, J. (2016) Use of visible and short wave near-infrared hyperspectral imaging to fingerprinting of anthocyanins in intact grape berries (In Press). DOI: 10.1021/acs.jafc.6b01999
DIAGO, M.P., KRASNOW, M., BUBOLA, M., MILLAN, B., TARDAGUILA, J. (2016) Assessment of vineyard canopy porosity using machine vision. American Journal of Enology and Viticulture 67:229-238. DOI: 10.5344/ajev.2015.15037
DIAGO, M.P., REY-CARAMÉS, C., LE MOIGNE, M., FADAILI, E.M., TARDAGUILA, J., CEROVIC, Z.G. (2016) Calibration of non-invasive fluorescence-based sensors for the manual and on-the-go assessment of grapevine vegetative status in the field. Australian Journal of Grape and Wine Research (In Press). doi: 10.1111/ajgw.12228
MILLAN, B., AQUINO, A., DIAGO, M.P., TARDÁGUILA, J. (2016) Image analysis-based modelling for flower number estimation in grapevine Journal of the Science of Food and Agriculture (In Press). DOI: 10.1002/jsfa.7797
GUTIERREZ, S., TARDAGUILA, J., FERNÁNDEZ-NOVALES, J., DIAGO, M.P. (2015) Support vector machine and artificial neural network models for the classification of grapevine varieties using a portable NIR spectrophotometer. PLOS One 10 (11) e0143197. doi:10.1371/journal.pone.0143197
AQUINO, A., MILLAN, B., GASTON, D., DIAGO, M., TARDAGUILA, J., (2015) vitisFlower® Development and testing of a novel android-smartphone application for assessing the number of grapevine flowers per inflorescence using artificial vision techniques. Sensors 15:21204
FERNANDES, A.M., MELO-PINTO, P., MILLAN, B., TARDAGUILA, J., DIAGO, M.P. (2015) Automatic discrimination of grapevine (Vitis vinifera L.) clones using leaves hyperspectral imaging and partial least squares. Journal of Agricultural Science, 153, 03, 455-465. DOI: 10.1017/S0021859614000252
REY-CARAMÉS, C., DIAGO, M.P., MARTIN, M.P., LOBO, A., TARDAGUILA, J. (2015) Using RPAS Multi-Spectral imagery to characterise vigour, leaf development, yield components and berry composition variability within a vineyard. Remote sensing 7, 14458-14481. DIAGO, M.P., SANZ-GARCIA, A., MILLAN, B., BLASCO, J., TARDAGUILA, J. (2014) Assessment of flower number per inflorescence in grapevine by image analysis under field conditions. Journal of the Science of Food and Agriculture, 94(10):1981-1987. DOI: 10.1002/jsfa.6512
BALUJA, J., DIAGO, M.P., BALDA, P., ZORER, R., MEGGIO, F., MORALES, F., TARDAGUILA, J. (2012) Assessment of vineyard water status variability by thermal and multispectral imagery using and unmanned aerial vehicle (UAV). Irrigation Science, 30:511-522.
Universidad de La Rioja: http://televitis.unirioja.es