Development and first tests of a mobile lab combining optical and analogical sensors for crop monitoring in precision viticulture

Actually Remote-Sensing (RS) is the most widely adopted technique used to realize crop monitoring in Precision Viticulture systems. This paper considers the possibility to integrate RS information obtained by different proximal sensing technologies employed directly in vineyards in order to enable a simultaneous evaluation of canopy health and vigour status. To this aim a mobile lab has been developed; it consists of: (a) a couple of GreenSeeker RT100, a commercial optical device calculating NDVI and Red/NIR indices in real time, (b) three couples of ultrasonic sensors for canopy thickness estimation, (c) a DGPS receiver to geo-reference data collected while travelling in vineyard. During the 2007-2008 campaign, tests were carried out in a commercial vineyard in order to evaluate the monitoring system performance regarding disease appearance and diffusion, and vegetative development variations due to the normal growing process of vine. Surveys with the mobile lab were conducted in two groups of rows, treated and non-treated with agrochemicals and compared to manual morphological and physiological observations that characterized the phytosanitary status of the canopy. Measurements repeatability has been verified; both NDVI values and ultrasonic data showed a high repeatability (with r=0.88 and r=0.85, respectively). Optical data have been processed in order to obtain NDVI maps, which clearly showed differences in canopy vigour evolution in the two examined groups, with low vegetative vigour in areas infected by Plasmopara viticola, as confirmed by manual assessment. Maps of Percentage Infection Index (PII) have been produced according to pathological manual survey results. The comparison between PII and NDVI maps confirmed qualitatively the real vine phytosanitary status. Ultrasonically measured Canopy Thickness (UCT) has been calculated and compared to Manually measured Canopy Thickness (MCT) (r=0.78). UCT and NDVI values have been compared in order to allow the identification of areas infested by disease among zones presenting critical vegetation conditions.