FluorescenceSensor Mapping for the in Vineyard NonDestructive Assessment of Crimson Seedless Table Grape Quality Nondestructive tools for the in situ evaluation of vine fruit quality and vineyard management can improve the market value of table grape. We proposed a new approach based on a portable fluorescence sensor to map the ripening level of Crimson Seedless table grape in five different plots in the East, CentralNorth and South of the Macedonia Region of Greece. The sensor provided indices of ripening and color such as SFRR and ANTHRG correlated to the chlorophyll and anthocyanin berry contents, respectively. The mean ANTHRG index was significantly different among all the plots examined due to the occurrence of different environmental conditions andor asynchronous ripening processes. The indices presented moderate, poor in some cases, spatial variability, probably due to a significant vinetovine, intravine and intrabunch variability. The cluster analysis was applied to the plot with the most evident spatial structure (at Kilkis). Krigged maps of the SFRR, ANTHRG and yield were classified by kmeans clustering in twozones that differed significantly in their mean values. ANTHRG and SFRR were inversely correlated over 64% of the plot. SFRR appeared to be a potential useful proxy of yield since it was directly correlated to yield over 66% of the plot. The grape color (ANTHRG) was slightly higher over the lowyield zones with respect to the highyield zones. Our study showed that the combination of anthocyanins and chlorophyll indices detected in the field on Crimson Seedless table grape by a portable fluorescence sensor can help in defining the best harvest time and the best areas for harvesting.

Monitoring Plant Status and Fertilization Strategy through Multispectral Images A crop monitoring system was developed for the supervision of organic fertilization status on tomato plants at early stages. An automatic and nondestructive approach was used to analyze tomato plants with different levels of watersoluble organic fertilizer (3  5 NK) and vermicompost. The evaluation system was composed by a multispectral camera with five lenses: green (550 nm), red (660 nm), red edge (735 nm), near infrared (790 nm), RGB, and a computational image processing system. The watersoluble fertilizer was applied weekly in four different treatments: (T0: 0 mL, T1: 6.25 mL, T2: 12.5 mL and T3: 25 mL) and the vermicomposting was added in Weeks 1 and 5. The trial was conducted in a greenhouse and 192 images were taken with each lens. A plant segmentation algorithm was developed and several vegetation indices were calculated. On top of calculating indices, multiple morphological features were obtained through image processing techniques. The morphological features were revealed to be more feasible to distinguish between the control and the organic fertilized plants than the vegetation indices. The system was developed in order to be assembled in a precision organic fertilization robotic platform.