Postprint (published version

9The changes in the shape and size of vines during the growing season, requires a 10 continuous adjustment of the applied dose to optimize spray application efficiency. 11Target detection with ultrasonic sensors can be used to adapt the applied dose following 12 the principles of the variable rate technology. A multi-nozzle air blast sprayer was fitted 13 with three ultrasonic sensors and three electro-valves, to modify the flow rate from the 14 nozzles in real time, in relation to the variability of crop width. A constant application 15 rate of 300 l·ha -1 was compared with a variable rate application using the tree row 16 volume principle at a 0.095 l·m -3 canopy. The total flow rate sprayed by the nozzles was 17 modified according to the variations of crop width measured by the ultrasonic sensors. 18On average 58% less liquid was applied compared to the constant rate application, with 19 similar deposition on leaves with both treatments. A detailed analysis of savings 20 indicates differences between the lower, middle and top part of the crop, in accordance 21 with the leaf area distribution with crop height. No significant differences between 22

Canopy characterization is a key factor to improve pesticide application methods in tree crops and vineyards. Development of quick, easy and efficient methods to determine the fundamental parameters used to characterize canopy structure is thus an important need. In this research the use of ultrasonic and LIDAR sensors have been compared with the traditional manual and destructive canopy measurement procedure. For both methods the values of key parameters such as crop height, crop width, crop volume or leaf area have been compared. Obtained results indicate that an ultrasonic sensor is an appropriate tool to determine the average canopy characteristics, while a LIDAR sensor provides more accuracy and detailed information about the canopy. Good correlations have been obtained between crop volume (CVU) values measured with ultrasonic sensors and leaf area index, LAI (R2 = 0.51). A good correlation has also been obtained between the canopy volume measured with ultrasonic and LIDAR sensors (R2 = 0.52). Laser measurements of crop height (CHL) allow one to accurately predict the canopy volume. The proposed new technologies seems very appropriate as complementary tools to improve the efficiency of pesticide applications, although further improvements are still needed.

Estimation of grapevine vigour using mobile proximal sensors can provide an indirect method for determining grape yield and quality. Of the various indexes related to\ud the characteristics of grapevine foliage, the leaf area index (LAI) is probably the most widely used in viticulture. To assess the feasibility of using light detection and ranging (LiDAR) sensors for predicting the LAI, several field trials were performed using a tractormounted LiDAR system. This system measured the crop in a transverse direction along the rows of vines and geometric and structural parameters were computed. The parameters evaluated were the height of the vines (H), the cross-sectional area (A), the canopy volume (V) and the tree area index (TAI). This last parameter was formulated as the ratio of the crop estimated area per unit ground area, using a local Poisson distribution to approximate\ud the laser beam transmission probability within vines. In order to compare the calculated indexes with the actual values of LAI, the scanned vines were defoliated to obtain LAI values for different row sections. Linear regression analysis showed a good correlation (R2 = 0.81) between canopy volume and the measured values of LAI for 1 m long sections.\ud Nevertheless, the best estimation of the LAI was given by the TAI (R2 = 0.92) for the same length, confirming LiDAR sensors as an interesting option for foliage characterization of grapevines. However, current limitations exist related to the complexity of data process and to the need to accumulate a sufficient number of scans to adequately estimate the LAI.Peer ReviewedPostprint (published version

The use of a low-cost tractor-mounted scanning Light Detection and Ranging (LIDAR) system for capable of making non-destructive recordings of tree-row structure in orchards and vineyards is described. Field tests consisted of several LIDAR measurements on both sides of the crop row, before and after defoliation of selected trees. Summary parameters describing the tree-row volume and the total crop surface area viewed by the LIDAR (expressed as a ratio with ground surface area) were derived using a suitable numerical algorithm. The results for apple and pear orchards and a wine producing vineyard were shown to be in reasonable agreement with the results derived from a destructive leaf sampling method. Also, good correlation was found between manual and sensor-based measurements of the vegetative volume of tree-row plantations. The Tree Area Index parameter, TAI, gave the best correlation between destructive and non-destructive (i.e.LIDAR-based) determinants of crop leaf area. The LIDAR system proved to be a powerful technique for low cost, prompt and non-destructive estimates of the volume and leaf-area characteristics of plants.