Lidar vs. test bench for measurement of drift as affected by sprayer type, air flow, nozzle type and density of vine canopy

Transcription

1 14th Workshop on Spray Application Techniques in Fruit Growing Hasselt (Belgium) May 2017 Lidar vs. test bench for measurement of drift as affected by sprayer type, air flow, nozzle type and density of vine canopy Javier Campos 1, Emilio Gil 1, Montserrat Gallart 1, Jordi Llorens 2, Ramón Salcedo 1, Jordi Llop 1 1 Department of Agro Food Engineering and Biotechnology Universitat Politècnica de Catalunya 2 Department of Agricultural and Forest Engineering, Research Group in AgroICT and Precision Agriculture, University of Lleida

2 Objectives Layout of the experiment and spray settings Canopy characterization Results Conclusions

3 Objectives Layout of the experiment and spray settings Canopy characterization Results Conclusions

4 Determine the effect of nozzle type and air assistance on PPP losses trough the last row during a vineyard spray application Evaluate the effect of canopy characteristics on drift reduction depending of different sprayer s settings Evaluate the potential use of LiDAR for estimating drift traversing the canopy

5 Objectives Layout of the experiment and spray settings Canopy characterization Results Conclusions

6 Assays were conducted in two consecutive years Growth stage BBCH 85(late July) with maximum canopy development Two different sprayers were used Different spray adjustments were selected, combining nozzle type and air assistance

7 Low air assistance High air assistance II I II I II I II I II I II I II I II I

8 Sprayer settings during the field trials Sprayer Air flow Pressure Droplet Application rate Nozzle type (n ) m s 1 m 3 h 1 (bar) size (1) L min 1(2) L ha 1 Year 1 Master ,507 ATR yellow (10) 8.0 VF ,507 TVI (10) 8.0 C Master ,959 ATR yellow (10) 8.0 VF ,959 TVI (10) 8.0 C Iris ,423 ATR orange (16) 8.0 VF Year 2 Master ,507 ATR yellow (10) 9.0 VF ,507 TVI (10) 8.0 C Master ,959 ATR yellow (10) 9.0 VF ,959 TVI (10) 8.0 C Iris ,804 ATR yellow (20) 9.0 VF ,804 TVI (20) 8.0 C Iris ,292 ATR yellow (20) 9.0 VF ,202 TVI (20) 8.0 C (1) According to BCPC classification (Doble et al. 1985)(VF: Very Fine; C: Coarse); (2) Flow rate per single nozzle.

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10 ½ row distance 1 x row distance 2 x row distance

11 Year 1 20 m 6.4 m 3.2 m

12 Year 2 20 m 3.2 m 1.6 m

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14 Deposition (on petri dishes) / Application rate factor Normalized Deposition.

15 Air characterization 3D ultrasonic anemometer Gill instruments, Hampshire, United Kingdom)

16 Sprayers settings Air characterization

17 Objectives Layout of the experiment and spray settings Canopy characterization Results Conclusions

18 Electronic canopy characterization LiDAR SICK MS 200

19 Electronic canopy characterization LiDAR SICK LMS 200

20 Canopy characterization with LiDAR Llorens, J., Gil, E., Llop, J., Queraltó, M Georeferenced LiDAR 3D vine plantation map generation. Sensors, 11:

21 Year 1 Year 2 1,6 1,4 LAI 1,4 1,2 1 0,8 0,6 LAI 1,2 1 0,8 0, TRV TRV LWA ,5 9 8,5 8 7,5 7 6,5 6 5,5 5 4,5 4 3,5 3 2,5 2 1,5 1 0,5 ROW DISTANCE (M) LWA ,5 9 8,5 8 7,5 7 6,5 6 5,5 5 4,5 4 3,5 3 2,5 2 1,5 1 0,5 ROW DISTANCE (M) Llorens, J., Gil, E., Llop, J., Queraltó, M Georeferenced LiDAR 3D vine plantation map generation. Sensors, 11:

22 Year 2 1,4 1,2 LAI 1 0,8 0,6 TRV LWA ,5 9 8,5 8 7,5 7 6,5 6 5,5 5 4,5 4 3,5 3 2,5 2 1,5 1 0,5 ROW DISTANCE (M) Llorens, J., Gil, E., Llop, J., Queraltó, M Georeferenced LiDAR 3D vine plantation map generation. Sensors, 11:

23 Objectives Layout of the experiment and spray settings Canopy characterization Results Conclusions

24 Year 1 A (3,2 m) B (6,4 m) V A (3,2 m) B (5,7 m) V A (3,2 m) B (5,7 m) V A (3,2 m) B (5,7 m) V

25 Year 1 Deposition Test Bench and CROP (m 2 vegetation/m)

26 Year 1 Deposition Test Bench and CROP (m 2 vegetation/m) A (3,2 m) B (6,4 m) V

27 Year 2 A (1,6 m) B (3,2 m) V A (1,6 m) B (3,2 m) V A (1,6 m) B (3,2 m) V A (1,6 m) B (3,2 m) V

28 Year 2 Deposition Test Bench and CROP (m 2 vegetation/m)

29 Year 2 A (1,6 m) B (3,2 m) V A (1,6 m) B (3,2 m) V A (1,6 m) B (3,2 m) V A (1,6 m) B (3,2 m) V

30 Year 2 Deposition Test Bench and CROP (m 2 vegetation/m)

31 Air injection Low air Air injection High air Conventional High air

32 Air injection High air Air injection Low air Conventional High air

33 a ab b b a a a a a ab ab b b b a c

34 Gil, E., Llorens, J., Llop, J., Fàbregas, X., Gallart, M Use of a terrestrial LIDAR sensor for drift Detection in vineyard spraying. Sensors, 13:

35 Objectives Layout of the experiment and spray settings Canopy characterization Results Conclusions

36 Conventional mistblower generates much more drift than multi row sprayer Air injection nozzles increases the amount of deposit in the nearest area close to the last row (< 5 m) Large air assistance with conventional nozzles enlarge the contaminated area Air assistance, sprayer type and nozzle type have different effect of drift: sprayer type > air assistance > nozzle type LiDAR allows to estimate/evaluate drift potential, but more research should be applied It seems difficult to quantify the effect of canopy characteristics (density, leaf area ) on the amount of liquid exceeding the last row

37 Thank you very much