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

Javier Campos1, Emilio Gil1, Montserrat Gallart1, Jordi Llorens2, Ramón Salcedo1, Jordi Llop1

1 Department of Agro Food Engineering and Biotechnology Universitat Politècnica de Catalunya2 Department of Agricultural and Forest Engineering, Research Group in AgroICT and Precision Agriculture, University of Lleida

14th Workshop on Spray Application Techniques in Fruit Growing – Hasselt (Belgium) May 2017


Objectives

Layout of the experiment and spray settings

Canopy characterization

Results

Conclusions


Determine the effect of nozzle type and air assistance on PPP lossestrough the last row during a vineyard spray application

Evaluate the effect of canopy characteristics on drift reduction dependingof different sprayer’s settings

Evaluate the potential use of LiDAR for estimating drift traversing thecanopy


Objectives



Results

Conclusions


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


III

III III

III

III

III III

III

Low air assistance High air assistance


SprayerAir flow

Nozzle type (n°) Pressure (bar)

Droplet size(1)

Application rate

m∙s−1 m3∙h−1 L∙min−1(2) L∙ha−1

Year 1

Master 2000 24.427,507 ATR yellow (10) 8.0 VF 0.92 369

27,507 TVI 80015 (10) 8.0 C 0.98 393

Master 2000 31.134,959 ATR yellow (10) 8.0 VF 0.92 369

34,959 TVI 80015 (10) 8.0 C 0.98 393Iris‐2 14.6 6,423 ATR orange (16) 8.0 VF 1.24 398

Year 2Master 2000 24.4 27,507 ATR yellow (10) 9.0 VF 0.97 413

27,507 TVI 80015 (10) 8.0 C 0.98 418Master 2000 31.1 34,959 ATR yellow (10) 9.0 VF 0.97 413

34,959 TVI 80015 (10) 8.0 C 0.98 418

Iris‐2 15.1 7,804 ATR yellow (20) 9.0 VF 0.97 4137,804 TVI 80015 (20) 8.0 C 0.98 418

Iris‐2 17.5 9,292 ATR yellow (20) 9.0 VF 0.97 4139,202 TVI 80015 (20) 8.0 C 0.98 418

Sprayer settings during the field trials

(1) According to BCPC classification (Doble et al. 1985)(VF: Very Fine; C: Coarse); (2) Flow rate per single nozzle.


½ row distance1 x row distance2 x row distance


3.2 m

6.4 m

Year 1

20 m


1.6 m

3.2 m

Year 2

20 m


Deposition (on petri dishes)

/

Application rate factor

Normalized Deposition.


Air characterization

3D ultrasonic anemometerGill instruments, Hampshire, United Kingdom)


Sprayers settings – Air characterization


Objectives



Results

Conclusions


Electronic canopy characterizationLiDAR SICK MS 200


Electronic canopy characterizationLiDAR SICK LMS 200


Canopy characterization with LiDAR

Llorens, J., Gil, E., Llop, J., Queraltó, M. 2011. Georeferenced LiDAR 3D vine plantation map generation. Sensors, 11:6237-6256.


0,60,81

1,21,41,6

LAI

0

2000

4000

6000

TRV

0250050007500

10000

10 9,5 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

LWA

ROW DISTANCE (M)

Year 1


0,6

0,8

1

1,2

1,4

LAI

0

2000

4000

6000

TRV

0250050007500

10000

10 9,5 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

LWA

ROW DISTANCE (M)

Year 2


0,6

0,8

1

1,2

1,4

LAI

0

2000

4000

6000

TRV

0250050007500

10000

10 9,5 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

LWA

ROW DISTANCE (M)

Year 2



Objectives



Results

Conclusions


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


Year 1

Deposition Test Bench and CROP (m2 vegetation/m)


A (3,2 m) B (6,4 m) V

Year 1



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


Year 2



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


Year 2



Air injectio

n –High

air

Air injectio

n –Low air

Conven

tiona

l –High

air


Air injection – Low air

Conventional – High air

Air injection – High air


a ab b b

a ab ab b

a a a a

b b a c


Gil, E., Llorens, J., Llop, J., Fàbregas, X., Gallart, M. 2013. Use of a terrestrial LIDAR sensor fordrift Detection in vineyard spraying. Sensors, 13: 516-534.


Objectives



Results

Conclusions


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


Thank you very much

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