For many of the pesticides, the label recommended range of application volumes is held in the pesticide database. The system retrieves this information and displays it to the screen. The range of volumes for the tank mix is calculated as the intersection of the component volume ranges and is displayed to the user in an editable form. A range of suitable flow rates are derived using the equation
f = (v s d ) / 600, (2)
where f is nozzle flow rate (litres min-1), v is application volume (litres ha-1), s is forward speed (km h-1) and d (m) is nozzle spacing on the boom. Default values of 12 km/h speed and 0.5 m nozzle spacing are assigned, although the user can alter both.
Retrieving Nozzles from the database of manufacturer nozzles
Once nozzle type and desired flow rate have been decided the user can select a suitable nozzle from a manufacturer’s catalogue. Alternatively, the system offers information on nozzles from a limited number of manufacturers. The information is stored in a database and includes the name of the nozzle, the ISO classification, minimum (Pm) and maximum allowable pressures, minimum flow rate (fm), and lowest and highest pressures at which the nozzles can attain a given spray quality class. From this information all viable flow rates for a given spray quality can be calculated using the interpolation formulae
m
m
P
P
f
f
=
/
(3)where fis the flow rate defined to occur at pressure P and fm is the flow rate defined to occur at pressure Pm. The system uses database queries to retrieve all the nozzles in the database of the user specified type that operate within the defined flow rate. The system displays the nozzle types along with a recommended pressure, application volume and speed to the user. The pressure is rounded to the accuracy of the user’s pressure gauge and the volume is adjusted to compensate.
Results
To illustrate the result of using the system we consider the example of an application of the herbicide Panther (isoproturon + diflufenican) (Bayer Crop Science) applied on 15 November. The output from WMSS tells the spray nozzle system that the crop is winter wheat and that the weeds the user is concerned with are Alopecurus myosuroides (black-grass), a grass weed, and Stellaria media (chickweed), a broad-leaved weed. At the time of the spray application the estimated crop growth stage is Zadoks 11 (Zadoks et al, 1974) and the estimated growth stages for black-grass and chickweed are Zadoks 11 and over 4 leaves respectively. At these growth stages black-grass is considered resistant to Panther and chickweed sensitive. The data on Panther in the database specifies that it should be applied with a medium spray, that the main mode of action is foliage acting, and that does not contain any actives that would suggest it were non-selective. Therefore the system deduces that the spray is targeting chickweed at a 2-5 cm across (see Table 1.) This defines the target problem. Using equation 1 the system evaluates each of the nozzles and ranks them according to score. The system output is shown in Fig. 1. The screen shows the assumptions made about the desired spray quality and target problem. If the efficacy/drift slider bar is moved the ranking of the nozzles changes. Fig. 2 shows the affect of moving the slider bar on the preference ordering of the suitable nozzles.
The second step in the calculation is to evaluate the flow rate range. Information retrieved from the database states that the range of application volumes should lay between 200 – 400 litres ha-1. With default nozzle spacing and forward speed the range of flow rate is 2.0 – 4.0 litres min-1. Now that suitable nozzle types and a range of application volumes are defined a manufacturer’s nozzle can be selected. The results for air induction type nozzles are shown in Fig. 3.
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Figure 1. The spray nozzle selection system main screen.
0 5
0 0.5 1 1.5 2
relative preference for efficacy and drift (p)
Figure 2. The affect of changing the drift/efficacy priority on nozzle ranking. The x- axis is the slider position with the far left indicating a high preference for efficacy and the far right a preference for drift. The y – axis is the nozzle score. Air induction , low drift flat fan …, low drift deflector - -, conventional flat fan x x.
Figure 3. A list of air induction nozzles from different manufacturers with suggested pressure, application volume and forward speed.
Discussion
The spray nozzle selection program aims to give decision support as to which spray nozzles and application volumes are suitable for a given tank mix of pesticides. It allows the user to explore which nozzles are more appropriate when considering a balance of drift control and efficacy. Decision support systems are not designed to make an absolute decision, but instead they collate and process relevant information and interpret and communicate a range of suitable options to be used in the decision making process.
Although designed to interface with WMSS it was straightforward to include nozzle selection rules relating to fungicides and insecticides as well. Therefore the programme has been written in such a way that it could interface with any pesticide selection DESSAC module. The system illustrates the potential value of infrastructures such as the one provided by DESSAC as it shows how simple systems can be produced to process extensive data and provide information to the user in a comprehensive way. It would take a lot longer for the user to lookup relevant information in catalogues and charts and make a decision than it would to run the system. The speed and ease with which the system provides the user with the information they need to make a decision should improve decision-making. Systems such as the one discussed here could play an important role in the transfer of knowledge on the importance of nozzle selection to the end user.
Acknowledgements
We would like to thank the HGCA for sponsoring this student bursary project, which is associated with WMSS (a Defra - through Sustainable Arable LINK project). We would also like to thank the following people for their support and advice during the project: Clare Butler Ellis, David Parsons, Dave Wilkinson (SRI), Peter Lutman, Jonathan Storkey, Laurence Benjamin (Rothamsted Research), James Clarke, Lynn Collings, Denise Ginsburg (ADAS), Ken Davies (SAC), Caroline Parker, Caroline Park (Glasgow Caledonian). We are also grateful to Syngenta, Dow AgroSciences, DuPont, Bayer CropScience and BASF.
References
Brooks D H, 1998. A Decision Support System for Arable Crops (DESSAC): an integrated approach to decision support. Proceedings BCPC Conference – Pests & Diseases, pp. 239-245. Collings LV, Ginsburg D, Clarke, J H, Milne A, Parsons, D J, Wilkinson, D J, Benjamin L, Mayes A,
Lutman P J, Davies D H K, 2003. WMSS: Improving the precision and prediction of weed management strategies in winter dominant rotations. Accepted for BCPC, Nov 2003
HGCA. 2002. Nozzle selection chart, HGCA, Caledonia House, 223 Pentonville Road, London N1 9HJ
Miller P C H, Butler Ellis M C, Gilbert A J. 2002. Extended the international (BCPC) spray classification. Aspects of Applied Biology 66, International Advances in Pesticide Application, pp. 17-24.
Parker C G. 1999. Decision Support Systems: Lessons from past failures. Farm Management 10: 273-289.
Southcombe E S E, Miller P C H, Ganzelmeier H, Van De Zande J C, Miralles A, Hewitt A J. 1997. The international (BCPC) spray classification system including drift potential factor. Proceedings BCPC Conference – Weeds, pp. 371-379.
Zadoks J C, Chang T T, Konzak C F. 1974. A decimal code for the growth stages of cereals. Weed Research 14: 415-421