Appendix 4: Survey methodology
Sampling and data collection
Using the June 2016 Agricultural Census (11) , two samples were drawn representing soft fruit cultivation in Scotland. The first sample was selected from holdings growing soft fruit crops grown in the open (non-protected crops) and the second from holdings growing soft fruit crops in glasshouses or under walk-in plastic structures (protected crops). Protected and non-protected crops are recorded separately in the Agricultural Census. Separate samples were drawn to ensure non-protected crops were not under-represented in the sample; however, pesticide information was collected for all soft fruit crops grown on all holdings
The country was divided into 11 land-use regions ( Figure 41). Each sample was stratified by these land-use regions and according to holding size. The holding size groups were based on the total area of soft fruit crops grown. The sampling fractions used within both regions and size groups were based on the areas of relevant crops grown rather than number of holdings, so that smaller holdings would not dominate the sample.
The survey covered pesticide applications to soft fruit crops where all or the majority of the growing season was in 2016. As well as recording treatments applied directly to the crop, data was also collected on land preparation treatments prior to sowing or planting the crop.
Following an introductory letter and phone call, data were collected by either personal interview during a visit to the holding or during a phone interview or by email. Where necessary, information was also collected from agronomists and contractors. In total, information was collected from 47 holdings growing soft fruit crops ( Table 38). These holdings represent 21 per cent of the total crop area grown.
National pesticide use was estimated by ratio raising. This is a standard statistical technique for producing estimates from a sample. It is the same methodology used by the other UK survey teams and has been used for all historical datasets produced by the Pesticide Survey Unit, allowing comparability over time. The sample data were multiplied by raising factors ( Table 43 & 44). These factors were calculated by comparing the sampled area in each of the two samples to the areas recorded in the Agricultural Census within each region and size group. An adjustment ( Table 44 & 46) was made for each crop within each region by applying the raising factors to the sample area of each crop grown and comparing this with the census area. This adjustment modifies the estimate to take into account differences in composition of crops encountered in the sample and those present in the population. A second adjustment is applied if crops which are present in the population are not encountered in all strata of the sample, this adjustment was not necessary in the 2016 survey. Due to the distribution of soft fruit crops in Scotland the land use regions were amalgamated into three areas before raising for the non-protected sample: the North (Highlands & Islands, Caithness & Orkney, Moray and Aberdeen), Angus (the main fruit growing region in Scotland) and the South (East Fife, Lothian, Central Lowlands, Tweed Valley, Southern Uplands and Solway). Protected Crops were raised at a national level as region has less influence on pesticide use on crops grown in a protected environment.
Figure 41: Land use regions of Scotland (13)
Changes from previous years
There are a number of changes which should be noted when comparing the 2016 data with the previous survey.
As with the previous surveys two samples were drawn in 2016 representing soft fruit cultivation in Scotland. The first sample was selected from holdings growing soft fruit crops grown in the open (non-protected crops) and the second from holdings growing soft fruit crops in glasshouses or under walk-in plastic structures (protected crops). Separate samples were drawn to ensure non-protected crops were not under-represented in the sample. In the previous survey, only information relating to non-protected crops was collected from the non-protected sample and the size group was based on the total area of non-protected crops grown on that holding, likewise for the protected crops in the protected sample. However in the 2016 survey, pesticide information was collected for all soft fruit crops (protected and non-protected) grown on all holdings and the size groups were based on the total soft fruit crop area grown on the holding. Pesticide use is influenced by farm size and basing the size groups on total soft fruit on each holding is the most appropriate method of sample selection.
In 2016,biopesticides have been grouped separately from biological control agents. In previous reports, all biological based pest control was presented under the category of biological control. However, as biopesticides require to be authorised like conventional pesticides, they can have a range of different functions including fungicides and insecticides and their rates of application can be collected, they are now reported separately. Biopesticide values have been re-calculated for the previous reports to allow for accurate comparisons.
The 2016 report contains a number of new data formats to help improve report quality for users. Data relating to the average number of applications for each crop and type of pesticide have been included in Table 1 and Figure 10. Pesticide application timings for each crop have been included in the pesticide usage section. Insecticides, fungicides and herbicides have been classified into groups according to their mode of action in Tables 30- 32. In addition, data on Integrated Pest Management activities (has been collected and are reported in Appendix 6.
Data from the 2014 soft fruit survey and data amalgamated from the 2011 protected edible (5) and 2012 soft fruit (4) surveys are provided for comparison purposes in Table 35. The previous survey in 2014 was the first soft fruit report to include pesticide usage data for crops grown both in the open and under temporary and permanent protection. Non-protected and semi-protected data from the 2012 Soft Fruit Crop survey have been amalgamated with protected data from the 2011 Protected Edible report to allow some longer-term comparisons. It should be noted that there was a number of changes in survey method between these survey years. The changes are fully outlined in Appendix 4 of the 2014 soft fruit survey report (3) .
Finally, the total number of refusals to participate in this voluntary survey (47 per cent) has increased from 32 per cent in 2014. This has resulted in a 2016 sample size 43 per cent lower than the target. It is possible that this decrease in sample size may influence the estimates made in this report, although the very similar relative standard errors for total soft fruit reported between the last two surveys provides some reassurance that the statistical robustness of the data has not been compromised.
Data quality assurance
The dataset undergoes several validation processes as follows; (i) checking for any obvious errors upon data receipt (ii) checking and identifying inconsistencies with use and pesticide approval conditions once entered into the database (iii) 100 per cent checking of data held in the database against the raw data. Where inconsistencies are found these are checked against the records and with the grower if necessary. Additional quality assurance is provided by sending reports for review to members of the Working Party on Pesticide Usage Surveys and other agricultural experts. In addition, the Scottish pesticide survey unit is accredited to ISO 9001:2015. All survey related processes are documented in Standard Operating Procedures ( SOPs) and our output is audited against these SOPs by internal auditors annually and by external auditors every three years.
Main sources of bias
The use of a random stratified sample is an appropriate survey methodology. A stratified random sample, grouped by farm size and region, is used to select holdings used in this survey. Sampling within size groups is based on area rather than numbers of holdings, so that smaller size groups are not over-represented in the sample. The pesticide survey may be subject to measurement bias as it is reliant on farmers/growers recording data accurately. As this survey is not compulsory it may also be subject to non-response bias, as growers on certain farm/holding types may be more likely to respond to the survey than others. Reserve lists of holdings are held for each stratum to allow non-responding holdings to be replaced with similar holdings.
Experience indicates that stratified random sampling, including reserves, coupled with personal interview technique, delivers the highest quality data and minimises non-response bias.
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