Pesticide Usage in Scotland: Outdoor Vegetable Crops 2017

Appendix 4 – Survey methodology

Sampling and data collection

Using the June 2017 Agricultural Census ⁽¹¹⁾, a sample was drawn representing vegetable cultivation in Scotland. The first sample was selected from holdings growing any vegetable crops excluding vining peas, and the second from holdings known to have grown vining peas. Two samples were taken to achieve a better representation of all vegetable crops, as most vining pea crops are grown on farms growing arable crops rather than vegetable crops.

The country was divided into 11 land-use regions (Figure 25). 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 either vegetable or vining peas 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 vegetable crops where all or the majority of the growing season was in 2017. 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 during a phone interview or by email. Where necessary, information was also collected from agronomists and contractors. In total, information was collected from 53 holdings growing vegetable crops and 31 holdings growing only peas (Tables 22 & 23). These 84 holdings represent 11 per cent of the total crop area grown.

Raising factors

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 (Tables 28 & 29). These factors were calculated by comparing the sampled area to the areas recorded in the Agricultural Census within each region and size group. An adjustment (Table 30) 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 was necessary for some crops which were present in the population, but were not encountered in the sample in some strata.

Figure 25 Land use regions of Scotland ⁽¹²⁾

Changes from previous years

There are a number of changes which should be noted when comparing the 2017 data with the previous survey.

The areas and weights treated with individual active substances are no longer included at crop level in this report. These data are now published separately as supplementary tables in Excel format to allow continued user access to the full dataset. In this report, the areas treated and weights of pesticide formulations (mixture of active substances in a product) by crop are presented in Tables 2-13 and summary active substance data are presented in Tables 15 to 20. The aim of this change is to focus on the key metrics at crop level and reduce the size of the published report. This approach is consistent with the output from the other UK pesticide survey teams.

For the first time, Brussels sprouts have been included in the ‘other brassica’ category. This is due to too few crops being encountered in the holdings sampled in 2017 to adequately represent usage. This must be taken into account when comparing other brassica data between surveys.

The previous report contained information about grower adoption of Integrated Pest Management ( IPM). IPM data was not collected during the 2017 survey. It is anticipated that IPM data will be collected and published every 4 years. This allows IPM uptake to be monitored over time but reduces the burden on, growers and surveyors.

It should also be noted that the total number of refusals to participate in this voluntary survey increased from 18 per cent in 2015 to 33 per cent in 2017. This has resulted in a 2017 sample size 12 per cent lower than target. This trend in decreased participation has been noted in our surveys in all crop sectors and it is possible that reduced sample size has influenced the estimates made in this report (please refer to appendix 5).

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 9001:2008. 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 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.