Pesticide use in agriculture (aei_pestuse)

National Reference Metadata in ESS Standard for Quality Reports Structure (ESQRS)

Compiling agency: Department of Agriculture Food and the Marine


Eurostat metadata
Reference metadata
1. Contact
2. Statistical presentation
3. Statistical processing
4. Quality management
5. Relevance
6. Accuracy and reliability
7. Timeliness and punctuality
8. Coherence and comparability
9. Accessibility and clarity
10. Cost and Burden
11. Confidentiality
12. Comment
Related Metadata
Annexes (including footnotes)
 



For any question on data and metadata, please contact: EUROPEAN STATISTICAL DATA SUPPORT

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1. Contact Top
1.1. Contact organisation

Department of Agriculture Food and the Marine

1.2. Contact organisation unit

  Pesticide Controls Division

1.5. Contact mail address

James Quirke, Pesticide Controls Division, Department of Agriculture, Food and Marine, Backweston Campus, Celbridge, Co Kildare, Ireland


2. Statistical presentation Top

This report addresses and details pesticide usage surveys carried out as follows:

Outdoor Vegetable crops pesticide usage survey 2015,

Protected Vegetable crops pesticide usage survey 2015,

Arable crops pesticide usage survey 2016,

Grassland & fodder crops pesticide usage survey 2017,

Top fruit pesticide usage survey 2018

Soft fruit pesticide usage survey 2018.

2.1. Data description

See sub-categories below.

2.1.1. Main characteristics of statistics

The outdoor vegetable survey (2015) was conducted  when a sample of 79 growers were statistically selected  and due to a weighting in the selection procedure towards larger farms the sample covered 61% of the total area of vegetbles grown in Ireland. Once the population  was defined and sample selected, the  surveyors were trained on how to collect the data and data was collected by pre-arranged  on farm visit. Data is inputted into excel specifically designed spreadsheets . Once all data is inputted it is checked and validated and then forwarded to biometrics unit for statistical analysis.

The protected vegetable survey (2015) was conducted  when a sample of 30 growers were statistically selected  and due to a weighting in the selection procedure towards larger farms the sample covered 67% of the total area of vegetables grown in Ireland. Once  the population  was defined and sample selected the  surveyors were trained on how to collect the data and data was collected by pre-arranged  on farm visit. Data is inputted into excel specifically designed spreadsheets . Once all data is inputted it is checked and validated and then forwarded to biometrics unit for statistical analysis.

Regarding the Arable crops survey (2016) a sample of 260 growers were statistically selected  and due to a weighting in the selection procedure towards larger farms the sample covered 7.58% of the total area. Once  the population  was defined and sample selected the  surveyors were trained on how to collect the data and data was collected by pre-arranged  on farm visit. Data is inputted into excel specifically designed spreadsheets . Once all data is inputted it is checked and validated and then forwarded to biometrics unit for statistical analysis. 

Regarding Grassland and fodder crops survey (2017) a sample of 530  growers were statistically  selected based on geographical location and farm size. Once  the population  was defined and sample selected the  surveyors were trained on how to collect the data and data was collected by pre-arranged  phone call . Data is inputted into excel specifically designed spreadsheets . Once all data is inputted it is checked and validated and then forwarded to biometrics unit for statistical analysis. 

Regarding soft fruit crops survey (2018) a sample of 29 growers were statistically  selected based on geographical location and farm size and represented 69% of total area grown. Once the population  was defined and sample selected the  surveyors were trained on how to collect the data and data was collected by pre-arranged  on farm visit. Data is inputted into excel specifically designed spreadsheets . Once all data is inputted it is checked and validated and then forwarded to biometrics unit for statistical analysis. 

Regarding top fruit  crops survey a sample of 30  growers were statistically  selected based on geographical location and farm size and represented 88% of totl area grown. Once  the population  was defined and sample selected the  surveyors were trained on how to collect the data and data was collected by pre-arranged  on farm visit. Data is inputted into excel specifically designed spreadsheets . Once all data is inputted it is checked and validated and then forwarded to biometrics unit for statistical analysis. 

2.1.2. Reference period of data collection

The reference period for each survey conducted was a s follows:

Outdoor vegetable crops survey ---data relates to 2015

Protected vegetable crops survey---data relates to  2015

Arable crops survey--- data relates to 2016

Grassland and fodder crops survey---data relates to  2017

Top fruitcrops survey---data relates to 2018

Soft fruit crops survey---data relates to  2018

2.1.3. National legislation
Yes

Annexes:
S.I. No. 159.2012
2.1.3.1. Name of national legislation

S.I. No. 159 of 2012 EUROPEAN COMMUNITIES (PLANT PROTECTION PRODUCTS) REGULATIONS 2012

2.1.3.2. Link to national legislation

The national legislation can be found using the folowing link:

http://www.irishstatutebook.ie/eli/2012/si/159/made/en/print

2.1.3.3. Responsible organisation for national legislation

The responsible organisation for the national legislation is the Department of Agriculture, Food and the Marine (DAFM)

2.1.3.4. Year of entry into force of national legislation

The date including year of enry into force was 17/5/2012

2.1.3.5. Coverage of variables required under EU regulation

No variables under EU regulation are not covered by the national legislation

2.1.3.6. Divergence national definitions from EU regulation

There are no national definitions which differ from EU definitions.

2.1.3.7. Legal obligation for respondents
Yes
2.1.4. Additional comments data description

None

2.2. Classification system

The classification used for pesticides corresponds to Annex III of Regulation (EC) No 1185/2009 (http://data.europa.eu/eli/reg/2009/1185/2017-03-09) of the European Parliament and of the Council.
The classification system for crops derives from the Annual crop statistics Handbook 2019 (https://ec.europa.eu/eurostat/cache/metadata/Annexes/apro_cp_esms_an1.pdf).

2.3. Coverage - sector

For all surveys the economic sector covered was agriculture.

Regarding the protected vegetable survey, land under these crops account for less than 1% of total UAA and pesticides applied to these crops account for less than 1% of total pesticides used in agriculture in Ireland. 

Regarding the outdoor/field vegetables survey, land under these crops account for less than 1% of total UAA and pesticides applied to these crops account for approximately 1% of total pesticides used in agriculture.

Regarding the Arable survey, land under arable crops accounts for approximately 6% of total UAA in Ireland and pesticides applied to these crops account for approximately 66% of total pesticdes used in agriculture.

Regarding the Grassland & fodder crops survey, land under these crops account for approximtely 93% of total UUA in Ireland and pesticides applied to these crops account for approximately 32% of total pesticdes used in agriculture.

Regarding the Top fruit survey, Land under these crops account for less than 1% of total UAA in Ireland and pesticides applied to these crops account for less than 1% of total pesticdes used in agriculture.

Regarding the Soft fruit survey, land under these crops account for less than 1% of totl UAA in Ireland and pesticides applied to these crops account for less than 1% of total pesticdes used in agriculture.

2.3.1. Crops covered by the statistics

See the attached Excel file in the Annexes.

2.3.2. Commercial non-agricultural uses of pesticides

Todate usage data on non-agricultural use of pesticides is not collected in Ireland.

2.4. Statistical concepts and definitions

The data reported are the quantity of each active substances listed in Annex III of Regulation 1185/2009 contained in plant protection products used on a selected crop, expressed in kg. The area treated with each substance are expressed in hectares.While aggregates of kgs of pesticides are included in the data transmitted no aggregates of treated area has been transmitted to avoid double counting. Consequently areas treated are only transmitted at active substance level  and not at aggregate level

2.5. Statistical unit

Crop areas and weight of pesticides applied recorded on agricultural holdings.

2.6. Statistical population

For each of the surveys listed the total population including agricultural  holding numbers, target crops and target crops areas was established. This polulation data was analysed including stratified by holding size and geographical location and a representative statistical sample was selected to be surveyed.The statistical analysis of the population and selection of sample farms to be surveyed is carried out by experienced statistical contractor.

2.7. Reference area

See sub-categories below.

2.7.1. Geographical area covered

The entire territory of the country to include the 26 counties of Ireland.

2.7.2. Inclusion of special territories

Not applicable to Ireland.

2.8. Coverage - Time

Usage data from 2011 to 2018 is the period for which usage data is available.

2.9. Base period

Not applicable for Pesticide Use Statistics, because it is not based on an index number of time series.


3. Statistical processing Top
3.1. Source data

See the attached Excel file in the Annexes.

3.2. Frequency of data collection

In Ireland DAFM operates a 4 year survey programme as follows:

Year 1- Field and protected vegetable crops

Year 2- Arable crops

Year 3-Grassland & fodder crops

Year 4- Top fruit and soft fruit crops

3.3. Data collection

See the attached Excel file in the Annexes.

3.4. Data validation

Survey management, data collection, accuracy are mostly issues for the survey coordinator and the data collection team.  There are likely to be some data errors during the data collection when growers provide inaccurate or approx. information to the surveyor during farm visits.In addition please note the following:

 

  1. The keying template includes various validation checks to ensure quality of data keyed in terms of crosschecking and ranges.

  2. Accuracy of pesticide products and doses are crosschecked against max range allowed for products. 

  3. Population coverage and weighting surveys are documented and applied by the statistician for each survey.

  4. Tables are created in versions that are unweighted and raised to population levels in agreed manner documented in 3 above and checked by both client and contractor statistician..

  5. The statistical estimated tables are created by ISO9001 approved contractor.

For  vegetable, arable, grassland & fodder crops, top fruit and soft fruit data, the Statistical contractor at Biometrics unit are ISO9001 acredited. This ensures that all data is checked, repeatable and reproducable and standard Operating procedures are carried out. Any issues identified during the analyses by the DAFM or by Biometrics can be corrected. Products and doses are crosscheck to manufacturers information. Data keying templates ensure that data is consistent. In addition the raw data is checked for completness of all identified products against approved products list and rates of use are checked. All tables are documented.

 

3.4.1. Data validation measures
Automatic
3.4.2. Target of data validation measures
Completeness
3.4.3. Specification target of data validation

not applicable

3.5. Data compilation

For all surveys (2015-2018) the statistical  contractor creates the survey estimates and tables using standard program scripts that have been used for many surveys. These scripts run on SPSS or R to produce files of holdings crops treatments, used pesticide products and active ingredients. Validation checks are included in the scripts that can highlight various diagnostic errors such as crops with no treatments.

Population weights are added in a separate files and the method validated against to an agreed raising method documented in a report known as a raising report for each survey.

Hierarchiel classes such as major groups are calciulated by using an excel spreadsheet including formulas in the format as per ANNEX III of Regulation 1185/2009.

For the purpose of surveys it is generally assumed that 1 kg is approximately equal to 1litre

Survey farms where data cannot be sourced from are replaced by similar farms of the same size and general location from a reserve list of farms.

No missing data is replaced (imputation) and all data is only generated from data collected from farms surveyed. The fact that no data is replaced means the results are reflective and representative  of the sampe data collected and recorded.

All efforts are made to ensure that as  complete a set of data is collected from the sample selected and if any non reponse occurs it is statistically accounted for and addressed in the analysis of the data by the statistical contractor.

Design weights and calibration (if used ) are professionally and statistically dealt with by  the statistical contractor.

Outliers that arise from the statistical analysis are queried with the survey coordinator and the farm surveyed and data collected  examined to ensure data was recorded correctly and inputted correctly.

The only source of data collected is from a sample survey of farms that are statistically selected from the population.

 

3.6. Adjustment

not applicable


4. Quality management Top
4.1. Quality assurance

See sub-categories below.

4.1.1. Quality management system in organisation
Yes
4.1.2. Specification of implementation

All surveys follow the following process specification:

Statistical contractors are accredited to ISO9001 for statistics and use Standard Operating Procedures to enable tables and results to be reproducible and repeatable long after the completion of the sample survey.

The contractor has 30 years of experience scientific computing producing Pesticide Survey estimates.

Weighting methods and data are retained and documented.

Regarding the survey the coordinator drafts and finalises  a standard operating  procedure (SOP) manual to be used and implemented by all surveyors who are recruited to conduct the surveyor. This ensures a consistent approach and technique implemented by all surveyors.

The coordinator drafts and finalises the survey recording forms to be used in the survey and also compiles agronomic notes to assist and guide the surveyors.

The coordinator finalises a training programme to be administered to all surveyors and a 2 day training course is organised. The training course includes a presentation on the following topics: Introduction to Regulation 1185/2009 and its relevance to Sustainable Use Directive. Reasons and benefits of the survey, Previous surveys, Survey details. After the presentation the survey team are trained on the full process of the survey via the standard operating procedure and all queries and questions are addressed. Day 1 of the training provides adequate and sufficient knowledge to each surveyor to allow them to commence the survey and record data at farm level.

When the survey team have surveyed a number of farms  and collected data,  day 2 of the training is organised and arranged. Day 2 involves the coordinator training each surveyor on inputting data collected into the data input document which is an specially designed excel document for the surveys. This data input document is designed and created by the statistical contractor in association with the survey coordinator. Day 2 of the training involves a practical aspect where each surveyor individually inputs data collected into the input document. When each surveyor has completed day 2, they are fully equiped to carry out all aspects of the survey and deal with any issues that may arise. The coordinator also carries out a number of surveys to inform himself of the potential issues encountered by the surveyors. In addition the coordinator provides technical back-up and guidance and expertise to all surveyors addressing any unforseen issues or problems encountered by the the survey team. The coordiantor also acts as a mentor for each surveyor and guides them to complete the survey. Each completed input document is forwarded to the coordinator where it is checked for any issues and anomalities and validated. Successfully validated input documents are amalgamated into one master document when again it is examined for any issues and anomalities and validated again. On final validation the document is transmitted to the statistical contractor for statistical analysis.

4.1.3. Peer review
Yes
4.1.4. Main conclusions peer review

An internal DAFM peer review is carreid out on all draft reports for each survey prior to publication

Conclusions are generally that the reports are well presented and very relevant in the area of pesticide usage in these crop sectors. Occassionally amendments/ suggestions are made and these are taken into account in the final version of the report.

4.1.5. Future quality improvements
Other
4.1.6. Specification of quality improvements

The survey coordinator  is always examining methods and identifying areas where improvements can be made to process. These may include survey form design, surveyor training, anticipating potential problems to be encountered etc.

In addition the statistical contractor is always examining ways of improving the survey data input document as well as data validation and quality control checks and all other areas of the process.

4.1.7. Additional comments quality assurance

None

4.2. Quality management - assessment

Overall every effort has been made for each survey and accross all surveys to ensure that the quality is of the highest possible standard and is consistent accross and within surveys. To date the same contrator has been used for all surveys and so this offers consistent practice and quality accross all surveys. The contrator has 30 years experience and knowlege in performing similar surveys. The coordinator works closely with the contractor from commencement to finish of each survey and the qualitative analysis of the data can be noted in other areas of this quality report.

4.2.1. Overall quality
Stable
4.2.2. Relevance
Stable
4.2.3. Accuracy and reliability
Stable
4.2.4. Timeliness and punctuality
Stable
4.2.5. Comparability
Stable
4.2.6. Coherence
Stable
4.2.7. Additional comments quality assessment

None


5. Relevance Top
5.1. Relevance - User Needs

-The classification of users  for  vegetable, arable, grassland & fodder crops, top fruit and soft fruit  data in Ireland would be the product authorisation holders, marketing companies, agencies, farm consultants, farmers/growers, research institutions and possibly some environmental groups.

-The respective needs of these groups vary from trends, market share, etc.

-The uses for which they want the statistical outputs vary  of these groups from trends, market share, research, education and knowledge sharing etc.

-The different categories of users feed back demonstrated that they were satisfied with the data outputs and no shortcomings were noted.

- No users informed us that there were any  unmet user needs.
-  No additional needs were identified
- No definitions which differ from requirements.

5.1.1. Unmet user needs

None identified

5.1.2. Plans for satisfying unfilled user needs

None identified

5.1.3. Additional comments user needs

None

5.2. Relevance - User Satisfaction

No user satisfaction surveys conducted, However general feed back is highly satifactory and always welcome.

5.2.1. User satisfaction survey
No
5.2.2. Year of user satisfaction survey

No user satisfaction surveys conducted but general feed back from users is positive and highly satisfactory

5.2.3. Satisfaction level
Highly satisfied
5.2.4. Additional comments user satisfaction

none

5.3. Completeness

See sub-category below.

5.3.1. Data completeness - rate

Not applicable for Pesticide Use Statistics because in this data collection, there is no target on the number of data. Member States are asked to collect data on representative crops without stipulating the number of crops.


6. Accuracy and reliability Top
6.1. Accuracy - overall

Random Sampling error is calculated by Standard Errors for total usage quantity and spray area for each surveys provided by DAFM.

Top Fruit 2018          
Univariate Statistics
  Estimate Standard Error 95% Confidence Interval
Lower Upper
Sum Total spha for all groups (excluding other) 13021.0 370.7626 12258.9 13783.1
Total quantity for all groups (excluding other) 9918.8 346.8148 9205.9 10631.6
           
Soft fruit 2018          
Univariate Statistics
  Estimate Standard Error 95% Confidence Interval
Lower Upper
Sum Total spha for all groups (excluding other) 3853.1 830.0678 2131.7 5574.6
Total quantity for all groups (excluding other) 1643.5 329.3641 960.4 2326.5
           
           
Field/ outdoor  Vegetables 2015        
           
Univariate Statistics
  Estimate Standard Error 95% Confidence Interval
Lower Upper
Sum Total spha for all groups (excluding other) 45004.8 3148.9154 38724.5 51285.2
Total quantity for all groups (excluding other) 20133.5 2076.1954 15992.6 24274.3
           
           
Protected vegetables 2015        
Univariate Statistics
  Estimate Standard Error 95% Confidence Interval
Lower Upper
Sum Total spha for all groups (excluding other) 523.7 88.0370 341.6 705.8
Total quantity for all groups (excluding other) 155.0 16.8504 120.1 189.8
           
           
Grassland and foddef crops 2017        
Univariate Statistics
  Estimate Standard Error 95% Confidence Interval
Lower Upper
Sum Total spha for all groups (excluding other) 725574.0 48697.9903 629748.7 821399.3
Total quantity for all groups (excluding other) 535300.8 39552.8215 457470.9 613130.7
           
           
Arable 2016          
Univariate Statistics
  Estimate Standard Error 95% Confidence Interval
Lower Upper
Sum Total spha for all groups (excluding other)         3,288,779                 103,212 3085519.1 3492038.0
Total quantity for all groups (excluding other)         1,080,062                   42,785 995804.1 1164320.8

 

This is due to the sample size, sampling design and variation in the treatments applied to crops.

Control of bias is a matter of designing the sample correctly, and weighting according to the sampling design apply different weights for small and large growers etc. 

Revisions… analyses can be revisited and logged as computer scripts programs can be rerun and changes to the data can only be made by the data provider.

The above demonstrates the quality and accuracy overall of the statistics for each of the surveys

 

6.1.1. Grading of accuracy
High
6.1.2. Factors lowering accuracy
Other
6.1.3. Specification of factors

Measurement error is likely to be the biggest source of error. Other sources are well controlled.

6.1.4. Additional comments overall accuracy

none

6.2. Sampling error

See the attached Excel file in the Annexes.

6.3. Non-sampling error

See sub-categories below.

6.3.1. Coverage error

See the attached Excel file in the Annexes.

6.3.2. Measurement error

See the attached Excel file in the Annexes.

6.3.3. Non response error

See the attached Excel file in the Annexes.

6.3.4. Processing error

See the attached Excel file in the Annexes.

6.3.5. Model assumption error

No model assumption erros noted in any of the surveys 2015-2018.

6.4. Seasonal adjustment

Seasonal adjustment is not applicable to pesticide use statistics since all plant protection treatments associated directly or indirectly with the crop during the reference period are reported.

6.5. Data revision - policy
For all data sets including vegetables, arable, grassland & fodder crops, top fruit and soft fruit the Policy is that if revised data is received then initial data compiled data will be revised as necessary and without delay and revised data transmitted to Eurostat and amended where published.
No change required to published data for arable, grassland and vegetables. At this time the top and soft fruit data has not yet been published.
6.6. Data revision - practice

Where new data or errors in process is discovered then the practice is to implement a revision of the data. every effort is made to ensure the highest quality of data is arrived at but if a revision is needed then it is implemented.

6.6.1. Data revision - average size

Data revision average size are not significant and the overall impact and effect is to ensure the data is as correct as possible but overll any revisions have insignificant implications on the data.

6.6.2. Data revisions - conceptual changes
No
6.6.3. Reason for revisions

Revisions are normally carried out for updated/ corrected data and/or where additional data is received.

6.6.4. Impact of revisions
Important
6.6.5. Additional comments data revisions

none


7. Timeliness and punctuality Top
7.1. Timeliness

See sub-categories below.

7.1.1. Time lag - first result

The time lag from the end of the reference year to first result  is aimed to be within 12-18 months for all surveys

7.1.2. Time lag - final result

The time lag from the end of the reference year to final result is aimed to be within 12-18 months for all surveys

7.1.3. Reasons for possible long production times?

Generally the main reasons for long production times maybe available/limited resources and other priority work.

7.2. Punctuality

See sub-categories below.

7.2.1. Punctuality - delivery and publication

There was no delay in sending/transmitting the data to Eurostat.

7.2.2. Data release according to schedule
YES
7.2.3. Data release on target date
YES
7.2.4. Reasons for delays

Not applicable


8. Coherence and comparability Top
8.1. Comparability - geographical

"Data are collected on a country level (NUTS 0). Therefore, the data are not comparable on a regional level. The geographical comparability between countries is evaluated by Eurostat."

8.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable, because there are no mirror flows in Pesticide Use Statistics.

8.2. Comparability - over time

Not applicable for Pesticide Use Statistics, because it is not based on time series.

8.2.1. Length of comparable time series

Not applicable for Pesticide Use Statistics, because it is not based on time series.

8.3. Coherence - cross domain

There are no other cross domain comparale data available and so no cross domain comparison is possible.

8.4. Coherence - sub annual and annual statistics

Not applicable for Pesticide Use Statistics, because the data collection is based on a five-year period.

8.5. Coherence - National Accounts

Not applicable, because it has no relevance for national accounts.

8.6. Coherence - internal

The outputs of the data are internally consistent and coherent. The process does not compromise data from different sources. The content of the reports which are published only contain data that is recorded in the surveys and statistically analysed to give an estimate at national level.


9. Accessibility and clarity Top
9.1. Dissemination format - News release

Not Applicable: Regarding vegetable, arable, grassland & fodder crops, top fruit and soft fruit, data will not be disseminated via News Release

9.1.1. Publication of news releases
No
9.1.2. Link to news releases

Not applicable as not published via news release

9.2. Dissemination format - Publications

Survey reports when published are published on www.pcs.agriculture.gov.ie/sud/pesticidestatistics/

Pesticide Usage in Ireland: Outdoor and protected Vegetables crops survey report 2015, Published by DAFM in 2017

Pesticide Usage in Ireland: Arabe Crops Survey Report 2016, Published by DAFM 2020

Pesticide Usage in Ireland:Grassland and fodder crops survey report 2017, Published by DAFM 2020

The top and soft fruit reports are due to be published in late 2020 or early 2021 and can be found using the above link.

9.2.1. Production of paper publication
No
9.2.2. English paper publication
No
9.2.3. Production of electronic publication
Yes
9.2.4. English electronic publication
Yes
9.2.5. Link to publications

All published pesticide usage reports can be found at www.pcs.agriculture.gov.ie/sud/pesticidestatistics/

 

9.3. Dissemination format - online database

No online database for the disseminated data is published on line. It is only the reports which are published.

9.3.1. Data tables - consultations

Not applicable

9.3.2. Accessibility of on-line database
No
9.3.3. Link to on-line database

Not applicable

9.4. Dissemination format - microdata access

No microdata will be  provided for vegetable, arable, grassland & fodder crops, top fruit  or soft fruit.

9.4.1. Accessibility of micro-data
No
9.4.2. Link to micro-data

Microdata is not accessible to users.

9.5. Dissemination format - other

For grassland & fodder crops, arable, top fruit, soft fruit and vegetable, no other independent data dissimination  available at this time.

9.6. Documentation on methodology

A standard operating procedure (SOP) is in place clearly outlining all steps involved in the methodology of the process involved. In addition a brief description of the  methodology is described in the PDF published survey report on line.

9.6.1. Availability of national reference metadata
No
9.6.2. Link to national reference metadata

no national reference metadata is available

9.6.3. Availability of methodological papers
No
9.6.4. Link to methodological papers

No methodological papers are provided. However a description of the methodology used in the survey process is included in the PDF survey reports published on line.

9.6.5. Availability of handbook
No
9.6.6. Link to handbook

No handbook is provided. A description of the methodology used is included in the PDF survey report published online.

9.7. Quality management - documentation

The contractor engaged to carry out the statistical analysis uses Standard Operating Procedures and is accredited to ISO9001 for statistics and conforms. Each survey has a document describing sample and weighting procedures.

9.7.1. Metadata completeness - rate

Data is provided in a report in PDF version. No metadata is provided publically.

9.7.2. Metadata - consultations

Data is provided in a report in PDF version. No metadata is provided publically.

9.7.3. Availability of quality report
NO
9.7.4. Link to quality report

No quality report provided.


10. Cost and Burden Top

The burden on respondents is not huge as all that is required from farmers and growers is their time and to supply their usage data on the relevant crops for the reference year. As a result while a cost itself is not calculated it is believed that the cost is minimal to growers /farmers involved. Average respondent time is 25-30 mins. Efforts to minimise time with respondents are always in focus and it is believed that 25-30 mins is maximum time on farm.

The range and detail of data collected on farm has been refined over time and now only absolute necessary data is recorded

No administrative data is available that would assist the survey further.

Data sought from farmers and growers is readily available to be recorded for the survey

The possibility to collect data using electronic means has been examined and found not to be feasible at this point in time. However, this possibility will continue to be explored going forward.

Data is recorded from the farmer/grower in consultation with their records. In the event where a record required is missing the required  then the farmers best estimate, and approximation are accepted.

Reporting burden is minimised but not aware if other surveys are being conducted with same respondent. In addition data is collected on an anonymous and confidential basis and so each survey must be independent and perceived to be so.

Please now find below a summary of the approximate cost involved in each survey 2015-2018.

Vegetable survey 2015

Survey component

Cost (approx.)

Cost of main superviser/coordinator of survey

€55,000

Cost of tendering and acquiring statistical analysis expertise

€27,800

Cost of surveying staff (5 surveyors—field and protected vegetable crops)

€25,000

Travel and subsistence cost for field and protected vegetable crops survey

€7,000

Total cost

€114,800

   
   
   

Arable survey 2016

Survey component

Cost (approx.)

Cost of main superviser/coordinator of survey

€55,000

Cost of tendering and acquiring statistical analysis expertise

€27,800

Cost of surveysing staff (9 surveyors—arable survey

€40,000

Travel and subsistence cost for arable survey

€15,000

Total cost

€137,800

   
   
   

Grassland & fodder crops survey 2017

Survey component

Cost (approx.)

Cost of main superviser/coordinator of survey

€55,000

Cost of tendering and acquiring statistical analysis expertise

€27,800

Cost of surveying staff (10 surveyors—grassland and fodder crops)

€45,000

Travel and subsistence cost for grassland and fodder crops survey

€7,000

Total cost

€134,800

   
   

Top & soft fruits survey 2018

Survey component

Cost (approx.)

Cost of main superviser/coordinator of survey

€55,000

Cost of tendering and acquiring statistical analysis expertise

€27,800

Cost of surveysing staff (2 surveyors-- top and soft fruit)

€10,000

Travel and subsistence cost for top and soft fruit surveys

€6,000

Total cost

98,800

10.1. Efficiency gains
Other
10.2. Specification efficiency gains

Effefiency gains are always being examined on an ongoing basis rgarding all areas of the process.

Focused training is applied and improved each year. This assists and prepares and informs the surveyors to collect only the core  data that is required for the survey.

Survey questionnaires are also refined and improved to guide the surveyor smoothly throught the data collection process

Surveyors are provided with survey specific crop agronomic notes and attend a 2 day survey specific training course organised by the coordinator.

Surveyors input the data collected on farms into specifically contructed electronic documents

Progress reports requested from surveyors identifying any issues encountered and overall progress.

Full backup is provided to each surveyor to address any issues encountered or queries raised

All inputed data is checked to ensure no errors exist which results in quiker analysis processing

Good lines of communication are preseent at all levels of the survey and data analysis to improve the process overall.

Grassland survey mostly conducted via phone to reduce time on farm and costs. This has been hughly successful and may be rolled out to other surveys if suitable.

All the above asisst, help and improved the overall effeciancy on the process

10.3. Measures to reduce burden
Less variables surveyed
More user-friendly questionnaires
10.4. Specification burden reduction

Not applicable


11. Confidentiality Top
11.1. Confidentiality - policy

Confidentiality of the vegetable, arable, grassland & fodder crop , top fruit and soft fruit data and that of the source, individual or company is treated as a very important matter by DAFM. However, as the pesticide use data is historical, cannot be linked to an individual and is only relevant to this crop and totals for other uses on other crops are not recorded it is deamed that this data can be published.

11.1.1. Transmission of confidential national data to Eurostat
No
11.1.2. Confidentiality according to Regulation
Yes
11.1.3. Data confidentiality policy

For sales data,if less than 3 companies are involved with a product or if there are less than 3 sources of active substance then the total for that product cannot be published on its own as one company knowing its own share could work out the others  market share. In these situations the total for the product is grouped with other products in the report. To date this is how confidentiality and commercially sensitive data  is treated within this organisation and to date has worked successfully with no issues. As this is usage data for vegetables, arable, grassland and fodder crops, top fruit and soft fruit   and not total sales data  and because it is collected at grower/farmer level and because it is historical and  only relevant to the crop being surveyed and does not reflect a total use of this active substance at national level it is deemed that this data can be published. In addition, in situations where there is certain minority crops (low areas and/or low numbers of growers) then these are amalgamated with other crops so that the minority crop area, farm, unit or individual cannot be directly or indirecly identified.

11.2. Confidentiality - data treatment

The following is applied to ensure statistical confidentiuality;

Data is examine from both a specific crop and location and size perspective.

For example a specific crop if grown on a small area may indirectly identify a farm or individual farmer.

To ensure statistical confidentiality crops of small national areas and/or in specific geographical locations are amalgamated with other crops so as not to directly or indicectly identify the farm or individual involved. This is carfully examined during the analysis and post analysis period and depending on outcomes amalgamation may be needed as detailed above and then data is re analysed.  This process is carried out prior to draft and final published survey report and this process is applicable to all surveys 2015-2018.

11.2.1. Procedures for confidentiality

The following is applied to ensure statistical confidentiality;

Data is examine from both a specific crop and location and size perspective.

For example a specific crop if grown on a small area may indirectly identify a farm or individual farmer.

To ensure statistical confidentiality crops of small national areas and/or in specific geographical locations are amalgamated with other crops so as not to directly or indicectly identify the farm or individual involved. This is carfully examined during the analysis and post analysis period and depending on outcomes amalgamation may be needed as detailed above and then data is re analysed. This process is carried out prior to draft and final published survey report and this process is applicable to all surveys 2015-2018.

 

11.2.2. Additional comments confidentiality - data treatment

None


12. Comment Top

None


Related metadata Top


Annexes Top
ESQRS ANNEX_PESTUSE-2015-2919_COMPLETED_IRELAND_JQ
2016 Arable survey forms IE
2017 Grassland & fodder crops survey forms IE
2015 Protected & outdoor vegetable crops survey forms IE
2018 Soft fruit crops survey forms IE
2018 Top fruit crops survey forms IE