Crop production (apro_cp)

National Reference Metadata in ESS Standard for CROPS Reports Structure (ESQRSCP)

Compiling agency: Central Statistics Office, Skehard Road, Cork, Ireland

Time Dimension: 2016-A0

Data Provider: IE1

Data Flow: CROPROD_ESQRSCP_A


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

Central Statistics Office, Skehard Road, Cork, Ireland

1.2. Contact organisation unit

Agriculture Surveys

1.5. Contact mail address

Central Statistics Office, Skehard Road, Cork, Ireland


2. Statistical presentation Top
2.1. Data description

Annual crop statistics provide statistics on the area under main arable crops, vegetables, and permanent crops, as well as production and yield levels.  The statistics are collected from a wide variety of sources: surveys, administrative records, experts and other data providers. The data collection covers early estimates (before the harvest) and the final data. Data are collected mostly at national level but regional data also exists for some crops (NUTS1/2).

2.2. Classification system

Hierarchical crop classification system.

2.3. Coverage - sector

Growing of non-perennial crops, perennial crops and plant propagation (NACE A01.1-01.3).

2.4. Statistical concepts and definitions

See: Annual Crop Statistics Handbook.

2.5. Statistical unit

Utilised agricultural area cultivated by an agricultural holding.

2.6. Statistical population

All agricultural holdings growing crops.

2.7. Reference area

The entire territory of the country.

2.8. Coverage - Time

Crop year.

2.9. Base period

Not applicable.


3. Statistical processing Top

See points 3.1, 3.2, 3.3 and 3.4

3.1. Source data

  Source 1 Source 2 Source 3 Source 4
Have new data sources been introduced since the previous Quality Report (2014)?  NO      
If yes, which new data sources have been introduced since the previous quality report (2014)?
Type of source?
To which Table (Reg 543/2009) do they contribute?
Have some data sources been dropped since the previous Quality Report (2014)? NO      
Which data sources have been dropped since the previous quality report (2014)?
Type of source?
Why have they been dropped?
Additional comments


Data sources: Please indicate the data sources which were used for the reference year 2016

  Type Name(s) of the sources If other type, which kind of data source?
Table 1: crops from arable land      
Early estimates for areas Expert estimate

Teagasc Expert Estimate (Teagasc is the agriculture and food development authority in Ireland. Its mission is to support science-based innovation in the agri-food sector and the broader bioeconomy that will underpin profitability, competitiveness and sustainability).

Final area under cultivation Administrative data

IACS

Production Other

NSI Calculation (using IACS & Teagasc Expert estimates)

Yield Expert estimate

Teagasc Expert Estimate

Non-existing and non-significant crops Administrative data
Expert estimate

 

 

IACS

Teagasc Expert Estimate

 
Table 2: Vegetables, melons and strawberries       
Early estimates for harvested areas Other

NSI estimate, with input from crop experts in Teagasc

Final harvested area Administrative data
Other

IACS

 

NSI estimate with input from crop experts in Teagasc 

Production Other

1.Ministry of Agriculture (MoA) Horticulture report. This is a summary table which we receive from the MoA listing areas and/or production for selected fruits and vegetables. This is provided directly to the NSI.

2.NSI Calculations (using IACS, MoA report & Teagasc Expert estimates)

Non-existing and non-significant crops Administrative data
Other

 IACS

MoA Horticulture report. This is a summary table which we receive from the Irish MoA listing areas and/or production for selected fruits and vegetables. This is provided directly to the NSI.

Table 3: Permanent crops      
Early estimates for production area Other

NSI estimate. In the absence of early estimates from the MoA, we carry Year T-1 values until such time as we receive IACS data from the MoA.

Final production area Survey
Administrative data

Orchard Survey (for apples every 5 years)

IACS
Production Survey

Orchard Survey (for apples every 5 years)

Non-existing and non-significant crops Administrative data
Expert estimate
Other

 

IACS
 
Teagasc Expert Estimate

MoA Horticulture report. This is a summary table which we receive from the Irish MoA listing areas and/or production for selected fruits and vegetables. This is provided directly to the NSI.

Table 4: Agricultural land use      
Main area Survey
Administrative data

June Crops & Livestock Survey

IACS
Non-existing and non-significant crops Administrative data

 

IACS
Total number of different data sources

7

   
Additional comments

Data source for the humidity

Put x, if used

Surveyed: farmers report the humidity

 x

Surveyed: farmers convert the production/yield into standard humidity     

 

Surveyed: whole sale purchasers report the humidity

 

Surveyed: whole sale purchasers convert the production/yield into standard humidity     

 

Surveyed by experts (e.g. test areas harvested and measured)

 

Estimated by experts

 x

Other type

 

If other type, please explain

 

Additional information

 

In the Teagasc survey, farmers report humidity. However, this is not converted into standard humidity.

   


Which method is used for calculating the yield for main arable crops? production divided by harvested area
If another method, describe it.
3.2. Frequency of data collection

  Source 1 Source 2 Source 3 Source 4 Source 5 Source 6 Source 7 Source 8 Source 9
Name of data source

IACS

Teagasc expert estimate

Other - includes June Crops & Livestock Survey and Crop Yield Survey

Planning (month-month/year)

Sept (year t)

Periodically according to Reg 543/2009 requirements for early estimates.

Depends on survey

Preparation (month-month/year)

Sept (year t)

Periodically according to Reg 543/2009 requirements for early estimates.

Depends on survey

Data collection (month-month/year)

Sept (year t)

Periodically according to Reg 543/2009 requirements for early estimates.

Depends on survey

Quality control (month-month/year)

Sept (year t)

Periodically according to Reg 543/2009 requirements for early estimates.

Depends on survey

Data analysis (month-month/year)

Sept (year t)

Periodically according to Reg 543/2009 requirements for early estimates.

Depends on survey

Dissemination (month-month/year)

Oct (year t)

Periodically according to Reg 543/2009 requirements for early estimates.

Depends on survey

If there were delays, what were the reasons?

Provisonal IACS file received in Sept (year t). Final IACS file received in Feb (year t+1)

Depends on survey

3.3. Data collection

Definitions

  Question In case yes, how do they differ?
Do national definitions differ from the definitions in Article 2 of Regulation (EC) No 543/2009? YES

Area under cultivation - the area under cultivation is the sown area. After the harvest, it does not exclude ruined areas (e.g. due to natural disasters).

Are there differences between the national methodology and the methodology described in the Handbook concerning e.g. the item and aggregate calculations? YES

In Ireland there is no additional information collected on the actual area harvested. This means that the reported value for area after harvest does not exclude non-harvested area (e.g. area ruined by natural disasters or area not harvested for economic reasons).

Are special estimation/calculation methods used for main crops from arable land? YES

The reported value for area after harvest does not exclude non-harvested area (e.g. area ruined by natural disasters or area not harvested for economic reasons). This means that the reported yield is lower than the real yield as ruined & non-harvested areas are not included in the calculation of yield.

Are special estimation/calculation methods used for vegetables or strawberries? NO
Are special estimation/calculation methods used for permanent crops for human consumption? NO
Are special estimation/calculation methods used for main land use? YES

As all Agriculture land use (principally grassland) is not registered in the Integrated Administration and Control System (IACS), the Irish NSI conducts an annual crops survey in June. Results for grassland agricultural land use area are based on a matched sample methodology. A series of SAS programs are run to identify all farmers who responded to the survey in both the current year and in the previous year. Then, for each categories of grassland, the percentage change between the two years is calculated. This percentage change is then applied to the published totals for the previous year to come up with estimates for the totals for the current year.

Do national crop item definitions differ from the definitions in the Handbook  (D-flagged data)? NO  
In case yes, how do they differ? ( list all items and explanations)
In case data are delivered for one of the items below, describe the crop species included in the item:


Population

Which measures were taken in order to make sure that the requirement stipulated in Art. 3.2 are met?
(Statistics shall be representative of at least 95 % of the areas of each table in the Regulation).

Comprehensive area data from both Census of Agriculture 2010 and IACS administrative data used to create strata and ensure adequate coverage and representativity.

Is the data collection based on holdings? YES
If yes, how the holdings were identified? Unique statistical farm identifier
If not, on which unit the data collection is based on?
When was last update of the holding register? (month/year)

May 2016 in advance of conducting Farm Structure Survey 2016

Was a threshold applied? NO
If yes, size of the excluded area Area excluded on the basis of the threshold in % of the total area for that crop
Cereals for the production of grain (in %)
Dried pulses and protein crops (in %)
Root crops (in %)
Oilseeds (in %)
Other industrial crops (included all industrial crops besides oilseeds)  (in %)
Plants harvested green from arable land (in %)
Total vegetables, melons and strawberries (in %)
Cultivated mushrooms (in %)
Total permanent crops (in %)
Fruit trees (in %)
Berries (in %)
Nut trees (in %)
Citrus fruit trees (in %)
Vineyards (in %)
Olive trees (in %)


Survey method (only for census and surveys)

  Survey 1  Survey 2 Survey 3  Survey 4 Survey 5  Survey 6 Survey 7
Name of the survey

June Crops & Livestock Survey/FSS

Which survey method was used? Postal questionnaire filled in by respondent
Telephone interview, paper questionnaire
If 'other', please specify
Please provide a link to the questionnaire

http://www.cso.ie/en/media/csoie/methods/cropsandlivestocksurveyjunefinal/Agriculture_Survey_June_2017.pdf

Data entry method, if paper questionnaires? Optical


Administrative data (This question block is only for administrative data)

  Admin source 1 Admin source 2 Admin source 3 Admin source 4 Admin source 5 Admin source 6
Name of the register

IACS

Description

IACS -Single Payment Scheme

Data owner (organisation)

Minsistry of Agriculture

Update frequency Every 6 months or more frequently
Reference date (month/year)

01/2016 and 09/2016

Legal basis

Single Payment Scheme-Council Regulation No 1782/2003

Reporting unit

Holding

Identification variable (e.g. address, unique code, etc.)

Unique Code (Herd Number)

Percentage of mismatches (%)

Not recorded

How were the mismatches handled?

Matched on name, address or another variable

Degree of coverage (holdings, e.g. 80%)

97% of holdings

Degree of completeness (variables, e.g. 60%)

95%

If not complete, which other sources were used ?

June Crops & Livestock Survey

How were the data used?
Sample frame
Data used for other purposes, which?

yes, updating register.

Which variables were taken from administrative sources?

All Crop variables (excluding strawberries)

Were there any differences in the definition of the variables between the administrative source and those described in the Regulation? NO
Please describe the differences
What measures were taken to eliminate the differences?
How was the reliability, accuracy and coherence (comparison to other available data) of the data originated from administrative data source (ante- and/or ex-post) checked?

Compare with expert estimates/forecasts from Teagasc (which is the agriculture and food development authority in Ireland. Its mission is to support science-based innovation in the agri-food sector and the broader bioeconomy that will underpin profitability, competitiveness and sustainability)

What were the possible limitations, drawbacks of using the data from administrative source(s)?

Difficult to use the 'unique identifier' as some holdings may have several identifiers attached.


Expert estimations (This question block is only for expert estimates)

  Expert estimate 1 Expert estimate 2 Expert estimate 3 Expert estimate 4 Expert estimate 5 Expert estimate 6
Name of the estimation

Crop Yield

Data owner (organisation)

Teagasc (National agricultural research body)

Update frequency (e.g. 1 year or 6 months) Yearly
Reference date (Month/Year  e.g. 1/16 - 8/16)

01/16- 09/16

Legal basis
Use purpose of the estimates?

Crop yields

What kind of expertise the experts have?

Crop experts/Crop advisers

What kind of estimation methods were used?

Yield readings on harvest for each NUTS4 region

Were there any differences in the definition of the variables between the experts' estimates and those described in the Regulation? NO
If yes, please describe the differences
What measures were taken to eliminate the differences?
How were the reliability, accuracy and coherence (comparison to other available data) of the data originated from experts' estimates (ante- and/or ex-post)checked?

Compare against other national publications/estimates in agri sector

What were the possible limitations, drawbacks of using the data from expert estimate(s)?
Additional comments
3.4. Data validation

Which kind of data validation measures are in place? Automatic and Manual
What do they target? Completeness
Aggregate calculations
Other
Is the data cross-validated against an other dataset? YES
If yes, which kind of dataset? Previous results
If other, please describe
3.5. Data compilation

Not applicable.

3.6. Adjustment

Not applicable.


4. Quality management Top
4.1. Quality assurance

  Completeness Punctuality Accuracy Reliability Overall quality
How would you describe the overall quality development since 2014? Improvement Improvement Improvement Improvement Improvement
Is there a quality management process in place for crop statistics? YES        
If, yes, what are the components?

Relevance, Accuracy, Reliability, Timeliness, Punctuality, Coherence, Compatability, Access, and Clarity.

       
Is there a Quality Report available? YES        
If yes, please provide a link(s)

http://www.cso.ie/en/media/csoie/methods/cropsandlivestocksurveyjunefinal/June_Crops_and_Livestock_Quality_Report.pdf

       
To which data source(s) is it linked?

Crops and Livestock June Survey

       
Has a peer-review been carried out for crop statistics? NO        
If, yes, which were the main conclusions?        
What quality improvement measures are planned for the next 3 years?        
If, other, please specify        
Additional comments        
4.2. Quality management - assessment

See the European Level Quality Report.


5. Relevance Top

See points 5.1 and 5.2

5.1. Relevance - User Needs

Are there known unmet user needs? NO
Describe the unmet needs
Does the Regulation 543/2009 meet the national data needs? YES
Does the ESS agreement meet the national needs? YES
If not, which additional data are collected?
Additional comments
5.2. Relevance - User Satisfaction

Have any user satisfaction surveys been done? NO
If yes, how satisfied the users were?
Additional comments

No formal satisfaction survey carried out. However, this NSI chairs an Agricultural Statistics Liasion Group of key users. The needs of these key users are discussed at length at these meetings and there is regular contact amongst members between meetings.

5.3. Completeness

See the European Level Quality Report

5.3.1. Data completeness - rate

See the European Level Quality Report


6. Accuracy and reliability Top

See points 6.2, 6.3.1, 6.3.2 and 6.3.3

6.1. Accuracy - overall

See the European Level Quality Report.

6.2. Sampling error

Sampling method and sampling error

  Survey 1 Survey 2 Survey 3 Survey 4 Survey 5 Survey 6 Survey 7
Name

June Crops & Livestock Survey

Sampling basis? Multiple frame
If 'other', please specify
Sampling method? Stratified
If stratified, number of strata?

20

If stratified, stratification basis? Size
Specialisation
If 'other', please specify
Size of total population

139,860

Size of sample

c.10,000

Which methods were used to assess the sampling error? 
If other, which?
Which methods were used to derive the extrapolation factor? 
If other, which?
If CV (co-efficient of variation) was calculated, please describe the calculation methods and formulas
If the results were compared with other sources, please describe the results
Which were the main sources of errors?


Sampling error - indicators

Not applicable


Coefficient of variation (CV) for the area (on the MS level)

  Survey 1  Survey 2 Survey 3  Survey 4 Survey 5  Survey 6 Survey 7
Name of the survey
Cereals for the production of grain (in %)
Dried pulses and protein crops (in %)
Root crops (in %)
Oilseeds (in %)
Other industrial crops (included all industrial crops besides oilseeds)  (in %)
Plants harvested green from arable land (in %)
Total vegetables, melons and strawberries (in %)
Cultivated mushrooms (in %)
Total permanent crops (in %)
Fruit trees (in %)
Berries (in %)
Nut trees (in %)
Citrus fruit trees (in %)
Vineyards (in %)
Olive trees (in %)
Additional comments

As almost all the annual crop variables are provided by IACS dataset, this June Survey is mainly used to collect proportional breakdowns of areas already collected in IACS, eg, area under temporary vs permanent grass.

           
6.3. Non-sampling error

See items 6.3.1-6.6

6.3.1. Coverage error

Over-coverage - rate

not applicable


Common units - proportion

not applicable


  Data source 1 Data source 2 Data source 3 Data source 4 Data source 5 Data source 6 Data source 7 Data source 8 Data source 9
Name of the data source

June Crops & Livestock Survey

Error type Under-coverage
Degree of bias caused by coverage errors Unknown
What were the reasons for coverage errors?

IACS database does not include growers without Basic Payment Scheme entitlements.

Which actions were taken for reducing the error or to correct the statistics?

Refer to other horticultural publications/reports for state totals 

Additional comments




 

6.3.1.1. Over-coverage - rate

not applicable

6.3.1.2. Common units - proportion

not applicable

6.3.2. Measurement error

  Data source 1 Data source 2 Data source 3 Data source 4 Data source 5 Data source 6 Data source 7 Data source 8 Data source 9
Name of the data source

June Crops & Livestock Survey

Was the questionnaire based on usual concepts for respondents? YES
Number of surveys already performed with the current questionnaire (or a slightly amended version of it)?

3

Preparatory (field) testing of the questionnaire? NO
Number of units participating in the tests? 
Explanatory notes/handbook for surveyors/respondents?  YES
On-line FAQ or Hot-line support for surveyors/respondents? YES
Were pre-filled questionnaires used? NO
Percentage of pre-filled questions out of total number of questions
Were some actions taken for reducing the measurement error or to correct the statistics? YES
If yes, describe the actions and their impact

Validation checks on data entry; validation against previous returns; vlaidation against IACS data.

6.3.3. Non response error

Unit non-response - rate

Not applicable


Item non-response - rate

not applicable


  Survey 1 Survey 2 Survey 3 Survey 4 Survey 5 Survey 6 Survey 7
Name

June Crops & Livestock Survey

Unit level non-response rate (in %)

14%

Item level non-response rate (in %)              
               - Min% / item

See additional comments

               - Max% / item

See additional comments

               - Overall%

See additional comments

Was the non-response been treated ? NO
Which actions were taken to reduce the impact of non-response?

See additional comments

Which items had a high item-level non-response rate? 

See additional comments

Which methods were used for handling missing data?
(several answers allowed)
In case of imputation which was the basis?
In case of imputation, which was the imputation rate (%)?
Estimated degree of bias caused by non-response? Unknown
Which tools were used for correcting the data?

See additional comments

Which organisation did the corrections?

See additional comments

Additional comments

In a postal survey such as this, it is difficult to identify if item non-response is actually non-response or simply not relevant to the respondent.

As almost all of the annual crop variables are provided by the IACS dataset, this June Survey is mainly used to collect proportional breakdowns of areas already collected in IACS, e.g. area under temporary vs permanent grass.

6.3.3.1. Unit non-response - rate

Not applicable

6.3.3.2. Item non-response - rate

not applicable

6.3.4. Processing error

Not applicable.

6.3.4.1. Imputation - rate

Not applicable.

6.3.5. Model assumption error

Not applicable.

6.4. Seasonal adjustment

Not applicable.

6.5. Data revision - policy

Not applicable.

6.6. Data revision - practice

Not applicable.

6.6.1. Data revision - average size

Not applicable.


7. Timeliness and punctuality Top
7.1. Timeliness

Time lag - first result


Time lag - final result


  Cereals Dried pulses and protein crops Root crops Oilseeds Other industrial crops Plants harvested green Vegetables and melons Strawberries Cultivated mushrooms Fruit trees Berries Nut trees Citrus fruit trees Vineyards Olive trees
How many main data releases there are yearly in the national crop statistics for the following types of crops?

3

3

3

3

1

1

How many of them are forecasts (releases before the harvest)?

0

0

0

0

0

0

When was  the first  forecasting published for crop year 2016? (day/month/year)
When were the final results published for crop year 2016? (day/month/year) 10/03/2017 10/03/2017 10/03/2017 10/03/2017 10/03/2017 10/03/2017
Additional comments

Timeliness may vary in years where structural farm surveys are carried out

Timeliness may vary in years where structural farm surveys are carried out

Timeliness may vary in years where structural farm surveys are carried out

Timeliness may vary in years where structural farm surveys are carried out

Timeliness may vary in years where structural farm surveys are carried out

Timeliness may vary in years where structural farm surveys are carried out

7.1.1. Time lag - first result
7.1.2. Time lag - final result
7.2. Punctuality

See the European Level Quality Report

7.2.1. Punctuality - delivery and publication

See the European Level Quality Report


8. Coherence and comparability Top

See points 8.2 and 8.3

8.1. Comparability - geographical

Not applicable.

8.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable.

8.2. Comparability - over time

Length of comparable time series

not applicable


  Crops from arable land
(Table 1)
Vegetables, melons and strawberries (Table 2) Permanent crops
(Table 3)
Agricultural land use
(Table 4)
Have there been major breaks in the time series since 2013? NO NO NO NO
If yes, to which were they related?
If other, which?
Which items were affected?
Year of break (number)
Impact on comparability
Additional comments
8.2.1. Length of comparable time series

not applicable

8.3. Coherence - cross domain

  Data source
With which other data sources the crop statistics data have been compared?  Other
If others, which?

Orchard survey

If no comparisons have been made, why not?

Administrative data is used as the source file for both Crop Statistics and FSS crop items.


Results of comparisons FSS 2016 (if available) Vineyard survey 2015 IACS Other source(s)  In case of other sources, which?
Cereals  
Dried pulses and protein crops  
Root crops  
Oilseeds  
Other industrial crops (than oilseeds)  
Plants harvested green  
Total vegetables, melons and strawberries  
Vegetables and melons  
Strawberries  
Cultivated mushrooms  
Total permanent crops  
Fruit trees  
Berries  
Nut trees  
Citrus fruit trees  
Vineyards
Olive trees  
If there were considerable differences, which factors explain them?  
8.4. Coherence - sub annual and annual statistics

Not applicable.

8.5. Coherence - National Accounts

Not applicable.

8.6. Coherence - internal

Not applicable.


9. Accessibility and clarity Top

See points 9.1, 9.2, 9.3, 9.5 and 9.6

9.1. Dissemination format - News release

Availability Links
NO
9.2. Dissemination format - Publications

  Availability Links
Publications Electronic

http://www.cso.ie/en/releasesandpublications/er/clsjf/cropsandlivestocksurveyjunefinal2016/

Publications in English Electronic

http://www.cso.ie/en/releasesandpublications/er/clsjf/cropsandlivestocksurveyjunefinal2016/

9.3. Dissemination format - online database

Data tables - consultations

not applicable


9.3.1. Data tables - consultations

not applicable

9.4. Dissemination format - microdata access

Availability Links
NO
9.5. Dissemination format - other

Not applicable.

9.6. Documentation on methodology

9.7. Quality management - documentation

Not applicable.

9.7.1. Metadata completeness - rate

Not applicable.

9.7.2. Metadata - consultations

Not applicable.


10. Cost and Burden Top

Efficiency gains if compared to the previous reference year (2013)
If other, which?
Burden reduction measures since the previous reference year  Less variables surveyed
Less respondents
Multiple use of the collected data
More user-friendly questionnaires
If other, which?


11. Confidentiality Top
Restricted from publication
11.1. Confidentiality - policy
Restricted from publication
11.2. Confidentiality - data treatment
Restricted from publication


12. Comment Top

As almost all of the annual crop variables are provided by IACS dataset, the June Survey is mainly used to collect proportional breakdowns of areas already collected in IACS, e.g. area under temporary vs permanent grass.


Related metadata Top


Annexes Top
ACS Quality Report - List of Sources