Crop production (apro_cp)

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

Compiling agency: Federal Statistical Office


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: Eurostat user support

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1. Contact Top
1.1. Contact organisation

Federal Statistical Office
1.2. Contact organisation unit

Sektion Wirtschaftsstruktur und Analyse, WSA
Dienststelle Land- und Forstwirtschaft, LFW
1.5. Contact mail address

Espace de l'Europe 10, 2010 Neuchâtel


2. Statistical presentation Top
2.1. Data description

Annual crop statistics provide statistics on the area under

  • main arable crops,
  • vegetables and
  • permanent crops and
  • production and
  • yield levels. 

The statistics are collected from a wide variety of sources:

  • surveys,
  • administrative sources,
  • 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 for some crops also regional data exist (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
3.1. Source data

  Source 1 Source 2 Source 3 Source 4
Have new data sources been introduced since the previous Quality Report?       
If yes, which new data sources have been introduced since the previous quality report?
Type of source?
To which Table (Reg 543/2009) do they contribute?
Have some data sources been dropped since the previous Quality Report?      
Which data sources have been dropped since the previous quality report?
Type of source?
Why have they been dropped?
Additional comments


Data sources: Please indicate the data sources which were used for the reference year on which is reported

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

Area panel-statistics
Final area under cultivation Administrative data

Farm structure survey
Production Survey
Expert estimate

Production panel-survey
Yield Survey
Expert estimate

Production panel-survey
Non-existing and non-significant crops Administrative data

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

data from previous year
Final harvested area Census

Vegetable surfaces/production
Production Census

Vegetable surfaces/production

 
Non-existing and non-significant crops Other
Table 3: Permanent crops      
Early estimates for production area Other

data from previous year
Final production area Census

Surfaces for permanent fruit cultures
Production Census

Surfaces for permanent fruit cultures
Non-existing and non-significant crops Census
Table 4: Agricultural land use      
Main area Administrative data

Farm structure survey
Non-existing and non-significant crops Administrative data

Farm structure survey
Total number of different data sources

2

    
Additional comments    


Which method is used for calculating the yield for main arable crops? yield is surveyed in the field and production volume is assessed on the basis of the yield
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

Farm structure survey

Vegetable surfaces/production

Surfaces for permanent fruit cultures

Permanent crop yield

Permanent grassland in alpine area
Planning (month-month/year)
Preparation (month-month/year)

March

March

March

March

March
Data collection (month-month/year)
Quality control (month-month/year)

Jan-Feb

Jan-Feb

Jan-Feb

Jan-Feb

Jan-Feb
Data analysis (month-month/year)

May-June

May-June

May-June

May-June

May-June
Dissemination (month-month/year)

April
If there were delays, what were the reasons?
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? NO
Are there differences between the national methodology and the methodology described in the Handbook concerning e.g. the item and aggregate calculations? NO
Are special estimation/calculation methods used for main crops from arable land? NO
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

for the permanent grassland in alpine area we have no data collection. There we do a estiamtion with the area statistics
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).

data is based on administrative sources which are used for the payment of subsidies
Is the data collection based on holdings? YES
If yes, how the holdings were identified? Identifier of the holder
If not, on which unit the data collection is based on?
When was last update of the holding register? (month/year)

every year
Was a threshold applied? YES
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 %)

< 1%
Dried pulses and protein crops (in %)

< 1%
Root crops (in %)

< 1%
Oilseeds (in %)

< 1%
Other industrial crops (included all industrial crops besides oilseeds)  (in %)

< 1%
Plants harvested green from arable land (in %)

< 1%
Total vegetables, melons and strawberries (in %)

< 1%
Cultivated mushrooms (in %)

< 1%
Total permanent crops (in %)

< 1%
Fruit trees (in %)

< 1%
Berries (in %)

< 1%
Nut trees (in %)

< 1%
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

Vegetable surfaces/production

Surfaces for permanent fruit cultures

Permanent crop yield

Arable crop yield
Which survey method was used? Other On-line electronic questionnaire filled in by respondent Other Other
If 'other', please specify

different survey methods, depending on the county which is responsible for the specific farm.

Paper/electronical survey on level of producers, traders, and cooperatives

Paper/electronical survey
Please provide a link to the questionnaire

http://members.swissfruit.ch/user/login?destination=/node/3184 the tool for data entry is only open for users.

Qustionaries are sent by E-mail and are personalised
Data entry method, if paper questionnaires? Manual
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

Coordinated agricultural farm-survey
Description

Annual survey that is principally used for subsidies-payments. It’s a full survey that is mandatory for all Swiss farms.
Data owner (organisation)

Swiss federal office of statistics
Update frequency Once per year or more often
Reference date (month/year)

01.2016
Legal basis
  • Federal Statistics Act (FStatA) of 9 October 1992;
  • Federal Act on Agriculture (Agriculture Act, AgricA) of 29 April 1998;
  • Federal Act on Data Protection of 19 June 1992 (FADP);
  • Ordinance on Agricultural Terminology and Recognition of Types of Farming;
  • Ordinance on Information Systems in the Field of Agriculture of 23 October 2013;
  • Ordinance on the Evaluation and Sustainability of Agriculture of 7 December 1998.
Reporting unit

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

Unique code
Percentage of mismatches (%)

0%
How were the mismatches handled?
Degree of coverage (holdings, e.g. 80%)

100%
Degree of completeness (variables, e.g. 60%)

100%
If not complete, which other sources were used ?
Were the data used for sample frame?
Data used for other purposes, which?

for calculation of subsidies payments
Which variables were taken from administrative sources?

We consider all data out of this survey as administrative data. The survey is mandatory for the payment of subsidies.
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?
What were the possible limitations, drawbacks of using the data from administrative source(s)?


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

Permanent grassland in alpine area
Data owner (organisation)

FSO
Update frequency (e.g. 1 year or 6 months) Yearly
Reference date (Month/Year  e.g. 1/16 - 8/16)
Legal basis
Use purpose of the estimates?
What kind of expertise the experts have?
What kind of estimation methods were used?

distribution of the permanent grassland to the different NUTS 2 region regarding to the ammount of surface.
Were there any differences in the definition of the variables between the experts' estimates and those described in the Regulation?
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?
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
Outliers
Is the data cross-validated against an other dataset? NO
If yes, which kind of dataset?
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 the previous quality report? Stable Improvement Stable Stable Stable
Is there a quality management process in place for crop statistics? YES        
If, yes, what are the components?

The normal annual quality check we do for production of our data. Eurostat data are aggregates of our annual, national statistics

        
Is there a Quality Report available? NO        
If yes, please provide a link(s)        
To which data source(s) is it linked?
       
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? Further automation        
If, other, please specify        
Additional comments        
4.2. Quality management - assessment

See the European level Quality Report.


5. Relevance Top
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
5.3. Completeness

See the European level Quality Report


6. Accuracy and reliability Top
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
Sampling basis?
If 'other', please specify
Sampling method?
If stratified, number of strata?
If stratified, stratification basis?
If 'other', please specify
Size of total population
Size of sample
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


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

Switzerland does not carry out surveys only for Eurostat purposes. All data delivered to Eurostat are from secondary use and are prepared for Eurostat categories. There are many different partners, providing data for Eurostat demand.

           
6.3. Non-sampling error
6.3.1. Coverage error

Over-coverage - rate


Common units - proportion


  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
Error type
Degree of bias caused by coverage errors
What were the reasons for coverage errors?
Which actions were taken for reducing the error or to correct the statistics?
Additional comments
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
Was the questionnaire based on usual concepts for respondents?
Number of surveys already performed with the current questionnaire (or a slightly amended version of it)?
Preparatory (field) testing of the questionnaire?
Number of units participating in the tests? 
Explanatory notes/handbook for surveyors/respondents? 
On-line FAQ or Hot-line support for surveyors/respondents?
Were pre-filled questionnaires used?
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?
If yes, describe the actions and their impact
6.3.3. Non response error

Unit non-response - rate


Item non-response - rate


  Survey 1 Survey 2 Survey 3 Survey 4 Survey 5 Survey 6 Survey 7
Name
Unit level non-response rate (in %)
Item level non-response rate (in %)              
               - Min% / item
               - Max% / item
               - Overall%
Was the non-response been treated ?
Which actions were taken to reduce the impact of non-response?
Which items had a high item-level non-response rate? 
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?
Which tools were used for correcting the data?
Which organisation did the corrections?
Additional comments
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

No data revision on national level
6.6. Data revision - practice

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?

2

2

2

2

2

2

0

0

0

0

0

0

0

1

0
How many of them are forecasts (releases before the harvest)?

1

1

1

1

1

1
When was the first  forecasting published for the crop year on which is reported? (day/month/year) 01/02/2020 01/02/2020 01/02/2020 01/02/2020 01/02/2020 01/02/2020
When were the final results published for the crop year on which is reported? (day/month/year) 31/03/2021 31/03/2021 31/03/2021 31/03/2021 31/03/2021 31/03/2021
Additional comments
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
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


  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 in the previous 5 years? 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
8.3. Coherence - cross domain

With which other data sources the crop statistics data have been compared?  None
If others, which?
If no comparisons have been made, why not?

No comparisions becuase many data have the same source. Farmstructure survey and Crop-statistics are on a national level combined with each other.

Estimations for the surface and the survey for yield are primary sources and not part of FSS.

 


Differences between ACS and other data sources (%)

Results of comparisons FSS 2016 Orchard survey 2017 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

No sub-annual statistics.
8.5. Coherence - National Accounts

Not applicable.
8.6. Coherence - internal

Not applicable.


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

Availability Links
YES

https://www.bfs.admin.ch/bfs/de/home/statistiken/land-forstwirtschaft/landwirtschaft.html
9.2. Dissemination format - Publications

  Availability Links
Publications Electronic

https://www.bfs.admin.ch/bfs/de/home/statistiken/land-forstwirtschaft/landwirtschaft.assetdetail.2348889.html
Publications in English None
9.3. Dissemination format - online database

Data tables - consultations


  Availability Links
On-line database accessible to users NO
Website National language

https://www.pxweb.bfs.admin.ch/default.aspx?px_language=de
9.4. Dissemination format - microdata access

Availability Links
NO
9.5. Dissemination format - other

Not applicable.
9.6. Documentation on methodology

  Availability Links
Methodological report None
Quality Report None
Metadata None
Additional comments  
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 quality report? Increased use of administrative data
If other, which?
Burden reduction measures since the previous reference year  Multiple use of the collected data
If other, which?


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


12. Comment Top


Related metadata Top


Annexes Top