Crop production (apro_cp)

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

Compiling agency: Service d'Economie Rurale

Time Dimension: 2016-A0

Data Provider: LU6

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

Service d'Economie Rurale

1.2. Contact organisation unit

Division des statistiques agricoles

1.5. Contact mail address

Service d'Economie Rurale

Division des statistiques agricoles

B.P. 2102

L-1021 Luxembourg


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. All data are collected at national level.

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 (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)?      
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 Administrative data

IACS

Final area under cultivation Administrative data

IACS

Production Other

Calculation

Yield Survey
Other

Harvest Inventory

Test fields

Potato producer organisation

Non-existing and non-significant crops Administrative data

IACS

Table 2: Vegetables, melons and strawberries       
Early estimates for harvested areas
Final harvested area Expert estimate

Fruit and vegetable expert

Production Expert estimate

Fruit and vegetable expert

Non-existing and non-significant crops Expert estimate

Fruit and vegetable expert

Table 3: Permanent crops      
Early estimates for production area
Final production area Administrative data
Expert estimate

Vineyard register

Fruit and vegetable expert

Production Administrative data
Expert estimate

Vineyard register

Fruit and vegetable expert

Non-existing and non-significant crops Expert estimate

Fruit and vegetable expert

Table 4: Agricultural land use      
Main area
Non-existing and non-significant crops Administrative data

IACS

Total number of different data sources

8

   
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

IACS

Harvest inventory

Test fields

Potato producer organisation

Fruit and vegetable expert

Vineyard register

Production estimates

Humidity

Planning (month-month/year)

10/2015

07/2016

07/2016

07/2016

07/2016

09/2016

08/2016

11/2016

Preparation (month-month/year)

03/2016

07/2016

07/2016

07/2016

07/2016

09-10/2016

09/2016

11/2016

Data collection (month-month/year)

05/2016

08-11/2016

08-11/2016

08-11/2016

08-12/2016

11-12/2016

09/2016

11-12/2016

Quality control (month-month/year)

07/2016

01/2017

01/2017

01/2017

01/2017

12/2016

09/2016

 

12/2016

Data analysis (month-month/year)

08/2016

01/2017

01/2017

01/2017

01/2017

12/2016

09/2016

12/2016

Dissemination (month-month/year)


09/2016

02/2017

01/2017

02/2017

03/2017

12/2016

09/2016

01/2017

If there were delays, what were the reasons?

expert not reliable

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? NO
Do national crop item definitions differ from the definitions in the Handbook  (D-flagged data)? YES  
In case yes, how do they differ? ( list all items and explanations)

P1300 Sweet lupins is included in P9000 Other dry pulses and protein crops n.e.c.
I1120 Sunflower seed and I1130 Soya are included in I1190 Other oilseed crops n.e.c.

In case data are delivered for one of the items below, describe the crop species included in the item: C1900 - Other cereals n.e.c. (buckwheat, millet, etc.)
P9000 - Other dry pulses and protein crops n.e.c.
R9000 - Other root crops n.e.c.
I1190 -Other oilseed crops n.e.c
I9000 - Other industrial crops n.e.c.
G9100- Other cereals harvested green (excluding green maize)

C1900: mix of cereals and leguminous plants wih > 60% cereals + any other cereals not included elsewhere

R9000: fodder beets

I9000: turf + any other industria plants not included elsewhere

G9100: Whole crop silage (for fodder and energy)

P9000 Other dry pulses and protein crops n.e.c. is including sweet lupins and any other dry pulses and protein crops n.e.c.

 


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).

area is based on IACS (100% coverage)

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)

04/2016

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 %)
Cultivated mushrooms (in %)
Total permanent crops (in %)
Fruit trees (in %)
Berries (in %)
Nut trees (in %)
Citrus fruit trees (in %)
Vineyards (in %)

<1%

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

harvest inventory

Humidity

Which survey method was used? Postal questionnaire filled in by respondent Other
If 'other', please specify

E-Mail list sent by respondent

Please provide a link to the questionnaire

see file attached

no link available

Data entry method, if paper questionnaires? Manual


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

Vineyard register

Description

agricultural area (crops + wine)

data on production of wine

Data owner (organisation)

Ministry of agriculture

Institut Viti-Vinicole (Ministry of agriculture)

Update frequency Once per year or more often Once per year or more often
Reference date (month/year)

04/2016

2016

Legal basis

reg CE 73/2009

reg (CE) 1308/2013

Reporting unit

agricultural holding

wine producing unit

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

holding id

holding id

Percentage of mismatches (%)

0

0

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

100%

100%

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

100%

100%

If not complete, which other sources were used ?
How were the data used?
Validation
Directly for estimates
Validation
Directly for estimates
Data used for other purposes, which?
Which variables were taken from administrative sources?

area

quantities of wine produced

Were there any differences in the definition of the variables between the administrative source and those described in the Regulation? NO 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?

IACS is submitted to internal and EU controls assuring reliability, accuracy and coherence

internal control, EU controls

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

none

none


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

Fruit and vegetable expert

Production estimates

Data owner (organisation)

Ministry of agriculture

Ministry of agriculture

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

01/16 - 12/16

01/16 - 12/16

Legal basis
Use purpose of the estimates?

area and production of fruit and vegetables

first estimate of crop production when survey result is not yet available

non significant and non existent crops

What kind of expertise the experts have?

LU has 1 expert in fruits and vegetables who has a good knowledge of the horticultural sector of Luxembourg

agricultural expert

What kind of estimation methods were used?

estimation based on producer survey (telephone interview with the main producers), consideration of administrative data (a part of the data on area is available in IACS) and contact with the producer organisations

estimation based on administrative data (area available in IACS)

Were there any differences in the definition of the variables between the experts' estimates and those described in the Regulation? NO 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?

no assessement possible

no assessement possible

What were the possible limitations, drawbacks of using the data from expert estimate(s)?

no limitations

no limitations

Additional comments
3.4. Data validation

Which kind of data validation measures are in place? Manual
What do they target? Completeness
Outliers
Aggregate calculations
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? Stable Stable Stable Stable Stable
Is there a quality management process in place for crop statistics? NO        
If, yes, what are the components?        
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?        
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

5.3.1. Data completeness - rate

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

Harvest inventory

Sampling basis? Other
If 'other', please specify

agricultural holdings doing a farm accountancy

Sampling method? Random
If stratified, number of strata?
If stratified, stratification basis?
If 'other', please specify
Size of total population

1455 (2015)

Size of sample

448

Which methods were used to assess the sampling error?  Relative standard error
If other, which?
Which methods were used to derive the extrapolation factor?  Basic weight
If other, which?
If CV (co-efficient of variation) was calculated, please describe the calculation methods and formulas

sqrt(var(x))

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

harvest inventory

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

The intention of the survey is to collect data on crop yields, so it doesn't make any sense to indicate a CV for the cultivated area as indicated above this table

           
6.3. Non-sampling error
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

harvest inventory

Error type Under-coverage
Degree of bias caused by coverage errors None
What were the reasons for coverage errors?
Which actions were taken for reducing the error or to correct the statistics?
Additional comments

nearly a third of the population took part in the survey

nearly a third of the population took part in the survey

nearly a third of the population took part in the survey

nearly a third of the population took part in the survey

nearly a third of the population took part in the survey

nearly a third of the population took part in the survey

nearly a third of the population took part in the survey

nearly a third of the population took part in the survey

nearly a third of the population took part in the survey




 

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

harvest inventory

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)?

50

Preparatory (field) testing of the questionnaire? NO
Number of units participating in the tests? 

0

Explanatory notes/handbook for surveyors/respondents?  NO
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

0

Were some actions taken for reducing the measurement error or to correct the statistics? YES
If yes, describe the actions and their impact

systematical interview with the respondents, with possibility for the bookkeeper to adress possible errors or questions concerning the harvest inventory

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

harvest inventory

Unit level non-response rate (in %)

<1%

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

<1%

               - Max% / item

<1%

               - Overall%

<1%

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

none

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

none

Which methods were used for handling missing data?
(several answers allowed)
Follow-up interviews
Reminders
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? None
Which tools were used for correcting the data?

none

Which organisation did the corrections?

none

Additional comments

non-response is considered 0

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

 3

 3

 1

 1

 1

 1

 1

 1

nd

 1

nd

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

 2

 2

 2

 2

 2

 2

 0

 0

 0

 0

 0

 0

 0

When was  the first  forecasting published for crop year 2016? (day/month/year) 30/09/2016 30/09/2016 31/10/2016 30/09/2016 31/10/2016 30/09/2016
When were the final results published for crop year 2016? (day/month/year) 31/03/2017 31/03/2017 31/03/2017 31/03/2017 31/03/2017 31/03/2017 31/03/2017 31/03/2017 31/03/2017 31/03/2017 31/03/2017 31/03/2017 31/03/2017
Additional comments
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
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 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
8.3. Coherence - cross domain

  Data source
With which other data sources the crop statistics data have been compared?  Farm structure survey 2016
Other
If others, which?

area in crop statistics is equal to area in FSS except fruit trees and vegetables

If no comparisons have been made, why not?


Results of comparisons FSS 2016 (if available) Vineyard survey 2015 IACS Other source(s)  In case of other sources, which?
Cereals

27855 ha

 

27855

Annual crop statistics (ha)

Dried pulses and protein crops

682 ha

 

682

Annual crop statistics (ha)

Root crops

769 ha

 

769

Annual crop statistics (ha)

Oilseeds

3541 ha

 

3541

Annual crop statistics (ha)

Other industrial crops (than oilseeds)

260 ha

 

260

Annual crop statistics (ha)

Plants harvested green

28428 ha

 

28428

Annual crop statistics (ha)

Total vegetables, melons and strawberries

124 ha

 

75

Annual crop statistics (ha)

Vegetables and melons

n.a.

 

73

Annual crop statistics (ha)

Strawberries

n.a.

 

2

Annual crop statistics (ha)

Cultivated mushrooms

0

 

0

Annual crop statistics (ha)

Total permanent crops

1551 ha

 

1569

Annual crop statistics (ha)

Fruit trees

161 ha

 

300

Annual crop statistics (ha)

Berries

2 ha

 

1

Annual crop statistics (ha)

Nut trees

n.a.

 

12

Annual crop statistics (ha)

Citrus fruit trees

nd

 

0

Annual crop statistics (ha)

Vineyards

 

1250

1256

Annual crop statistics (ha)

Olive trees

nd

 

0

Annual crop statistics (ha)

If there were considerable differences, which factors explain them?

different concepts

different year (2015 vs 2016)

 
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
9.1. Dissemination format - News release

Availability Links
NO
9.2. Dissemination format - Publications

  Availability Links
Publications Electronic

http://www.ser.public.lu/statistik/pflanz_produktion/index.html

Publications in English Electronic

http://www.ser.public.lu/statistics/crop_production/index.html

9.3. Dissemination format - online database

Data tables - consultations

Not applicable


  Availability Links
On-line database accessible to users NO
Website
9.3.1. Data tables - consultations

Not applicable

9.4. Dissemination format - microdata access

Availability Links
NO
9.5. Dissemination format - other

Free : http://www.ser.public.lu/publikationen/Landwirtschaft_in_Luxbg/index.html

9.6. Documentation on methodology

  Availability Links
Methodological report None

 

Quality Report English

EUROSTAT

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 reference year (2013)
If other, which?
Burden reduction measures since the previous reference year 
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


Related metadata Top


Annexes Top
list of sources
questionnaire for harvest inventory survey