Orchard (orch)

2.1.1 Describe shortly the main characteristics of the statistics	Structural orchard statistics provide data on the area, age and density of apple, pear, peach, nectarine, apricot, citrus fruit and olive orchards and vineyards producing table grapes. The statistics are collected from surveys and administrative data sources. Data are collected on national level and for some variables also at NUTS1 level. The data collection concerns countries with more than 1000 ha of area for any single fruit tree type.
2.1.2 Which of the fruit tree types are covered by the data collection?	Dessert apple trees Apple trees for industrial processing Pear trees for industrial processing Dessert pear trees
2.1.3 If Other, please specify

Reference period

2.1.4 Reference period of the data collection	2017
2.1.5 When was the data collection done (month(s) and year)	March 2017

National legislation

2.1.6 Is there a national legislation covering these statistics?	Yes
If Yes, please answer all the following questions.
2.1.7 Name of the national legislation	Lov om Danmarks Statistik (Law of Statistics Denmark)
2.1.8 Link to the national legislation	https://dst.dk/en/OmDS/lovgivning
2.1.9 Responsible organisation for the national legislation	Statistics Denmark
2.1.10 Year of entry into force of the national legislation	2000
2.1.11 Please indicate which variables required under EU regulation are not covered by national legislation, if any.
2.1.12 Please indicate which national definitions differ from those in the EU regulation, if any.	Coverage (All agricultural farms growing apples or pears according to IACS) differs from "Growing of perennial crops (NACE A01.2)". IACS provides the best coverage of the activities and Nace would likely lead to underestimation.
2.1.13 Please indicate which additional variables have been collected if compared to Regulation (EU) 1337/2011, if any?
2.1.14 Is there a legal obligation for respondents to reply?	Yes

Additional comments on data description

2.2. Classification system

Species and variety group classification, age and density classifications available in RAMON

2.3. Coverage - sector

All agricultural farms growing apples or pears according to IACS

2.4. Statistical concepts and definitions

See: Orchard statistics Handbook

2.4.1 Do national crop item definitions differ from the definitions in the Handbook (D-flagged data)?	No
2.4.2 If Yes, please specify the items and the differences
2.4.3 If the fruits for industrial processing are not separately surveyed, are they included in dessert fruit categories?	Yes
2.4.4 If yes, for which fruit tree types?	Apple trees Pear trees
In case data are delivered for one of the items below, describe the 10 biggest varieties included in the item:
2.4.5 Other dessert apples n.e.c.
2.4.6 Other dessert pears n.e.c.
2.4.7 Other oranges n.e.c.
2.4.8 Other small citrus fruits, including hybrids

2.5. Statistical unit

Utilised agricultural area used for the cultivation of permanent crops mentioned in point 2.1, cultivated by an agricultural holding producing entirely or mainly for the market.

2.6. Statistical population

All agricultural holdings growing entirely or mainly for the market permanent crops mentioned in point 2.1.

2.7. Reference area

2.7.1 Geographical area covered	The entire territory of the country.
2.7.2 Which special Member State territories are included?

2.8. Coverage - Time

2012 and 2017 data are available for an unlimited number of years.

2.9. Base period

3. Statistical processing

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3.1. Source data

Overall summary

3.1.1 Total number of different data sources used	2
The breakdown is as follows:
3.1.2 Total number of sources of the type "Census"	1
3.1.3 Total number of sources of the type "Sample survey"	0
3.1.4 Total number of sources of the type "Administrative source"	1
3.1.5 Total number of sources of the type "Experts"	0
3.1.6 Total number of sources of the type "Other sources"	0

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 3.1 of the annexed Excel file
3.1.7 Name/Title	Agricultural and Horticultural Survey
3.1.8 Name of Organisation responsible	Statistics Denmark
3.1.9 Main scope	The farm structure statistics include figures on number of farms, livestock and crops distributed by for instance size and geography.
3.1.10 Target fruit tree types	Dessert apple trees Dessert pear trees Apple trees for industrial processing Pear trees for industrial processing
3.1.11 List used to build the frame	The population includes all local units in the Business Register marked as active in agriculture.
3.1.12 Any possible threshold values	All producers of apples or pears according to IACS with at least 0,5 ha are included in the sample.
3.1.13 Population size	Population of holdings producing apples or pears 366 Gross population (Farm Structure Survey): 36618
3.1.14 Additional comments

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 3.1 of the annexed Excel file
3.1.15 Name/Title
3.1.16 Name of Organisation responsible
3.1.17 Main scope
3.1.18 Target fruit tree types
3.1.19 List used to build the frame
3.1.20 Any possible threshold values
3.1.21 Population size
3.1.22 Sample size
3.1.23 Sampling basis
3.1.24 If Other, please specify
3.1.25 Type of sample design
3.1.26 If Other, please specify
3.1.27 If Stratified, number of strata
3.1.28 If Stratified, stratification criteria
3.1.29 If Other, please specify
3.1.30 Additional comments

Administrative source

These questions only apply to administrative sources. If there is more than one administrative source, please describe the main source below and the additional ones in table 3.1 of the annexed Excel file
3.1.31 Name/Title	IACS
3.1.32 Name of Organisation responsible	ministry of agriculture
3.1.33 Contact information (email and phone)	https://eng.lbst.dk/
3.1.34 Main administrative scope	For subsidies (SFP)
3.1.35 Target fruit tree types	Dessert apple trees Dessert pear trees
3.1.36 Geospatial Coverage	National Regional
3.1.37 Update frequency	Annual
3.1.38 Legal basis
3.1.39 Are you able to access directly to the micro data?	No
3.1.40 Are you able to check the plausibility of the data, namely by contacting directly the units?	Yes
3.1.41 How would you assess the proximity of the definitions and concepts (including statistical units) used in the administrative source with those required in the EU regulation?	Very good
3.1.42 Please list the main differences between the administrative source and the statistical definitions and concepts	n.a.
3.1.43 Is a different threshold used in the administrative source and statistical data?	Yes
3.1.44 If Yes, please specify	0,5 ha in Census.
3.1.45 Additional comments

Experts

If there is more than one Expert source, please describe the main one below and the additional ones in table 3.1 of the annexed Excel file
3.1.46 Name/Title
3.1.47 Primary purpose
3.1.48 Target fruit tree types
3.1.49 Legal basis
3.1.50 Update frequency
3.1.51 Expert data supplier
3.1.52 If Other, please specify
3.1.53 How would you assess the quality of those data?
3.1.54 Additional comments

Other sources

If there is more than one other statistical activity, please describe the main one below and the additional ones in table 3.1 of the annexed Excel file
3.1.55 Name/Title
3.1.56 Name of Organisation
3.1.57 Primary purpose
3.1.58 Target fruit tree types
3.1.59 Data type
3.1.60 If Other, please specify
3.1.61 How would you assess the quality of those data?
3.1.62 Additional comments

3.2. Frequency of data collection

Every 5 years

3.3. Data collection

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 3.3 of the annexed Excel file
3.3.1 Name/Title	Agricultural and Horticultural Survey
3.3.2 Methods of data collection	Electronic questionnaire Other
3.3.3 If Other, please specify	Paper questionnaires (as an exception)
3.3.4 If face-to-face or telephone interview, which method is used?
3.3.5 Data entry method, if paper questionnaires?	Manual
3.3.6 Please annex the questionnaire used (if very long: please provide the hyperlink)	See annexed file.
3.3.7 Additional comments

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 3.3 of the annexed Excel file
3.3.8 Name/Title
3.3.9 Methods of data collection
3.3.10 If Other, please specify
3.3.11 If face-to-face or telephone interview, which method is used?
3.3.12 Data entry method, if paper questionnaires?
3.3.13 Please annex the questionnaire used (if very long: please provide the hyperlink)
3.3.14 Additional comments

Administrative source

These questions only apply to administrative sources. If there is more than one administrative source, please describe the main source below and the additional ones in table 3.3 of the annexed Excel file
3.3.15 Name/Title	IACS
3.3.16 Extraction date	January 2017
3.3.17 How easy is it to get access to the data?	Access granted after negotiations
3.3.18 Data transfer method	Secure online transfer.
3.3.19 Additional comments

Experts

If there is more than one other statistical activity, please describe the main one below and the additional ones in table 3.3 of the annexed Excel file
3.3.20 Name/Title
3.3.21 Methods of data collection
3.3.22 Additional comments

3.4. Data validation

3.4.1 Which kind of data validation measures are in place?	Manual Automatic
3.4.2 What do they target?	Completeness Outliers Aggregates Consistency
3.4.3 If Other, please specify

3.5. Data compilation

3.5.1 Describe the data compilation process	Data from web questionnaires are aggregated.Imputation, weighting, adjustment for non-response have not been relevant.
3.5.2 Additional comments

3.6. Adjustment

No adjustments.

4. Quality management

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4.1. Quality assurance

4.1.1 Is there a quality management system used in the organisation?	Yes
4.1.2 If yes, how is it implemented?	Periodical quality management systems. Reviews of surveys by Methodological apartment.
4.1.3 Has a peer review been carried out?	No
4.1.4 If Yes, which were the main conclusions?
4.1.5 What quality improvements are foreseen?	Further automation
4.1.6 If Other, please specify
4.1.7 Additional comments

4.2. Quality management - assessment

Development since the last 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

5. Relevance

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5.1. Relevance - User Needs

5.1.1 If certain user needs are not met, please specify which and why
5.1.2 Please specify any plans to satisfy needs more completely in the future
5.1.3 Additional comments

5.2. Relevance - User Satisfaction

5.2.1 Has a user satisfaction survey been conducted?	No
If Yes, please answer all the following questions
5.2.2 Year of the user satisfaction survey
5.2.3 How satisfied were the users?
5.2.4 Additional comments

5.3. Completeness

5.3.1 Data completeness - rate	100%
5.3.2 If not complete, which characteristics are missing?
5.3.3 Additional comments

6. Accuracy and reliability

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6.1. Accuracy - overall

6.1.1 How good is the accuracy?	Good
6.1.2 What are the main factors lowering the accuracy?	Measurement error
6.1.3 If Other, please specify
6.1.4 Additional comments

6.2. Sampling error

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.2 of the annexed Excel file

6.2.1 Name/Title

6.2.2 Methods used to assess the sampling error

6.2.3 If Other, please specify

6.2.4 Methods used to derive the extrapolation factor

6.2.5 If Other, please specify

6.2.6 If coefficients of variation are calculated, please describe the calculation methods and formulas

6.2.7 Sampling error - indicators

Please provide the coefficients of variation in %

	CV (%)
Dessert apple trees
Apple trees for industrial processing
Dessert pear trees
Pear trees for industrial processing
Apricot trees
Dessert peach and nectarine trees
Peach and nectarine trees for industrial processing (including group of Pavie)
Orange trees
Small citrus fruit trees
Lemon trees
Olive trees
Table grape vines

6.2.8 Additional comments

6.3. Non-sampling error

See sections below.

6.3.1. Coverage error

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file
6.3.1.1 Name/Title	Agricultural and Horticultural Survey
Over-coverage
6.3.1.2 Does the sample frame include wrongly classified units that are out of scope?	No
6.3.1.3 What methods are used to detect the out-of scope units?
6.3.1.4 Does the sample frame include units that do not exist in practice?	No
6.3.1.5 Over-coverage - rate
6.3.1.6 Impact on the data quality	None
Under-coverage
6.3.1.7 Does the sample frame include all units falling within the scope of this survey?	No
6.3.1.8 If Not, which units are not included?
6.3.1.9 How large do you estimate the proportion of those units? (%)
6.3.1.10 Impact on the data quality	None
Misclassification
6.3.1.11 Impact on the data quality	None
Common units
6.3.1.12 Common units - proportion	100% of the units in the census are covered by administrative sources.
6.3.1.13 Additional comments	Very small holdnings are not surveyed - as accepted in the regulation.

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file
6.3.1.14 Name/Title
Over-coverage
6.3.1.15 Does the sample frame include wrongly classified units that are out of scope?
6.3.1.16 What methods are used to detect the out-of scope units?
6.3.1.17 Does the sample frame include units that do not exist in practice?
6.3.1.18 Over-coverage - rate
6.3.1.19 Impact on the data quality
Under-coverage
6.3.1.20 Does the sample frame include all units falling within the scope of this survey?
6.3.1.21 If Not, which units are not included?
6.3.1.22 How large do you estimate the proportion of those units? (%)
6.3.1.23 Impact on the data quality
Misclassification
6.3.1.24 Impact on the data quality
Common units
6.3.1.25 Common units - proportion
6.3.1.26 Additional comments

Administrative data

These questions only apply to administrative sources. If there is more than one administrative source, please describe the main source below and the additional ones in table 6.3 of the annexed Excel file
6.3.1.27 Name/Title of the administrative source	IACS
Over-coverage
6.3.1.28 Does the administrative source include wrongly classified units that are out of scope?	No
6.3.1.29 What methods are used to detect the out-of scope units?
6.3.1.30 Does the administrative source include units that do not exist in practice?	No
6.3.1.31 Over-coverage - rate	0%
6.3.1.32 Impact on the data quality	None
Under-coverage
6.3.1.33 Does the administrative source include all units falling within the scope of this survey?	Yes
6.3.1.34 If Not, which units are not included?
6.3.1.35 How large do you estimate the proportion of those units? (%)
6.3.1.36 Impact on the data quality	None
Misclassification
6.3.1.37 Impact on the data quality	None
6.3.1.38 Additional comments	Very small holdnings are not surveyed - as accepted in the regulation.

6.3.2. Measurement error

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file
6.3.2.1 Name/Title	Agricultural and Horticultural Survey
6.3.2.2 Is the questionnaire based on usual concepts for respondents?	Yes
6.3.2.3 Number of censuses already performed with the current questionnaire?	4 (at least)
6.3.2.4 Preparatory testing of the questionnaire?	No
6.3.2.5 Number of units participating in the tests?
6.3.2.6 Explanatory notes/handbook for surveyors/respondents?	Yes
6.3.2.7 On-line FAQ or Hot-line support for surveyors/respondents?	Yes
6.3.2.8 Are there pre-filled questions?	No
6.3.2.9 Percentage of pre-filled questions out of total number of questions	0
6.3.2.10 Other actions taken for reducing the measurement error?	Yes, only standard validation actions as checking the sum of areas with information on total area for apples and pears, respectively
6.3.2.11 Additional comments

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file
6.3.2.12 Name/Title
6.3.2.13 Is the questionnaire based on usual concepts for respondents?
6.3.2.14 Number of surveys already performed with the current questionnaire?
6.3.2.15 Preparatory testing of the questionnaire?
6.3.2.16 Number of units participating in the tests?
6.3.2.17 Explanatory notes/handbook for surveyors/respondents?
6.3.2.18 On-line FAQ or Hot-line support for surveyors/respondents?
6.3.2.19 Are there pre-filled questions?
6.3.2.20 Percentage of pre-filled questions out of total number of questions
6.3.2.21 Other actions taken for reducing the measurement error?
6.3.2.22 Additional comments

6.3.3. Non response error

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file
6.3.3.1 Name/Title of the survey	Agricultural and Horticultural Survey
6.3.3.2 Unit non-response - rate	None.
6.3.3.3 How do you evaluate the recorded unit non-response rate in the overall context?	Very low
6.3.3.4 Measures taken for minimising the unit non-response	Follow-up interviews Legal actions
6.3.3.5 If Other, please specify
6.3.3.6 Item non-response rate	Low
6.3.3.7 Item non-response rate - Minimum	n.a.
6.3.3.8 Item non-response rate - Maximum	n.a.
6.3.3.9 Which items had a high item non-response rate?	Some problems on dividing areas and trees into age groups as this knowledge not always exists
6.3.3.10 Additional comments

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file
6.3.3.11 Name/Title of the survey
6.3.3.12 Unit non-response - rate
6.3.3.13 How do you evaluate the recorded unit non-response rate in the overall context?
6.3.3.14 Measures taken for minimising the unit non-response
6.3.3.15 If Other, please specify
6.3.3.16 Item non-response rate
6.3.3.17 Item non-response rate - Minimum
6.3.3.18 Item non-response rate - Maximum
6.3.3.19 Which items had a high item non-response rate?
6.3.3.20 Additional comments

6.3.4. Processing error

Census

These questions only apply to censuses. If there is more than one census, please describe the main census below and the additional ones in table 6.3 of the annexed Excel file
6.3.4.1 Name/Title	Agricultural and Horticultural Survey
6.3.4.2 Imputation - rate	0%
6.3.4.3 Imputation - basis
6.3.4.4 If Other, please specify
6.3.4.5 Additional comments

Sample survey

These questions only apply to surveys. If there is more than one survey, please describe the main survey below and the additional ones in table 6.3 of the annexed Excel file
6.3.4.6 Name/Title
6.3.4.7 Imputation - rate
6.3.4.8 Imputation - basis
6.3.4.9 If Other, please specify
6.3.4.10 How do you evaluate the impact of imputation on Coefficients of Variation?
6.3.4.11 Additionnal comments

6.3.5. Model assumption error

N.a.

6.4. Seasonal adjustment

N.a.

6.5. Data revision - policy

Annexes:
Revision Policy in Statistics Denmark

6.6. Data revision - practice

6.6.1 Data revision - average size	None.
6.6.2 Were data revisions due to conceptual changes (e.g. new definitions) carried out since the last quality report?	No
6.6.3 What was the main reason for the revisions?
6.6.4 How do you evaluate the impact of the revisions?
6.6.5 Additional comments

7. Timeliness and punctuality

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7.1. Timeliness

7.1.1 When were the first results for the reference period published?	25nd January 2018
7.1.2 When were the final results for the reference period published?	25nd January 2018
7.1.3 Reasons for possible long production times?

7.2. Punctuality

7.2.1 Were data released nationally according to a pre-announced schedule (Release Calendar)?	Yes
7.2.2 If Yes, were data released on the target date?	Yes
7.2.3 If No, reasons for delays?
7.2.4 Number of days between the national release date of data and the target date	0

8. Coherence and comparability

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8.1. Comparability - geographical

To be assessed by Eurostat

8.1.1. Asymmetry for mirror flow statistics - coefficient

8.2. Comparability - over time

8.2.1 Length of comparable time series	2002-
8.2.2 Have there been major breaks in the time series?	No
8.2.3 If Yes, please specify the year of break and the reason
8.2.4 Additional comments

8.3. Coherence - cross domain

8.3.1 With which other national data sources have the data been compared?

Annual crop statistics 2017
FSS 2016

8.3.2 If Other, please specify

Administrative data

8.3.3 Describe briefly the results of comparisons

Results should be expressed as percentage deviation from the corresponding areas in the orchard survey.

	Annual Crop Statistics (2017)	FSS (2016)	IACS	Other source
Dessert apple trees	0%	0%	<2%
Apple trees for industrial processing	0%	0%	<2%
Dessert pear trees	0%	0%	<2%
Pear trees for industrial processing	0%	0%	<2%
Apricot trees
Dessert peach and nectarine trees
Peach and nectarine trees for industrial processing (including group of Pavie)
Orange trees
Small citrus fruit trees
Lemon trees
Olive trees
Table grape vines

8.3.4 If no comparisons have been made, explain why

8.3.5 Additional comments

The census is integrated in FSS. The frame build on IACS.

8.4. Coherence - sub annual and annual statistics

8.5. Coherence - National Accounts

8.6. Coherence - internal

9. Accessibility and clarity

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9.1. Dissemination format - News release

9.1.1 Do you publish a news release?	No
9.1.2 If Yes, please provide a link

9.2. Dissemination format - Publications

9.2.1 Do you produce a paper publication?	No
9.2.2 If Yes, is there an English version?
9.2.3 Do you produce an electronic publication?	Yes
9.2.4 If Yes, is there an English version?	No
9.2.5 Please provide a link	https://www.dst.dk/da/Statistik/nyt/NytHtml?cid=18796

9.3. Dissemination format - online database

9.3.1 Data tables - consultations	Not available
9.3.2 Is an on-line database accessible to users?	Yes
9.3.3 Please provide a link	http://statistikbanken.dk/statbank5a/default.asp?w=2021

9.4. Dissemination format - microdata access

9.4.1 Are micro-data accessible to users?	No
9.4.2 Please provide a link

9.5. Dissemination format - other

9.6. Documentation on methodology

9.6.1 Are national reference metadata files available?	Yes
9.6.2 Please provide a link	https://dst.dk/en/Statistik/dokumentation/documentationofstatistics/agricultural-and-horticultural-survey
9.6.3 Are methodological papers available?	No
9.6.4 Please provide a link
9.6.5 Is a handbook available?	No
9.6.6 Please provide a link

9.7. Quality management - documentation

9.7.1 Metadata completeness - rate	N.a.
9.7.2 Metadata - consultations	N.a.
9.7.3 Is a quality report available?	Yes
9.7.4 Please provide a link	https://www.dst.dk/en/Statistik/dokumentation/documentationofstatistics/agricultural-and-horticultural-survey

10. Cost and Burden

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10.1 Efficiency gains if compared to the previous quality report	Other
10.2 If Other, please specify	Data on production of apples and pears were included in the survey for the benefit of crop statistics and collected together with the FSS survey.
10.3 Burden reduction measures since the previous quality report	Other
10.4 If Other, please specify	Data on production of apples and pears were included in the survey for the benefit of crop statistics and collected together with the FSS survey.

11. Confidentiality

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11.1. Confidentiality - policy

11.1.1 Are confidential data transmitted to Eurostat?	No
11.1.2 If yes, are they confidential in the sense of Reg. (EC) 223/2009?
11.1.3 Describe the data confidentiality policy in place	https://www.dst.dk/ext/502998790/0/formid/Data-Confidentiality-Policy-at-Statistics-Denmark--pdf

11.2. Confidentiality - data treatment

11.2.1 Describe the procedures for ensuring confidentiality during dissemination	When designing statistical tables the aim is to secure that no table cells contain very few farm, less than 5.
11.2.2 Additional comments

12. Comment

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Related metadata

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Annexes

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ESQRS_ANNEX_DK
FSS Questionnaire