Orchard (orch)

National Reference Metadata in ESS Standard for Orchard survey Quality Report Structure (esqrsor)

Compiling agency: Swedish Board of Agriculture


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

Swedish Board of Agriculture

1.2. Contact organisation unit

Division of Statistics

1.5. Contact mail address

Swedish Board of Agriculture

SE-55182 Jönköping

Sweden


2. Statistical presentation Top
2.1. Data description

Main characteristics

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
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)

June-September 2018


National legislation

2.1.6 Is there a national legislation covering these statistics?  No
If Yes, please answer all the following questions.   
2.1.7 Name of the national legislation 
2.1.8 Link to the national legislation 
2.1.9 Responsible organisation for the national legislation 
2.1.10 Year of entry into force of the national legislation 
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. 
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? 


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

Growing of perennial crops (NACE A01.2)

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
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.

Ingrid Marie, Aroma, Discovery, Rubinola, Frida, Santana, Gravensteiner, Gloster, Alice, Katja

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

2007-2017 (every fifth year)

2.9. Base period


3. Statistical processing Top
3.1. Source data

Overall summary

3.1.1 Total number of different data sources used

1

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"

0

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

Fruktträd 2017 (Fruit Trees 2017)

3.1.8 Name of Organisation responsible

Swedish Board of Agriculture, Division of Statistics

3.1.9 Main scope

The census targeted all professional apple producers with an area of at least 0.25 hectares of horticultural production in Sweden.

3.1.10 Target fruit tree types Dessert apple trees
3.1.11 List used to build the frame
3.1.12 Any possible threshold values

The census targeted professional apple growers with utilized areas for horticultural cultivation of at least 0,25 hectares

3.1.13 Population size

278 holdings

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
3.1.32 Name of Organisation responsible
3.1.33 Contact information (email and phone)
3.1.34 Main administrative scope
3.1.35 Target fruit tree types 
3.1.36 Geospatial Coverage
3.1.37 Update frequency
3.1.38 Legal basis
3.1.39 Are you able to access directly to the micro data?
3.1.40 Are you able to check the plausibility of the data, namely by contacting directly the units?
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?
3.1.42 Please list the main differences between the administrative source and the statistical definitions and concepts
3.1.43 Is a different threshold used in the administrative source and statistical data?
3.1.44 If Yes, please specify
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

Fruktträd 2017 (Fruit Trees 2017)

3.3.2 Methods of data collection Postal questionnaire
3.3.3 If Other, please specify
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)
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
3.3.16 Extraction date
3.3.17 How easy is it to get access to the data?
3.3.18 Data transfer method
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
3.4.2 What do they target? Completeness
Consistency
Outliers
3.4.3 If Other, please specify
3.5. Data compilation
3.5.1 Describe the data compilation process

Imputations:

Non-responding holdings for which data existed for total apple plantation area for 2017 as well as plantation year and tree type distribution for 2012 were imputated based on these values.

The total number holdings for which full imputations were made was 36, representing 21% of the total estimated area.

 

Adjustments for non-response:

As non-respoding holdings did not differ significantly from responding holdings (based on average area and geographic distribution), results were weighted up by straight multiplication of all variables.

The contribution of the responding and imputated holdings to the total estimated area was 68%.

 

3.5.2 Additional comments
3.6. Adjustment

No adjustments were made


4. Quality management Top
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?

By following a set procedure based on Code of Practice criteria

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
Improve data validation
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 Top
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 Top
6.1. Accuracy - overall
6.1.1 How good is the accuracy? Good
6.1.2 What are the main factors lowering the accuracy? Non-response error
Measurement error
6.1.3 If Other, please specify
6.1.4 Additional comments

It is generally very difficult for the respondents to estimate the area and number of trees of different apple varieties. This results in low response rates and a high risk of measurement error.

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

Fruktträd 2017 (Fruit Trees 2017)

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?

Units are included in frame based on a recent census of horticultural production. Only active apple cultivators were included.

6.3.1.4 Does the sample frame include units that do not exist in practice? No
6.3.1.5 Over-coverage - rate

0%

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? Yes
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

Not applicable. Only one data source used (the census).

6.3.1.13 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 
6.3.1.14 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
Over-coverage
6.3.1.28 Does the administrative source include wrongly classified units that are out of scope?
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?
6.3.1.31 Over-coverage - rate
6.3.1.32 Impact on the data quality
Under-coverage
6.3.1.33 Does the administrative source include all units falling within the scope of this survey?
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
Misclassification 
6.3.1.37 Impact on the data quality
6.3.1.38 Additional comments
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

Fruktträd 2017 (Fruit Trees 2017)

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?

1

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?  No
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
6.3.2.10 Other actions taken for reducing the measurement error?

None

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

Fruktträd 2017 (Fruit Trees 2017)

6.3.3.2 Unit non-response - rate

46%

6.3.3.3 How do you evaluate the recorded unit non-response rate in the overall context? High
6.3.3.4 Measures taken for minimising the unit non-response Reminders
Imputation
Weighting
6.3.3.5 If Other, please specify
6.3.3.6 Item non-response rate

Cannot determine

6.3.3.7 Item non-response rate - Minimum

Cannot determine

6.3.3.8 Item non-response rate - Maximum

Cannot determine

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

Fruktträd 2017 (Fruit Trees 2017)

6.3.4.2 Imputation - rate

13% (36 of 278 holdings)

6.3.4.3 Imputation - basis Same unit in previous data
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

No modelling was used.

6.4. Seasonal adjustment

No seasonal adjustments were made. The census targeted the maximum extent of the cultivation during the reference year.

6.5. Data revision - policy

Data revisions are made when significant errors in the produced statistics are encountered. Data revision procedures follow the guidelines in the Code of Practice. 

6.6. Data revision - practice
6.6.1 Data revision - average size

Not applicable

6.6.2 Were data revisions due to conceptual changes (e.g. new definitions)  carried out since the last quality report?
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 Top
7.1. Timeliness
7.1.1 When were  the first  results for the reference period published?

09/18

7.1.2 When were  the final results for the reference period published?

09/18

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


8. Coherence and comparability Top
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

Data are fully comparable from the reference year 2007 onwards.

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
8.3.2 If Other, please specify
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  ACS area was 8% lower than the Orchard Survey area (1532 vs. 1660 ha).      
Apple trees for industrial processing  NA      
Dessert pear trees  NA      
Pear trees for industrial processing  NA      
Apricot trees  NA      
Dessert peach and nectarine trees  NA      
Peach and nectarine trees for industrial processing (including group of Pavie)  NA      
Orange trees  NA      
Small citrus fruit trees  NA      
Lemon trees  NA      
Olive trees  NA      
Table grape vines  NA      
8.3.4 If no comparisons have been made, explain why
8.3.5 Additional comments
8.4. Coherence - sub annual and annual statistics

NA

8.5. Coherence - National Accounts

National Accounts are based on the Annual Crop Production statistics, the results of which deviate only slightly from the Orchard Survey results.

8.6. Coherence - internal

All internal groupings, geographic as well as apple type groupings, are fully coherent and comparable.


9. Accessibility and clarity Top
9.1. Dissemination format - News release
9.1.1 Do you publish a news release? Yes
9.1.2 If Yes, please provide a link

http://www.jordbruksverket.se/omjordbruksverket/pressochmedia/nyhetsrum.4.4e9a8c7a160cb216910c6a37.html#/latest_news

9.2. Dissemination format - Publications
9.2.1 Do you produce a paper publication? Yes
9.2.2 If Yes, is there an English version? No
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
9.3. Dissemination format - online database
9.3.1 Data tables - consultations

Not applicable

9.3.2 Is an on-line database accessible to users? No
9.3.3 Please provide a link
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

http://www.jordbruksverket.se/omjordbruksverket/statistik/statistikomr/tradgardsodling.4.67e843d911ff9f551db80004686.html

9.6.3 Are methodological papers available? Yes
9.6.4 Please provide a link

http://www.jordbruksverket.se/omjordbruksverket/statistik/statistikomr/tradgardsodling.4.67e843d911ff9f551db80004686.html

9.6.5 Is a handbook available? Yes
9.6.6 Please provide a link

http://www.jordbruksverket.se/omjordbruksverket/statistik/statistikomr/tradgardsodling.4.67e843d911ff9f551db80004686.html

9.7. Quality management - documentation
9.7.1 Metadata completeness - rate

100%

9.7.2 Metadata - consultations

0 consultations per year

9.7.3 Is a quality report available? Yes
9.7.4 Please provide a link

http://www.jordbruksverket.se/omjordbruksverket/statistik/statistikomr/tradgardsodling.4.67e843d911ff9f551db80004686.html


10. Cost and Burden Top
10.1 Efficiency gains if compared to the previous quality report None
10.2 If Other, please specify
10.3 Burden reduction measures since the previous quality report Less variables surveyed
More user-friendly questionnaires
Less respondents
10.4 If Other, please specify


11. Confidentiality Top
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
11.2. Confidentiality - data treatment
11.2.1 Describe the procedures for ensuring confidentiality during dissemination

No detailed data provided when fewer than 3 holdings make up a subgroup.

11.2.2 Additional comments


12. Comment Top


Related metadata Top


Annexes Top
ESQRS_ANNEX_SE
Questionnaire SE Orchards 2017