Orchard (orch)

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

Compiling agency: Federal Statistical Office of Germany


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)
 



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1. Contact Top
1.1. Contact organisation

Federal Statistical Office of Germany
1.2. Contact organisation unit

Division G1: Agriculture and Forestry, Fisheries

Section G101: Horticulture and Forestry
1.5. Contact mail address

Graurheindorfer Straße 198, 53117 Bonn, Germany


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
Apple trees for industrial processing
Dessert pear trees
Pear trees for industrial processing
Other
2.1.3 If Other, please specify

Sweet cherries, sour cherries, all kinds of plums and other tree fruits (e.g. apricots, peaches, walnuts)


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)

January until June 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 

Agricultural Statistics Act (Agrarstatistikgesetz - AgrStatG)
2.1.8 Link to the national legislation 

https://www.destatis.de/DE/Methoden/Rechtsgrundlagen/Statistikbereiche/Inhalte/115_AgrStatG.pdf?__blob=publicationFile

http://www.gesetze-im-internet.de/agrstatg/AgrStatG.pdf
2.1.9 Responsible organisation for the national legislation 

Federal Ministry of Food and Agriculture
2.1.10 Year of entry into force of the national legislation 

17.12.2009
2.1.11 Please indicate which variables required under EU regulation are not covered by national legislation, if any.

None
2.1.12 Please indicate which national definitions differ from those in the EU regulation, if any. 

None
2.1.13 Please indicate which additional variables have been collected if compared to Regulation (EU) 1337/2011, if any?

Sweet and sour cherries, all kind of plums, other tree fruits; number of holdings and trees, use of other fruits than apples and pears, organic production.
2.1.14 Is there a legal obligation for respondents to reply?  Yes


Additional comments on data description

The first version of the national legislation was installed on 15.03.1989, the current legislation was newly formulated on 17.12.2009 and latest amended concerning orchard survey on 05.12.2014. 
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? No
2.4.4 If yes, for which fruit tree types?
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.

Topaz (815,5 ha), Kanzi (670,2 ha), Delbarestivale (460,3 ha), Rubinette (364,0 ha), Wellant (316,7 ha), Santana (200,8 ha), Diwa (140,4 ha), Gloster (104,8 ha), Rubens (62,7 ha), Mairac (59,7 ha), Nicigreen 50,6 ha), Gravensteiner (50,4 ha).   
2.4.6 Other dessert pears n.e.c.

Alexander Lucas (362,2 ha), Nojabrskaja (115,4 ha), Köstliche von Charneu (61,1 ha), Concorde (42,8 ha), Clapps Liebling (31,0 ha), Condo (19,1 ha), Gute Luise (18,0 ha), Gellerts Butterbirne (12,1 ha).
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 those permanent crops mentioned under 2.1.2 and 2.1.3 entirely or mainly for the market. In DE all units are included in the census, which produce tree fruits for the market on an area of at least 0,5 Hectar (threshold).
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

Data is available since 1972. Censuses were carried out every 5 years from 1972 to 2017.

The thresholds for the surveyed areas of fruit tree production changed from 0,1 ha in 1972 to 0,15 ha for 1977 - 1997, then to 0,3 ha for the surveys in 2002 and 2007 and since 2012 the threshold is 0,5 ha.   
2.9. Base period


3. Statistical processing Top
3.1. Source data

Overall summary

3.1.1 Total number of different data sources used

One
The breakdown is as follows: 
3.1.2 Total number of sources of the type "Census"

One
3.1.3 Total number of sources of the type "Sample survey"

None
3.1.4 Total number of sources of the type "Administrative source"

None
3.1.5 Total number of sources of the type "Experts"

None
3.1.6 Total number of sources of the type "Other sources"

None


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

"Baumobstanbauerhebung"
3.1.8 Name of Organisation responsible

Federal statistical office and statistical offices of the Länder.
3.1.9 Main scope

All agricultural holdings growing permanent crops mentioned in point 2.1 entirely or mainly for the market. In DE all units are included in the census, which produce tree fruits for the market on an area of at least 0,5 Hectar (threshold).
3.1.10 Target fruit tree types Dessert apple trees
Apple trees for industrial processing
Dessert pear trees
Pear trees for industrial processing
Other
3.1.11 List used to build the frame

farm register
3.1.12 Any possible threshold values

In DE all units are included in the census, which produce tree fruits for the market on an area of at least 0,5 Hectar (threshold).
3.1.13 Population size

In DE 2017 existed 7167 tree fruit producers according to the target statistical population requested in the national legislation.

According to the European legislation 5682 apple producers were counted and 3385 producers of pears.
3.1.14 Additional comments

Administrative sources were used to update the farm register.


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

"Baumobstanbauerhebung"
3.3.2 Methods of data collection Postal questionnaire
Electronic questionnaire
Telephone interview
3.3.3 If Other, please specify
3.3.4 If face-to-face or telephone interview, which method is used? Electronic questionnaire
3.3.5 Data entry method, if paper questionnaires? Manual
Optical
3.3.6 Please annex the questionnaire used (if very long: please provide the hyperlink)

https://www.destatis.de/DE/Themen/Branchen-Unternehmen/Landwirtschaft-Forstwirtschaft-Fischerei/Obst-Gemuese-Gartenbau/Publikationen/Downloads-Obst/baumobstflaechen-2030314179004.pdf?__blob=publicationFile&v=3  (starting from page 162).
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
Automatic
3.4.2 What do they target? Completeness
Outliers
Aggregates
Consistency
Data flagging
Other
3.4.3 If Other, please specify

Coherence, population/threshold check, time series check
3.5. Data compilation
3.5.1 Describe the data compilation process

The predominant parts of the answers were collected by using electronic questionnaires filled in by respondents themselves. Only few replies were collected by postal questionnaires or phone calls. This first step of the survey is usually done by the statistical offices of the Länder. They also practice the direct validation of the questionnaires (which is harmonized on national level) and stay in contact with the farmers. The Länder results are joined up in a common database, where the confidentiality rules are applied in a synchronised way. After that the tables for publication have been produced.
3.5.2 Additional comments
3.6. Adjustment

All kinds of adjustmend of the data (when identifying outliers, missing data, etc.) were usually done by contacting the fruit tree farmers.

In exceptional cases where this was not possible, the data were aligned to the prior orchard survey or to the data of one of the annual crop surveys if the fruit tree producer was included in the sample.


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?

Basis is a handbook of quality guidelines and after realisation of a survey the quality guidelines are checked for the whole process including those of the federal office and the offices of the Länder.
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?
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 Improvement
4.2.5 Comparability Improvement
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

None
5.1.2 Please specify any plans to satisfy needs more completely in the future

There are no plans at the moment.
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

Every few years user conferences are realized and there is a steady contact to the most importent Ministries (federal and Länder level) and data users, which are mainly interested in the data. 
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? Very good
6.1.2 What are the main factors lowering the accuracy? Other
6.1.3 If Other, please specify

May be that in very few cases the farmers did not insert all fruit varieties of dessert apples/pears, but instead put them to the fruit trees for industrial processing because of less effort.
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

"Baumobstanbauerhebung"
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?

Automatic validation rules.
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

None
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

"Baumobstanbauerhebung"
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?

0
6.3.2.4 Preparatory testing of the questionnaire? Yes
6.3.2.5 Number of units participating in the tests? 

4
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

Zero
6.3.2.10 Other actions taken for reducing the measurement error?

Explanations in the questionnaire, consistency checks, regulary updates of the farm register by using also administrative data (IACS, agricultural insurance companies, etc).

 
6.3.2.11 Additional comments

Minor inaccuracies are expected for net and gross area results, as this is often differently interpreted by the fruit tree farmers.


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

"Baumobstanbauerhebung"
6.3.3.2 Unit non-response - rate

0,5%
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
Reminders
Legal actions
Imputation
6.3.3.5 If Other, please specify
6.3.3.6 Item non-response rate

Very low.
6.3.3.7 Item non-response rate - Minimum

0%
6.3.3.8 Item non-response rate - Maximum

5%
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

"Baumobstanbauerhebung"
6.3.4.2 Imputation - rate

Very low.
6.3.4.3 Imputation - basis Similar units
Same unit in previous data
Other sources
6.3.4.4 If Other, please specify

Survey on agricultural land use (yearly).
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

Not relevant.
6.4. Seasonal adjustment

None.
6.5. Data revision - policy

Up to now no data revisions needed.
6.6. Data revision - practice
6.6.1 Data revision - average size

No revisions.
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 Top
7.1. Timeliness
7.1.1 When were  the first  results for the reference period published?

15.09.2017
7.1.2 When were  the final results for the reference period published?

15.09.2017
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

Full comparable to 2012 data of the same census.

With some restrictions (threshold modifications - see item 2.8) comparable with all former censuses on fruit tree production (1972 to 2007).
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
8.3.3 Describe briefly the results of comparisons

esults 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        
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        

FSS 2016: 10 694 units of fruit tree producers and 518 units of nut producers with in total 54 885 ha of orchards (including nuts).

Crop Statistics 2017:  10 260 units of fruit tree producers and 560 units of nut producers with in total 54 400 ha of orchards (including nuts).

Both survey data indicate all farms with any production of fruit trees without threshold and no relevance to the use for the market or own use.

Compared to the target population in the orchard survey (regarding all fruit and nut trees), where 7 167 fruit tree producers with a production area of 49 934 ha were included, these data look comprehensible. According to the European legislation 5 682 apple producers with 33 981 ha and 3 385 producers of pears with 2 137 ha were counted. The diffence belongs to other fruits and nuts.
8.3.4 If no comparisons have been made, explain why
8.3.5 Additional comments
8.4. Coherence - sub annual and annual statistics

The orchard survey is used as area basis for the annual production estimation on tree fruit harvest.
8.5. Coherence - National Accounts

Not available
8.6. Coherence - internal

As the data result only from one source the data is coherent as such.


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

https://www.destatis.de/DE/PresseService/Presse/Pressemitteilungen/2017/09/PD17_328_412.html

https://www.destatis.de/EN/PressServices/Press/pr/2017/09/PE17_328_412.html
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? Yes
9.2.5 Please provide a link

https://www.destatis.de/DE/Themen/Branchen-Unternehmen/Landwirtschaft-Forstwirtschaft-Fischerei/Obst-Gemuese-Gartenbau/Publikationen/Downloads-Obst/baumobstflaechen-2030314179004.pdf?__blob=publicationFile&v=3

https://www.destatis.de/DE/Themen/Branchen-Unternehmen/Landwirtschaft-Forstwirtschaft-Fischerei/Obst-Gemuese-Gartenbau/_inhalt.html

https://www.destatis.de/DE/Themen/Branchen-Unternehmen/Landwirtschaft-Forstwirtschaft-Fischerei/Obst-Gemuese-Gartenbau/Tabellen/baumobstanbau-bundeslaender.html

https://www.destatis.de/DE/Themen/Branchen-Unternehmen/Landwirtschaft-Forstwirtschaft-Fischerei/Obst-Gemuese-Gartenbau/Tabellen/baumobstanbauerhebung.html

https://www.destatis.de/DE/Themen/Branchen-Unternehmen/Landwirtschaft-Forstwirtschaft-Fischerei/Obst-Gemuese-Gartenbau/Tabellen/flaechen-erntemengen-marktobstanbau.html

https://www.destatis.de/DE/Themen/Branchen-Unternehmen/Landwirtschaft-Forstwirtschaft-Fischerei/Obst-Gemuese-Gartenbau/Tabellen/oekologisches-obst.html

 

English (the english homepage is currently in updating process and therefore not available):

https://www.destatis.de/EN/FactsFigures/EconomicSectors/AgricultureForestryFisheries/FruitVegetablesHorticulture/Tables/2_2AreaofTreeFruits.html

https://www.destatis.de/EN/FactsFigures/EconomicSectors/AgricultureForestryFisheries/FruitVegetablesHorticulture/Tables/2_3FruitTreesCultivation.html

 
9.3. Dissemination format - online database
9.3.1 Data tables - consultations

2017: 1423
9.3.2 Is an on-line database accessible to users? Yes
9.3.3 Please provide a link

https://www-genesis.destatis.de/genesis/online/data;sid=404B0225C1D6AFC9CD675D076755C9E6.GO_1_1?operation=sprachwechsel&language=de

Dann unter:  Datenangebot -> Themen -> 41 Lamd- und Forstwirtschaft, Fischerei -> 412 Bodennutzung und Ernte -> 41231 Baumobstanbauerhebung

 

English:

https://www-genesis.destatis.de/genesis/online;sid=1E6059276AB8AD28081974861C83E12F.GO_1_1?Menu=Willkommen

Then find under:  Available data -> Themes -> 41 Agriculture, forestry, fisheries -> 412 Land use and crop production -> 41231 Orchard survey
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

Metadata are included in the publication (in German only)

https://www.destatis.de/DE/Themen/Branchen-Unternehmen/Landwirtschaft-Forstwirtschaft-Fischerei/Obst-Gemuese-Gartenbau/Publikationen/Downloads-Obst/baumobstflaechen-2030314179004.pdf?__blob=publicationFile&v=3

 

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

https://www.destatis.de/DE/Methoden/Qualitaet/Qualitaetsberichte/Land-Forstwirtschaft-Fischerei/baumobstanbauerhebung.pdf?__blob=publicationFile&v=3  (only in German)
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

100%
9.7.2 Metadata - consultations

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

https://www.destatis.de/DE/Methoden/Qualitaet/Qualitaetsberichte/Land-Forstwirtschaft-Fischerei/baumobstanbauerhebung.pdf?__blob=publicationFile&v=3  (German only)


10. Cost and Burden Top
10.1 Efficiency gains if compared to the previous quality report Further automation
Other
10.2 If Other, please specify

Improved questionnaire and automatic processing.
10.3 Burden reduction measures since the previous quality report Less variables surveyed
More user-friendly questionnaires
10.4 If Other, please specify


11. Confidentiality Top
11.1. Confidentiality - policy
11.1.1 Are confidential data transmitted to Eurostat? Yes
11.1.2 If yes, are they confidential in the sense of Reg. (EC) 223/2009? Yes
11.1.3 Describe the data confidentiality policy in place

Confidentiality in Germany was regulated by the Federal Data Protection Act. Section 5 of the Law states that persons employed in data processing shall not collect, process or use personal data without authorization (confidentiality). On taking up their duties such persons, in so far as they work for private bodies, shall be required to give an undertaking to maintain such confidentiality. This undertaking shall continue to be valid after termination of their activity.

Statistics for Federal Purposes Act of 20 October 2016 protects confidentiality stricter than Federal Data Protection Law. Article 16 of the Law states that individual data on personal circumstances or the material situation provided for federal statistics shall not be disclosed by the incumbents and the person specially sworn in for public services who are entrusted with the operation of federal statistics unless otherwise stipulated by special legal provision. The obligation to confidentiality applies also to those persons who are recipients of individual data pursuant to a special legal provision or for the purpose of scientific projects.
Article 16 also regulates the transmission of the individual data between persons and agencies entrusted with the operation of federal statistics, the transmission of individual data to the Länder statistical offices, to agencies of communities and local authorities and the transmission for the purposes of scientific projects.
The respondents will be notified in writing or electronically about the rules governing statistical confidentiality (Article 17 of the Law).
Interview findings indicate that nobody has tried to identify an individual from data or statistical output.

As regards the confidentiality of tables, methods of primary (by automatic procedure) and secondary confidentiality have been developed and are used, also in co-operation with Eurostat. For business and agriculture surveys disclosure risk assessment is based on concentration-rules. Cell suppression is used to prevent residual disclosure in tables for dissemination.
Primary confidentiality includes single units as well as dominace rules.

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

To assure confidentiallity of tables, primary confidentiallity (by automatic procedure) includes single cases/units and dominance rule. Secondary confidentiality is added by manual operation to avoid disclosure by calculation. As area, age and density classes differ between national and european tables, this was done again for the European data transmission. 
11.2.2 Additional comments


12. Comment Top


Related metadata Top


Annexes Top
National publication
Questionnaire
National quality report