Annual crop production


Metadata
Period: Every three years
Year: 2022

REFERENCE METADATA
01. Contact
02. Metadata update
03. Statistical presentation
04. Unit of measure
05. Reference Period
06. Institutional Mandate
07. Confidentiality
08. Release policy
09. Frequency of dissemination
10. Accessibility and clarity
11. Quality management
12. Relevance
13. Accuracy and reliability
14. Timeliness and punctuality
15. Coherence and comparability
16. Cost and Burden
17. Data revision
18. Statistical processing
19. Comment

SDMX Download
01. ContactTop
01.1. Contact organisation

Statistical Office of the Republic of Serbia

01.2. Contact organisation unit

Agriculture and Forestry Division - Unit for Crop production Statistics and Forestry

01.3. Contact name

Mrs. Jelena Perac

01.4. Contact person function

Head of Unit for Crop Production Statistics and summary indicators

01.5. Contact mail address

Milana Rakica 5, Belgrade, Serbia

01.6. Contact email address

jelena.perac@stat.gov.rs 

01.7. Contact phone number

+381 11 2410 397

01.8. Contact fax number

Not needed


02. Metadata updateTop
02.1. Metadata last certified
24/12/2020
02.2. Metadata last posted
5/3/2024
02.3. Metadata last update
4/3/2024

03. Statistical presentationTop
03.1. Data description

Annual crop statistics provide statistics on the area under main arable crops, vegetables and permanent crops and production and yield levels.  The statistics are collected from  a wide variety of sources: surveys, administrative sources, experts and other data providers. The data collection covers early estimates (before the harvest) and the final data. Data are collected  at national and regional level  (NUTS2).

03.2. Classification system

Hierarchical crop classification system

03.3. Coverage - sector

The field of statistics on crop production includes the cultivation of annual crops, perennial plantations and production of crops and greenhouse in greenhouses (NACE A01.1-01.3).

03.4. Statistical concepts and definitions

See: Annual crop statistics Handbook

Since 2014, the Republic of Serbia has officially carried out statistical surveys on crop production in accordance with the  Regulation of European Union (EC) No 543/2009 and Eurostat Annual crop statistics Handbook.

03.5. Statistical unit

Utilised agricultural area cultivated by an agricultural holding.

03.6. Statistical population

All agricultural holdings growing crops.

03.7. Reference area

The entire territory of the country.

Note: Since 1999, the Republic Statistical Office does not have data for the Autonomous Province of Kosovo and Metohija, so they are not included in the coverage of data for the Republic of Serbia (total).

03.8. Coverage - Time

Crop year.

03.9. Base period

Not applicable.


04. Unit of measureTop
04. Unit of measure

Land measure: ha, ar

Production measure: t

Yield measure: t/ha


05. Reference PeriodTop
05. Reference Period

Reference period is harvested year. Harvested year is the calendar year in which the crop harvest begins.


06. Institutional MandateTop
06.1. Institutional Mandate - legal acts and other agreements
The data on crop production statistics are published on the basis of the Official Statistics Act ("Official Gazette of the Republic of Serbia", No. 104/09) and the Annual Official Statistics Plan published in the "Official Gazette of the Republic of Serbia".

In addition, the legal framework for the production and dissemination of data is also the Official Statistics Program for a five-year period. This program provides an overview of the expected results of the official statistics by areas with data on their periodicity and planned activities.
 
According to harmonisation proces in Republic of Serbia with standards of EU , statistics of crop productiopn delivered to Eurostat regularly data on ACS, according to delivery schedule defined in Regulation (EC) No 543/2009.
06.2. Institutional Mandate - data sharing

Data represent official statistics and serve to meet national and international needs (Eurostat, FAO).


07. Confidentiality Top

08. Release policyTop

09. Frequency of disseminationTop

10. Accessibility and clarityTop
10.1. Dissemination format - News release

Availability Links
YES

http://www.stat.gov.rs/en-US/oblasti/poljoprivreda-sumarstvo-i-ribarstvo/biljna-proizvodnja
10.2. Dissemination format - Publications

  Availability Links
Publications Electronic

http://www.stat.gov.rs/sr-Cyrl/oblasti/poljoprivreda-sumarstvo-i-ribarstvo/biljna-proizvodnja
Publications in English Electronic

http://www.stat.gov.rs/en-US/oblasti/poljoprivreda-sumarstvo-i-ribarstvo/biljna-proizvodnja

10.3. Dissemination format - online database

Data tables - consultations

Not applicable


  Availability Links
On-line database accessible to users YES

http://data.stat.gov.rs/Home/Result/130102?languageCode=en-US

Website National language
English

http://www.stat.gov.rs/en-US/

10.4. Dissemination format - microdata access

Availability Links
NO  
10.5. Dissemination format - other

http://data.stat.gov.rs/?caller=SDDB&languageCode=en-US

Data on crop production statistics can be found in the database of agricultural statistics, published on the SORS website. The database contains all  indicators collected in crop production statistics and displayed in the time series since the year 1947. Using of Database is for free.

10.6. Documentation on methodology

  Availability Links
Methodological report National language
English

   https://www.stat.gov.rs/sr-cyrl/istrazivanja/methodology-and-documents/?a=13&s=1301

Quality Report National language
English

http://data.stat.gov.rs/Home/Result/130102?languageCode=en-US#    


  

Metadata National language
English

http://data.stat.gov.rs/Home/Result/130102?languageCode=en-US#
 

Additional comments    

 

10.7. Quality management - documentation

Not applicable.


11. Quality managementTop
11.1. Quality assurance

  Completeness Punctuality Accuracy Reliability Overall quality
How would you describe the overall quality development since the previous quality report? Improvement Improvement Improvement Improvement Improvement
Is there a quality management process in place for crop statistics? YES        
If, yes, what are the components?

In conducting surveys on crop production statistics, SORS respected quality elements: relevance, accuracy, timeliness, punctuality, accessibility, comparability and coherence. It also aim to meet the standards prescribed by Regulation 543/2009 relating to the coverage, frequency and surveys reference period as well as precision requirements (coefficient of variation of the data to be provided by 30 September n+1, at national level).   

        
Is there a Quality Report available? YES        
If yes, please provide a link(s) https://data.stat.gov.rs/Home/Result/130102?languageCode=sr-Cyrl        
To which data source(s) is it linked?

Annual crop production statistics

        
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? Increase of resources
Systematic validation improvements
Quality report
Other		        
If, other, please specify Census of Agriculture 2023        
Additional comments          

 

11.2. Quality management - assessment

See the European level Quality Report.


12. Relevance Top
12.1. User needs

Are there known unmet user needs? YES
Describe the unmet needs

SORS is not in a position, from the reason of budget limitation, to carry out sample surveys big enough to provide easily all the data on the level of districts and municipalitys, which is in most cases the needs of our data users. Some data are not reliable in the final assessment, and these data can not be published.
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  

 

12.2. User satisfaction

Have any user satisfaction surveys been done? YES
If yes, how satisfied the users were? Satisfied
Additional comments  
12.3. Completeness

See the European level Quality Report


13. Accuracy and reliabilityTop
13.1. Overall accuracy

See the European level Quality Report.

13.2. Sampling error

Sampling method and sampling error

  Survey 1 Survey 2 Survey 3 Survey 4 Survey 5 Survey 6 Survey 7
Name

Sample survey on sown areas at the end of spring sowing season, May/Jun 2022

Sample survey on crop production, November 2022

Sample survey on autumn sowing, November 2022

Sample survey on horticultural production, November 2022

      
Sampling basis? Other Other Other Other      
If 'other', please specify

Statistical Farm Register

Statistical Farm Register

Statistical Farm Register

Statistical Farm Register

      
Sampling method? Random
Stratified		 Random
Stratified		 Random
Stratified		 Random
Stratified		      
If stratified, number of strata?

121

121

35

32

      
If stratified, stratification basis? Location
Size
Legal status
Specialisation		 Location
Size
Legal status
Specialisation		 Location
Size
Legal status
Specialisation		 Location
Size
Legal status
Specialisation		      
If 'other', please specify              
Size of total population

601199

601199

445578

113073

      
Size of sample

7074

5235

3626

2508

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

Taylor linearization was used for variance estimation by applying Swedish ETOS based on software SAS. Sample design and weighting has been taken into account because it is required by ETOS.

Taylor linearization was used for variance estimation by applying Swedish ETOS based on software SAS. Sample design and weighting has been taken into account because it is required by ETOS.

Taylor linearization was used for variance estimation by applying Swedish ETOS based on software SAS. Sample design and weighting has been taken into account because it is required by ETOS.

Taylor linearization was used for variance estimation by applying Swedish ETOS based on software SAS. Sample design and weighting has been taken into account because it is required by ETOS.

      
If the results were compared with other sources, please describe the results

Comparison were done with Register of agricultural holdings by MoA and there were expected differences. 

The difference occurs because of a different number of farms covered by the statistical survey and the number of farms covered by this administrative source.

The area of the most important crops that farm are reported in this subsides register are less for about 30% in accordance to statistical survey. For the same percentage is the smaller number of farms in this registry than in a statistical survey or AC2012.

The comparison was made also with the estimates of Agricultural extension services and there were no significant differences.  

Comparison were done withestimates of Agricultural extension services:

The data on harvested area and yield for cereals obtained in this sample survey on crop production were almost the same as the estimates of Agricultural extension services (especially for wheat and maize) as well as for industrial crops.

Comparison were done with estimates of Agricultural extension services:

The data on sown area for cereals obtained in this sample survey  were almost the same as the estimates of Agricultural extension services.

Comparison were done with estimates of Agricultural extension services:

The data on horticultural production obtained in this sample survey  were almost the same as the estimates of Agricultural extension services.

 

      
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

Sample survey on sown areas at the

end of spring sowing season, May/Jun 2022

The sample survey on crop production , November 2022

Sample survey on autumn sowing; November 2022

Sample survey on horticultural production, Novmber 2022

      
Cereals for the production of grain (in %)

3.5

4.74

5.03

 

      
Dried pulses and protein crops (in %)

6.9

12.94

          
Root crops (in %)

6.76

7.08

          
Oilseeds (in %)

2.8

7.37

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

12.9

12.65

          
Plants harvested green from arable land (in %)

6.08

8.05

          
Total vegetables, melons and strawberries (in %)

9.64

 9.0  

5.01

      
Cultivated mushrooms (in %)

-

-

-

-

      
Total permanent crops (in %)

5.8

4.46

-

-

      
Fruit trees (in %)

6.7

6.72

-

-

      
Berries (in %)

8.2

7.9

-

-

      
Nut trees (in %)

15.5

24.4

-

-

      
Citrus fruit trees (in %)              
Vineyards (in %)

12.87

9.27

-

-

      
Olive trees (in %)              
Additional comments

The reason of increased the coefficient of variation for the group of other industrial crops is very low persentage of respondent units for this crop group (only 3%). The same reason is for increased the coefficient of variation of nut trees in sample survey of crop production, where the respondent units are only 2% for nut trees. 

            

 

13.3. Non-sampling error

Non sampling errors include: people who refused to answer the questionnaires, size of questionnaires (both surveys: Sample survey on sown areas at the end of spring sowing season, May/Jun 2022  and sample survey on crop production , November 2022 includes for about 100 indicators), questions interpretation by CATI interviewers  and data entry errors by CATI and regional offices interviewers.  


14. Timeliness and punctualityTop
14.1. 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?

5

2

3

3

-

1

-

1

-

3

3

1

-

2

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

3

-

 

2

2

 

-

-

-

-

-

2

2

-

-

1

-
When was the first  forecasting published for the crop year on which is reported? (day/month/year) 01/02/2022   30/06/2022 30/06/2022           30/06/2022 30/06/2022     23/09/2022  
When were the final results published for the crop year on which is reported? (day/month/year) 01/03/2023 28/02/2023 28/02/2023 28/02/2023 28/02/2023 28/02/2023 28/02/2023 28/02/2023   28/02/2023 28/02/2023 28/02/2023   28/02/2023  
Additional comments                              

 

14.2. Punctuality

See the European level Quality Report


15. Coherence and comparabilityTop
15.1. Comparability - geographical

Not applicable.

15.2. Comparability - over time

Length of comparable time series

Not applicable


  Crops from arable land
(Table 1)		 Vegetables, melons and strawberries (Table 2) Permanent crops
(Table 3)		 Agricultural land use
(Table 4)
Have there been major breaks in the time series in the previous 5 years? NO NO YES YES
If yes, to which were they related?     Methods Other
If other, which?

 

 

 

Revision of data on utilized agricultural area as a result of revision of data on area of permanent crops
Which items were affected?     F1110 - Apples
F1120 - Pears
F1210 - Peaches
F1220 - Nectarines
F1230 - Apricots
F1240 - Cherries
F1241 - Sour cherries
F1250 - Plums
F3200 - Raspberries
F4100 - Walnuts
F4200 - Hazelnuts
F3110 - Blackcurrants
F3300 - Blueberries		 PECR - Permanent crops
F0000 - Fruits, berries and nuts (excluding citrus fruits, grapes and strawberries)
Year of break (number)  

 

2017

2017
Impact on comparability     Low Low
Additional comments    

Serbia has carried out the Orchard survey in 2017, for the first time. The survey collected data on areas, planting density and age for apples, pears, apricots and peaches, by varieties, regardless of whether they are dessert or varieties for industrial processing. Also, data on areas for fruit species in total (not by varieties) were collected, for: plums, cherries, cherries, raspberries, quinces, walnuts, hazelnuts, almonds, blackberries and blueberries.

Due to the low differences beatween data collected before and after Orchard survey, data for years 2013-2016 were recalculated and new time series were published.

Serbia has carried out the Orchard survey in 2017, for the first time. The survey collected data on areas, planting density and age for apples, pears, apricots and peaches, by varieties, regardless of whether they are dessert or varieties for industrial processing. Also, data on areas for fruit species in total (not by varieties) were collected, for: plums, cherries, cherries, raspberries, quinces, walnuts, hazelnuts, almonds, blackberries and blueberries.

Due to the low differences beatween data collected before and after Orchard survey, data for years 2013-2016 were recalculated and new time series were published.

15.3. Coherence - cross domain

With which other data sources the crop statistics data have been compared?  IACS
Other
If others, which?

Price statistics

National accounts
If no comparisons have been made, why not?  


Differences between ACS and other data sources (%)

Results of comparisons FSS 2016 Orchard survey 2017 IACS Other source(s)  In case of other sources, which?
Cereals    

29.82%

 

 
Dried pulses and protein crops    

23.65%

 

 
Root crops    

43.20%

 

 
Oilseeds    

39.10%

 

 
Other industrial crops (than oilseeds)    

13.05%

 

 
Plants harvested green    

37.43%

 

 
Total vegetables, melons and strawberries    

13.44%

 

 
Vegetables and melons    

7.17%

 

 
Strawberries    

60.67%

 

 
Cultivated mushrooms          
Total permanent crops

 0.37%

  

10.25%

 

 
Fruit trees

 -0.64%

0.5%

3.02%

 

 
Berries

 -4.17

  

-8.40%

 

 
Nut trees

 -1.47%

  

-25.45%

 

 
Citrus fruit trees          
Vineyards

 0.17%

  

44.28%

 

 
Olive trees

 

        
If there were considerable differences, which factors explain them?

 

  

Register of agricultural holdings on behalf of Ministry of Agriculture, Forestry and Water Managment (MoA) is register for subsidies applying. The result of differences between Register of MoA and regular annual crop statistics in 2019 are results of different total number of agricultural holdings as well as different number of agricultural holdings specialized for crop production. Register of MoA includes approximately 400 thousand of family agricultural holdings what is a half of the total number of family agricutural holdings in Statistical Farm Register (621.445).   

Also, the Ministry of Agriculture doesn’t perform subsidies for all grown crops, so the crop registration by holdings is restricted.

    

 

15.4. Coherence - internal

Not applicable.


16. Cost and BurdenTop
16. Cost and Burden

Efficiency gains if compared to the previous quality report? Further automation
Increased use of administrative data
Staff further training
If other, which?

Implementation of new sample surveys insted of experts etimates, caused greater efficiency and speed
of data providing, as well as data reliability.
Burden reduction measures since the previous reference year  Less frequent surveys
Less variables surveyed
More user-friendly questionnaires
Multiple use of the collected data
If other, which?  

17. Data revisionTop
17.1. Data revision - policy

Not applicable.

17.2. Data revision - practice

Not applicable.


18. Statistical processingTop
18.1. Source data

  Source 1 Source 2 Source 3 Source 4
Have new data sources been introduced since the previous Quality Report?  NO      
If yes, which new data sources have been introduced since the previous quality report?        
Type of source?        
To which Table (Reg 543/2009) do they contribute?        
Have some data sources been dropped since the previous Quality Report? NO      
Which data sources have been dropped since the previous quality report?        
Type of source?        
Why have they been dropped?        
Additional comments        


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

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

Sample survey on sown areas at the end of spring sowing season, May/Jun 2022;

Sample survey on expected yield of late crops, fruit and grapes and realized production of early crops and fruits, September 2022;

Sample survey on autumn sowing; November 2022.

Weekly reporting on the seasonal agricultural works, area estimates and condition of major agricultural crops, permanent crops and the yield forecast, by Agricultural advisory services.

  
Final area under cultivation Survey
Administrative data

Sample survey on sown areas at the end of spring sowing season, May/Jun 2022

Register of agricultural holdings by Ministry of agriculture

  
Production Survey
Expert estimate

Sample survey on expected yield of late crops, fruit and grapes and realized production of early crops and fruits, September 2022;

The sample survey on crop production, November 2022

Weekly reporting on the seasonal agricultural works, area estimates and condition of major agricultural crops, permanent crops and the yield forecast, by Agricultural advisory services.

  
Yield Survey
Expert estimate

Sample survey on expected yield of late crops, fruit and grapes and realized production of early crops and fruits, September 2022

The sample survey on crop production, November 2022

Weekly reporting on the seasonal agricultural works, area estimates and condition of major agricultural crops, permanent crops and the yield forecast, by Agricultural advisory services.

  
Non-existing and non-significant crops Survey

The sample survey on crop production, November2022

Farm structure survey, October 2018.

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

Weekly reporting on the seasonal agricultural works, area estimates and condition of major agricultural crops, permanent crops and the yield forecast, by Agricultural advisory services.

  
Final harvested area Survey

Sample survey on horticultural production, November 2022

  
Production Survey

Sample survey on horticultural production, November 2022

  
Non-existing and non-significant crops Survey

The sample survey on crop production , November 2022

Farm structure survey, October 2018.

  
Table 3: Permanent crops      
Early estimates for production area Survey
Expert estimate

Sample survey on sown areas at the end of spring sowing season, May/Jun 2022;

Sample survey on expected yield of late crops, fruit and grapes and realized production of early crops and fruits, September 2022

Weekly reporting on the seasonal agricultural works, area estimates and condition of major agricultural crops, permanent crops and the yield forecast, by Agricultural advisory services.

  
Final production area Survey

The sample survey on crop production , November 2022

  
Production Survey

The sample survey on crop production , November 2022

  
Non-existing and non-significant crops Census
Survey

AC2012

The sample survey on crop production , November 2018

Farm structure survey, October 2018.

  
Table 4: Agricultural land use      
Main area Survey

Sample survey on sown areas at the end of spring sowing season, May/Jun 2022

  
Non-existing and non-significant crops Survey

Sample survey on sown areas at the end of spring sowing season, May/Jun, 2022

Farm structure survey, October 2018.

  
Total number of different data sources

4                                                                                                                                                                                            

 

    
Additional comments

Data source for the humidity

Put x, if used

Surveyed: farmers report the humidity

 

Surveyed: farmers convert the production/yield into standard humidity     

 x

Surveyed: whole sale purchasers report the humidity

 

Surveyed: whole sale purchasers convert the production/yield into standard humidity     

 

Surveyed by experts (e.g. test areas harvested and measured)

 

Estimated by experts

 

Other type

 

If other type, please explain

 

Additional information

 
   


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.  

 

18.2. 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

Sample survey on sown areas at the end of spring sowing season, May/Jun 2022

Sample survey on expected yield of late crops, fruit and grapes and realized production of early crops and fruits, September 2022

Sample survey on crop production,  November 2022

Sample survey on autumn sowing, November 2022

Sample survey on horticultural production, November 2022

Weekly reporting on the seasonal agricultural works, area estimates and condition of major agricultural crops, permanent crops and the yield forecast

      
Planning (month-month/year)

January-February/2022

June-August/2022

July-Septembar/2022

July-Septembar/2022

July-Septembar/2022

January/2022

      
Preparation (month-month/year)

April -May/2022

August/2022

 

October-November/2022

October-November/2022

October-November/2022

March-November 2022

      
Data collection (month-month/year)

23 May-06 Jun/2022

06 - 13 September/2022

24 November - 16 December 2022

24 November - 16 December 2022

24 November - 16 December 2022

 

March-November 2022

      
Quality control (month-month/year)

Jun/2022

September/2022

November - December/2022

November - December/2022

November - December/2022

March-November 2022

      
Data analysis (month-month/year)

Jun-July/2022

September/2022

December-January /2022

December-January /2022

December-January /2022

March-November 2022

      
Dissemination (month-month/year)

July/2022

September/2022

February/2022

February/2022

February/2016

no dissemination

      
If there were delays, what were the reasons?                  
18.3. 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)? NO  
In case yes, how do they differ? ( list all items and explanations)    
In case data are delivered for one of the items below, describe the crop species included in the item:    


Population

Which measures were taken in order to make sure that the requirement stipulated in Art. 3.2 are met?
(Statistics shall be representative of at least 95 % of the areas of each table in the Regulation).

In order to provide data in accordance with the requirements of Regulation, SORS didn’t make cut off while creating a sample frame for the Sample survey on sown areas at the end of spring sowing season, May/Jun 2022. Also, there was no cut off for a sample frame  for Sample survey on expected yield of late crops, fruit and grapes and realized production of early crops and fruits, (September 2022).

Sample for survey on crop production, November 2022 is created as a subsample of the agricultural holdings selected for the Survey on sown areas at the end of spring sowing season, May/Jun 2022 and all sample selection criteria are valid as for this survey.

Within the Sample survey on crop production, it was created and a separate samples for survey on areas sown in autumn sowing (for 6 winter crops) and separate sample for survey on horticultural production. Sampling frame was created from the SFR base. There  were allocated only those family farms that had Cereals for the production of grain or horticultural production In this way, statistics is representative of over 97% for total area under cultivation of crops from arable land.

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)

February 2022
Was a threshold applied? NO
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 %)  
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 %)  


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

Sample survey on sown areas at the end of spring sowing season May/Jun 2022

Sample survey on expected yield of late crops, fruit and grapes and realized production of early crops and fruits, September 2022

Survey on crop production, November 2022

Survey on autumn sowing, November 2022

Survey on horticultural production, November 2022

 

  
Which survey method was used? Postal questionnaire filled in by respondent
Telephone interview, electronic questionnaire
Face-to-face interview		 Postal questionnaire filled in by respondent
Telephone interview, electronic questionnaire		 Postal questionnaire filled in by respondent
Telephone interview, electronic questionnaire		 Postal questionnaire filled in by respondent
Telephone interview, electronic questionnaire		 Postal questionnaire filled in by respondent
Telephone interview, electronic questionnaire		    
If 'other', please specify              
Please provide a link to the questionnaire

http://publikacije.stat.gov.rs/G2018/PdfE/G201824093.pdf

http://publikacije.stat.gov.rs/G2018/PdfE/G201824052.pdf

http://publikacije.stat.gov.rs/G2018/PdfE/G201824052.pdf 

http://publikacije.stat.gov.rs/G2018/PdfE/G201824052.pdf

    
Data entry method, if paper questionnaires? Manual Manual Manual Manual 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

Register of agricultural holdings by Ministry of Agriculture, Forestry and Water Management

          
Description

Register record a members of the agricultural budget, record the number of agricultural holdings, production structure and capacity, and give the opportunity to define a strategy of agricultural development and lead a successful agricultural policy by Ministry of agriculture. In 2022  the number of registered agricultural holdings was 450.000

          
Data owner (organisation)

 Ministry of Agriculture, Forestry and Water Management

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

May/2022

          
Legal basis

Law on agriculture and rural development ("Off.Gazette ofRS", no.41/09)

          
Reporting unit

Farmers, entrepreneurs and legal entities

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

Unique code of a. holding, name, surname and personal identification number of residence ofthe holding, residential address and farm location address, numberof family membersandtheir personal data and other banking and accounting data holdings.

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

70%

          
Degree of completeness (variables, e.g. 60%)            
If not complete, which other sources were used ?

AC 2012, FSS 2018

          
Were the data used for sample frame? Sample frame
Validation
Directly for estimates		          
Data used for other purposes, which?            
Which variables were taken from administrative sources?

Identification variables and area of main crops registered (cereals, root crops, oil seed crops, other industrial crops, plants harvested green)

          
Were there any differences in the definition of the variables between the administrative source and those described in the Regulation? NO          
Please describe the differences            
What measures were taken to eliminate the differences?            
How was the reliability, accuracy and coherence (comparison to other available data) of the data originated from administrative data source (ante- and/or ex-post) checked?

Data comperison is done on the level of holdings and there were negligable differences.

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

Registration renewal and updating is voluntary and based on the request of holder. Also, the register doesn’t contain data on orchards and vineyards by holdings.

          


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

Early estimates for crop production

          
Data owner (organisation)

Ministry of Agriculture, Forestry and Water Management

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

Week

          
Legal basis

Memorandum of anderstending between Ministry of Agriculture and Environmental protection (MoA) and Statistical Office of Republic of Serbia (SORS)

          
Use purpose of the estimates?

Expert estimates are made in order to monitor the seasonal agricultural work, area planting and condition of major agricultural crops, permanent crops and yield forecast by Ministry of Agriculture and Environmental protection.

          
What kind of expertise the experts have?

They are agricultural engineers, employed in agricultural advisory services at the Ministry of Agriculture.

          
What kind of estimation methods were used?

The methodology defines regular reporting on planted and harvested areas of crops, fruit trees and grape vines , using estimates from agricultural advisory services, as the only reliable way to determine the yield forecasts every week.

For this purpose, SORS has created a web questionnaire for data entry by the Agriculture extension services as well as final reports from the same aplication. This ensures a unique collection of high quality data, necessary for the MoA to conduct agricultural policy, and information which will SORS forwarded to Eurostat.

          
Were there any differences in the definition of the variables between the experts' estimates and those described in the Regulation? 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? The data obtained on the basis of expert assessments (Agricultural Advisory and Expert Stations) are compared with statistical surveys and available administrative data sources, at the level of the region and the Republic of Serbia, and there were no significant discrepancies.          
What were the possible limitations, drawbacks of using the data from expert estimate(s)?            
Additional comments

In 2014, SORS has replaced the previously used method of providing EECP and establish a new system, which means engagement of agriculture extension services. For now, there are no plans to replace the expert’s estimates for EECP by other data sources. 

          

 

18.4. Data validation

Which kind of data validation measures are in place? Automatic and 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? Other dataset
If other, please describe

Available administrative sources. 

Records of associations and communities for cereals, fruits and vegetables, records of subsidies applications by Ministry of Agriculture, Data of sugar production industry, export/import data, survey on purchase of agricultural products, data of oil producers, calculation of supply balance sheets.

Which kind of data validation : Logical and computational control at data entry. 
18.5. Data compilation

Not Applicable.

18.6. Adjustment

Not applicable.


19. CommentTop
19. Comment

In the process of harmonization of agricultural statistical system with the statistical systems of the European Union (EU), SORS has adopted the standards and definitions of the EU, which completely changed the methodology of Annual Crop Statistics. Previously, till 2014th, the methodology of Annual Crop statistics were based on experts estimates. Several problems characterized this way of data collecting, but the most important were tardiness of cadastral data used for estimation as well as the almost complete absence of quality checks of data on crop production statistics. Also, a report on the quality of the data was not possible.

Now, Annul Crop Statistics, is based on the principle of full harmonization with Regulation (EC) No 543/2009 as well as with the definitions and concepts presented in the Eurostat Handbook for Annual Crop Statistics. Data collection is conducted on the basis of several annual sample surveys, one three annul sample survey on horticultural production and five annual Orchard survey.

This is the third Quality report on Annual Crop Statistics, refers to 2022.