Crop production (apro_cp)

National Reference Metadata in ESS Standard for Quality Reports Structure (ESQRS)

Compiling agency: Ministerio de Agricultura, Pesca y Alimentación (MAPA) Ministry of Agriculture, Fisheries and Food


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
Ministerio de Agricultura, Pesca y Alimentación (MAPA)
Ministry of Agriculture, Fisheries and Food
1.2. Contact organisation unit

Subdirección General de Análisis, Coordinación y Estadística

Sub-Directorate General for Analysis, Coordination and Statistics

 
1.5. Contact mail address
Ministry of Agriculture, Fisheries and Food:
 
MINISTERIO DE AGRICULTURA, PESCA Y ALIMENTACIÓN
Subdirección General de Análisis, Coordinación y Estadística
Despacho B-25
Paseo Infanta Isabel 1
28071 Madrid
SPAIN


2. Statistical presentation Top
2.1. Data description

Annual crop statistics provide statistics on the area under main arable crops, vegetables and permanent crops and production and yield levels.  The statistics are collected from  a wide variety of sources: surveys, administrative sources, experts and other data providers. The data collection covers early estimates (before the harvest) and the final data. Data are collected mostly at national level but for some crops also regional data exist (NUTS1/2).
2.2. Classification system

Hierarchical crop classification system
2.3. Coverage - sector

Growing of non-perennial crops, perennial crops and plant propagation (NACE A01.1-01.3)
2.4. Statistical concepts and definitions

See: Annual crop statistics Handbook
2.5. Statistical unit

Utilised agricultural area cultivated by an agricultural holding.
2.6. Statistical population

All agricultural holdings growing crops.
2.7. Reference area

The entire territory of the country.
2.8. Coverage - Time

Crop year.
2.9. Base period

Not applicable.


3. Statistical processing Top
3.1. Source data

  Source 1 Source 2 Source 3 Source 4
Have new data sources been introduced since the previous quality report?  YES      
If yes, which new data sources have been introduced since the previous quality report?

REGEPA: Registro General de la Producción Agrícola (General Register of Agricultural Production). Created in accordance with the provisions of article 5.4 of Royal Decree 9/2015, of 16 January (*), which regulates the conditions for the application of Community legislation on hygiene in primary agricultural production.

(*) Real Decreto 9/2015, de 16 de enero, por el que se regulan las condiciones de aplicación de la normativa comunitaria en materia de higiene en la producción primaria agrícola

 

Agrarian Census 2020

Vineyard register
Type of source? Administrative data Census Administrative data
To which Table (Reg 543/2009) do they contribute? Table3
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

Concerning the new data sources, the General Register of Agricultural Production contribute to tables 1, 2, 3 and 4, as it is taken into account to provide with estimations as multisource statistic.

Concerning the new data sources, the Agrarian Census 2020 contribute to tables 1, 2, 3 and 4, as it is taken into account to provide with estimations as multisource statistic. Agrarian Census is considered as a contrast source, as temporal reference is not the reference of ACS 2022.


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
Administrative data
Other

Survey: ESYRCE

Administrative data: Farmers declarations (IACS)

Administrative data: REGEPA (General Register of Agricultural Production)

Other: Monthly Early Estimates of Crop Area and Production (Avances Mensuales de Superficies y Producciones de Cultivos). Multisource statistic.

Other: Consultation of sectoral organisations on the production of specific crops

  
Final area under cultivation Survey
Administrative data

Survey: ESYRCE

Administrative data: Farmers declarations(IACS)

Administrative data: REGEPA (General Register of Agricultural Production)
Production Administrative data
Survey
Other

Administrative data: Farmers declarations(IACS)

Administrative data: REGEPA (General Register of Agricultural Production)

Survey: ESYRCE

Other: Consultation of sectoral organisations on the production of specific crops
Yield Survey
Other

Survey: ESYRCE

Other: Consultation of sectoral organisations on the production of specific crops
Non-existing and non-significant crops Administrative data

Farmers declarations (IACS)

Administrative data: REGEPA (General Register of Agricultural Production)
Table 2: Vegetables, melons and strawberries       
Early estimates for harvested areas Survey
Administrative data
Other

Survey: ESYRCE

Administrative data: Farmers declarations (IACS)

Administrative data: REGEPA (General Register of Agricultural Production)

Other: Monthly Early Estimates of Crop Area and Production (Avances Mensuales de Superficies y Producciones de Cultivos). Multisource statistic.

Other: Consultation of sectoral organisations on the production of specific crops
Final harvested area Survey
Administrative data

Survey: ESYRCE

Administrative data: Farmers declarations(IACS)

Administrative data: REGEPA (General Register of Agricultural Production)
Production Administrative data
Survey
Other

Administrative data: Farmers declarations(IACS)

Administrative data: REGEPA (General Register of Agricultural Production)

Survey: ESYRCE

Other: Consultation of sectoral organisations on the production of specific crops
Non-existing and non-significant crops Administrative data

Farmers declarations (IACS)

Administrative data: REGEPA (General Register of Agricultural Production)
Table 3: Permanent crops      
Early estimates for production area Survey
Administrative data
Other

Survey: ESYRCE

Administrative data: Farmers declarations (IACS)

Administrative data: REGEPA (General Register of Agricultural Production)

Administrative data: vineyard register

Other: Monthly Early Estimates of Crop Area and Production (Avances Mensuales de Superficies y Producciones de Cultivos). Multisource statistic.

Other: Consultation of sectoral organisations on the production of specific crops
Final production area Survey
Administrative data

Survey: ESYRCE

Administrative data: Farmers declarations(IACS)

Administrative data: REGEPA (General Register of Agricultural Production)

Administrative data: vineyard register
Production Administrative data
Survey
Other

Administrative data: Farmers declarations(IACS)

Administrative data: REGEPA (General Register of Agricultural Production)

Administrative data: vineyard register

Survey: ESYRCE

Other: Consultation of sectoral organisations on the production of specific crops
Non-existing and non-significant crops Administrative data

Farmers declarations (IACS)

Administrative data: REGEPA (General Register of Agricultural Production)
Table 4: Agricultural land use      
Main area Survey
Administrative data

Survey: ESYRCE

Administrative data: Farmers declarations(IACS)

Administrative data: REGEPA (General Register of Agricultural Production)

Administrative data: vineyard register
Non-existing and non-significant crops Administrative data

Farmers declarations (IACS)

Administrative data: REGEPA (General Register of Agricultural Production)

 
Total number of different data sources

5

  
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     

 

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

 X

Other type

 

If other type, please explain

 

Additional information

 
   


Which method is used for calculating the yield for main arable crops? Production divided by sown area
If another method, describe it.




 
3.2. Frequency of data collection

  Source 1 Source 2 Source 3 Source 4 Source 5 Source 6 Source 7 Source 8 Source 9
Name of data source

ESYRCE (Encuesta de Superficies y Rendimientos de Cultivos). 

Area Frame Survey for Area and Yield on Crops

Administrative data (IACS)

Administrative data

Registro General de la Producción Agrícola (REGEPA) / General Register of Agrarian Production

Administrative data (Vineyard Register)
Planning (month-month/year)

10-11/2021: sample selection for field data gathering, photo interpretation

01/2022
Preparation (month-month/year)

11/2021 - 02/2022: updating of orthophotos, updating of documentation for field agents, updating of computer processes, preparation of training courses for field agents, etc.

01/2022
Data collection (month-month/year)

03/2022 - 06/2022: field data collection campaign in Canary Islands for crops harvested in Summer

05/2022 - 08/2022: field data collection campaign in the rest of Spain for crops harvested in Summer

08/2022 - 10/2022: field data collection campaign for the crops harvested in Autum

11/2022 - 12/2022: field data collection campaign for the crops harvested in Winter

01/2023 - 02/2023: additional field data collection campaign for crops grown in greenhouses (campaign 2022)

03/2022 - 07/2022

05/2023 - 07/2023
Quality control (month-month/year)

04/2022 - 02/2023: quality control of the information is carried out continuously throughout the field data collection campaign, as the information from the field is entered into the database. These controls include control of the alphanumeric information and of the graphic information.

07/2022 - 

10/2023
Data analysis (month-month/year)

10/2022 - 11/2022: analysis of data on provisional results for rainfed and irrigated areas from the summer fieldwork covering the entire sample.

02/2023: further analysis on the results of rainfed and irrigated areas, as well as sowing methods and soil cover, based on field work carried out during the summer, covering the whole sample.

03/2023 - 04/2023: analysis of final results on areas, yields, cropping systems (rainfed/irrigated), planting status of permanent crops, yields, matrices of land cover change between N-1 and N, etc.

07/2019 - 10/2020
Dissemination (month-month/year)

11/2022: provisional results on crop area by rainfed and irrigated land, and area under greenhouses

 

03/2023: results of the analysis of irrigated crops by irrigation techniques

03/2023: results of the analysis of sowing methods and protective cover on permanent crops and fallow land.

05/2023: complete final results

 

11/2022: preliminary results

02/2023: final results

The results are made available to the Sub-Directorate-General for Analysis, Coordination and Statistics under a special administrative information exploitation request for statistical pourposes.

07/2023: final results

The results are made available to the Sub-Directorate-General for Analysis, Coordination and Statistics under a special administrative information exploitation request for statistical pourposes.
If there were delays, what were the reasons?

New variables for olive varieties have been introduced in the survey for crop year 2022. This has generated some classification problems that have affected the historical series and more time has been necessary for the confirmation or correction of the field information. However, this delay has not affected the use of the data for the estimation of Annual Crop Statistics under Regulation 543/2009.






 
3.3. Data collection

Definitions Question In case yes, how do they differ?
Do national definitions differ from the definitions in Article 2 of Regulation (EC) No 543/2009? NO
Are there differences between the national methodology and the methodology described in the Handbook concerning e.g. the item and aggregate calculations? NO
Are special estimation/calculation methods used for main crops from arable land? NO
Are special estimation/calculation methods used for vegetables or strawberries? NO
Are special estimation/calculation methods used for permanent crops for human consumption? NO
Are special estimation/calculation methods used for main land use? NO
Do national crop item definitions differ from the definitions in the Handbook  (D-flagged data)? YES  
In case yes, how do they differ? ( list all items and explanations) F1110 - Apples
F1112 - Apples for processing
F1120 - Pears
F1122 - Pears for processing
F1210_1220 - Peaches and nectarines
F1212_1222 - Peaches and nectarines for processing

Part of the area of apples for processing is included in the area of apples for fresh consumption, as only area and production of apples for cider is collected separately from the rest of the apples. Thus, in Spain we cannot obtain the total area of apples for processing separately.

For that reason, the item F1112-Apples for processing is flagged with “E”.

 

The area of pears for processing is included in the area of pears for fresh consumption, as in Spain we cannot obtain this area separately.

For that reason, the item F1122-Pears for processing is flagged with “E”.

The area of peaches and nectarines for processing is included in the area of peaches and nectarines for fresh consumption, as Spain cannot obtain this area separately.

For that reason, the item  F1212_F1222- Peaches and nectarines for processing is flagged with “E”.
In case data are delivered for one of the items below, describe the crop species included in the item: C1900 - Other cereals n.e.c. (buckwheat, millet, etc.)
P9000 - Other dry pulses and protein crops n.e.c.
R9000 - Other root crops n.e.c.
G2900 - Other leguminous plants harvested green n.e.c.
G9100- Other cereals harvested green (excluding green maize)
G9900 - Other plants harvested green from arable land n.e.c.
V1900 - Other brassicas n.e.c.
V2900 - Other leafy or stalked vegetables n.e.c.
V3900 - Other vegetables cultivated for fruit n.e.c.
V4900 - Other root, tuber and bulb vegetables n.e.c.
V5900 - Other fresh pulses n.e.c.
V9000 - Other fresh vegetables n.e.c.
U1900 - Other cultivated mushrooms n.e.c.
F1190 - Other pome fruits n.e.c.
F1290 - Other stone fruits n.e.c.
F2900 - Other fruits from subtropical and tropical climate zones n.e.c.
F3900 - Other berries n.e.c.
F4900 - Other nuts n.e.c.
T1900 - Other oranges n.e.c.
T2900 - Other small citrus fruits (including hybrids) n.e.c.
T9000 - Other citrus fruits n.e.c.
W1900 - Grapes for other purposes n.e.c.
H9000 - Other permanent crops for human consumption n.e.c.
PECR9 - Other permanent crops

 C1900 - Other cereals n.e.c. (buckwheat, millet, etc.)

  • millet (Panicum miliaceum L.),
  • einkorn  (triticum monococcum),
  • buckwheat (Fagopyrum esculentum Mill.),
  • canary seed (Phalaris canariensis L.),
  • foxtail millet (Setaria itálica),
  • other cereals not elsewhere classified.


P9000 - Other dry pulses and protein crops n.e.c.

  • Other protein crops harvested dry for grain not elsewhere classified.

R9000 - Other root crops n.e.c.

  • Other root crops not elsewhere classified (excluding seed).
  • Fodder beet (Beta vulgaris L.)
  • Kale for fodder
  • Kohlrabi for fodder
  • Carrot (Daucus carota, L.) not used for human consumption
  • Turnips (Brassica rapa L. var. rapa (L.) Thell.) for fodder
  • Pumpkins for fodder
  • Jerusalem artichoke (Helianthus tuberosus L.) for fodder
  • Fodder parsnips (Pastinaca sativa L.)
  • Yam (Dioscorea spp.) for fodder or for seed
  • Sweet potatoes (Ipomoea batatas (L.) Lam.) for fodder or for seed

 

I1190- Other oilseed crops n.e.c

  • Other crop grown for their oil content which are not elsewhere classified.
  • Carthame (Carthamus tinctorius L.)
  • Peanuts (Arachis hypogaea)
  • Camelina (Camelina sativa )
  • Mustard (Sinapis alba L.)

 

I2900- Other fibre crops n.e.c

  • Other plants grown mainly for fibre content, not elsewhere classified

 

G2900 - Other leguminous plants harvested green n.e.c.

  • Annual or perennial clovers pure or in mixture with other species,
  • Other leguminous plants harvested green not elsewhere classified (excluding seed),
  • Vetches for fodder (Vicia sativa L.)
  • Sainfoin (Onobrychis viciifolia Scop.)
  • Sulla (Hedysarum coronarium)


G9100- Other cereals harvested green (excluding green maize)

  • Other cereals harvested green (excluding green maize) not elsewhere classified.


G9900 - Other plants harvested green from arable land n.e.c.

  • Other annual plants harvested green not elsewhere classified,
  • Rye-grass (Lolium perenne)

 

V1900 - Other brassicas n.e.c.

  • All other brassicas not elsewhere


V2900 - Other leafy or stalked vegetables n.e.c.

  • Other leafy and stalked vegetables not elsewhere classified.
  • Curly endive (Cichorum endivia)
  • Mangold (Beta vulgaris var. cicla)
  • Cardoon  (Cynara cardunculus)
  • Rapini (Brassica rapa)
  • Corn salad  (Valerianella locusta)
  • Rocket (Eruca sativa L.)
  • Borage (Borago officinalis)

 


V3900 - Other vegetables cultivated for fruit n.e.c.

  • Other vegetables cultivated for fruit not elsewhere classified.


V4900 - Other root, tuber and bulb vegetables n.e.c.

  • Other root, tuber and bulb vegetables for human consumption, not elsewhere classified.


V5900 - Other fresh pulses n.e.c.

  • Other fresh pulses for human consumption not elsewhere classified (Green broad beans (Vicia faba L.)

 

V9000 - Other fresh vegetables n.e.c.

  • All other fresh vegetables for human consumption not elsewhere classified.


U1900 - Other cultivated mushrooms n.e.c.

  • Other cultivated mushrooms not elsewhere classified.

 

F1190 - Other pome fruits n.e.c.

  • Other pome fruits not elsewhere classified.

 

F1290 - Other stone fruits n.e.c.

  • Other stone fruits not elsewhere classified

 

F2900 - Other fruits from subtropical and tropical climate zones n.e.c.

  • Other fruits from subtropical and tropical climate zones not elsewhere classified.
  • Custard apple (Annona cherimola)
  • Pomegranate (Punica granatum L.)
  • Dates (Phoenix dactylifera L.)
  • Prickly pear (Opuntia ficus-indica),
  • Mango (Mangifera spp.)
  • Persimmons (Diospyros kaki L.f.)

 

F3900 - Other berries n.e.c.

  • Other berries not elsewhere classified
  • Strawberry tree (Arbutus unedo L.)

 

F4900 - Other nuts n.e.c.

  • Other nuts not elsewhere classified

 

T1900 - Other oranges n.e.c.

  • All other varieties of oranges not elsewhere classified

 

T2900 - Other small citrus fruits (including hybrids) n.e.c.

  • All other small citrus fruits not elsewhere classified.

 

T9000 - Other citrus fruits n.e.c.

  • Other citrus fruit not elsewhere classified

 

W1900 - Grapes for other purposes n.e.c.

  • Grape varieties for other purposes not elsewhere classified (not for wine, juice, must, table use or raisins)

 

H9000 - Other permanent crops for human consumption n.e.c.

  • Other permanent crops for human consumption not elsewhere classified
  • Other permanent crops under glass or high accessible cover

 

PECR9 - Other permanent crops 

  • Permanent crops not elsewhere classified on the utilised agricultural area.

 


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).

ACS statistics are compiled as a multisource statistic combining adminstrative data, statistica data, consultations to agricultural organisations and sectoral organisations. Concerning the statistical data, the main source for ACS is ESYRCE, with a geographical scope covering all the territory. Together with ESYRCE, IFS is also used as a source for some categories, and as a contrast source.

The following comments make reference to ESYRCE, that is the Ministry of Agriculture, Fisheries and Food's own statistical operation.
Is the data collection based on holdings? NO
If yes, how the holdings were identified?
If not, on which unit the data collection is based on?

Area Frame Survey. The sampling unit is called a segment, and is a 700 m x 700 m quadrant in which information is taken on all the parcels, agricultural or not, contained in it.
When was last update of the holding register? (month/year)
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

ESYRCE (Encuesta de Superficies y Rendimientos de Cultivos)
Which survey method was used? Other
If 'other', please specify

Area Frame Survey, with:

- field data gathering for sample units of agricultural importance (in % if the surface of the sample unit)

- photo interpretation for sample units of non agricultural importance with accesibility problems

- information from previous years for sample units of non agricultural importance without accesibility problems (all sample units at NUTS 3 are visited in field every 6 - 8 years)
Please provide a link to the questionnaire

https://www.mapa.gob.es/es/estadistica/temas/estadisticas-agrarias/agricultura/esyrce/default.aspx

 
Data entry method, if paper questionnaires?


Administrative data (This question block is only for administrative data)

  Admin source 1 Admin source 2 Admin source 3 Admin source 4 Admin source 5 Admin source 6
Name of the register

IACS (is made following European Regulation for CAP payment. For this reason this table is not being filled).

Registro General de la Producción Agrícola (REGEPA) / General Register of Agricultural Production

Vineyard register
Description

Farmer declarations

Farmer declarations

The Vineyard Register is an official register where data is collected on the identification, location and ownership of the vineyard plots as well as their characteristics: cadastral reference, Agrarian Parcel Information System referencie, area of parcel, grape varieties, year of planting, etc.
Data owner (organisation)

FEGA (Spanish Agrarian Guarantee Fund) (belonging to the Ministry of Agriculture, Fisheries and Food)

Ministry of Agricutlure, Fisheries and Food

Autonomous Communities (NUTS 2 Administrattions)
Update frequency Once per year or more often Once per year or more often Continuous
Reference date (month/year)

07/2022

07/2022
Legal basis

Regulation (EU) 2021/2115 of the European Parliament and of the Council of 2 December 2021 establishing rules on support for strategic plans to be drawn up by Member States under the common agricultural policy (CAP Strategic Plans) and financed by the European Agricultural Guarantee Fund (EAGF) and by the European Agricultural Fund for Rural Development (EAFRD) and repealing Regulations (EU) No 1305/2013 and (EU) No 1307/2013.

Regulation (EU) 2021/2116 of the European Parliament and of the Council of 2 December 2021 on the financing, management and monitoring of the common agricultural policy and repealing Regulation (EU) No 1306/2013. 

 

Ley 30/2022, de 23 de diciembre, por la que se regulan el sistema de gestión de la Política Agrícola Común y otras materias conexas.

Law 30/2022 of 23 December 2002 regulating the management system of the Common Agricultural Policy and other related matters.

 

Real Decreto 1047/2022, de 27 de diciembre, por el que se regula el sistema de gestión y control de las intervenciones del Plan Estratégico y otras ayudas de la Política Agrícola Común.

Royal Decree 1047/2022 of 27 December, which regulates the system for the management and control of the interventions of the Strategic Plan and other aids of the Common Agricultural Policy.

 

Real Decreto 1048/2022, de 27 de diciembre, sobre la aplicación, a partir de 2023, de las intervenciones en forma de pagos directos y el establecimiento de requisitos comunes en el marco del Plan Estratégico de la Política Agrícola Común, y la regulación de la solicitud única del sistema integrado de gestión y control.

Royal Decree 1048/2022 of 27 December on the application, as from 2023, of intervention in the form of direct payments and the establishment of common requirements in the framework of the Strategic Plan for the Common Agricultural Policy, and the regulation of the single application for the integrated administration and control system.

Real Decreto 9/2015, de 16 de enero, por el que se regulan las condiciones de aplicación de la normativa comunitaria en materia de higiene en la producción primaria agrícola

Royal Decree 9/2015, of 16 January, which regulates the conditions for the application of Community regulations on hygiene in primary agricultural production

Regulation (EU) No 1308/2013 of the European Parliament and of the Council of 17 December 2013 establishing a common organisation of the markets in agricultural products and repealing Council Regulations (EEC) No 922/72, (EEC) No 234/79, (EC) No 1037/2001 and (EC) No 1234/2007.

 

Commission Delegated Regulation (EU) 2018/273 of 11 December 2017 supplementing Regulation (EU) No 1308/2013 of the European Parliament and of the Council as regards the scheme of authorisations for vine plantings, the vineyard register, accompanying documents and certification, the inward and outward register, compulsory declarations, notifications and publication of notified information, and supplementing Regulation (EU) No 1306/2013 of the European Parliament and of the Council as regards the relevant checks and penalties, amending Commission Regulations (EC) No 555/2008, (EC) No 606/2009 and (EC) No 607/2009 and repealing Commission Regulation (EC) No 436/2009 and Commission Delegated Regulation (EU) 2015/560

 

Real Decreto 1338/2018, de 29 de octubre, por el que se regula el potencial de producción vitícola.

Royal Decree 1338/2018 of 29 October 2018 regulating wine production potential.
Reporting unit

Applicants for aid under the common agricultural policy

Farmers (consistent with Agricultural Parcel Informatioin System)
Identification variable (e.g. address, unique code, etc.)
Percentage of mismatches (%)

Not applicable
How were the mismatches handled?

Not applicable
Degree of coverage (holdings, e.g. 80%)
Degree of completeness (variables, e.g. 60%)
If not complete, which other sources were used ?
Were the data used for sample frame?
Data used for other purposes, which?
Which variables were taken from administrative sources?
Were there any differences in the definition of the variables between the administrative source and those described in the Regulation?
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?
What were the possible limitations, drawbacks of using the data from administrative source(s)?


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

Not applicable
Data owner (organisation)
Update frequency (e.g. 1 year or 6 months)
Reference date (Month/Year  e.g. 1/22 - 8/22)
Legal basis
Use purpose of the estimates?
What kind of expertise the experts have?
What kind of estimation methods were used?
Were there any differences in the definition of the variables between the experts' estimates and those described in the Regulation?
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?
What were the possible limitations, drawbacks of using the data from expert estimate(s)?
Additional comments


 
3.4. Data validation

Which kind of data validation measures are in place? Automatic and Manual
What do they target? Completeness
Outliers
Aggregate calculations
Other
Is the data cross-validated against an other dataset? YES
If yes, which kind of dataset? Previous results
Other dataset
Farm Structure Survey
If other, please describe

Agricultural Census 2020

  

The 3.4. table concern the Survey (ESYRCE) and the Administrative Sources






 
3.5. Data compilation

Not Applicable.
3.6. Adjustment

Not applicable.


4. Quality management Top
4.1. Quality assurance

  Completeness Punctuality Accuracy Reliability Overall quality
How would you describe the overall quality development since the previous quality report? Improvement Improvement Improvement Improvement Improvement
Is there a quality management process in place for crop statistics? NO        
If, yes, what are the components?        
Is there a quality report available? NO        
If yes, please provide a link(s)        
To which data source(s) is it linked?
       
Has a peer-review been carried out for crop statistics? NO        
If, yes, which were the main conclusions?        
What quality improvement measures are planned for the next 3 years? Increase of resources
Systematic validation improvements
Further automation
Quality report
Peer review		        
If, other, please specify        
Additional comments        






 
4.2. Quality management - assessment

See the European level Quality Report.


5. Relevance Top
5.1. Relevance - User Needs

Are there known unmet user needs? NO
Describe the unmet needs
Does the Regulation 543/2009 meet the national data needs? YES
Does the ESS agreement meet the national needs? YES
If not, which additional data are collected?
Additional comments






 
5.2. Relevance - User Satisfaction

Have any user satisfaction surveys been done? NO
If yes, how satisfied the users were?
Additional comments






 
5.3. Completeness

See the European level Quality Report
5.3.1. Data completeness - rate

See the European level Quality Report


6. Accuracy and reliability Top

See points 6.2, 6.3.1, 6.3.2 and 6.3.3
6.1. Accuracy - overall

See the European level Quality Report.
6.2. Sampling error

Sampling method and sampling error

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

ESYRCE (Encuesta de Superficies y Rendimientos de Cultivos) 

Area Frame Survey on Crop Areas and Yields
Sampling basis? Area
If 'other', please specify
Sampling method? Clustered
Stratified
If stratified, number of strata?

4 strata (for each NUTS 3 administrative division):

- intensive agriculture (irrigated)
- extensive (rainfed) agriculture
- low cropping areas
- no-tillage areas
If stratified, stratification basis? Specialisation
If 'other', please specify
Size of total population

502,831
Size of sample

24,038
Which methods were used to assess the sampling error?  Relative standard error
If other, which?
Which methods were used to derive the extrapolation factor?  Basic weight
If other, which?
If CV (co-efficient of variation) was calculated, please describe the calculation methods and formulas
If the results were compared with other sources, please describe the results
Which were the main sources of errors?


Sampling error - indicators

Not applicable


Coefficient of variation (CV) for the area (on the MS level)

  Survey 1  Survey 2 Survey 3  Survey 4 Survey 5  Survey 6 Survey 7
Name of the survey

ESYRCE (Encuesta de Superficies y Rendimientos de Cultivos)

Area Frame Survey on Crop Areas and Yields
Cereals for the production of grain (in %)

1.94
Dried pulses and protein crops (in %)

3.52
Root crops (in %)

7.63
Oilseeds (in %)

2.98
Other industrial crops (included all industrial crops besides oilseeds)  (in %)

11.49
Plants harvested green from arable land (in %)

2.49
Total vegetables, melons and strawberries (in %)

4.31
Cultivated mushrooms (in %)

59.00
Total permanent crops (in %)

2.50
Fruit trees (in %)

3.45
Berries (in %)

24,94
Nut trees (in %)

3.85
Citrus fruit trees (in %)

7.80
Vineyards (in %)

3.02
Olive trees (in %)

1.60
Additional comments

ACS is estimated as a multisource statistic, where aggregates are estimated as a combination of both statistical and administrative sources.with high error crops are taken from Administrative Sources.

            




 
6.3. Non-sampling error
6.3.1. Coverage error

Over-coverage - rate

not applicable


Common units - proportion

not applicable


  Data source 1 Data source 2 Data source 3 Data source 4 Data source 5 Data source 6 Data source 7 Data source 8 Data source 9
Name of the data source
Error type
Degree of bias caused by coverage errors
What were the reasons for coverage errors?
Which actions were taken for reducing the error or to correct the statistics?
Additional comments




 
6.3.2. Measurement error

  Data source 1 Data source 2 Data source 3 Data source 4 Data source 5 Data source 6 Data source 7 Data source 8 Data source 9
Name of the data source

ESYRCE
Was the questionnaire based on usual concepts for respondents? NO
Number of surveys already performed with the current questionnaire (or a slightly amended version of it)?

32
Preparatory (field) testing of the questionnaire? YES
Number of units participating in the tests? 

50
Explanatory notes/handbook for surveyors/respondents?  YES
On-line FAQ or Hot-line support for surveyors/respondents? YES
Were pre-filled questionnaires used? YES
Percentage of pre-filled questions out of total number of questions

40%
Were some actions taken for reducing the measurement error or to correct the statistics? YES
If yes, describe the actions and their impact

In situ inspections






 
6.3.3. Non response error

Unit non-response - rate

Not applicable


Item non-response - rate

Not applicable


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

ESYRCE
Unit level non-response rate (in %)

0.21% (51 sampling units inaccesible over a sample of 24,038 units)

The sampling unit (segment) is a quadrant of 700 metres on each side (700 m x 700 m) in which information on crop/land cover, irrigation techniques, sowing methods, production status of permanent crops, etc. is collected from all the plots contained in it.

Unit non-response rate is calculated over the part of the inaccesible segments, thus information cannot be collected for any plot contained in the segments.
Item level non-response rate (in %)              
               - Min% / item
               - Max% / item
               - Overall%

0.52% (3,791 plots inaccesible over a total number of plots in accesible segments of 732,381 plots)

Average number of plots in a segment: 40.71

The average number of unseen plots persegment is 4.9% (within segments where there are inaccessible plots).

Item level non-response rate is calculated considering those inaccesible plots in the accesible sampling units (segments).
Was the non-response been treated ? YES
Which actions were taken to reduce the impact of non-response?

 

For unit non-response :

- Imputation based on information from previous years.

- Imputation based on photo interpretation of plots.

 

For item non-response

- Imputation based on photo interpretation of plots.

- Contact with land owners or foremen

In all of them, photo-interpretation or the dragging of the previous information is most common method applied. Sometimes alternative methods have been used to collect information without the need to physically access the plot, such as the use of drones. In ESYRCE 2022, 272 plots have been visited with drones (7.17% of the 3,791 inaccessible plots).
Which items had a high item-level non-response rate? 

the source of item non response originates from impediments to access to the plots on the ground, so that no parallel can be drawn with questions to a questionnaire in this case. However, access to large areas of greenhouses is problematic because of sanitary restrictions that may affect crops grown under very sophisticated conditions.
Which methods were used for handling missing data?
(several answers allowed)
In case of imputation which was the basis? Imputation based on the same unit in previous data
In case of imputation, which was the imputation rate (%)?

0.80% of total numer of plots of the sample
Estimated degree of bias caused by non-response? None
Which tools were used for correcting the data?

Orthophoto
Which organisation did the corrections?

Ministerio de Agricultura, Pesca y Alimentación (Ministry of Agriculture, Fisheries and Food)

Subdirección General de Análisis, Coordinación y Estadística (Sub-Directorate General for Analysis, Coordination and Statistics) through a contractor

www.mapa.gob.es

https://www.mapa.gob.es/es/estadistica/temas/default.aspx

https://www.mapa.gob.es/es/ministerio/funciones-estructura/organigrama/
Additional comments




 
6.3.4. Processing error

Not applicable.
6.3.4.1. Imputation - rate

Not applicable.
6.3.5. Model assumption error

Not applicable.
6.4. Seasonal adjustment

Not applicable.
6.5. Data revision - policy

Not applicable.
6.6. Data revision - practice

Not applicable.
6.6.1. Data revision - average size

Not applicable.


7. Timeliness and punctuality Top
7.1. Timeliness

Time lag - first result

No time lag for first result


Time lag - final result

No time lag for 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?

15

15

15

15

15

15

12

15

15

15

15

15

15

15

15
How many of them are forecasts (releases before the harvest)?

12

12

12

12

12

12

15

12

12

12

12

12

12

12

12
When was the first  forecasting published for the crop year on which is reported? (day/month/year) 25/12/2022 25/04/2022 24/03/2022 25/05/2022 21/06/2022 25/04/2022 24/03/2022 25/01/2022 21/09/2022 24/03/2022 22/02/2022 25/04/2022 22/08/2022 22/08/2022 22/08/2022
When were the final results published for the crop year on which is reported? (day/month/year) 31/10/2023 31/10/2023 31/10/2023 31/10/2023 31/10/2023 31/10/2023 30/04/2023 30/04/2023 30/04/2023 30/04/2023 30/04/2023 30/04/2023 31/10/2023 30/04/2023 30/04/2023
Additional comments




 
7.2. Punctuality

See the European level Quality Report
7.2.1. Punctuality - delivery and publication

See the European level Quality Report


8. Coherence and comparability Top
8.1. Comparability - geographical

Not applicable.
8.1.1. Asymmetry for mirror flow statistics - coefficient

Not applicable.
8.2. Comparability - over time

Length of comparable time series

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 NO NO
If yes, to which were they related?
If other, which?
Which items were affected?
Year of break (number)
Impact on comparability
Additional comments

 

 





 
8.2.1. Length of comparable time series

Not applicable
8.3. Coherence - cross domain

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

Agrarian Census (IFS 2020)

Vineyard Survey 2020
If no comparisons have been made, why not?


Differences between ACS and other data sources (%)

Results of comparisons IFS 2020 Vineyard survey 2020 IACS Other source(s)  In case of other sources, which?
Cereals    

97,70%
Dried pulses and protein crops    

144,06%
Root crops    

232,71%
Oilseeds    

103,24%
Other industrial crops (than oilseeds)    

72,71%
Plants harvested green    

204,41%
Total vegetables, melons and strawberries    

232,52%
Vegetables and melons    

232,75%

 
Strawberries    

221,66%

 
Cultivated mushrooms

186%

  

557.709,51%

(few IACS declarations)

 
Total permanent crops

109,05%

  

 
Fruit trees

115,56%

Not applicable.

695,53%

 
Berries

154,90%

  

285,99%

 
Nut trees

118,37%

  

120,87%

 
Citrus fruit trees

108,52%

Not applicable.

141,93%

 
Vineyards

107,31%

101,32%

124,24%

 
Olive trees

106,93%

Not applicable.

115,86%

 
If there were considerable differences, which factors explain them?

Few declarations for certain crops

Different classifications and classes that difficult comparison (p.e. crops associations as classes: Olive trees - Fruit trees, Vineyard - Fruit trees, Vineyard - Olive trees, Citrus trees - Fruit trees...)

  





 
8.4. Coherence - sub annual and annual statistics

Not applicable.
8.5. Coherence - National Accounts

Not applicable.
8.6. Coherence - internal

Not applicable.


9. Accessibility and clarity Top
9.1. Dissemination format - News release

Availability Links
NO






 
9.2. Dissemination format - Publications

  Availability Links
Publications Electronic

https://www.mapa.gob.es/es/estadistica/temas/estadisticas-agrarias/agricultura/

https://www.mapa.gob.es/es/estadistica/temas/estadisticas-agrarias/agricultura/superficies-producciones-anuales-cultivos/

 https://www.mapa.gob.es/es/estadistica/temas/publicaciones/anuario-de-estadistica/default.aspx

 

 
Publications in English None






 
9.3. Dissemination format - online database

Data tables - consultations

Not applicable


  Availability Links
On-line database accessible to users NO
Website





 
9.4. Dissemination format - microdata access

Availability Links
NO






 
9.5. Dissemination format - other

Not applicable.
9.6. Documentation on methodology

  Availability Links
Methodological report National language

https://www.mapa.gob.es/estadistica/pags/anuario/2021/CAPITULOS%20PDF/AE21-C07.pdf
Quality Report None
Metadata None
Additional comments

Other documents of interest regarding crop statistics:

Glosario: Nomenclatura y taxonomía fines estadisticos: Crop classes and their scientific name, as well as their translation to other languages (English, French, and Cooficial Spanish Languages).

https://www.mapa.gob.es/es/estadistica/temas/estadisticas-agrarias/agricultura/glosario/

 

Calendarios de Siembra, Recolección y Comercialización: sowing, harvesting and marketing calendar for main crops.

https://www.mapa.gob.es/es/estadistica/temas/estadisticas-agrarias/agricultura/calendarios-siembras-recoleccion/

  






 
9.7. Quality management - documentation

Not applicable.
9.7.1. Metadata completeness - rate

Not applicable.
9.7.2. Metadata - consultations

Not applicable.


10. Cost and Burden Top

Efficiency gains if compared to the previous quality report? Increased use of administrative data
Staff further training
If other, which?
Burden reduction measures since the previous reference year  Multiple use of the collected data
Other
If other, which?

ACS is compiled as a multisource statistic by the Ministry of Agriculture, Fisheries and Food (MAPA) in collaboration with NUTS 2 regional administration. Since the last reference year of the ACS quality report (2019), the MAPA is providing with a statistical exploitation of administrative data from IACS at NUTS 3 level for different land classes (arable land, permanent crops, grasslands...) to statistical staff in the regions to facilitate the production of annual crop statistics. 

This is a great advantage for staff in the regions as access to administrative data in this way is often quicker and more complete, as crop declarations on parcels in one region can be made in a different region.






 


11. Confidentiality Top
11.1. Confidentiality - policy
Restricted from publication
11.2. Confidentiality - data treatment
Restricted from publication


12. Comment Top


Related metadata Top


Annexes Top