Crop production (apro

Crop production (apro_cp)

National Reference Metadata in ESS Standard for CROPS Reports Structure (ESQRSCP)

Compiling agency: DEPARTMENT FOR ENVIRONMENT FOOD & RURAL AFFAIRS

Eurostat metadata

Reference metadata

1. Contact
2. Statistical presentation
3. Statistical processing
4. Quality management
5. Relevance
6. Accuracy and reliability
7. Timeliness and punctuality
8. Coherence and comparability
9. Accessibility and clarity
10. Cost and Burden
11. Confidentiality
12. Comment
Related Metadata
Annexes (including footnotes)

For any question on data and metadata, please contact: Eurostat user support

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1. Contact

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1.1. Contact organisation

DEPARTMENT FOR ENVIRONMENT FOOD & RURAL AFFAIRS

1.2. Contact organisation unit

Defra Statistics

1.5. Contact mail address

ROOM 201, FOSS HOUSE, KINGS POOL, 1-2 PEASHOLME GREEN, YORK YO1 7PX, UNITED KINGDOM

2. Statistical presentation

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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

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3.1. 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?
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			The Early Bird Survey published by Agriculture and Horticultural Development Borad / Andersons Consultants every autumn and provides a reliable guide to growers cropping intentions - especially for Wheat, Winter Barley, Spring Barley, Oats, Other Cereals (rye triticale and mixed grain) Oilseed Rape, other oilseeds (linseed and borage) Pulses and Other crops (potatoes, sugar beet, vegetables maize and temporary grass). https://ahdb.org.uk/cereals-oilseeds/early-bird-survey
Final area under cultivation	Survey	June survey of agriculture
Production	Survey	Cereal production survey, Oilseed rape production survey
Yield	Survey	Cereal production survey, Oilseed rape production survey
Non-existing and non-significant crops
Table 2: Vegetables, melons and strawberries
Early estimates for harvested areas
Final harvested area	Survey Administrative data	June survey of agriculture Potato Council Planting Returns (admin source)
Production	Survey	Potato yield panel, Fruit panel survey, Vegetable expert survey, Ornamental expert survey
Non-existing and non-significant crops
Table 3: Permanent crops
Early estimates for production area
Final production area	Survey	June survey, Fruit panel survey
Production	Survey Expert estimate	Fruit panel survey Ornamentals expert survey	Mixture of a survey and expert estimate: The Fruit Crop Intelligence Committees provide information during the summer months and this is supplemented by direct contact with fruit Producer Organisations, English Apples and Pears (EAP), Propagators and cider makers. Information is also gathered from ADAS and independent consultants.
Non-existing and non-significant crops
Table 4: Agricultural land use
Main area	Survey	June survey of agriculture
Non-existing and non-significant crops
Total number of different data sources	7
Additional comments

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	June survey of agriculture	Crop production surveys	Potato Council Planting Returns	Potato Grower Panel Survey	Fruit panel survey	Vegetable Expert Survey	Ornamentals Expert Survey
Planning (month-month/year)	Feb-Apr 2019	May-Jun 2019	April 2019
Preparation (month-month/year)	Feb-Apr 2019	May-Jun 2019	April 2019
Data collection (month-month/year)	June 2019	Aug-Oct 2019	May-Jun 2019	Sep-Nov 2019	March 2020	March 2020	March 2020
Quality control (month-month/year)	Jun-Sep 2019	Aug-Oct 2019	June 2019	Nov 2019	March 2020	March 2020	March 2020
Data analysis (month-month/year)	Aug-Dec 2019	Sep-Dec 2019	June 2019	Nov 2019	April 2020	April 2020	April 2020
Dissemination (month-month/year)	Aug-Dec 2019	Sep-Dec 2019	June 2019	Nov 2019	May 2020	May 2020	May 2020
If there were delays, what were the reasons?

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?
Are special estimation/calculation methods used for main crops from arable land?
Are special estimation/calculation methods used for vegetables or strawberries?
Are special estimation/calculation methods used for permanent crops for human consumption?
Are special estimation/calculation methods used for main land use?
Do national crop item definitions differ from the definitions in the Handbook (D-flagged data)?
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:	P9000 - Other dry pulses and protein crops n.e.c. R9000 - Other root crops n.e.c. I1190 -Other oilseed crops n.e.c G2900 - Other leguminous plants harvested green n.e.c. G9900 - Other plants harvested green from arable land n.e.c. V2900 - Other leafy or stalked vegetables n.e.c. V9000 - Other fresh vegetables n.e.c.	R9000 - Other root crops n.e.c.: I1190 -Other oilseed crops n.e.c P9000 - Other dry pulses and protei:n crops n.e.c.: G2900 - Other leguminous plants harvested green n.e.c.: G9900 - Other plants harvested green from arable land n.e.c.: V2900 - Other leafy or stalked vegetables n.e.c.: V9000 - Other fresh vegetables n.e.c.: estimate for all other non specified veg - not collected as individual types

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).
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?	Own farm register, admin sources (RPA) and payments register
When was last update of the holding register? (month/year)	Continuous updates
Was a threshold applied?	YES
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 %)	0.1%
Dried pulses and protein crops (in %)	0.1%
Root crops (in %)	0.1%
Oilseeds (in %)	0.1%
Other industrial crops (included all industrial crops besides oilseeds) (in %)	0.2%
Plants harvested green from arable land (in %)	0.2%
Total vegetables, melons and strawberries (in %)	0.2%
Cultivated mushrooms (in %)	0%
Total permanent crops (in %)	1.9%
Fruit trees (in %)	1.9%
Berries (in %)	1.9%
Nut trees (in %)	n/a
Citrus fruit trees (in %)	n/a
Vineyards (in %)	1.9%
Olive trees (in %)	n/a

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	June survey of agriculture	Crop production survey	Oilseed rape production survey	Potato Grower Panel Survey (yield)	Fruit Panel Survey	Vegetables Expert Survey	Ornamentals Expert Survey
Which survey method was used?	On-line electronic questionnaire filled in by respondent Postal questionnaire filled in by respondent	Postal questionnaire filled in by respondent	Postal questionnaire filled in by respondent	On-line electronic questionnaire filled in by respondent Postal questionnaire filled in by respondent	On-line electronic questionnaire filled in by respondent Postal questionnaire filled in by respondent Face-to-face interview	Telephone interview, paper questionnaire Face-to-face interview	Telephone interview, paper questionnaire Face-to-face interview
If 'other', please specify
Please provide a link to the questionnaire
Data entry method, if paper questionnaires?	Manual	Manual	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	Potato Council Planting Returns
Description	Data held on the Council database covers every potato crop from 1996 onwards for variety, area, statistical county (old county boundaries). From 2003 it includes market sector data for each crop, and from 2004 accurate georeferences verified via GIS. It is a statutory requirement that any person in GB who grows three hectares or more of potatoes in any calendar year must pay a levy based on area planted and must provide AHDB with the following information: (a) the area planted or intended to be planted that calendar year; and (b) the identity of the fields planted; Growers in Northern Ireland are not covered by the Potato Council and therefore are not required to fill out a Planting Return. Census. All growers with at least 3 hectares potatoes are required to complete a Planting Return each year (2150 farmers). Growers with less than 3hectares of potatoes are not surveyed.
Data owner (organisation)	Agricultural and Horticultural Development Board
Update frequency	Once per year or more often
Reference date (month/year)	June 2019
Legal basis	Yes
Reporting unit	Potato grower
Identification variable (e.g. address, unique code, etc.)	n/a
Percentage of mismatches (%)	n/a
How were the mismatches handled?	n/a
Degree of coverage (holdings, e.g. 80%)	100%
Degree of completeness (variables, e.g. 60%)	100%
If not complete, which other sources were used ?
Were the data used for sample frame?	Directly for estimates Other
Data used for other purposes, which?	For payment of levies
Which variables were taken from administrative sources?	Potato area
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?
What were the possible limitations, drawbacks of using the data from administrative source(s)?	None

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
Data owner (organisation)
Update frequency (e.g. 1 year or 6 months)
Reference date (Month/Year e.g. 1/16 - 8/16)
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?
If other, please describe	Locigal consistency

3.5. Data compilation

Not Applicable.

3.6. Adjustment

Not applicable.

4. Quality management

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4.1. Quality assurance

	Completeness	Punctuality	Accuracy	Reliability	Overall quality
How would you describe the overall quality development since the previous quality report?	Stable	Stable	Stable	Stable	Stable
Is there a quality management process in place for crop statistics?	YES
If, yes, what are the components?	The Code of Practice for Official Statistics, assessment audits by the UK Statistics Authority, Defra’s quality strategy for statistics.
Is there a Quality Report available?	YES
If yes, please provide a link(s)	https://uksa.statisticsauthority.gov.uk/publication/statistics-on-agriculture/ https://uksa.statisticsauthority.gov.uk/wp-content/uploads/2015/11/images-assessmentreport271statisticsonagricultur_tcm97-43550.pdf https://code.statisticsauthority.gov.uk/
To which data source(s) is it linked?	June Survey of agriculture and horticulture Crop Production Survey Stocks Surveys Usage surveys ADAS panel estimates for fruit and vegetables Potato Council estimates Basic Horticultural Statistics + unpublished report
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?	Other
If, other, please specify	Review of spreadsheet design. Simplification of data flows. Specific reviews under the Defra quality strategy. Areas for review not yet identified.
Additional comments	The main source of agricultural statistics in the UK is the annual June Survey of Agriculture, which collects detailed information on crop and grassland areas and livestock populations. The survey has been running since 1866 and is a very stable and reliable source. The June survey is then used to target other, smaller surveys that collect information on cereal and oilseed rape production and yields. Information on detailed horticultural areas and production are sourced from industry experts' information.

4.2. Quality management - assessment

See the European level Quality Report.

5. Relevance

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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

6. Accuracy and reliability

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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	June survey of agriculture and horticulture	Crop Production Surveys	Potato Grower Panel Survey (yield)	Fruit Panel Survey	Vegetable Expert Survey	Ornamentals Expert Survey
Sampling basis?	List	List	List Other	Other	Other	Other
If 'other', please specify			The Grower Panel (GP) is a voluntary survey of a sample of around 450 growers giving data on varieties, yields, seed usage, sale prices, wastage, and storage. Approximately 20% of growers are in the panel.	The Fruit Crop Intelligence Committees provide information during the summer months and this is supplemented by direct contact with fruit Producer Organisations, English Apples and Pears (EAP), Propagators and cider makers. Information is also gathered from ADAS and independent consultants.	Information sought from a range of sources; ADAS consultants, external specialist consultants, British Grower Associations (BGA) where they exist for the specified crop, individual growers and producers, including larger producers and packers.	Based on acquired knowledge of sector; information sought from a range of stakeholders including growers, plant propagators, propagation material (seeds and cuttings) suppliers, cut flower packers
Sampling method?	Stratified	Stratified	Other	Other	Other
If stratified, number of strata?	6	16		The Fruit Crop Intelligence Committees provide monthly reports during the summer for all the major production areas for the major fruit crops. This is supplemented by information from ADAS and independent consultants including the areas and crops not covered by the Committees. In the winter months stored top fruit data is collected from a database of all the major top fruit storing organisations.	Direct contact by visits, phone calls and emails to businesses or associations with specific questions relevant to sector by ADAS and independent consultants. Focus on major production areas, main known producers/producer groups, maintaining a geographical spread. Data provided and collated from seed houses by the British Growers Association (BGA) and individual growers that are members of the BGAs associations	Direct contact with businesses with specific questions relevant to sector by ADAS and independent consultants
If stratified, stratification basis?	Size	Location Size
If 'other', please specify			From around the 450 growers, 700-800 fields are selected. Sampling is proportional to planted area, and therefore approximately proportional to market sector, variety and region.	Informally stratified by focus on larger producers, producer groups and others in the supply chain.	Informally stratified by focus on larger producers, producer groups and others in the supply chain	Informally stratified by focus on larger producers, producer groups and others in the supply chain
Size of total population	218609	7805	2150	The total number of fruit producers is difficult to estimate as the sector encompasses a range of diverse businesses from small independent producers and PYO businesses to large independent businesses or members of POs that produce the majority of product.	The total number of vegetable producers is difficult to estimate as in some crops there are small family-run businesses to some very large businesses or producer organisations that produce the majority of some products.	The number of ornamentals producers is difficult to estimate as the sector encompasses a range of diverse businesses: many small businesses (e.g. family-run businesses with <10 employees) and fewer large businesses that produce the majority of product. Information is sought from a population that includes growers, plant propagators, plant propagation material suppliers, cut flower packers and organisation e.g. the BPOA (British Protected Ornamentals Association), Cut Flower Centre with specific; some contacts respond on behalf of a number of growers for some categories.
Size of sample	98920	5219	450	The data provided by the Crop Intelligence committees, Producer Organisations, ADAS and independent consultants and other organisations in the supply chain covers the majority of commercial fruit producers in England and Wales. There are 410 contacts for fruit data and an estimated average coverage of 85%.	The sample covers the major Vegetable and salad growing areas in England and Wales covering individual growers, grower groups and large producers and packers. There are 431 contacts for vegetables and salad data and an estimated average coverage of just below 80%	The sample is not homogeneous as it extends beyond growers to other members of the supply chain (propagators, suppliers, plant and flower packers). Some contacts respond on behalf of a number of growers for some crop categories. There are 200 contacts for ornamentals data and an average coverage of 80%.
Which methods were used to assess the sampling error?	Relative standard error	Relative standard error		Other	Other	Other
If other, which?				Comparison / cross-checking of data from different sources. Responses which include ‘outlier’ values are checked with originator	Comparison / cross-checking of data from different sources. Responses which include ‘outlier’ values are checked with originator	Comparison / cross-checking of data from different sources. Responses which include ‘outlier’ values are checked with originator
Which methods were used to derive the extrapolation factor?	Other	Other
If other, which?	Ratio estimation (current data compared to previous years data to estimate ratio and compared to previous years total)	Crop yields (production/area) for respondent holdings, applied to the June Survey national crop area to get estimates of total crop production
If CV (co-efficient of variation) was calculated, please describe the calculation methods and formulas			95% confidence limits for the mean yield are estimated conventionally from the standard deviation of the sample of net yield, and are applied to the GB production estimate. Typically these are of the order of ±2% on a sample size of 750 crops, or around ±120,000 t on a production of 6 million t.
If the results were compared with other sources, please describe the results	Industry expectations. Results were broadly as expected.	Industry surveys. Results were broadly in line.		Data for fruit in store during the winter provided by the ADAS database of top fruit storing organisations is compared to information from English Apples and Pears. On the whole there has been a good measure of agreement for most varieties.	Data collated from direct consultation with businesses are compared with that provided by the Grower Associations. If there are considerable disparities between the data, the source is revisited to check and verify the methodology used.	Where there are significant differences, data is doubled checked with the source and an explanation sought e.g. there can be significant differences in value for similar products depending on market (e.g. garden centre vs. DIY store vs. landscaper); the value of hanging baskets and planted containers is variable depending on container size, complexity of planting and plant choice.
Which were the main sources of errors?	Sampling error	Sampling error		Non return of data sheets by some contributors (for both sources)

Sampling error - indicators

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	June survey of agriculture
Cereals for the production of grain (in %)	0.7%
Dried pulses and protein crops (in %)	3.5%
Root crops (in %)	2.0%
Oilseeds (in %)	1.7%
Other industrial crops (included all industrial crops besides oilseeds) (in %)	7.9%
Plants harvested green from arable land (in %)	1.1%
Total vegetables, melons and strawberries (in %)	3.9%
Cultivated mushrooms (in %)	n/a
Total permanent crops (in %)	2.7%
Fruit trees (in %)	2.7%
Berries (in %)	7.2%
Nut trees (in %)	n/a
Citrus fruit trees (in %)	n/a
Vineyards (in %)	15.7%
Olive trees (in %)	n/a
Additional comments

6.3. Non-sampling error

6.3.1. Coverage error

Over-coverage - rate

Common units - proportion

	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	June Survey of Agriculture & Horticulture	Crop production surveys	Potato Council Planting Returns (area)	Potato growing panel survey (yield)	Fruit Panel Survey	Vegetable Expert Survey	Ornamentals Expert Survey
Error type	Under-coverage	Under-coverage	Under-coverage	Under-coverage	Under-coverage	Under-coverage	Under-coverage
Degree of bias caused by coverage errors	Low	Low	Low	Low	Low	Low	Low
What were the reasons for coverage errors?	Sample size is fixed and targeted to larger farms.	Fixed sample size targeted to larger cereal growing regions	New growers don’t automatically submit a return despite it being a legal requirement.	Unregistered plantings.	Survey focuses on large growers	Survey focuses on large growers	Survey focuses on large growers
Which actions were taken for reducing the error or to correct the statistics?	A rolling sample of the smallest farms was introduced to ensure all were sampled at a regular basis (every 5 years minimum)	Increased sample size in smaller, wetter regions	By observing that the grower size-area distribution is a regular function that is left censored (at 3-ha), the area below 3-ha can be estimated by integration as approximately 2% of registered plantings. This gives an unreported area of 5-6% (fluctuating slightly each year depending on audit results). Applying this expansion factor gives the estimated the total GB potato plantings.	Annual helicopter audits with ground checks on approx 15% of plantings indicates rate of unregistered plantings at about 6%. GB area estimates factored up by this amount, using 5 year rolling average.	Survey achieves an 85% coverage of production	Survey achieves an 80% coverage of prduction	Survey achieves an 80% coverage of production
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	June Survey of Agriculture & Horticulture	Crop production surveys	Potato Council Planting Returns (area)	Potato Grower Panel Survey (yield)	Fruit Panel Survey	Vegetable Expert Survey	Ornamentals Expert Survey
Was the questionnaire based on usual concepts for respondents?	YES	YES		YES	YES	YES	YES
Number of surveys already performed with the current questionnaire (or a slightly amended version of it)?	Over 20 years	Over 20 years		12	Fruit data has been collected by the Fruit Crop Intelligence Committees and consultants for decades	Vegetables data has been collated by ADAS and independent consultants over decades and was modified three years ago to include additional sources such as the BGA	Although not a survey, according to ADAS records, ornamentals estimates have been provided in the current format since 2004
Preparatory (field) testing of the questionnaire?	NO	NO		NO
Number of units participating in the tests?
Explanatory notes/handbook for surveyors/respondents?	YES	YES
On-line FAQ or Hot-line support for surveyors/respondents?	YES	YES	YES	YES	YES	YES	YES
Were pre-filled questionnaires used?	NO	YES	NO	NO	NO	NO	NO
Percentage of pre-filled questions out of total number of questions		20%
Were some actions taken for reducing the measurement error or to correct the statistics?	YES	YES	YES	YES	NO	NO	NO
If yes, describe the actions and their impact	Validation checks are carried out at point of entry on-line or when keyed data received by surveys team. A comprehensive series of validation checks look at both incorrect records (i.e. sections don't add up to totals) or large changes from previous responses. Farmers are contacted to correct the data	Validation checks are carried out on the returned data. Farmers are contacted to confirm or correct the data	Levy data is subject to several kinds of technical audit to verify accuracy and completeness. Area levy returns are monitored by helicopter surveys which cover approximately 20% of GB each year and identify all visible potato fields on a GPS system, cross checking them for presence and area accuracy with return data. Tonnage returns are monitored by a continuous process of audits, verifying returns against purchase invoice, with physical inspection of stores where needed. Corrections are applied to data held as a result of audit observations. Legal action is employed where necessary to encourage correct and complete returns.	The GP data is validated on entry by a series of logical cross-checks, and is corrected during analysis if outlier or anomalous values are noted in the data.

6.3.3. Non response error

Unit non-response - rate

Item non-response - rate

	Survey 1	Survey 2	Survey 3	Survey 4	Survey 5	Survey 6	Survey 7
Name	June Survey of Agriculture & Horticulture	Crop Production Surveys	Potato Council Planting Returns (area)	Potato Grower Panel Survey (yield)	Fruit Panel Survey	Vegetable Expert Survey	Ornamentals Expert Survey
Unit level non-response rate (in %)	30%	30%		Approx. 16%	Although we cannot guarantee the complete accuracy of responses given, the long-standing association between ADAS and industry contacts means that a refusal to supply data is very rare, if not unknown. Some information is supplied to ADAS on the basis of a signed confidentiality agreement.	Although we cannot guarantee the complete accuracy of responses given, the long-standing association between ADAS and industry contacts means that a refusal to supply data is very rare, if not unknown	Although we cannot guarantee the complete accuracy of responses given, the long-standing association between ADAS and industry contacts means that a refusal to supply data is very rare, if not unknown
Item level non-response rate (in %)
- Min% / item	0%	0%
- Max% / item	0%	0%
- Overall%	0%	0%
Was the non-response been treated ?	YES	YES	YES	YES	NO	NO	NO
Which actions were taken to reduce the impact of non-response?	3 sets of reminder cards/emails are sent out at intervals throughout the survey	2 sets of reminder cards are sent out at intervals through the survey	Legal action is taken if a grower refuses to respond after being followed up.	Non-respondents are removed from the survey. They sample size is adjusted accordingly.
Which items had a high item-level non-response rate?	All returned forms are complete	All returned forms are complete
Which methods were used for handling missing data? (several answers allowed)	Imputations			Other
In case of imputation which was the basis?	Imputation based on the same unit in previous data Imputation based on similar units
In case of imputation, which was the imputation rate (%)?	30%
Estimated degree of bias caused by non-response?	Insignificant	Insignificant	None	None	Insignificant	Insignificant	Insignificant
Which tools were used for correcting the data?				Sample size is adjusted.
Which organisation did the corrections?	Defra farm surveys team	Defra farm surveys team		AHDB
Additional comments				Missing item data are treated as error records. Respondent is contacted for resolution. If not resolved, entire record is excluded.

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.

7. Timeliness and punctuality

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7.1. 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?

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

When was the first forecasting published for the crop year on which is reported? (day/month/year)

When were the final results published for the crop year on which is reported? (day/month/year)

19/12/2019

30/08/2019

19/12/2019

Additional comments

Provisional estimates were published on 10 October 2019. Final area, yield and production 19 December 2019

Provisional estimates were published on 10 October 2019. Production estimates were published on 20 June 2020.

Provisional estimates were published on 10th October 2019

Provisional estimates were published on 10 October 2019. Production estimates were published on 20 June 2020.

Provisional estimates were published on 10 October 2019. Production estimates were published on 31 May 2020.

Provisional estimates were published on 10 October 2019. Production estimates were published on 31 May 2020

Provisional estimates were published on 10 October 2019. Production estimates were published on 31 May 2020.

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

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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

	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

8.3. Coherence - cross domain

With which other data sources the crop statistics data have been compared?	Farm structure survey 2016
If others, which?
If no comparisons have been made, why not?	No FSS or Orchard Fruit survey for 2019

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
Dried pulses and protein crops
Root crops
Oilseeds
Other industrial crops (than oilseeds)
Plants harvested green
Total vegetables, melons and strawberries
Vegetables and melons
Strawberries
Cultivated mushrooms
Total permanent crops
Fruit trees
Berries
Nut trees
Citrus fruit trees
Vineyards
Olive trees
If there were considerable differences, which factors explain them?

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

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9.1. Dissemination format - News release

Availability	Links
YES

9.2. Dissemination format - Publications

	Availability	Links
Publications	Electronic
Publications in English	Electronic	https://www.gov.uk/government/collections/agriculture-in-the-united-kingdom#agriculture-in-the-united-kingdom-2019 https://www.gov.uk/government/statistics/latest-horticulture-statistics https://www.gov.uk/government/statistics/farming-statistics-provisional-crop-areas-yields-and-livestock-populations-at-1-june-2019-united-kingdom

9.3. Dissemination format - online database

Data tables - consultations

	Availability	Links
On-line database accessible to users	NO
Website	National language English	https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/865769/structure-jun2019final-uk-22jan20-rev_v2.pdf https://www.gov.uk/government/statistics/latest-horticulture-statistics https://www.gov.uk/government/statistical-data-sets/agriculture-in-the-united-kingdom

9.4. Dissemination format - microdata access

Availability	Links
YES

9.5. Dissemination format - other

Not applicable.

9.6. Documentation on methodology

	Availability	Links
Methodological report	National language English	https://osr.statisticsauthority.gov.uk/publication/statistics-on-agriculture/ https://code.statisticsauthority.gov.uk/
Quality Report	National language English	https://osr.statisticsauthority.gov.uk/publication/statistics-on-agriculture/ https://code.statisticsauthority.gov.uk/
Metadata
Additional comments

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

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Efficiency gains if compared to the previous quality report?	On-line surveys Further automation
If other, which?
Burden reduction measures since the previous reference year	More user-friendly questionnaires Multiple use of the collected data
If other, which?

11. Confidentiality

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Restricted from publication

11.1. Confidentiality - policy

Restricted from publication

11.2. Confidentiality - data treatment

Restricted from publication

12. Comment

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Related metadata

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Annexes

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