Field Crop Reporting Series: December 2017 Farm survey (CROP)

Detailed information for December 2017




5 times per year

Record number:


The purpose of the field crop surveys is to obtain information on seeded and harvested field crop areas, average yields, production and on-farm stocks at strategic times over the course of a typical crop cycle, which ranges from spring to late fall. Therefore, the field crop surveys are conducted in March, June, July, November and December.

Data release - Scheduled for February 5, 2018


This is a series of five data collection activities which are used in the release of estimates at pre-scheduled, strategic times during the crop year.

These data are meant to provide accurate and timely estimates of seeding intentions, seeded and harvested area, production, yield and farm stocks of the principal field crops in Canada at the provincial level. The crops surveyed include wheat, oats, barley, rye, flaxseed, canola, corn for grain, soybeans, sunflower seed, dry beans, dry field peas, lentils, mustard seed, Canary seed and chick peas.

PLEASE NOTE: As of fall of 2017, and between mid-September to following early December of each year, the most current reference year's data in CANSIM table 001-0017 is updated with model-based estimates obtained from satellite imagery. Please refer to IMDB 5225 for more details about the methodology used to obtain these model-based estimates.

The data are used by Agriculture and Agri-food Canada and other federal departments to develop and administer agricultural policies. This information is also used by provincial departments for production and price analysis and for economic research.

Reference period: Seeded area (all occasions); harvested area, yield and production ( July and November); stocks (calendar year end (December), financial year end (March), crop year end (July)).

Collection period: Electronic questionnaire collection starts on March 1st. Active collection period begins on March 14. The overall collection ends on March 29.


  • Agriculture
  • Crops and horticulture

Data sources and methodology

Target population

The target population for the field crop surveys includes all farms in Canada enumerated in the Census of Agriculture except institutional farms, farms on First Nations reserves and farms from the Northwest Territories, Yukon and Nunavut.

Field crop surveys collect data from Quebec, Ontario, Manitoba, Saskatchewan and Alberta at all survey occasions. However they only collect data twice a year (in the 2018 Field Crop Survey - June on seeded areas and in the 2018 Field Crop Survey - November on final crop production) for Newfoundland and Labrador, Prince Edward Island, Nova Scotia, New Brunswick and British Columbia.

Instrument design

The questionnaire was originally designed in 1908, and has evolved over the years in order to address Statistics Canada and Canadian agricultural requirements. Consultations have taken place between subject matter specialists and provincial and industry experts. Testing is conducted in-house for flow and consistency. Questions will be changed, added or removed as the need arises.

As of March 2018, the questionnaire is also offered in electronic format for use on Statistics Canada website.


This is a sample survey with a cross-sectional design.

Probability surveys can use two types of sampling frames: list and area. In the field crop surveys, only the list frame is used in sample selection. This list frame is stratified into homogeneous groups on the basis of Census characteristics (such as farm size and crop area) and sub-provincial geographic boundaries. The sample units (farms) are selected from Statistics Canada's Business Register.

Data sources

Data collection for this reference period: 2018-01-03 to 2018-01-15

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

This survey data is now collected using a web-based electronic version of the questionnaires (EQ). A letter or an email containing a Survey Access Code (SAC)is sent to respondents to access their survey on-line. Follow up with an interviewer is also conducted using Computer assisted telephone interview (CATI), in conjunction with the Business Collection Portal (BCP). The conducting of the interview is offered in both official languages and takes on average 18 minutes to complete.

View the Questionnaire(s) and reporting guide(s).

Error detection

With the electronic questionnaire (EQ) and the Computer Assisted Telephone Interview (CATI) system, it is possible to implement edit procedures at the time of survey completion. Computer programmed edit checks in the EQ and CATI systems report possible data errors, which can then be corrected immediately by the respondent and/or the interviewer.

Data are then compared on a year-to-year basis. Analysts cross check each other's work and group reviews are performed. All top contributors are also reviewed.


When non-response occurs, when respondents do not completely answer the questionnaire, or when reported data are considered incorrect during the error detection steps, imputation is used to fill in the missing information and modify the incorrect information. Many methods of imputation may be used to complete a questionnaire, including manual changes made by an analyst. The automated, statistical techniques used to impute the missing data include: deterministic imputation, replacement using historical data (with a trend calculated, when appropriate), replacement using auxiliary information available from other sources, replacement based on known data relationships for the sample unit, and replacement using data from a similar unit in the sample (known as donor imputation). Usually, key variables are imputed first and are used as anchors in subsequent steps to impute other, related variables.

Imputation generates a complete and coherent micro data file that covers all survey variables.


Information applicable to all field crop surveys:

The sample used for estimation comes from a single-phase sampling process. An initial sampling weight (the design weight) is calculated for each unit of the survey and is simply the inverse of the probability of selection that is conditional on the realized sample size. The weight calculated for each sampling unit indicates how many other units it represents. The final weights are usually either one or greater than one. Sampling units which are "Take-all" (also called "must-take") have sampling weights of one and only represent themselves. Estimation of totals is done by simple aggregation of the weighted values of all estimation units that are found in the domain of estimation. Also from two level indicators, it is possible to derive unbiased ratio indicators such as the pair change ratio of the seeded acreage from year to year. These level indicators then undergo a validation process, based on subject matter analysis, before final estimates are published.

Since March 2014, for response burden matters, the operations that have a total crop area lower than a sub-provincial threshold are excluded from field crop survey samples. This threshold, which varies for each sub-provincial region, is such that all farms having an area greater than the threshold itself represent, altogether, 95% of the total crop acreage of the region. The estimate share of the non-surveyed farms is then modeled and added to the estimation derived from surveyed farms, in order to draw a complete picture of field crop areas or productions.

The field crop surveys conducted in March and June estimate farmers' seeding intentions and actual seeded areas, respectively. The field crop surveys conducted in July and November mainly estimate farmers' yields and production obtained from the crops they seeded. In addition, crop yield and production data is also derived in September of each year, but using satellite imagery. For more information on these model-based principal field crop estimates, see IMDB page # 5225.

The survey data from all occasions are weighted to produce estimates at the provincial and crop district levels.

Information applicable to surveys collecting data on farm stocks:

Farm stocks are estimated at December 31, March 31 and July 31.
A major tool used in the verification of these estimates is the farm supply-disposition (or supply-demand) balance sheet. This table reflects activity on farm only before grain enters the commercial system. The supply and disposition numbers must be equal.

The supply is composed of opening farm stocks and production. The disposition is comprised of deliveries, seed use, closing farm stocks as well as feed, waste and dockage. The production and farm stocks are estimated from field crop surveys conducted by Statistics Canada. Seed use data are based on average seeding rates. A major portion of the deliveries are licensed grain deliveries obtained from the Canadian Grain Commission (CGC). The "feed, waste and dockage (fwd)" component is a residual in the balance sheet. Indicators such as the number of grain consuming animal units, harvest conditions affecting grain quality, established ratios of dockage to delivered grain and grain inspections are used to ensure data accuracy.

National supply and disposition tables provide further information to aid in estimating farm stocks.

Quality evaluation

Prior to the data release, combined survey results are analyzed for comparability; in general, this includes a detailed review of: individual responses (especially for the largest companies), general economic conditions, coherence with results from related economic indicators, historical trends, and information from other external sources (e.g. associations, trade publications, newspaper articles).

Disclosure control

Statistics Canada is prohibited by law from releasing any information it collects that could identify any person, business, or organization, unless consent has been given by the respondent or as permitted by the Statistics Act. Various confidentiality rules are applied to all data that are released or published to prevent the publication or disclosure of any information deemed confidential. If necessary, data are suppressed to prevent direct or residual disclosure of identifiable data.

In order to prevent any data disclosure, confidentiality analysis is done using the Statistics Canada generalized confidentiality system (G-CONFID). G-CONFID is used for primary suppression (direct disclosure) as well as for secondary suppression (residual disclosure). Direct disclosure occurs when the value in a tabulation cell is composed of or dominated by few enterprises while residual disclosure occurs when confidential information can be derived indirectly by piecing together information from different sources or data series.

Revisions and seasonal adjustment

Seeded areas published from all Field Crop surveys of a typical crop year represent preliminary estimates until the November instance of the survey, and can be changed over the course of the crop year. Yield and crop production estimates published from the July instance of the survey also represent preliminary estimates until November instance. The areas and production estimates published at the end of the crop year through the November instance of the survey are considered final, but are subject to change for 2 years, and to intercensal revisions if applicable. The revision period for stocks data also lasts 2 years.

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