Field Crop Reporting Series

Detailed information for September 2009




6 times per year

Record number:


The purpose of this set of farm surveys is to obtain information on grains and other field crops stored on farms (March, July, September and December Farm surveys), seeded area (all surveys except December Farm survey), harvested area, expected yield and production of field crops (July, September and November Farm surveys).

Data release - October 2, 2009


This is a series of six 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.

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: Area, yield and production (March, June, July, September, November); Stocks (calendar year end (December), financial year end (March), crop year end (July/August))

Collection period: Collection period for each survey occasion starts approximately 4 weeks prior to the release of the results, and lasts 6 to 10 days, depending on the size of the sample.


  • Agriculture and food (formerly Agriculture)
  • Crops and horticulture

Data sources and methodology

Target population

The target population for the Farm 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.

Farm surveys collect data from Quebec, Ontario, Manitoba, Saskatchewan and Alberta at all survey occasions. However they only collect data twice a year (in the June Farm survey on seeded areas and in the November Farm survey 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.


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

The frame is derived from the Census of Agriculture and stratified according to farm size (area). A random sample of farms is selected from each stratum along with a weight. These weights are used to expand the data obtained from the sample to an estimate of the entire stratum.

Data sources

Data collection for this reference period: 2009-09-01 to 2009-09-09

Responding to this survey is mandatory.

Data are collected directly from survey respondents.

The data are collected by Computer assisted telephone interview (CATI) from the regional offices and transferred electronically to headquarters in Ottawa.

Reference periods of the collected data - Area (the last week of March and the week at the end of May and beginning of June); yield and production (the week at the end of July and beginning of August, the second week of September, and from the last week of October until the third week of November); stocks (the first week of January, the last week of March, and the week at the end of July and beginning of August, except grain corn and soybeans at the second week of September). There is about a three-week period between the end of the collection period and the release of the data. Data collection for the field crop surveys is undertaken using both Computer assisted telephone interview (CATI) and Electronic data reporting (EDR) systems. No further follow-up is done.

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

Error detection

With the CATI system, it is possible to implement edit procedures at the time of the interview. Computer programmed edit checks in the CATI system inform interviewers during the interview of possible data errors, which can then be corrected immediately by the interviewer and respondent. CATI significantly reduces the need for subsequent telephone follow-up, thereby reducing respondent burden and survey processing time.

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.


Imputation is only done for yield for the production surveys (July, September and November Farm surveys), using an average yield by crop calculated from all complete records in a given crop district. The average is imputed into records with missing values for yield.


The information collected in the probability sample is weighted to produce unbiased survey estimates called level indicators. These level indicators are representative of the entire farm operator population. 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. Ratio indicators are used to estimate seeded/harvested area and average yield estimation.

The March Seeding Intention Survey, estimates farmers' seeding intentions at March 31. In June, preliminary seeded acreage results are published and in November the estimates are revised with information from the fall surveys. Estimates are established on the basis of area level indicators and the pair change ratio applied to the previous year's estimate.

The July 31, September 15 and November surveys provide data on the harvested area, average yield and/or production of crops on farms. The survey data are weighted to estimate production at the provincial and crop district levels. The level indicators are established for production and harvested acreage. From these two indicators, the average yield for the crop district or province is calculated. Production and yield estimates obtained from the July 31 and September 15 surveys are preliminary, as the harvest is usually still in progress at that time. The November survey provides the first post-harvest production and yield estimates. These post- harvest estimates are revised, if necessary, with the December 31 farm stocks survey. Farm stocks are estimated at December 31 (calendar year end), March 31 (fiscal year end), July 31 (crop year end), and August 31 (crop year end for grain corn and soybeans). Several level indicators are produced from the stocks surveys, including harvested area, farm stocks and production. Also various ratio indicators are derived using the level indicators. For example, multiplying the ratio of the farm stocks level indicator to the level production indicator by the production published in November provides another farm stocks indicator. Also ratio indicators of stocks to harvested area or to previous year stocks are calculated. An analysis of supply and disposition tables makes it possible to integrate data from the CWB, the CGC, trade statistics, etc, and reconcile the various indicators.

Quality evaluation

The estimates are based on level indicators obtained from a probability survey of farming operations. The potential error introduced by sampling can be estimated from the sample itself by using a statistical measure called the "coefficient of variation" (c.v.). Over repeated surveys, 95 times out of 100, the relative difference between a sample estimate and what should have been obtained from an enumeration of all farming operations would be less than twice the c.v.. This range of values is referred to as the "confidence interval". While published estimates may not exactly equal the level indicators due to the validation, these estimates do remain within the confidence interval of the survey level indicators. For the July Farm Survey, c.v.'s range from 2% to 10% for the major crops. Coefficients of variation for specialty crops are usually within 11% to 25%.

The survey results are also evaluated through comparisons to previous estimates and other sources when available. Market and growing conditions for crop production are used as a guide when evaluating the data.

Totals may not equal the sum of their parts due to the use of conversion factors or rounding of fractions to whole numbers.

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 Disclosure Control 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

Every five years, the Census of Agriculture collects information on Agricultural operations across Canada, including institutional farms, community pastures, Indian reservations etc. The Census of Agriculture provides a list of farms and their areas.

Data accuracy

Field crop estimates are based on a random sample of agricultural operations and, as such, are subject to sampling and non-sampling errors.

Non-sampling errors may occur for many reasons. For example, non-response, coverage, differences in the interpretation of questions, incorrect information from respondents, mistakes in reporting, coding and processing of data.

Non-response error is related to respondents that may refuse to answer, are unable to respond or are too late in reporting. Usually by the end of the collection period, 85% of the questionnaires have been fully completed. The refusal rate to the survey is approximately 2 to 5%. The remainder of the sample unaccounted for can be explained by non-contact.

Coverage error can result from the fact that farm size and number may change between Census of Agriculture periods, resulting in under-coverage of new or larger farms.

Data response error may be due to questionnaire design, the characteristics of a question, inability or willingness of the respondent to provide correct information, misinterpretation of the questions or definitional problems. These errors are controlled through careful questionnaire design and use of simple concepts and consistency checks.

Processing error may occur at various stages of processing such as data entry, editing and tabulation. Historical ratios aid in eliminating outliers created by data entry. Tabulation is also automated to eliminate human error.

Sampling errors arise because estimates are derived from sample data and not the entire population. These errors depend on factors such as sample size, sampling design and the method of estimation.

An important feature of probability sampling is that sampling errors can be measured from the sample itself by using a statistical measure called the coefficient of variation (CV). Over repeated surveys, 95 times out of 100, the relative difference between a sample estimate and what should have been obtained from an enumeration of all farming operations would be less than twice the coefficient of variation. This range of values is referred to as the confidence interval. While published estimates may not exactly equal the level indicators (due to the validation and consultation process), these estimates do remain within the confidence interval of the survey level indicators. CVs at the Canada level range from 5% to 20% for the major crops.

For June Seeded Area Survey, the coefficients of variation at the Canadian level range from 1% to 5% for crops. Coefficients of variations for specialty crops and small areas of major crops are usually within 5% to 15%.

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