B. Survey Design and Sampling
1. Survey Design
For this 2018/2019 Harvest Report, the target population was yellow corn from the 12 key U.S. corn-producing states representing approximately 95.0% of U.S. corn exports.1 A proportionate stratified, random sampling technique was applied to ensure a sound statistical sampling of the U.S. corn crop at the first stage of the market channel. Three key characteristics define the sampling technique: the stratification of the population to be sampled, the sampling proportion per stratum and the random sample selection procedure.
Stratification involves dividing the survey population of interest into distinct, non-overlapping subpopulations called strata. For this study, the survey population was corn produced in areas likely to export corn to foreign markets. The USDA divides each state into several ASDs and estimates corn production for each ASD. The USDA corn production data, accompanied by foreign export estimates, were used to define the survey population in the 12 key corn-producing states. The ASDs were the subpopulations or strata used for this corn quality survey. From those data, the Council calculated each ASD’s proportion of the total production and foreign exports to determine the sampling proportion (the percent of total samples per ASD) and ultimately, the number of corn samples to be collected from each ASD. The number of samples collected for the 2018/2019 Harvest Report differed among the ASDs, due to their different shares of estimated production and foreign export levels.
The number of samples collected was established so the Council could estimate the true averages of the various quality factors with a certain level of precision. The level of precision chosen for the 2018/2019 Harvest Report was a Relative ME no greater than ±10.0%, estimated at a 95.0% level of confidence. A Relative ME of ±10.0% is a reasonable target for biological data such as these corn quality factors.
To determine the number of samples for the targeted Relative ME, ideally, the population variance (i.e., the variability of the quality factor in the corn at harvest) for each of the quality factors should be used. The more variation among the levels or values of a quality factor, the more samples needed to estimate the true mean with a given confidence limit. In addition, the variances of the quality factors typically differ from one another. As a result, different sample sizes for each of the quality factors would be needed for the same level of precision.
Since the population variances for the 18 quality factors evaluated for this year’s corn crop were not known, the variance estimates from the 2017/2018 Harvest Report were used as proxies. The variances and ultimately the estimated number of samples needed for the Relative ME of ±10.0% for 15 quality factors were calculated using the 2017 results of 627 samples. Broken corn, foreign material and heat damage were not examined. Stress cracks and stress crack index, with a Relative ME of 11.3% and 13.5%, respectively, were the only quality factors for which the Relative ME exceeded ±10.0% for the U.S. Aggregate. Based on these data, a minimum sample size of 600 would allow the Council to estimate the true averages of the quality characteristics with the desired level of precision for the U.S. Aggregate, with the exception of stress cracks and stress crack index. However, the targeted number of samples became 608, due to the rounding of the targeted number of samples per ASD and the criterion of a minimum of two samples per ASD.
The same approach of proportionate stratified sampling was used for the mycotoxin testing of the corn samples as for the testing of the grade, moisture, chemical and physical characteristics. In addition to using the same sampling approach, the same level of precision of a Relative ME of ±10.0%, estimated at a 95.0% level of confidence, was desired. Testing at least 25.0% of the minimum number of samples (600) was estimated to provide that level of precision. In other words, testing at least 150 samples would provide a 95.0% confidence level that the percent of tested samples with aflatoxin results below the FDA action level of 20.0 ppb would have a Relative ME of ±10.0%. In addition, it was estimated that the percent of tested samples with DON results below the FDA advisory level of 5.0 ppm would also have a Relative ME of ±10.0%, estimated at a 95.0% level of confidence. The proportionate stratified sampling approach also required testing at least one sample from each ASD in the sampling area. To meet the sampling criteria of testing 25% of the minimum number of samples (600) and at least one sample from each ASD, the targeted number of samples to test for mycotoxins was 181 samples.
The random selection process was implemented by soliciting local grain elevators in the 12 states by email and phone. Postage-paid sample kits were mailed to elevators agreeing to provide the 2,050-gram to 2,250-gram corn samples requested. Elevators were told to avoid sampling loads of old crop corn from farmers cleaning out their bins for the current crop. The individual samples were pulled from inbound farm-originated trucks when the trucks underwent the elevators’ normal testing procedures. The number of samples each elevator provided for the survey depended on the targeted number of samples needed from the ASD along with the number of elevators willing to provide samples. Each sampling kit mailed to the participating locations contained bags to collect a maximum of four samples. A total of 618 unblended corn samples pulled from inbound farm-originated trucks were received from local elevators from August 27 through November 28, 2018.