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Showing posts with the label Yield

Fungicide Applications on Corn and Soybeans

Farmers will be urged to make fungicide applications on their crops this month. Todd Gleason discussed the issues related to both corn and soybean diseases with ILLINOIS Extension Plant Pathologist Nathan Kleczewski.

Corn Yield Implications of Late Planting

University of Illinois Extension Agronomist Emerson Nafziger discusses the impact of late corn planting and how farmers should set about nitrogen applications this spring. He was interviewed May 1, 2019 by Todd Gleason.

The following summary is taken from a May 1, 2019 University of Illinois farmdocDaily article written by agricultural economists Scott Irwin and Todd Hubbs.

“The impact of late planting on projections of the U.S. average corn yield is an important question right now due to the very wet conditions so far this spring through much of the Corn Belt. We estimate that the relationship of late planting with corn yield trend deviations is highly non-linear, with a largely flat segment up to 10 percent above average late planting and then a steeply sloped segment for late planting that is 10 percent or more above average. This nicely matches the curvature of planting date effects on corn yield estimated in agronomic field trials (e.g., farmdoc daily, May 20, 2015; Nafziger, 2017). The key then for 2019 is whether late corn planting will be 10 percent or more above average, where the negative impact on corn yield is relatively large. Specifically, when late planting is 10 percent or more above average the chance of corn yield being below trend is 83 percent and the average deviation from trend yield is –6.1 bushels per acre. We analyze topsoil surplus moisture patterns in analog years to 2019 and the analysis suggests late planting this year is likely to be at least 10 percent. The implication is that there is a significantly elevated probability of a below-trend corn yield in 2019 and that present projections of U.S. average corn yield should likely be reduced to 170 bushels per acre or less. It is important to recognize that good summer weather conditions can offset the projected negative impact of late planting on the national average corn yield, but history indicates the probability of this happening is not very high if wet conditions in the Corn Belt persist through mid-May.” - Irwin and Hubbs, University of Illinois

Good Yields! Yes but a Warning | an interview with Gary Schnitkey



by Gary Schnitkey, University of Illinois
read farmdocDaily article

On a national basis, corn and soybean yields were near record-breaking levels in 2018, with exceptional yields in central Illinois and the eastern United States contributing heavily to those near-record U.S. yields. Other areas had below-trend yields. The county yields for corn and soybeans presented in this article illustrate these facts. Much higher U.S. yields are possible if all areas have exceptional yields. However, all areas including Illinois should not expect above-trend yields in every year.

Corn Yields

The 2018 corn yield for the United States was 176.4 bushels per acre, just .2 bushels below the record yield of 176.6 bushels per acre set in 2017 (all yields in this article are from QuickStats, a website maintained by the National Agricultural Statistical Service). From a national standpoint, corn yields were excellent in 2018.

Contributing to these high yields were counties having average yields above 220 bushels per acre. Several of these counties were in the Northwest U.S. and Nebraska where irrigation often is used in corn production (see Figure 1). In predominately non-irrigated counties, there were a concentration of counties in eastern Iowa and extending through central Illinois with over 220 bushels per acre average yields (see Figure 1). Three counties in this region, all in Illinois, had average yields over 240 bushels per acre: Douglas County (246.0 bushels per acre), Piatt (241.8), and Warren (241.7). Eleven counties – again, all in Illinois – had average yields between 230 and 240 bushels per acre: Macon (239.9), Sangamon (236.4), Logan (236.2), Tazewell (235.4), Effingham (235.2), Coles (234.2), Stark (234.0), Moultrie (233.9), Hancock (233.9), Christian (232.9), and Mercer (231.3). Eighteen counties had yields between 220 and 230 bushels per acre: 6 counties in Iowa and 12 in Illinois.



High yields are a measure of good growing conditions, but it does not take into consideration the inherent productivity of soil. Yield deviations from trend consider an area’s productivity. For each county, a 2018 trend yield was calculated using linear regression to fit a straight line through actual county yields from 1972 to 2017. The straight line then was extended to give the 2018 trend yield which represents the expected yield given approximately average growing conditions. A yield deviation then equals the actual yield minus the trend yield. A yield deviation of 20 bushels per acre means the actual 2018 yield is 20 bushels higher than the trend yield, an indicator of a very good yield. Conversely, a –20 yield deviation indicates that the county yield is 20 bushels below the trend yield, an indicator of poor growing conditions.

As would be expected, eastern Iowa and central Illinois had yields with positive yield deviations, with many counties having yield trends above 30 bushels per acre (see Figure 2). Note that yield deviations paint a broader area of excellent yields. That area includes southern Illinois, central and southern Indiana, western Ohio, western Kentucky, and parts of central Tennessee.



Other areas did not fare as well. Counties along the Iowa-Minnesota border had below-trend yields (see Figure 2). Other regions of poor yields in include Colorado, eastern Kansas and western Missouri, Texas, Arkansas and Louisiana, North Carolina, and New York.
Soybeans Yields Similar to corn, soybeans almost had a record-breaking yield. The average U.S. soybean yield for 2018 was 51.6 bushels per acre, .3 bushels below the record yield set in 2016 of 51.9 bushels per acre.

There were many areas of exceptional soybean yields (see Figure 3). Twenty-nine counties had average county yields over 70 bushels per acre. Three of these counties were in Nebraska: Gosper (75.2 bushels per acre), Dawson (73.2), and Buffalo (70.6). The remaining 26 counties were in Illinois. Three Illinois counties had average county yields over 80 bushels per acre: Sangamon County (82.3 bushels per acre), Morgan (81.6), and Douglas (80).



Yield deviations suggest that central and southern Illinois had exceptional growing conditions in 2018 (see Figure 4). Excellent growing conditions continued into Indiana, Ohio, Kentucky, and Tennessee. Other areas did not have as productive of a year. Yields were below trend along the Iowa-Minnesota board, North and South Dakota, Nebraska, Wisconsin, Michigan, Pennsylvania, and in North and South Dakota.



Commentary The U.S. had near-record yields for corn and soybeans in 2018. Above-trend yields in central and southern Illinois, central and southern Indiana, western Ohio, Kentucky, and Tennessee where large contributors to the near-record U.S. yields.

The examination of county yields suggests two warnings. Illinois farmers should note that many several areas in the country had below-trend yields in 2018. Therefore, the 2018 experience indicates that below-trend yields are still possible. Illinois farmers should not plan on having above-trend yields in every year. It is entirely possible that the area of below-trend yields centered along the Iowa-Minnesota border in 2018 could occur in central Illinois. At the same time, Iowa and Minnesota could have above-trend yields. If that reversal occurs in 2019, there would be large, negative incomes on many Illinois farms.

Somewhat counter to the first warning, the second warning is for the possibility of much larger national corn and soybean supplies. It is possible that all areas of the U.S. have above-trend yields. That is, the western Corn Belt could have had above-trend yields at the same time the eastern Corn Belt has above-trend yields. If this occurs, national yields would be record-breaking, resulting in falling corn and soybean prices, leading to very low farm incomes.

January Crop Report Yield Expectations

The January USDA reports have been delayed until further notice because of the government shutdown. It is expected once these numbers are released the changes in the national yields for corn and soybeans could be positive for price.

The last time USDA updated corn and soybean yields was in the month of November. Both crops saw a drop in predicted yield for the 2018 harvest. This drop has been since complicated by harvest problems. Todd Hubbs from the University of Illinois says history can sometimes be a guide to how the January Crop Production report might change. More often than not when the yields from October to November go down, the U of I commodities specialist says they drop again in January, “And what you see is when you see a yield change from November to October that is negative, we tend to see a similar change from January to November. Now it doesn’t always hold, but if that were to materialize we probably see a corn number around 177.2 bushels to the acre. I think it might be a little bit higher than that, but even if it is if we lose half to one bushel out of the current projection of 178.9, then that is really supportive for corn prices moving forward.”

Hubbs says a similar pattern holds for soybean yields. On average he says that’s been about a quarter of a bushel per acre… a little better than that actually… and if it came to fruition this year it would put the 2018 soybean yield at 51.8 bushels to the acre. That would clearly be supportive to price says Hubbs, even though the trade issues with China are continuing, “We could also see some acreage come out of both corn and soybeans as harvest was really tough in some places. Particularly out in Kansas and the southern plains. This has more implications for winter wheat seedings than it does for anything else. Right now, by my projections, I think winter wheat acreage will be down by one-point-five percent from last year’s 32.5 million acres. This may have implications for both corn and soybean acreage in the southern plains as we move into 2019 and think about what kind of acreage we will have.”

The implication being a potential increase in corn or soybean acreage in that area. USDA says it will announce the date for the release of the January reports once the government shutdown has ended.

January Crop Report Yield Expectations

The January USDA reports have been delayed until further notice because of the government shutdown. It is expected once these numbers are released the changes in the national yields for corn and soybeans could be positive for price.

The last time USDA updated corn and soybean yields was in the month of November. Both crops saw a drop in predicted yield for the 2018 harvest. This drop has been since complicated by harvest problems. Todd Hubbs from the University of Illinois says history can sometimes be a guide to how the January Crop Production report might change. More often than not when the yields from October to November go down, the U of I commodities specialist says they drop again in January, “And what you see is when you see a yield change from November to October that is negative, we tend to see similar change from January to November. Now it doesn’t always hold, but if that were to materialize we probably see a corn number around 177.2 bushels to the acre. I think it might be a little bit higher than that, but even if it is if we lose half to one bushel out of the current projection of 178.9, then that is really supportive for corn prices moving forward.”

Hubbs says a similar pattern holds for soybean yields. On-average he says that’s been about a quarter of a bushel per acre… a little better than that actually… and if it came to fruition this year it would put the 2018 soybean yield at 51.8 bushels to the acre. That would clearly be supportive to price says Hubbs even though the trade issues with China are continuing, “We could also see some acreage come out of both corn and soybeans as harvest was really tough in some places. Particularly out in Kansas and the southern plains. This has more implications for winter wheat seedings than it does for anything else. Right now, by my projections I think winter wheat acreage will be down by one-point-five percent from last year’s 32.5 million acres. This may have implications for both corn and soybean acreage in the southern plains as we move into 2019 and think about what kind of acreage we will have.”

The implication being a potential increase in corn or soybean acreage in that area. USDA says it will announce the date for the release of the January reports once the government shutdown has ended.

Yield Implications of Delayed Corn Planting

read farmdocDaily article

The late spring has many worried. Others are confident farmers can plant a corn crop in 5 working days. University of Illinois agricultural economists have gone through the USDA data to see if this is true and what impact a late planting season might have on corn yields.

The grand prairie of Illinois is still lying dormant. Its soils are just beginning to reach that magical 50-degree mark. That’s when the corn planters begin to roll. It’s a late start to the season this year, and despite the increased size of the machinery University of Illinois Agricultural Economist Scott Irwin says it’ll still take about as much time to plant the corn crop this season as it did nearly 30 years ago, “If we are operating at our maximum capacity, it takes about fourteen days and when we say days we mean field days not calendar days, to get the job done”.

The reason is simple. There are fewer farmers using bigger machines. So, it is pretty likely it will take a while to get the corn crop in the ground says Irwin, and that has some serious implications, “Our optimum window clearly closes May 1st based on the agronomic trials we have access to and by May 10th we are definitely into the late planting time frame and it is hard to see, unless we get extraordinarily lucky with a planting window opening up, that we are not going to have above average late planted acres. Certainly in Illinois, and I am 100 percent confident of that as you go north where they are still melting the snow.”

ILLINOIS analysis suggests the number of late planted corn acres could 5 to 10% more than usual. If so, the impact on the nation wide corn yield could be between a bushel and quarter to two-and-half bushels to the acre lost.

Exceptional Corn and Soybean Yields in 2017

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Many areas of the country had above trend yields in 2017. While still not the majority, county yields of over 200 bushels per acre are becoming common and may be expected in the center of the corn-belt. Similarly, counties with over 60 bushels per acre are occurring with some regularity. Todd Gleason talks with University of Illinois Agricultural Economist Gary Schnitkey.

What Is Up with Soybean Yields

read farmdocDaily arcticle
by Scott Irwin, Agricultural Economist - University of Illinois

Soybean yields in the U.S. have been very high the last four years. The U.S. average yield set new records in a stair-step fashion each year between 2014 and 2016. The 2016 yield reached the remarkable level of 52.1 bushels. While not a record, the 2017 yield (based on the November 1 USDA estimate) was 49.5 bushels, the second largest ever. On top of the high U.S. average yields are the numerous reports of field-level yields in the 70s, 80s, and even a few in the 90s.





The high soybean yields of recent years have sparked a debate about what is driving the exceptional yields. In thinking about this debate it is important to understand that there are only three possible sources of soybean yield gain. The first is weather during the growing season. The second is genetic improvement in soybean varieties. The third is a management, which encompasses all aspects of the soybean production process. Genetic improvement and management sometimes go hand-in-hand so that one requires the other.

It is a not an easy task to disentangle the complex and sometimes interacting impacts of weather, genetics, and management on soybean yields. One approach is to use a crop weather regression model to estimate the separate impacts of weather and technology on soybean yield, where technology is the combined impact of genetic improvement and management. I estimated this type of model for U.S. average soybean yields over 1970–2017. A linear time trend was used to represent technological change and summer precipitation and temperature variables were used to represent growing season weather. The modeling results showed that U.S. average soybean yields in 2014, 2015, and 2017 could be explained by a continuation of the linear improvement in technology and good growing season weather. The exception was 2016, when yield was substantially higher than what could be predicted based on a linear technology trend and good weather. It is not clear from this exercise whether we should view the 2016 yield like a 100-year flood or a permanent jump in soybean yield potential.

Agronomic data can be helpful in further disentangling genetic improvement from other sources of soybean yield gain. One recent study collected seed for over 150 soybean varieties released from the 1920s through the 2000s. Using randomized trials from across the country in 2010 and 2011, the study estimated “pure” genetic improvement in soybean yields. The results indicated a linear progression of soybean genetic yield gain from 1970 through 2008. This indicates that the historical pattern of soybean genetic gains in yield have been steady and marked jumps in the rate of improvement are rare. Soybean variety test results from the Department of Crop Sciences at the
University of Illinois provide relevant data through 2017. The yield of conventional soybean varieties relative to the older Williams variety shows no change of trend in recent years. Overall, there is little evidence to date that soybean genetics have been improving at a faster rate in recent years.

If we dig into the soybean yield data for the U.S. state-by-state an interesting pattern emerges that points to important changes in management practices. In general, soybean trend yields in the Southeastern U.S. have been growing at a much faster rate than in other growing regions. This non-linear trend appears to be related to a number of management practices, which can be roughly described as having the purpose of replicating Midwestern growing conditions. This includes planting much earlier in the past, planting earlier maturing indeterminate varieties, including corn in the crop rotation to increase organic matter in the soil, and using raised bed production systems. These management practices have allowed soybean yields in the Southeast to largely catch up with those in the rest of the country.

In sum, the data indicate that the biggest factor explaining high soybean yields in recent years is simply exceptionally good growing season weather. Improved management practices, particular in the Southeastern U.S., have also certainly contributed. A jump in the rate of genetic improvement in soybeans was not likely a big contributor to the surge in soybean yields.

Assessing the Prospects for 2017 Corn Production

The August Crop Production report surprised many market observers by forecasting 2017 corn production at 14.153 billion bushels. In particular, the corn yield forecast of 169.5 bushels per acre came under scrutiny due to higher than expected yield forecasts in major producing states. The question is whether the corn production forecast will change enough to result in higher prices than those currently reflected the market.



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How USDA Collects Yield Data

How USDA NASS Gathers Crop Production Report Data

USDA NASS will release the first corn and soybean Crop Production Report of the season Thursday August 10th, 2017 at 11am central. Todd Gleason talks with USDA NASS State Statistician Mark Schleusener (shloy-seh-ner) about how the information is collected and calculated.



USDA Crop Production Reports | a primer with Scott Irwin

A year ago University of Illinois agricultural economist Scott Irwin and Darrel Good wrote an article about how USDA predicts corn yields for the farmdocDaily website. Todd reviews this article with Scott Irwin as a primer to the August Crop Production report.

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Opening Up the Black Box

We have written extensively about U.S. corn yield forecasts issued by the National Agricultural Statistics Service (NASS) of the USDA (Irwin and Good, 2006; Irwin and Good, 2011; Irwin, Sanders and Good, 2014; farmdoc daily, August 28, 2013; August 29, 2014; August 18, 2016). As indicated in these previous publications, NASS uses two surveys to provide indicators of corn yield prior to harvest. These include the Agricultural Yield Survey (or farmer-reported survey) and the Objective Yield Survey (or field-measurement survey) in major corn producing states. A formal Agricultural Statistics Board (ASB) of NASS statisticians is convened in each month of the forecasting cycle to review yield indicators and determine an official yield forecast. In our previous publications we focused on the survey procedures used by NASS and had relatively little to say about the methodology used by the ASB to combine the various yield indicators and determine an official yield forecast. This omission reflects the fact that NASS has historically provided very little information about this part of the forecasting methodology. Fortunately, several publications have appeared in the scientific literature during the last several years that provide important insights into the nature of the different survey yield indications and the other non-survey information used by the ASB to determine official published yield forecasts. The purpose of this article is to review the information in these scientific articles and provide a more informed understanding of the role of the ASB in generating these important market-moving forecasts.

NASS Corn Yield Survey Indicators

We begin with a brief review of the two surveys that form the backbone of the NASS corn yield forecasting methodology–the Agricultural Yield Survey (or the farmer-reported survey) and the Objective Yield Survey (or the field measurement survey). For the August 2016 forecast, the Agricultural Yield Survey (AYS) included 22,144 operations for all crops and was conducted in 32 states for corn. The sample of farm operations surveyed was drawn from those who responded to the survey of planted acreage in June. The same operations will be interviewed each month from September through November. In the August survey, respondents were asked to identify the number of acres of corn to be harvested and to provide a forecast of the final yield.

The Objective Yield Survey (OYS) is designed to generate yield forecasts based on actual plant counts and measurements. The sample of fields for the OYS survey is selected from farms that reported corn planted or to be planted in the June survey of acreage. Samples are selected in the 10 principal corn producing states. A random sample of fields is drawn with the probability of selection of any particular field being proportional to the size of the tract. For the August 2016 OYS, a total of 4,544 plots were sampled for corn, soybeans, cotton, and winter wheat.

Two counting areas, or plots, are randomly selected in each field. Objective measurements (such as counts of plants and ears) are made for each plot each month during the survey cycle. When mature, the plots are harvested and yield is calculated based on actual production minus an allowance for harvest loss. During the August survey, the operator is asked to verify, field-by-field, the acreage reported in June. For corn, each of the two independently located sample plots in a field consists of two parallel 15 foot sections of row. Each plot is selected by using a random number of rows along the edge of the field and a random number of paces into the field. Enumerators count all fruit and fruiting positions in corn and, if ears have formed, a sample of ears is measured for length and circumference. Just before the field is harvested, both plots are hand harvested and weighed by the enumerator.

At each visit, the enumerator establishes a corn maturity category for the plot, ranging from 1 (no ear shoots) to 7 (mature). Prior to the blister stage the number of ears is forecast based on the number of stalks, ear shoots, or ears and both the weight per ear and harvest loss are forecast based on the 5-year average. From the blister through the dough stage, the weight per ear is forecast based on kernel row length and harvest loss is forecast based on the past 5-year average. Ear weight is measured in the dent and/or mature stage. Harvest loss is measured following harvest.

Prior to maturity and harvest, the OYS corn yield is forecast based on the forecast of the number of ears, the forecast of the weight per ear, and the forecast of harvest loss. Forecasts are based on conditions as of the survey date and projected assuming normal weather conditions for the remainder of the growing season. The OYS forecast of gross corn yield then is based on the following formula:

Gross Yield= [number of ears X weight per ear at 15.5% moisture] ÷ 56

Number of ears and ear weight are either forecast or actual and 56 is a conversion from weight to bushels.

The ASB

The survey and forecasting procedures described above produce a number of indictors of the net yield of corn from the AYS and OYS. It is the job of the Agricultural Statistics Board (ASB) to combine the information from these indicators and determine the official published estimates. How does the ASB actually do this? The latest version of the official NASS publication on yield forecasting programs describes the ASB’s role this way:

“The sample surveys are designed to produce State level estimates of acreage, expected yields, final yields, and total production. The surveys are conducted by each State, and the first level of analysis is done by each State. Each Field Office does its independent appraisal of the relationships between the survey estimates and the final official statistics and forwards this information to Headquarters. While each Field Office is analyzing its survey data, statisticians in Headquarters are doing a parallel analysis of all survey data at the State, U.S., and regional levels. For the major field crops discussed in this paper, a formal Agricultural Statistics Board is convened to review regional indications and determine the official forecast or estimate. This Board is made up of 7 to 10 statisticians representing different divisions of NASS. Each Board member evaluates the regional survey indications and supporting data and determines their forecast or estimate. Each member brings their individual perspective to the review which can result in different conclusions being drawn. Through review and discussion, the Board must collectively reach a consensus and establish the National number. The Board process ensures all perspectives are examined and the national or regional forecast or estimate is the result of a thorough analysis. The summation of the individual State estimates as prepared by each State is compared to the Board number. The Headquarters statisticians will re-examine all national and State data relationships and either adjust State estimates so they sum to the U.S. or change the previously determined U.S. number.”

“The formal meeting of the ASB to establish the final numbers and prepare the report is conducted under ”lock up“ conditions. Lock up begins with a complete isolation of all facilities required by the Board. All doors are locked, windows and elevators are covered and sealed, phones are disconnected, and the computer network inside ”lock up“ is isolated from the full network. Transmitters are not permitted and the area is monitored for electronic signals. Highly speculative data are decrypted only after the area is secure. Only after all security is in place does the Board begin final deliberations. The area remains locked up until a prescribed release time (8:30 a. m. for Crop Production) at which time the report is disseminated in electronic and paper forms.” (pp. 96–97)

While this provides a helpful overview of the ASB in general times, it provides almost no detail on the nature of yield indications, the non-survey information, if any, used to supplement the survey indications, or how the ASB reaches a collective consensus.

In terms of statistical properties, NASS does acknowledge in its official yield forecasting publication that the AYS yield indications are biased:

“Note that AYS data are the respondents’ expected yield. The crop may not be mature and ready for harvest for another several weeks after the respondent has been contacted. Experience has shown these responses tend to be conservative (biased down). Under drought conditions, this bias gets much larger as respondents perceptions of a crop are influenced by current weather conditions. Therefore, the interpretation phase of the review must recognize this tendency and factor it into the final deliberations.” (p. 19)

Likewise, NASS acknowledges that OYS yield indications may also be biased:

“Forecasts of state or regional yields are inherently subject to differ from the final, administratively determined, yield. The difference is due to weather and crop conditions yet to be encountered at the time the forecast is made, the difference between weather and crop conditions in the current year and the historic weather and crop conditions utilized to predict current yields, and systematic non-sampling errors which contribute to forecast error. NASS makes every attempt to minimize the impact of these three sources of error by means of administratively determine final values. These final, sometimes referred to as official, values are used as dependent variables to estimate an ordinary least squares equation with the averages calculated from objective yield samples as the independent variable. For example, each state will have an administratively determined, official corn yield for all previous years. To forecast the official corn yield for the current year, NASS regresses the objectively determined State level average corn yields from previous years to the corresponding official corn yields. This process provides a historical context for weather, biases, and non-sampling errors.” (p. 38)

The fact that both yield indications are biased is interesting in and of itself, but the really important question is by how much and in what direction. We know the direction of bias for the AYS (downward) but neither the direction nor magnitude of bias for the OYS. If the biases are relatively small then this is largely a technical issue that has little practical import, but if the biases are large it becomes an important part of how the ASB generates published yield estimates.

A recent paper by Wang et al. (2011) is the first we know of to present data on actual AYS and OYS corn yield indications for an extended sample period. Figure 1 is taken directly from the Wang et al. article, and it presents: i) the OYS indications for the corn objective yield region and each report release month over 1993–2009; ii) the AYS yield indications for the same corn objective yield region and each report release month over 2001–2009; and iii) the December Agricultural Survey (DAS) corn yield indication for each year over 1996–2009. The objective region yield is simply the weighted-average yield for the objective yield states (10 since 2005) and the DAS is very close to the final yield estimates released in January. After viewing the chart, it is probably more understandable why NASS has been so cautious in disclosing this data previously. The magnitude of the bias in both yield indications is striking. The coarseness of the scales prevents precise measurements, but the upward bias in the OYS, regardless of the release month, varies from around 10 to 15 bushels per acre (using the DAS as the benchmark). The downward bias in the AYS in August ranges from about 10 to 20 bushels, and then generally declines in September and October and is usually, but not always, fairly small in November. The pattern of bias in the AYS yield indications make sense, in that farmer-reported yields should become more accurate as the growing season progresses and harvest eventually is completed.




What this means from a practical standpoint is that the ASB is confronted with substantial bias in its two most important yield indications. For example, based on Figure 1, the final DAS objective region yield for corn in 2009 was about 175 bushels and the August OYS yield indication was around 190 bushels and the AYS yield indication was around 155 bushels, a spread of 35 bushels. A more recent paper by Nandram, Berg, and Barboza (2014) provides precise measurements. They report that the average biases for the OYS objective region corn yield indications relative to the DAS over 1993–2010 were 13.96, 11.62, 13.13, 14.99 and 14.97 bushels for August, September, October, November and December, respectively (note that we assume the bias estimates were stated in bushels but the article does not explicitly state the units). The average differences between the AYS indications and the DAS indications were respectively –12.26, –13.42, –9.81, and –4.10 bushels for August, September, October, and November. These imply AYS/OYS yield indicator spreads that average 26.22, 25.04, 22.94, and 19.09 bushels. It is important to keep in mind that these spreads are not symmetric around zero, as the AYS bias diminishes substantially by November but the OYS bias does not. Assuming these bias estimates are similar to the estimates available to the ASB when making published estimates in recent years, we can use the averages to provide a rough estimate of the OYS and AYS corn yield indications for the objective region in August 2016. The published objective region corn yield this year was 182 bushels, which combined with the bias estimates suggest an OYS yield of about 196 bushels and an AYS yield of about 170 bushels.

From this discussion, it should be obvious that the corn yield indications have to be adjusted for bias by the ASB in order to make useful published estimates. The key is the consistency of the bias across time. Figure 1 suggests there is some variation in the bias for a given report month across years and this likely contributes to the errors in the published corn yield estimates. Nonetheless, there appears to be a strong degree of consistency in the bias from year-to-year and this can be used to efficiently “de-bias” the AYS and OYS yield indications applying standard statistical techniques. The larger question is why the biases exist in the first place. Nandram, Berg, and Barboza (2014) conjecture that:
One possible reason for the bias of the OYS indications is that the measurement process leads to a systematic overestimation of the plant density in a field. Two potential reasons for the biases in the AYS indications are pessimism on behalf of the farmers and exclusion of farms in the largest size stratum from the sampling frame. Large farms are conjectured to have higher average yields than moderately sized farms because of greater investment in advanced technology. (p. 510)

There is also a large literature (e.g., Poate, 1988) that formally evaluates the accuracy of so-called “crop cutting” yield estimates, and the evidence shows that such techniques have a tendency to over-estimate actual yields for a variety of reasons, including variability in population density. So, it is not surprising that the OYS yield indicator is biased upwards. NASS has also been aware of the bias in OYS indications for decades and has conducted extensive research to better understand the underlying reasons for the bias, apparently without great success (Warren, 1985). The underlying reasons for the downward bias in the AYS yield indicator are hard to pinpoint beyond a general conservatism among farmers about yield prospects before harvest. Given the dramatic shrinkage in the AYS bias through November and the fact that the same farms are surveyed each month for a given year, it is unlikely that under-sampling large farm operations is one of the main reasons for the AYS bias, as suggested by Nandram, Berg, and Barboza (2014).

In light of the level and variability of the bias in AYS and OYS yield indications, it is sensible for the ASB to seek out additional non-survey information when generating published yield estimates. The Wang et al. (2011) article provides helpful information in this regard:

Each month (August through December), estimates are produced by the ASB with the primary objective of providing the most accurate projection or end-of-season estimate given the survey indications and standard errors, in addition to other factors. When projecting corn yield, information on crop maturity, planting date, weather conditions, and other auxiliary factors is also taken into consideration by the ASB. (p. 85)

Since two of the co-authors of this paper at the time of its publication were NASS employees, we take this as authoritative evidence that the ASB uses “auxiliary” information when generating published estimates. While the details of exactly what type of auxiliary information the ASB uses when making corn estimates is not available, several recent articles by provide important clues. The stated purpose of the Wang et al. (2011), Adrian (2012), and Nandram, Berg, and Barboza (2014) articles is to basically formalize the decision-making process of the ASB in making corn yield forecasts. In order to do so, the models in the articles incorporate a variety of auxiliary information, including trend yields, planting progress, July temperature and precipitation, and crop condition ratings, which presumably reflect variables actually used by the ASB in the estimation process. Another type of auxiliary information used by the ASB in recent years is remote-sensing satellite data (Adrian, 2012; Johnson, 2014), such as the Normalized Difference Vegetative Index (NDVI), a measure of biomass density.

In sum, NASS has an active research program to try to formalize and improve the ASB methodology (e.g., Adrian, 2012; Wang et al., 2011; Nandram, Berg, and Barboza, 2014; Cruze, 2015). This provides important clues about the types of non-survey information used by the ASB, but we still don’t have any information about the weights placed on this information in ASB deliberations. There is obviously some concern within NASS about the subjective weights placed on the survey and non-survey information given discussions found in the articles cited above. For example, Adrian (2012) notes that the emphasis placed on different information, “will inevitably vary from person to person and depend upon the composition of the Board.” Our view is that an element of subjective expert judgement will likely always be a necessary component of a process as complex and difficult as forecasting crop yields. We concur with the late Bruce Gardner, who made this trenchant observation after sitting through ASB lock-up deliberations for an early 1990s Crop Production report:

“A NASS board in Washington then assesses all the indicators of yield, including the estimates of a month earlier. This is not done using a pre-specified formula–in which case a computer could replace the NASS board–but through a consensus of the Board members based on their experience and the full information before them.” (Gardner, 1992, p. 1068)

ASB Track Record

When viewing the details of the ASB forecasting methodology, especially the magnitude of the bias in the AYS and OYS yield indications, it is easy to lose sight of the big picture. That is, the ASB is tasked with combining the AYS and OYS yield indications with other relevant information in order to make the best possible published estimates of corn yield, and it is the accuracy of the final published estimates that ultimately matters. So, we updated our earlier evaluation (farmdoc daily, August 29, 2014) of the historic accuracy of USDA published August forecasts of the U.S. average corn yield relative to the “final” yield estimate released in January (we say “final” because January estimates are sometimes revised based on the Agricultural Census conducted every five years). The differences between the forecasts and the final estimates in percentages over 1990–2015 are presented in Figure 2. When interpreting the errors, note that a positive error implies an under-estimate on the part of USDA and a negative error implies an over-estimate. The errors associated with the USDA corn yield forecasts are occasionally very large, such as 1993 and 1995. These examples of large errors are not surprising due to the unusual weather events that occurred in those years. It is interesting to note that USDA corn yield forecast errors in 2012 were extremely small, with the August forecast exactly equal to the final estimate, and thus, having a zero forecast error. This is surprising given the magnitude of drought conditions that prevailed in 2012 and the difficulty of forecasting corn yields under these circumstances. Accuracy was also exceptional in 2015, when the forecast error was only –0.2 percent. The plot suggests a clear downward trend in USDA corn forecast errors over time.

Forecast performance after 2011 has been particularly impressive.



It is important to emphasize that the USDA track record of forecasts evaluated here is based on “real-time” forecasts. In other words, this is the record of actual forecasts produced and released to the public over time. As Tetlock and Gardner (2015) observe in their best-selling book Superforecasting:

The Art and Science of Prediction, measurement and evaluation of a large sample of real-time quantitative forecasts is the only scientifically-valid way of determining true forecasting skill.

Recently, there has been a considerable media coverage of several new “big data” firms that claim to produce superior corn yield forecasts to that of the USDA (e.g., Brokaw, 2016; Woyke, 2016). What is not emphasized is that the evidence for these claims is based on historical simulations of model performance, or “backcasting,” a much lower and less rigorous hurdle. These firms may actually be able to beat the USDA, but real-time track records will be required to convincingly prove the point. Until then, the available evidence indicates it is hard to beat the accuracy of USDA corn yield forecasts.

Implications

The Agricultural Statistical Board (ASB) of the National Agricultural Statistics Service (NASS), is responsible for determining the official published corn yield estimates of the USDA. While there is considerable information available about the survey methodology used by NASS to generate yield indications, until recently, very little information has been publically available about the nature of the corn yield indications, the non-survey information, if any, used by the ASB to supplement the survey indications, or how the ASB reaches a collective consensus. Several publications have appeared in the scientific literature during the last several years that help open up the ASB “black box.” These publications present for the first time historical data on the separate Agricultural Yield Survey (AYS) and the Objective Yield Survey (OYS) corn yield indications and the results are striking. The upward bias in the OYS corn yield indications, regardless of the release month, varies from around 10 to 15 bushels per acre, while the downward bias in the AYS in August ranges from about 10 to 20 bushels, and then generally declines in September and October and is usually, but not always, fairly small in November. Given the level and variability of the bias in AYS and OYS yield indications, it is sensible for the ASB to seek out additional non-survey information when generating published yield estimates. The recent publications indicate that the ASB incorporates a variety of auxiliary information, including trend yields, planting progress, July temperature and precipitation, crop condition ratings, and satellite imagery data. Unfortunately, we still don’t have any information about the weights placed on this information in ASB deliberations. While it is important to better understand all aspects of the NASS corn yield forecasting methodology, and ASB procedures in particular, in the end what matters is the accuracy of the final published estimates.
On that score, the evidence suggests USDA corn yield forecasts are still hard to beat.

Extrapolating Yields from USDA's Crop Conditions



It’s about this time of year that USDA’s Crop Condition reports can be used, in part, to develop corn and soybean yields.

The agricultural economists at the University of Illinois have been tweaking yields out of the USDA crop conditions reports for quite some time. They say the later in the season it gets the more accurate they become. Right about now is usually when the good to excellent ratings, along with all the rest, begin to zero in on what’s really happening across America says Darrel Good, "We do know that the initial ratings for both crops are generally a bit on the high side. That is crops always look good early in the season before weather has had its chance to take a toll on the crop. And then on average ratings decline as you go to the final report of the year. If you recognized that bias, and correct the weekly observations for that bias the in-season ratings can be very useful because there is a very high correlation between final ratings and yields."

Typically, says Good, by mid-July the ratings for corn are pretty close. This is on average. That point is later in the season for soybeans, usually sometime in early August. Here are the yields the U of I has generated from this week’s USDA Weekly Crop Progress and Conditions report (July 30, 2017).
Darrel Good - If we relied entirely on the crop conditions model, today’s ratings would point to of 167.2, with soybeans at 47.7.
"If we relied entirely on the crop conditions model", says Good, "today’s ratings would point to of 167.2, with soybeans at 47.7. Again, I’m not sure I would ever rely one-hundred-percent on crop conditions as a way to form crop expectations, but as one component it does give you a good barometer or where we are."

One other note here on making calculations. A one percent move in the good and excellent category is worth about 7/10ths of a bushel says Darrel Good. This week corn is 15 points lower in those categories than last year when the national yield was 174.6. If you add in the trend line bump and do the math, it’s in that 166–167 range.

A Weather Market & Corn Yields

Each day the weather changes and just as often, it seems, so has the direction of corn prices. Todd Hubbs from the University of Illinois was of the opinion a couple of weeks ago that corn market had a some upside potential. It did, but now, maybe it doesn’t. This has him thinking about the number of acres of corn in the United States, the impact of the weather on yield, and how the market might react August 10th when the United States Department of Agriculture releases the first corn crop production report of the season, "We talk about increased corn acreage and maybe a yield loss below trend. Is that seven bushels to the acre, five bushels, or two bushels. It is really hard at this point to say, but I am looking at, out of my little model, 168 bushel national yield.

Still it is hard to say what USDA is going to put out on August 10th. Hubbs says he is looking forward to seeing what they say about yields. If the market is pricing in 164/165 bushels to the acre for yield corn and USDA releases a 168/169 yield, then Hubbs says the price moves won’t be good.

Here’s the upshot for Hubbs. He does not think the amount of corn left over from last year is particular oppressive to the market place. It’s big, but not enough to really weigh heavily on price. So, if this year’s corn crop isn’t near average there will be upside price potential, “I’m not as high on corn prices as I was before, but I think there is still a possibility. I see the seasonal average farm price for 17/18 corn in that $3.80 to $3.85 range with some runs.”

I see the seasonal average farm price for 17/18 corn in that $3.80 to $3.85 range with some runs - Todd Hubbs

You may read more from University of Illinois Agricultural Economist most Monday’s on the farmdocDaily website.

Crop Progress Reports & End of Season Yields

read blog post

Last week USDA released its first national corn condition rating of the season. The crop, as you’ll hear, wasn’t in great shape. While it doesn’t mean much at this time of year, there is a relationship between the first crop condition rating and the end of the season yield.

The weekly Crop Progress report is mostly the work of Extension and FSA employees, at the least the data collection part. They report local crop conditions to state USDA offices, mostly on Monday morning, who in-turn tally those numbers and pass them along to Washington, D.C. for compilation and release on Monday afternoon. Work at the University of Illinois shows a strong relationship between the end-of-season crop condition ratings and crop yield, however, agricultural economist Scott Irwin says that doesn’t hold so well for the rest of the season, “but, of course, what you really want to know is how soon do they become really predictive of final yields. Our analysis says they become pretty useful about mid-July for corn and not until about mid-August in soybeans”.

The first corn rating of the season, released just after Memorial Day, wasn’t good. the crop had been cold and wet. It showed up, or in this case didn’t show up, in the good and excellent categories USDA NASS uses. Those are the two grades the U of I economist say correlate. The math works like this; the first corn condition rating was 65% good or excellent, minus 8 points for the average drop to the end of the season rating, which brings you to 57% and then you plug that into the relationship the U of I presented in the article says Irwin, “and you end up with 164.3, basically on that set of calculations. It is an intriguing and pretty low number. Clearly that is not where the market is at and it is just one model, one exercise. Certainly, it is something to keep your eye on”.

“and you end up with 164.3”

If you do, in about mid-July you can use the math in the farmdocDaily article to forward calculate the national average yield for corn; mid-August for soybean.

Areas of Above & Below Trend Yields in the Corn-Belt

read farmdocDaily post

Farmers in Illinois and other parts of the eastern corn belt have had above average yields over the last several years. Gary Schnitkey wondered if this was due to the weather or some other reason. He explored the topic and came to three conclusions.



First, yield expectations in the current year likely are more heavily influenced by more recent experience. In those areas where yields have been high, it may be tempting to building financial budgets and expectations on relatively high yields. Doing so could result in higher projections of incomes than are warranted. Farmers in Illinois and other recent high yielding areas should be cautious about building in high yield expectations.

Second, the comparison of above average yields in Illinois and near average yields in Iowa is instructive in understanding whether high yields are caused by technological change. The high yields in Illinois in recent years likely are not a result of technological changes. If technological change was causing the yield differences, Iowa would have had above trend yields as well as Illinois. Rather, high Illinois’ yields likely are the result of good growing conditions. Over time, areas with good growing conditions will move around the greater Corn Belt, as has happened in the past.



Third, the above yield maps likely are indicative of relative financial performance since 2012. Overall, incomes have been lower since 2012. However, farmers in Illinois and other higher yielding areas likely have fared better than farmers in Iowa and other regions with near average yields. Again, weather variations can change from year-to-year, so areas with higher and lower yields will change over time.

Too Early to Worry About Late Planting

Farmers have been a bit worried about getting into the field because of rains throughout the Midwest. It looks like those will clear out for the week, mostly, and even if they don’t, there isn’t much to worry about, yet. Todd Gleason has more on when the ag economist at the University of Illinois think late planting impacts the markets and yields.

2016 Corn and Soybean Yields in Perspective


read the full article

The National Agricultural Statistical Service (NASS) recently released 2016 county yields for both corn and soybeans. In this article, maps are produced showing actual 2016 yields minus 2016 trend yields. Examination of these maps shows areas of above trend and below trend yields for 2016. Areas of above trend yields will have higher 2016 incomes relative to those areas with below trend yields.


Individual county trend yields are calculated using data from 1972 through 2016. A linear line is fit through these yields using ordinary least squares. The 2016 trend yields were based on these linearly fit relationships.

The following maps report actual minus trend yields. By calculating trend yields, the inherent productivity of the farmland is taken into consideration, and actual yields are stated relative to that productivity.






Schnitkey reports those areas with above trend yields will have relatively higher incomes than those areas with below trend yields. In 2016, lower grain farm incomes will be more pronounced in the eastern corn belt and particularly in Indiana and Ohio.

Assessing Argentina Soybean Yield Risks



by Todd Hubbs, Scott Irwin, and Darrel Good
source article

We recently began a series of articles to evaluate the history of corn and soybean yields and deviations from trend yield in Brazil and Argentina. The objective of the yield analysis is to provide a basis for forming expectations about the likely yields of the 2017 crops. The first six articles focused on the alternative sources of historical yield estimates, the selection of the appropriate series to use in the analysis for both corn and soybeans, the selection of the best-fitting trend model for each commodity and country, trend yield deviations in each country for corn, and trend yield deviations in Brazil for soybeans (farmdoc daily, November 2, 2016; November 9, 2016; November 16, 2016; December 14, 2016; December 15, 2016; and January 12, 2016). Today’s article examines soybean yield trend estimates and trend deviations for the Argentinian soybean crop. Since Argentina is the world’s third largest producer of soybeans and is the largest exporter of soybean meal and oil, yield and production prospects have important price implications.

Background

We begin by providing some perspective on regional soybean production in Argentina. The production map of Argentina from the USDA/FAS gives a visual sense of the concentration. The top three soybean production provinces consist of Buenos Aires, Cordoba, and Santa Fe. Table 1 presents soybean production by country from 1971 through 2016 and gives an indication of overall growth in soybean production in the world, and Argentina in particular. Soybean production in Argentina grew rapidly in the early 2000’s with a significant jump in 2001. Figure 1 presents the soybean acreage for Brazil and Argentina provided by USDA/FAS estimates from 1978–2016. Both nations exhibited large growth in soybean acreage over the sample period with Argentinian acreage leveling off at the end of the period. Current estimates place Argentina soybean acreage at 48.1 million acres this year.





Figure 2 presents the annual soybean yields in Argentina for the period 1978 through 2016. As previously discussed in the farmdoc daily article of November 16, 2016, we chose a linear trend to fit the soybean yield data for Argentina. Note that these yield estimates are provided by the USDA’s Foreign Agricultural Service (FAS) and are based on past trends, expert opinion, industry intelligence, and AgMin, the Argentinian Ministry of Agriculture, estimates. Yields have obviously trended higher over time. The linear trend indicates annual average yield increases 0.37 bushels for Argentina. A linear trend explains about 49 percent of the annual variation in actual yields in Argentina. The historical soybean yields in Argentina show large variation around the trend with an extended period of above trend yields from 1998–2003. The linear trend since 1978 explains a much smaller percentage of yield variation than is the case for the U.S. (81 percent) and Brazil (79 percent).



Historical Deviations

Historical deviations for Argentine soybean yields for the period 1978 - 2016 are shown in Figure 3. Over the 39-year period, the average soybean yield in Argentina was above trend in 22 years and below trend in 17 years. The largest deviation below trend was 9.79 bushels per acre in 2009. The largest positive deviation from trend was 5.80 bushels per acre in 1998. The average positive deviation was 2.66 bushels while the average negative deviation was –3.44 bushels. The deviation from trend is asymmetric with more years of positive trend deviation and larger magnitudes associated with negative trend deviations. This differs substantially from soybean trend deviations for Brazil. Since 2012, Argentinian soybean yields demonstrate a wide variation around trend with significant yield loss in 2012 and a large positive deviation in 2015. Based on the historical trend deviations, the unconditional probability of a negative deviation is 43.6 percent. If a negative deviation occurs, the unconditional probability of a negative deviation of greater than two bushels is 65 percent, and there is a 29 percent probability of a greater than four-bushel deviation. The probability of a negative yield deviation greater than two (four) bushels, then, is 28 (13) percent. Based on the historical trend deviations, the unconditional probability of a positive deviation of greater than two bushels is 59 percent, and there is a 23 percent probability of a greater than four-bushel deviation. The probability of a positive yield deviation greater than two (four) bushels, then, is 33 (13) percent.



Implications

An examination of the national average soybean yields in Argentina for the period 1978 through 2016 reveals an upward yield trend with substantial annual variation. The estimated linear yield trend points to a 2017 average soybean yield of 42.2 bushels per acre, 1.10 bushels below the 2016 average. Based on the projections of harvested acreage in the USDA’s January 12, 2017 World Agricultural Production report, yield at trend value for Argentina points to a 2017 crop of 2.03 billion bushels, 57 million bushels (2.73 percent) smaller than the 2016 crop. Using estimates of the historical yield trend deviations, we estimate there is an unconditional probability of 62 percent of a two bushel trend deviation. A trend yield deviation of two bushels per acre would add or subtract approximately 96 million bushels to our projection of Argentina’s 2017 production.

The USDA projects the 2017 Argentinian yield at 43.57 bushels per acre (1.37 bushels above the trend value) and production at 2.094 billion bushels, 7 million bushels larger than the 2016 crop. The USDA estimated production level for Argentine soybeans is 64 million bushels larger than implied by a trend yield. Recent reports in Argentina indicate severe flooding in many growing regions with the potential to reduce production by 100–150 million bushels. If the production reduction materializes in Argentina, 2017 will produce yields well below trend estimates. In the next article, we will examine the impact of La Nina events on Brazilian and Argentinian soybean and corn production.

Not Much Chance USDA Will Change Corn Yield or Acreage

Early corn yield reports have been good, but pretty variable. There are more than few concerns about a disease called diplodia, too. Some are beginning to piece these items together to make a case for USDA to lower its corn yield estimate. This isn’t very likely thinks University of Illinois Agricultural Economist Darrel Good.

“The fact is”, says Darrel Good, “if you look at the last 20 years of history, there is a strong tendency of the corn yield estimate to get higher in January compared to what it was in September. This has happened 70% of the time in the last 20 years, and almost 70% of the time in the last 40 years. So, those looking for a lower estimate are bucking history, but you can’t rule it out.”

Maybe not, but even if the USDA yield changes it won’t be by much thinks Darrel Good. Certainly not enough to really alter the supply/demand balance sheet changing it from a surplus to a tight supply situation. He doesn’t expect USDA to change the acreage numbers much either. This is because the difference between the Farm Service Agency reported acreage figures released in August and then again in September was very small.

This tells Darrel Good reporting has occurred in a very timely fashion. Therefore, he doesn’t look for an FSA increase in subsequent reports. Historically when the dust settles on corn, NASS acreage is three to three-and-a-half percent higher than FSA, says the U of I number cruncher, and about two percent higher on soybeans. This is right in the range where the FSA numbers set today.

Consequently, Darrel Good does not expect NASS to change its corn acreage estimate very much going forward. If this is the case, it leaves the U.S. with record corn yield and production figures.

Summer Weather, El Niño, & Corn Yields

The agricultural economists at the land grant university in Illinois have gone through 56 years of weather data to see if there is any connection between the current El Niño event and trend yields for corn.



The trend yield for corn has been going up 1.8 bushels per yer for about 50 years say the number crunchers from the University of Illinois. It means, under normal weather conditions with a little adjustment upward, this year’s corn crop should average 166.2 bushels to the acre nationwide.



The 166.2 is the norm, but it lives within a range that would be indicative of really good years like 2004 and really bad years like 2012 says U of I’s Scott Irwin, “Now what we want to ask is if we should skew our expectations of this risk given this outside factor that doesn’t happen every year that we call El Niño”.

ILLINOIS’ research suggests the answer to this question is a qualified yes. The qualification is that the El Niño event is measured strictly as an effect of water temperature in the Pacific Ocean near the equator and that only the most extreme of these events, those a full degree or more centigrade above the norm for three months running, would be considered strong enough to regularly have a real measurable impact on U.S. crops.

The warmest one, to date, was 1997/98 and it peaked at 2.3 degrees centigrade above normal. If you take the same period and you estimate trend yields going back to 1960 there were 11 El Niño episodes at least one centigrade degree above normal. The Illinois agricultural economists filtered this data so these spikes had to occur in what they called the pre-season periods for corn production. This would be from September to March prior to the crop year. It is exactly what has happened this year and the spike is more than two degrees centigrade. It’s a really big one.
Irwin - What we find is, in these big spiking El Niños that occur in the pre-season period, that corn on average is about 4 to 5 bushels to the acre below trend.
Having said that, Irwin points to a large range of occurrences from 11 bushels above trend in 1992 to 23 bushels below trend in 1982. 1988 and 2012, the two worst drought years, also count under this construct.



The model used very reliably predicts summer heat waves, however, it is not so great at determining the amount of rainfall. Recall the reference Irwin made to the 1997/98 pre-season El Niño, the largest on record, similar to this year. The national corn yield was 3 bushels to the acre above trend. The heat wave came, it was just very last in August and early September after the corn crop had been made.

Benchmarking Soybean Production Systems

Soybean farmers in ten states across the Midwest are being asked twenty questions. Todd Gleason has more on a Soybean Checkoff funded project to benchmark the yield impact of different production practices.