… you find one of these in a corn field.

I was walking through knee high corn and found it sliding across the ground. At first I thought it was a slug but it was moving much too fast. If you haven’t guessed by now, it’s a leech. In 20 years of walking fields this is the first one I have ever found.

     With the recent explosion of foliar applied nitrogen products in the marketplace, I often field questions regarding whether or not these products actually work or are they just another in an endless line of snake-oil products. This is a fair question; especially since the products are not cheap to buy and/or apply, but if they do perform as advertised they have the potential for a nice return on investment.

     So how do we know if they work or not? The first step in evaluating these products is to look at the agronomics behind the stated benefits. With many companies claiming nutrient use efficiencies through foliar feeding, as well as a long window of availability through “controlled release” formulations, it’s imperative that we understand just how these products work.

Foliar Efficiencies

     One of the main selling points of foliar applied nutrients is the increased efficiency of foliar application versus soil applied applications. One of the more popular foliar N products on the market even goes so far as to claim that 1 pound of foliar N can replace 5 pounds of soil applied N, for a 5:1 efficiency ratio. But is this true?

     Plant leaves, by design, are not very efficient in taking up nutrients. Instead, they were designed for a different purpose. Darren Goebel, Area Agronomist with Pioneer Hybrids addressed this subject in an article last summer. He said;

… leaves are designed to collect sunlight, photosynthesis, transport sugars to other parts of the plant and transpire water vapor and gases. Leaves are covered by a waxy cuticle, making them virtually impervious to water and carbon dioxide. Stomata make up 10% of the leaf surface and account for 90% of the water and gas movement on the leaf.

   Goebel goes on to say this;

Because such small amounts of nutrients can enter plant leaves, macronutrients like nitrogen, phosphorus, and potassium should not be considered for a one-or two-shot foliar feeding program. It is highly improbable that foliar feeding can get enough of these nutrients into the plant to make a difference. In fact, several University studies have confirmed little difference in yield when foliar applying macronutrients to corn and soybeans.

     Obviously there isn’t much of a gain in efficiency when trying to feed macronutrients through the leaves of the plant; the plant is not capable absorbing nutrients in large enough quantities to do much good. However, if you have seen the advertisements for these products, you know that the inability of the leaf to absorb large amounts of nutrients makes no difference because you only need a small amount of product to see a sizable yield increase. In fact, most of these products have a recommended application rate of 1-3 gallons per acre, which at 2.5 lbs. of nitrogen per gallon, definitely qualifies as a small amount of N being applied.

     Most of these products are recommended to be applied with glyphosate as a planned application program. At this time – especially in corn – the plants N usage is beginning to increase rapidly. This also coincides with the particular growth stages when the plant is determining ear size (corn) and setting pods (beans). The theory behind this is that a little extra N at this critical time can pay big dividends. The question is; is there any validity to the theory? We shall see.

Note: From here on, I’m going to focus on corn, but what I am going to say can certainly be applied to beans also.

     As I mentioned previously, at the time these products are recommended to be applied, the plants N usage is increasing at a rapid rate. As you can see from the chart below, a corn plant’s N consumption increases from 1.5 lbs. per day for 4″ corn to 6.0 lbs. per day when the corn is waist high. This is the period of time when foliar applications are recommended because you want to make sure the plant has enough N when it needs it the most. In theory, this makes a lot a sense. Although one must remember that this is theory – reality is usually somewhat different.

     Lets assume that we have a normal corn crop. The corn was planted in a timely fashion, we have a good stand, and the corn is not showing any N deficiencies. In this example, it is recommended that we apply 1 gallon of a 25% controlled release nitrogen product with our normal glyphosate application. Since it’s a 25% N containing material and it weighs 10 lbs. per gallon, we are applying 2.5 lbs. of nitrogen per acre.

     Under normal circumstances, the timing of the glyphosate application would occur around the V5 to V6 growth stage. Looking at the N use chart, we can see that at the V5-V6 stage the corn plant is using somewhat less than 6.0 lbs. of N per day. We know at this point, the corn plant is just beginning a period of extremely rapid development so we can safely assume the plant is using between 3 and 4 lbs. of N per day. It’s important to note that the plant is using this amount regardless of whether it is taken up by the roots or absorbed through the leaves.

     Given the above facts, it’s obvious that the 2.5 lbs. of N we are applying with the foliar product is not even supplying enough nitrogen to feed the plant for one day. But in reality, the plant is not receiving the full 2.5 lbs. because not all of the product is being intercepted by the plant. A significant portion of the material is hitting the ground rather than the leaves.

     When spraying corn that is approximately 16″ tall (V6), the crop canopy intercepts approximately 50% of the spray (assuming nozzles positioned both directly over the row and between the row), which results in an application of only 1.25 lbs. of N to the crop. This is barely enough N to feed the plant for 1/2 a day. Now we begin to see the futility in foliar feeding macronutrients. But there’s more to the story, so let’s continue. 

     From the label of the product we are using, 75% of the N is in the urea form with the remainder in a slow or controlled release form (I’ll have more on controlled release later). With urea nitrogen, approximately 70% of the N is absorbed into the leaf within the first 24 hours – the rest of the N is lost. If we plug the 70% figure into our calculations, only 0.875 lbs. of N is being absorbed by the plant. This is only enough N to feed the plant for 6 hours. By this point I’m sure somebody is going to bring up the fact that they use more than 1 gallon of product, but even at the 3 gallon rate, we are supplying enough N to feed the plant for 18 hours instead of 6 hours. This is still a minute amount of N when compared to the plant’s needs.

Slow Release Formulations

     Another argument that frequently comes up is the fact that the product is slow or controlled release, thereby spoon-feeding the crop over a 3 to 4 week period. Assuming that all the N being applied is in the slow release form (as implied through the advertisements), 0.875 lbs. of N spread over a 4 week period only amounts to 0.031 lbs. of N available to the plant per day.  But we know this is not the case because only a small portion of the N is in the controlled release form.

     Remember the label stated that 75% of the N is in the urea form. This means that only 25%, or 0.63 lbs., is in the controlled release formulation. If we take 0.63 lbs. and divide that by a 4 week period, we come up with 0.0225 lbs. of N provided to the plant each day. To you and I, this would be like taking 1 milligram of Human Growth Hormone (HGH) per day when the recommended amount is 165 milligrams, and expecting to look like Arnold Schwarzenegger in a few weeks; it’s not going to happen. And so it goes with slow release nitrogen. The plant is receiving such an infinitesimally small amount of nutrient, it is not possible to affect a positive change in the crop.

Conclusions

     Although the theory sounds good and the sales pitch can be very convincing, foliar feeding macronutrients such as nitrogen is just not feasible. Because plants require such large amounts of these nutrients (it’s why they are called macronutrients) over an extended period of time, and because leaves are not designed for the absorption of nutrients, it’s physically impossible (without harming the plant) to introduce enough nutrient into the plant in order to gain a benefit. A person should look upon these types of products with a skeptical eye and weigh the stated claims against known agronomic principles. Oftentimes, one will find that the claims just don’t add up.

With all the discussion about zone sampling versus grid sampling between advocates of both systems, I think it’s absolutely essential to know the benefits and shortcomings of each system.  

There is no doubt that zone sampling saves money versus grid sampling. With grid sampling, in order to ensure an acceptable degree of accuracy, a lot of samples need to be pulled and analyzed which drives up costs. Conversely, zone sampling reduces costs because it is assumed that given areas within a field, as one poster in a thread below so eloquently put it, are homogeneous. In other words, the variance in pH and nutrient levels are minimal so these zones can be sampled as a composite, thus reducing costs. But is this true? Are zones homogeneous enough that we can in fact reduce sampling frequency in order to reduce costs? I have found that the answer to that question is usually a resounding no. Here’s why…..

Over a period of several years, I have had the opportunity to grid sample a number of fields on 1.1 acre grids. This has provided me with the ability to view nutrient variability on a scale not typically seen in the industry. With this density of samples, I not only get an excellent look at field scale variability, but I can also measure the variability within differing soil types within the field. What I consistently find is that with respect to P & K levels, they are not homogeneous within these zones - although pH is a different story.

Here is a field showing sample points on 1.1 acre grids and also the different soil types:

The next image is the field broken into different sampling zones based on the soil types seen above:

Now that the field is broken down into sampling zones based on soil types, an analysis of the samples that fall within each zone can be done.

After breaking down the samples within their respective zones, it becomes quite apparent that there is a lot of variability within the zones themselves. In order to get an idea on how large the variability actually is within the zones, I did a standard deviation calculation on each zone. Keep in mind that the standard deviation is the average variation from the zone average. For P & K (actually P2O5 & K2O), it’s easy to see that the variation is quite large, and for pH, the variation is somewhat smaller. But what does all this mean? And how does it affect the amount of fertilizer that is recommended to be applied?

The next step is to calculate the average amount of error as compared to the zone average:

This chart shows the percent error of the zone average when compared to the individual samples (the chart is labeled incorrectly). In other words, the zone average over/underestimates the nutrient level by the listed percentage. Clearly we can see that for P & K, using the average for the zones results in a large amount of error. A person needs to keep in mind that over/underestimating the level of fertility directly affects the amount of fertilizer being applied by roughly the same percentage. So in effect, if I were to use the zone average as a basis for a fertilizer recommendation, I would be overapplying or underapplying P by approximately 40% and K by 20%. In my opinion, this is unacceptable.

I do think anything under 10% is acceptable, so for pH and the application of limestone, using a composite average by zone is a viable alternative. But not for P & K.

I know someone is going to bring up the fact that this is only one field and I am cherry-picking the data. I have run many of these analysis on different fields it it almost always comes up the same. Very seldom does a composite sample by soil type accurately reflect the P & K fertility within that zone. Again, pH is a different story. In the majority of fields, pH correlates fairly well with soil type, so a zone composite is usually acceptable. But who is going to sample pH by zone and P & K by grid? It’s simply not feasible so grid sampling is the best option and far superior to zone sampling.

I will add one caveat however. Zone sampling for mobile nutrients such as nitrogen may produce acceptable results, but since we do not sample for nitrogen in Illinois, I have not done a similar analysis.

With corn planting only 50% to 70% complete across much of the corn belt, many growers are beginning to question whether or not a switch to a shorter season hybrid would be warranted. The fear is that with a full season hybrid, the plant would not mature in time to avoid an early frost at the end of the growing season. This is a valid concern because an early frost on a hybrid that has not reached maturity will ultimately result in a reduction in yield.

So now, the question becomes: at what point/date should a person make the switch? Leave it to Bob Nielson at Purdue University to come up with some timely information on this very subject!

I would highly recommend everyone read Bob’s excellent article. He not only looks at average frost dates, but he also discusses a not entirely well known phenomena of a hybrids ability to adjust it’s GDU’s downward the later it is planted.

Be sure to check out Bob’s article.

Late Planting/Replanting & Relative Hybrid Maturity

With crop planting here in Central Illinois in full swing, I’ve been unable to update this blog with any new posts. As soon as the mad rush of corn planting is over with, I should be back to a schedule that will allow enough time to post on a more frequent basis. In the coming weeks look for further posts on the ethanol biofuel issue as well as posts dealing with various agronomic issue’s.

Just a quick note on planting progress…

Corn planting is nearly finished in this area. I would expect by Wednesday, most farmers will be done with corn and starting on bean planting. I’m sure this comes as a disappointment to the ethanol doomsayers who have been predicting a lower yielding corn crop because of planting delays, but the fact is, the corn crop will be just fine. We generally see little to no yield penalty if the crop is planted before May 15.

For the most part, the wheat in this area is mostly good to excellent. I’ve been out in a few fields and at present, there is no disease to speak of. This could change quickly if warmer temps are accompanied by additional rainfall, but for now, diseases are being held in check. It looks like those who chose to make an early fungicide application did so needlessly. If you are considering applying a fungicide at flowering, please use the Wheat Disease Prediction Tool I posted about earlier. This will help to avoid further unneeded applications.

The media and the environmentalists say the high food prices are a result of ethanol biofuel production. The agriculture industry says it’s because of soaring fuel prices (among other things).

So who’s right and who’s wrong?

I was going to make a long post detailing the answer to this question, but instead, I’ll let you decide for yourself.

 Sources: Historical Crude Oil Prices & Historical Grain Prices

I’m sure everyone has heard the news by now, rising food prices are “threatening the poor worldwide” and causing riots around the globe. The cause of these high food prices? Well, biofuels of course, and ethanol in particular. Recent news articles have lambasted the ethanol industry. 

Time magazine calls ethanol “The Clean Energy Scam”.  A recent article titled The Great Biofuel Famine said: “biofuel policies will significantly contribute to the early, avoidable deaths of between 10 and 20 million people in the year 2008 alone.” Former president Bill Clinton, at the Progressive Governance Summit in England, made this terribly misguided statement:

“What’s really hurting the food markets is America moving into ethanol. People there are moving into corn and you have pasta riots in Italy related to what some people are doing in farming in America.”

A recent editorial in the New York Times titled, The World Food Crisis, chastised the “rich world” for “exacerbating” the rise in food prices by “supporting the production of biofuels.” In this same editorial, it’s interesting to note that the Times Editorial Board characterizes food prices as “controllable” and fuel prices as “uncontrollable”. In reality, fuel prices are just as controllable as food prices – all you have to do is produce more oil. But the Times does not support drilling for oil because it causes more global warming, so higher fuel prices are fine by them. After all,  higher fuel prices force people to use less, and less use means saving the planet. What they won’t admit though, and as I’ll demonstrate in just a little bit, the increased cost of fuel is the primary driver of soaring food prices. Ethanol biofuel is just a bit player in the whole scheme of things.

So is all this criticism warranted? Is the diversion of corn into ethanol production actually what’s driving the increases in food prices? In part, yes. But it’s only a small role, as we shall see.

In order to get a clear picture of the effect ethanol is having on prices, I’ll go through, on-by-one, some of the food items that are heavily dependent on corn. We’ll have a detailed look at what’s really driving prices – but be forewarned, what I have found might surprise you. I’ll also look at the law of unintended consequences: the argument that the price of some foods, even though they are not derived from corn, are rising because farmers are planting less acres of a crop in order to plant more corn for biofuels. Wheat is a prime example, and it’s where I’ll begin my analysis.   

Bread

The prime ingredient of a loaf of bread is wheat flour. The price of wheat flour has increased considerably because the price of wheat has more than doubled in the last few years. This in turn has caused an increase in bread prices. Perception amongst consumers is that the price of wheat is mostly to blame. But is this true? Is the price of wheat flour driving store prices, or is their some other factor involved – like the cost of fuel?

According to the U.S. Department of Labor’s Bureau of Labor Statistics, the price of bread has risen 32 cents since 2004. That equates into a 32% increase in just a few years, which is a lot, and it is definitely being felt in the consumers pocketbook. But is the 32% increase because of the higher cost of wheat? In order to find out, let’s do some calculations.

From the Kansas Wheat Commission, we know that a bushel of wheat will make approximately 70, one-pound loaves of white bread. We also know, from The United States Department of Agriculture’s Economic Research Service (ERS), that the average price a farmer received for a bushel of hard red winter wheat in January, 2008 was $7.60 per bushel. If we take $7.60 per bushel and divide that by 70 loaves of bread, we know that we have 11 cents of wheat in a loaf of bread. That’s the farmers share of the price of a loaf of bread.

Now, if we go back to 2004, we know from the (ERS) that the average price of a bushel of hard red winter wheat was $3.43 per bushel. Take the $3.43 per bushel and divide that by 70 loaves of bread, we know that we had 5 cents worth of wheat in loaf of bread in 2004. We can now see that even though the price of wheat has more than doubled, we have only 6 cents more wheat in today’s loaf of bread as compared to 2004.  That’s only a 6% rise in price! But the price of bread has went up 32%! Where is the other 26 cents going?

I don’t have a definitive answer to that last question but I do know that a large part of the extra 26 cent increase is because of the price of fuel. It takes a lot of energy to process the wheat into flour, package it, and then ship it to the retailer. This is undoubtedly a major expense on the part of the processor.

One other thing to consider is the way margins are figured at the retail level. I’m sure everyone has seen where a retailer has been quoted as saying that his percent markup hasn’t changed so the increases are not his fault. In this case, the retailer is not being entirely truthful. Let’s use the price of bread as an example.

Let’s assume that in 2004, the retailers cost of a loaf of bread was $0.80. In order for him to make 30% from the sale of the bread, he takes $0.80 and divides that by 0.7 to get his 30% markup. This makes his sale price $1.14 per loaf, so he’s making 34 cents per loaf.  Now let’s say his cost for a loaf of bread today is $1.00 even. He takes the $1.00 and divides that by .7 to get his 30% markup, so his new selling price is $1.43. He’s now making 43 cents per loaf instead of 34 cents. In other words, the retailer has increased his profit by 9 cents for each loaf sold. 

It’s important to note that I have no problem with a retailer making more money. A retailers expenses go up just like everybody else, and he needs to cover those expenses in order to stay in business. But I do have a problem when a retailer is being less than truthful about where the price increases are occurring. The claim that their retail margins have not increased is pure nonsense.

Meat (Beef)

This article from the Washington Post tells us that beef prices are on the rise, and that greater demand for corn is squarely to blame. The Post illustrates this by saying: ”… cattle ranchers have to pay more for animal feed that contains corn. Those costs are reflected in cattle prices, which have gone from about $82.50 per 100 pounds a year ago to $91.15 today.” Wow, almost a $10.00 increase in just a year, all because of the high cost of corn! But is this true? Is the farmer passing the increased feeding costs through to the retailer? I think not! I’ll explain why.

Thankfully, the USDA tracks monthly retail meat prices along with the farm sale price of cattle and hogs. From this data we can calculate the difference between what the farmer receives when he markets the animal and the final sales price of the meat at the grocery store. This is referred to as “the spread”, and I’ve illustrated this in the following chart:

Figure 1. Retail Value and Net Farm Value of Beef. Retail value is defined as the average value of the selected cut of meat at the grocery store, measured in cents per pound of retail weight. Net Farm Value is defined as the gross farm value minus the value of byproducts; represents the value of the meat to the farmer.

Notice in Figure 1 that the gap between Retail Value and Net Farm Value looks to stay relatively the same (looks can be deceiving) throughout the 1990’s and then beginning somewhere around 2002, the gap starts to widen. This is our first indicator that something is amiss. The chart clearly indicates that in the recent past, retail prices are rising faster than farm prices. By how much it’s difficult to tell, because you have to eyeball the difference between the two prices, but it’s readily apparent the spread is growing.

Next, to illustrate this further, I subtracted the Net Farm Value from the Retail Value which gives us the difference in price between the farmer and the retailer. Now we can see how quickly retail prices have outpaced farm prices:

Figure 2. Retail Value minus Net Farm Value

I think one would have to agree that the results in Figure 2 are simply stunning! Since 1990, the retail price of beef has been growing faster than the farm price, and in the early 2000’s the price difference has accelerated greatly. This is clearly an indicator that increased corn prices are having little to no affect on the price of meat at the grocery counter. By calculating the difference between the retail price and the farm price, we know that the majority of the increase in the price of beef is occurring after the animal leaves the farm. In other words, the enormous price increases are occurring either at the wholesale level or the retail level, or a combination of the two together.

The take-home message here is that the increase in the price of beef has little to do with the increased price of corn. The majority of the increases we have seen to date are occurring after the animal leaves the farm and reaches the meat packing plant. The reason for this is obvious – the price of energy has skyrocketed. As it is with wheat flour, it takes a lot of energy to process the meat, package it, and then transport it to the marketplace.

Meat (Pork)

I’m not going to go into as much detail about the rise in pork prices as I did with beef prices because the story is the same – the majority of the price increase is occurring after the animal leaves the farm. I have illustrated this in the two charts below:

Figure 3. Retail Value and Net Farm Value of Pork.

Figure 4. Retail Value minus Net Farm Value

Again it’s not too hard to see that the farmer is not passing the increased cost of his corn feed on to the consumer. In fact, the farmer can’t pass on the extra costs because, as this article so skillfully points out, farmers are “price takers”, not price makers. Farmers do not establish their sales price, the commodities market sets the price for them. It’s a take it or leave it proposition. The farmer either has to take the price offered or not sell his product, it’s as simple as that.

Poultry (Meat & Eggs)

Although the available data for poultry prices is limited, it appears that the increased cost of corn is having an effect at the local grocery. While my knowledge of the poultry industry is virtually zero, I suspect the reason why corn prices are affecting poultry prices more than beef or pork is because poultry products are not commodities. It appears that most of the poultry wholesalers also raise their own birds. Because the wholesaler sets the price to the retailer, they are able to pass along the increased costs of raising the birds. The following chart illustrates this relationship nicely. With the exception of eggs, the price increases are not originating at the retail level.

Figure 5. Retail to consumer spreads for poultry and eggs = Difference between what the retail grocery store pays for the product (wholesale price plus a delivery charge) and what the store charges the consumer.

Milk & Cheese

I don’t think there’s a household in the United States that doesn’t consume milk in one form or the other. Because of this, hardly a day goes by that I don’t here a complaint about the price of milk.

So what’s behind the price increases? Is the price of corn the dominating factor?

The answer to those two questions is complex, but in short, corn is only a small factor in today’s milk prices. The real reason milk prices have went through the roof is because of the laws of supply and demand. Demand is up, and according to the International Herald Tribune, it’s because people are becoming more affluent in the Asian countries:

“But the biggest force driving up milk prices is the same one that has driven up prices for conventional commodities like iron ore and copper: a roaring global economy. Rising incomes in emerging economies from China and India to Latin America and the Middle East are lifting millions of people out of poverty and into the middle class.

It turns out that, along with zippy cars and flat-panel TVs, milk is the mark of new money, a significant source of protein that factors into much of any affluent person’s diet.”

 The Tribune goes on to note that:

… The average person in China now consumes more than six gallons of milk a year, up from more than two gallons in 2000.

But there’s more to the story than just demand from China. As it turns out, supply is down sharply. There are a couple of important factors that have affected worldwide milk supplies: drought in Australia and recent record low milk prices that forced dairy farmers to reduce the size of their herds.

Australia is the third-largest dairy exporter in the world. Recent droughts have reduced Australia’s dairy production by almost 1 billion litres, which has reduced worldwide supplies. With the recent La Nina rains in Australia, the situation has improved, but it will take some time for their dairy industry to recover and ramp up production.

Also, few people remember that just a few short years ago, milk prices were very low and the dairy industry was losing a lot of money. Profits were so bad that many referred to the situation as “dire”.  This caused many farmers to liquidate their herds, as these numbers from the state of Washington show:

Year	Farms	Cows
1996	902	257,000
1997	825	253,000
1998	770	248,000
1999	725	247,000
2000	680	246,000
2001	655	246,000
2002	630	247,000
2003	602	247,000
2004	585	240,000
2005	560	237,000
2006	550	233,000

 Source: Washington Dairy Products Commission

 Most experts agree that milk prices will ease a bit in the future, but it’ll probably be another year or two before that happens. In the meantime, we should urge media outlets such as The Daily Green and Senators such as Charles Schumer to (actually) brush up on Econ 101, and stop advocating terribly misguided policy changes which will do nothing to fix high food prices. There is no reason to hamstring the ethanol industry because ethanol is not the main cause of the problem.

Thanks to the researchers at Penn State University, Ohio State University, Kansas State University, Purdue University, North Dakota State University, and South Dakota State University, we have a new wheat disease prediction tool available to wheat producers East of the Rocky Mountains. This new tool comes in the form of predictive models which are designed to forecast an outbreak of Fusarium head blight (FHB)(head scab) in wheat.

According to the University of Kentucky, economic losses resulting from head scab were in excess of 3 billion dollars in the 1990’s. It’s a devastating disease, and a considerable amount of effort has been put forth in an attempt to minimize it’s impact. The FHB prediction tool is a direct result of that effort. 
 

The main benefit to those who grow wheat is the ability to predict a disease outbreak before it happens. This is especially welcomed in the case of FHB because you can not scout for this disease. If you find that you have the disease, it’s too late – the disease has already done it’s damage and caused a yield loss. This has caused many growers to move to a planned fungicide application across every acre every year – regardless of whether or not environmental conditions are favorable for disease development. The problem with this approach is that it results in a lot of fungicides being applied when they are not needed. Now however, we have a viable alternative.

According to the developers, the models can predict an FHB epidemic of greater than 10% severity at an accuracy rate of 80%. It accomplishes this high rate of accuracy by analyzing weather variables that occur before flowering. More specifically, for winter wheat, the model “considers the duration of time that relative humidity is 90% or greater and temperature is also between 48 and 85°F (9 -30°C).” For spring wheat it’s a bit different in that the model incorporates varietal resistance into the equation, but weather is again an important factor.

Risk Assessment

The key feature in obtaining a prediction for your wheat crop is the Risk Map Tool. It’s an easy to use web based interface that allows for a quick assessment of the potential for a FHB outbreak in any given area. In just a matter of a few clicks, you can see whether or not your crop is at risk. There are however a few key items of information that you will need to know beforehand. The prediction center recommends the following:

Key Items Needed to Obtain a Prediction

Flowering date– You will be asked to identify the flowering date for your fields. Visit fields to determine the date when anthers are exposed on 15% of the heads. Wheat is most susceptible during the flowering growth stage, and the models will use weather conditions observed during the seven days prior to the flowering date you select. Planting date and variety will affect flowering dates so each field may have a different flowering date. (You can use the 24 and 48 hour forecast buttons in the upper left corner of the tool to help you estimate risk several days before the actual flowering date).

We suggest that you monitor the risk of disease in your area for a full week prior to flowering. As the wheat crop approaches the actual flowering date, we recommend that you also monitor your local weather forecast. The greatest risk for scab occurs when weather conditions prior to flowering have been conducive for reproduction of the fungus (indicated by yellow or red colors on the risk map), and when weather during the early stages of kernel development favors infection. Three or more days with frequent rainfall and moderate temperatures (65 to 80 F) during the kernel development may significantly increase the risk of head scab.

Wheat class– Identify whether you are growing a spring wheat (spring planted) or winter wheat (fall planted). This selection will activate different components of the system and customize the prediction for your crop.

Production practices– If you select spring wheat, you will be asked to provide information about the resistance level of the variety planted in your fields. This is important because planting a susceptible variety may significantly increase your risk of disease. Most varieties of wheat are susceptible to head scab, and we advise that you use this as the default level of resistance unless you know that your wheat variety has a different level of resistance to head scab. More information about the resistance level of spring wheat varieties can be found in the variety evaluation reports provided by North Dakota State University.

With the above information in hand, you’re now ready to use the map tool. Just follow the three easy steps at the beginning, and you’ll soon have a map something like the one shown below.

Be sure to choose the weather station closest to your field so that you can get a more detailed assessment of the risk for a disease outbreak.  You’ll also get a summary of the conditions during the past 7 days for that particular area as well as a risk rating of low, medium, or high.

There is one drawback to the prediction model – it can’t predict future weather conditions. As you and I both know, the weather can change in an instant. Conditions may not have been favorable for disease development, but it could be in the near future, so the decision to apply a fungicide should be based not only on the model but also on the weather forecast over the next 7 to 10 days. 

As an agronomist, I can’t stress the importance of using this new tool. Any application of fungicide should be based upon the potential risk of disease development rather than treating every acre every year regardless of whether conditions warrant an application or not. I know some will argue that applications are warranted based upon a “plant health” standpoint alone, but field trial data does not back this up. The data clearly shows that a return on investment is consistent with the level of disease present in the crop. Under conditions of low or no disease presence, the return per dollar invested is very inconsistent. The only exception is for grain grown for food or seed. Fungicides can increase grain quality which oftentimes results in a higher premium, so that has to be taken into consideration. Otherwise, if you don’t need it, don’t spray it.

Bob Nielson, Purdue University, offers this tongue-in-cheek recipe on how to get as poor of a stand of corn as possible. Of course he’s not serious, but it does serve as an important reminder that stand establishement is a very important part in raising a good crop. Here’s Bob’s recipe:

Ingredients:

• One (1) field, level and poorly drained.
• One (1) or more hybrids of your choice, but preferably ones with poor seed quality and low vigor.
• Do NOT add any starter fertilizer to the recipe.
• Add a dash of seed rot or seedling blight organisms.
• Add a pinch of wireworms or seedcorn maggots.
• Plenty of spring tillage to maximize soil compaction, though one pass with a disc will suffice if the soil is “on the wet side” when worked.
• Flavor with amide or growth regulator herbicides as desired.
• Add minimum of 0.5 to 1.0 inch of rain per week after planting to maintain saturated soil condition.

Mix well and plant early or any time before soils have consistently warmed to more than 50^oF. Maintain average daily soil temperatures at 50^oF or less for three weeks or more after planting. Plant “on the wet side” to ensure good sidewall compaction. Plant either excessively deep or excessively shallow. Plant as fast as you possibly can to ensure uneven seed drop. For best results, follow corn with corn, especially with minimal fall tillage. Top off with a thick soil crust and serve cold.

Will serve 6 people (farmer, fertilizer & ag chemical dealer, industry tech rep, seed dealer, county agent, university specialist) and amuse the entire neighborhood.

 Be sure to read the rest of Bob’s article here: http://www.agry.purdue.edu/ext/corn/news/articles.08/crappyrecipe-0422.html

Forever is a long time, I know, but according to this study: Policy Options for Integrated Energy and Agricultural Markets by Wallace E. Tyner and Farzad Taheripour at Purdue University - as long as we have ethanol, the price of corn will rise and fall in direct relation to world crude oil prices. Good, bad, or indifferent, this is the face of reality for today’s ag industry.

With the potential of up to 40% of the U.S. corn crop being devoted to the production of ethanol, the authors point out that agricultural and energy markets will be closely linked.  The theory is that as the price of oil goes up, the ethanol industry becomes more profitable which leads to more ethanol production. When the industry produces more it increases the demand for corn, which in turn drives up the price of the commodity. It’s essentially a chain reaction with the price of oil as the catalyst.

 Tyner and Taheripour calculated the profitability of producing ethanol under different combinations of “corn-crude” prices. They illustrate this relationship with the following chart:

As we can see, profitability is calculated with and without the 51 cent blenders subsidy. According to the authors, the addition of the blenders subsidy “adds about $1.60/bu. to the break-even price”. An additional $1.60/bu. is a substantial amount and given today’s market conditions of high oil prices and high grain prices, I look for the 51 cent subsidy to become an increasingly contentious issue. Whether or not we’ll lose the subsidy is open for debate, but as the price of food continues to increase, the voices against the ethanol industry will become louder and the blenders credit will be squarely in their crosshairs.

Beyond the subsidy, the chart gives a clear indication of how high the price of corn could go. It also explains why the price of corn is hovering around the $6.00 mark. The price of crude closed slightly above $116 per barrel in Friday’s trade and looks to be on it’s way to $120 per barrel or higher. If the above chart is correct (so far it’s spot-on accurate), corn prices will move even higher.

At the other end of the spectrum is falling crude oil prices. Under this scenario it’s not hard to envision what the consequences will be. With corn at $6.00/bu. a substantial drop in the price of crude will quickly make the ethanol industry unprofitable, resulting in a lowering of production. Tyner and Taheripour explain the net effect:

…corn price would have to fall because many of the plants would cease production with lower oil prices and high corn prices. That reduced demand for corn for ethanol would, in turn, lead to a drop in corn prices.

 The connection with the price of crude oil is unmistakable. For the time being corn and crude are inextricably linked, which is a big change for our industry. Tyner and Taheripour sum it up nicely when they say:

So clearly, we are in a new era – one with a tight long-term connection between crude oil and corn prices. Since this tight linkage will exist between crude oil and corn, we can expect it to exist between crude oil and other agricultural commodities as well.

In the paper, Tyner and Taheripour explore the relationship between corn and crude under differing scenario’s via a computer model. One of the scenario’s they simulate is the elimination of the blender subsidy and in it’s place, a new subsidy tied directly to the price of crude. They use a trigger point of $70.00 per barrel, with ethanol subsidies kicking in if oil falls below that price. Right or wrong, it makes for an interesting policy discussion and may be something that needs to be considered in the future. For further details, be sure to read their paper.