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Mycotoxins, which are poisonous byproducts of naturally occurring mold fungi commonly growing on grain, are the single greatest natural contaminant threat in our food supply.
Perhaps the single best-known mycotoxins would be aflatoxin, which was first discovered in the UK following the death of more than 100,000 young turkeys on poultry farms in England. Animal fatalities, however, are only the tip of the iceberg for the agriculture industry. What we much more commonly see is that there’s an effect on the general health and productivity of the animal.
And, while mycotoxins are a major threat to farm animals, they also pose a risk for humans when they’re carried over into animal products that humans consume, such as milk or eggs.
Weather, which creates a great deal of uncertainty in the agricultural industry from year to year, is the single most important factor that affects the type and level of mycotoxins that may be present in each year’s harvest.
BIOMIN has developed a tool to monitor and predict the risk of mycotoxins in corn and wheat based on weather. Our tool is designed to reduce the amount of guessing needed by the agriculture industry.
Predicting mycotoxin risk
BIOMIN, an animal nutrition company that develops and produces feed additives for mycotoxin risk management, uses data from The Weather Company, an IBM Business, delivered through the Watson Decision Platform for agriculture on the IBM Cloud, to look at how weather affects mycotoxin risk. In conjunction, our company technicians also evaluate the global occurrence of mycotoxins in feed using mycotoxin test data dating from 2004 to the present.
The company has a very intricate series of models to predict how weather is affecting different mycotoxin risks in different regions. Some fungi like warm, wet conditions; but, for example, in the case of aflatoxin, the risk can actually increase if the conditions are hot and dry.
The BIOMIN Mycotoxin Prediction Tool starts predicting mycotoxin risk in grain crops from around the time of flowering, which is the first critical period when moisture and temperature affect how a fungus can infect, grow in grain and produce mycotoxins.
Choosing The Weather Company
BIOMIN chose to work with The Weather Company because of the validated weather data that’s generated on a grid fashion worldwide, with a 15-day forecast of hourly information. BIOMIN’s prediction tool downloads hourly weather data for 61,000 points around the world.
It’s not good enough to know whether it’s going to be a wet day or not. BIOMIN wants to know how many hours of wetness there will be, because it makes a big difference for the fungus. Fungi can grow really fast.
BIOMIN uses historical weather data going back to 2013 as well as the current weather forecast to model data worldwide. Altogether, BIOMIN churns through one terabyte of data a day.
The output of the BIOMIN tool is a worldwide “heat map” that provides an advanced estimation of mycotoxin risk.
Using data to warn farmers and help reduce risk
BIOMIN will use its heat map to warn farmers in certain regions that they may need to do more intensive or earlier testing, or plan for an earlier harvest.
For example, if a farmer tests and confirms that the mycotoxin levels look reasonably high, they could actually harvest their crop earlier. They won’t get as high a yield because the crop may not have finished maturing, but they can get a crop that has lower mycotoxin levels. They might accept that the yield of corn is going to be 20 percent less than what it would have been in tons per hectare, but the mycotoxin level is not going to be above a legal limit, over which they might not be able to sell or use the harvest to feed their animals.
Aside from realizing higher crop yields and more productive livestock, farmers are compliant with federal guidelines, if they exist.
BIOMIN benefits by being able to predict and meet high regional demand for its mycotoxin deactivation product.
In the future, BIOMIN intends to use the IBM Global High-Resolution Atmospheric Forecasting System (GRAF). The system will be able to predict something as small as a thunderstorm anywhere on Earth using crowdsourced data from millions of sources. For example, since there’s not a weather station at each specific location where weather data is needed, GRAF uses multiple algorithms combined with cellular data to determine what the atmospheric pressure is in whatever latitude and longitude is requested.
Learn more about how companies are using The Weather Company, an IBM Business, products and services across industries.