Using statistics to improve wheat yields πŸŒΎπŸž

You can find wheat in the ingredient list of so many foods eaten day to day: bread πŸ₯–, cake 🍰 , pizza πŸ•, pasta 🍝…(I should know – I am allergic to it! 😭). As with most crops, the average amount of wheat produced (or the yield) per year increased through the second half of the 1900s with the technical advances in agriculture and more intensive land use. Over the last 20 years however, wheat yields have stayed about the same year on year despite our advancements in knowledge of biotechnology (like genetic modifications to make crops resistant to disease) and climate, during this time. This has caused us to question whether we have reached a maximal level of wheat production?πŸ€” Well luckily, we can use maths to test this theory as well as testing possible trade-offs between trying to get a better yield and the potential resultant damage to the environment if we do. 🌾

Extreme Value Theory uses statistical distributions to find (in our case) if there is an upper limit for a wheat yield and if so, what this value is. We can also find out whether other factors such as location or fertilizer use are able to improve this maximum yield by comparing the statistical distributions of each factor level. Knowing this information enables farms πŸ§‘πŸΌβ€πŸŒΎ across the country to find ways of increasing their production to close to this maximum as well as helping with the allocation of fundingπŸ’°to improve yields across the board.

These methods are more commonly used to estimate the probability that an extreme event occurs, such as large-scale flooding 🌊, dramatic temperature spikes πŸ”₯ or even volcanos erupting! πŸŒ‹

This research is being undertaken by Emily Mitchell at the University of Nottingham. πŸ™ŒπŸ»

#appliedmathematicsΒ #usingmathsΒ #mathsinlifeΒ #foodproductionΒ #environmentΒ #wheatΒ #increasingyieldsΒ #sustainabilityΒ #keeplearningΒ #statisticsΒ #distributionsΒ #stemΒ #scicomm

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