You see an olive tree and think “ugh, another olive tree.” And that’s normal: there are 282,696,000 olive trees in Spain. How can we not underestimate them? How can we not get bored of them? What happens is that, behind each of these olive trees, there is a very complex physiological machinery that produces a curious agronomic phenomenon: that olive trees remember.
What do the olive trees remember? We already knew that, as Diego Barranco, professor at the University of Córdoba in the Department of Agronomy of the School of Agricultural Engineers, explained to us, “the olive tree produces olives based on how much it has grown the previous year (…) If, let’s say, in 2023 it doesn’t grow much because it hasn’t had water, in 2024 it won’t produce much more because it doesn’t have growth to sustain that production, even if it has water.”
But their memory goes further. Olive trees have the ability to “remember the environmental conditions and climatic events to which they have been exposed throughout their lives” and adjust their “growth, health and productivity of the specimens over time.”
An “insurance” in our favor. That is the key that has allowed them to resist for centuries to all kinds of adverse conditions from “prolonged droughts to sudden changes in temperature” and it is also what continues to allow them to regulate “the production of olives based on their previous trajectory” and to cushion bad harvests (when these are punctual).
What if we’re not getting the most out of that memory? This is what a group of researchers from the University of Jaén and the Olive and Oil Technology Centre asked themselves three years ago. The idea is simple: if all this information has been available since the end of the previous year’s campaign, couldn’t they make a reliable forecast of how the next campaign will go, which would help us to manage the oil better?
The work consisted of reviewing all existing agronomic prediction systems and procedures, searching for influential variables at the municipal level and designing a model adjusted for the provinces of Jaen, Córdoba and Granada. The result is Predic I, which has just been presented.
Why do we want to have an early prediction? Predict I does more, of course: “it allows you to query historical farm production and analyse the dynamic behaviour of the crop over time.” However, early prediction is an essential part of ending the uncertainty that, as we have seen in recent years, is inherent to the world of olive oil.
It won’t eliminate it entirely. That’s true. Every campaign is critically dependent on temperatures and rainfall. That’s something the model can’t predict. However, it does give us a basis to work on: an estimate that will allow us to manage reserves much more effectively.
What can we expect? The big problem in the oil world today is what will happen to oil reserves: with the suspicion that prices will fall too much, the sector has incentives to sell now. However, as reserves are low, those who hold out can make a lot of money in the final sprint. With better forecasting systems, uncertainty would be less and Price regulation would be easier.
Image | Miguel Angel Masegosa Martinez
At WorldOfSoftware | The sky-high prices of olive oil are just a symptom. The real problem is a sector on the road to disaster