In order to achieve the perfection a careful ingredients selection is
crucial. One of the most important ingredients is tomato. True pizza
Margherita (and also pizza Napoletana) use San Marzano tomatoes.
Wikipedia says, that San Marzano tomatoes originate from the small town
of San Marzano sul Sarno, near Naples, Italy, and were first grown in
volcanic soil in the shadow of Mount Vesuvius. One story goes that the
first seed of this tomato came to Italian province of Campania in 1770,
as a gift from the Viceroyalty of Peru to the Kingdom of Naples, and
that it was planted in the area of San Marzano. It is considered the
most important tomato variety of 20th century.
Unfortunately San Marzano - as well as other varieties of tomatoes - is one of the favorite host plants for Cotton bollworm (Helicoverpa armigera).
This pest is not really picky and its caterpillars can feed on
different host plants which makes it one of the most economically
important pest worldwide with estimated damage of around $5 billion
annually. To make things even more complicated, it is a great traveler
and can travel several hundreds of kilometers using high altitude winds.
Monitoring and acting against this pest is thus quite a challenge.
Here is where a network of automated pest monitoring traps comes into
play. Knowing what is happening with pest population in real time is
crucial. Knowing what will happen in next few days completely changes
decision making progress. This is not about collecting only weather data
and using that data in more or less adopted biological models. It is
about automatically collecting pest data with relevant weather data and
using artificial intelligence to forecast pest development way more
accurate and location specific than what has been possible so far. In
order to achieve that, high quality and high resolution data is needed.
That's why at Trapview
we are setting up networks of fully automated traps that include high
efficiency catching (funnel trap) combined with
self-cleaning mechanism to minimize maintenance needs. That's why the
lures are standardized to have reliable and comparable catches. And
that's why every device collects also relevant weather data.
Of course all above is combined with proved Trapview platform, where
the "magic" of intelligent processing of all this data is done. While
"Magic" of artificial intelligence is often just a combination of
buzzword and wishful thinking, in Trapview can be very concrete - like
identifying targeted pest from the pictures with better accuracy than
human.
There is so much knowledge hidden in the data. Utilizing machine
learning helps us unlock this knowledge and deliver a simple, yet so
powerful outcome - accurately telling you what will happen in the next
few days.
Matej Štefančič
