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Data science in agriculture helping predict pest and disease migration

Forecasting Plant Disease and Insect Migration

How do you predict the future? This question sits at the heart of predictive analytics. In modern agriculture, advanced algorithms are being used to decode the patterns and behavior of mother nature. Forecasting the invasion of pests, spotting the spread of microscopic disease—even helping farmers adapt to climate change. With the progression of predictive algorithms, analytics, and other emerging technologies, modern agriculture is pursuing ways to, in a sense, predict the future and see the invisible.

Big Data Pest Patrol

More and more, advanced analytics in agriculture are informing how farmers manage pests. As one aspect of a larger movement known as integrated pest management, data analysis and digital tools in agriculture are being deployed to more precisely and scientifically deal with harmful insects. A recent evolution of this practice is using various sets of data to predict the migration of invasive pests.

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Some insects can be incredibly beneficial to farmers, while others play an innocuous role. But a select group of harmful insects earn the title of “pest”.

Creatures of the Night

Some insects, like corn earworm moths, migrate only at night. Considering insects are generally small and excel at blending in with their surroundings, spotting them as they invade a field is exceedingly difficult. To overcome this challenge, modern agriculture is exploring how the behavior of pests are connected to weather patterns. The intent of this emerging technology is to forecast insect migration. 

Predicting Insect Invasion

Seed companies, universities, and government agencies are developing sophisticated systems for tracking harmful pests. For example, the National Weather Service is using a network of radars to observe the speed and migration of corn earworm moths.1 In the past, this technology monitored birds and bats. Today, it creates an early warning system for farmers. If wind, atmospheric pressure, and other factors forecast a “high risk” zone in their area, a system like this can send email alerts to farmers— sometimes days in advance. The more accurately modern agriculture can use data to track pest migration, the more precisely farmers can deploy methods of crop protection. Advances like this can empower farmers to use less insecticide, more effectively.

Climate change is making the behavior of insect populations more unpredictable.  

Calculating Climate Change

Traditionally, farmers have a several-week window of time to expect harmful insects to arrive on their land. With warming temperatures due to climate change, the ETAs of these insects have shifted. Pests are showing up earlier, staying longer, and reaching plants at a more vulnerable stage of growth.2, 5

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Calculating Climate Change

Traditionally, farmers have a several-week window of time to expect harmful insects to arrive on their land. With warming temperatures due to climate change, the ETAs of these insects have shifted. Pests are showing up earlier, staying longer, and reaching plants at a more vulnerable stage of growth.2, 5

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Having more real-time and accurate models help farmers adapt to changing conditions. Powered by in-field sensors, radar, weather forecasts, and scouting reports, modern agriculture is developing methods that can more precisely predict when certain insects will begin their invasion.4

Along with insects, there is another unseen threat to plant health.

The Movement of Disease

Plant disease is a silent destroyer. Farmers can only see the symptoms of plant disease, not the pathogen itself. This poses a challenging question, “How do you see the invisible?” Advances in optical sensors may help modern agriculture shed light on these unseen threats.6

Taking the Temperature of Plants

Thermographic imaging, similar to technology used in night vision goggles, can monitor the surface temperature of certain crops.3 When the leaves reach a certain threshold, one can safely assume the plant is in a state of stress and needing attention.

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Taking the Temperature of Plants

Thermographic imaging, similar to technology used in night vision goggles, can monitor the surface temperature of certain crops.3 When the leaves reach a certain threshold, one can safely assume the plant is in a state of stress and needing attention.

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By using highly sensitive remote sensors or images taken by satellites, these digital tools can spot trouble well before the traditional signs of wilting, browning, or discoloration. With these earlier alerts, farmers can know exactly which plants are healthy and which are compromised.7

Understanding The Nature Of Mother Nature 

Mother Nature is immensely complex. In every ecosystem, there is a diverse set of variables, any one of which can profoundly impact the rest of the habitat. So when it comes to predicting what will happen next in nature, modern agriculture must rely on more than instinct to understand our planet.

Using data science, predictive analytics, machine learning, and other emerging technology, the leaders of modern agriculture are building a deeper, more comprehensive understanding of the habits and patterns of our ecosystem. Through learning more, modern agriculture can continue to use natural resources more efficiently and sustainably.

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