We now have more tools than ever to develop sustainable IPM systems that are only going to get better with time.
Will new ag tech enable farmers to farm sustainably and concurrently reduce their agrochemical dependence? That’s what investors are hoping for in their new startup portfolios and what regulatory agencies are targeting to meet their aggressive Integrated Pest Management (IPM)/pesticide reduction goals.
However, farmers are left wondering if and how these technologies can be integrated into their agronomic practices in a cost-effective manner — or if new chemicals are being substituted for those lost to resistance or other reasons.
This leads to an even more impactful question: why are we still losing relatively recent and highly effective pest management products to resistance, considering that pesticide resistance was first identified as a problem with lime sulfur in 1914, then to a much greater extent with DDT in the 1940s?
The answer could be that although we have engaged in eight decades of IPM rhetoric, we have not diligently practiced its principles: identifying pests, beneficial organisms, and hosts; monitoring; establishing action thresholds/economic injury levels; and utilizing good farming practices.
Perhaps monitoring efforts have been too costly or labor intensive. It could be due to neglecting the process of cleaning up the overwintering harborage for next year’s pests. Maybe we didn’t develop relevant economic injury and treatment models.
We may not be really reducing chemical dependence after all, but IPM remains part of the solution
Regardless of the reason, we have abandoned many of the basic tenets of IPM simply because it’s easier and cheaper to use pesticides which typically don’t require integrating anything to manage your pests. But farmers are now being told that they need to implement IPM and utilize new chemistries or products — which are more complicated, costly, require more precision in time of treatment, and may only be active during certain developmental stages of the pest. We may not be really reducing chemical dependence after all, but IPM remains part of the solution.
The good news is we now have more tools than ever to develop sustainable IPM systems. Autonomous in-field sensors can monitor pests in real-time, eliminating labor and inaccurate data. Pest and crop information can be supplemented through additional in-field sensors as well as satellite, drone, market, and weather data. With the help of artificial intelligence (AI) and machine learning, field data can now be further analyzed to produce models with outcomes based on economic gain/loss when using various products.
For example, consider a farmer who is alerted that the first generation of a major pest has been detected by in-field sensors; in subsequent days, a population model could accurately predict timing for mating, egg and larvae development, and next generations. With this predictive information, the use of pheromone disruption, ovicides, insect growth regulators, feeding deterrents, RNAi, sterile insects, or natural enemies can be timed more precisely — or not at all if the market outlook is poor.
Since IPM models are by definition, dynamic, they are only going to get better with time
The power of AI and machine learning is that they — when coupled together — can be used to analyze massive amounts of data to accurately describe the current situation, predict, and provide solutions based on the economic return to the farmer. Once the model is established, it continues to learn with new data and since IPM models are by definition, dynamic, they are only going to get better with time. We aren’t there yet, but it’s not that far away.
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