Greenhouse Canada

Guest Column: Exploringing the human challenge of IPM

September 5, 2023  By Rita Sterne

If the casual definition of pest is “one that pesters or annoys” (according to, it might be reflective to consider the human role within Integrated Pest Management (IPM) challenges in the greenhouse industry. How might we get in the way of solving IPM struggles?

We understand that IPM is complex and the situations are constantly evolving. When one issue is solved, another appears. When one encounter is eliminated, another erupts. When parameters change, the deck gets shuffled yet again.

From what growers have shared and what I’ve learned from technology experts, IPM is a delicate cycle of understanding and assessing signals and signs, generating and weighing options, making decisions, and then predicting and monitoring the effects of the decision in a new context (which may have changed during the last decision cycle). Kudos to growers – this is complexity at its most difficult!


Artificial intelligence (AI) and robotics are technologies that are increasingly supporting growers. Relying on knowledge from science and experience, these technologies will also be increasingly able to support decision making by helping to generate potential responses for growers. Enter our human shortcomings when making decisions.

Human brains are not great at effectively processing more than five to seven different things at once. Our brains have developed shortcuts for making decisions and we trust these shortcuts because they’ve worked well for us in the past.  

Consider that today’s grower faces an incredibly complex situation characterized by constant change. They also face massive risks from making the wrong decision. A dynamic environment means our brain’s shortcuts are not always reliable, particularly when we are experiencing novel disruptions (for example, weather patterns) that further complicate IPM issues. 

Along with the research of incredibly brilliant researchers working on the biology of IPM, AI and robotics, technologies are now partners in solving IPM challenges and labour shortages. AI and robotics are increasingly supporting larger growers with data sets that “learn” and can integrate data from additional parameters. AI and adaptive learning help humans effectively and efficiently manage far more than five to seven parameters at a time. And increasingly, growers leveraging the power of massive data sets are starting to build confidence in IPM decisions — even in an ever-changing context. 

IPM strategies and decisions in the future will also require that humans build and expand new relationships and forge networks to support the increasing complexity around decision making in the industry. As a wider variety of crops are grown indoors, these difficulties again multiply. AI and adaptive technology are necessary tools if our brains are to successfully manage future IPM struggles.  

What could the IPM future look like?  

  • Robot bees are already pollinating crops. Could we see “micro robot beneficial insects” in our greenhouses?  
  • Scientists are learning more about the power of “smell” and scent markers. Will robots of the future smell pests and disease instead of seeing them?  
  • Learning about biomimicry and copying nature’s solutions to a challenge also holds promise.  Will AI help researchers to borrow a solution from nature and then more quickly develop and implement it for growers? 
  • Work to support digitization in the Netherlands is leading the way with a shared greenhouse language and standards for data exchange. Will AI technologies support better relationships with value chain partners to more quickly help industry react to IPM threats in future?

New technologies are providing solutions across a multitude of IPM issues. Reminding ourselves to invest heavily in value chain relationships and industry networks could be a great strategy to ensure that we address the human factor of IPM.   

Rita Sterne, PhD (Mgmt), is the manager of the Greenhouse Technology Network (GTN). The Greenhouse Technology Network, a Niagara-College-led consortium of research institutions, can help bring together greenhouse and technology businesses with research institutions to advance development and adoption of new technologies. 

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