(Sajjan Grover between Sugarcane aphids on sorghum plants)
Insect monitoring has immense value in various industries, and agriculture is one of the leading sectors. As concerns grow regarding reports of declining insect abundance and diversity worldwide, understanding the dynamics of whole agroecosystem health has never been more important. Traditional monitoring and research focused primarily on direct impacts to target pests, yet whole communities interact in complex ways not fully understood. Promising new techniques are emerging that could gain valuable ecological insights if integrated with traditional methods. In this interview, Sajjan Grover, Ph.D., Senior Scientist in the Entomology Pipeline Testing Platform at Bayer Crop Science in Chesterfield, Missouri, discusses the benefits and limitations of various monitoring approaches, as well as opportunities for innovations through collaborative projects analyzing a wider range of factors. Combining strengths across fields promises to reveal hidden dynamics shaping agricultural landscapes in new ways, supporting more proactive, sustainable management over the long term.
Here are our five key takeaways:
Controlled experiments introduce biases versus complex field conditions with many variable factors.
Long-term monitoring is needed to track unintended ecosystem impacts emerging over decades.
Better initial monitoring of agricultural products could help predict emerging pest population changes earlier.
Existing ways of working in agricultural industries overlook collecting valuable climate and plant health data that could provide insights.
Technologies like volatile profiling show promise if databases are expanded through collaboration.
Sam: Thank you for speaking with us. To start, can you provide context on traditional monitoring methods?
Sajjan: From product development point of view, entomology research/efficacy testing is mainly divide into two categories, one what we do under controlled environment and another what we do under field. Controlled environments, like growth chambers, allow for careful tracking of insect numbers and behaviors over time. However, field experiments present numerous challenges.
For example, in one of my projects during my Ph.D., we artificially infested plants with insect egg masses in the field. After 10 days, we aimed to analyze treatment outcomes but were unable to recover all the insects we had introduced. There are simply too many undefined variables in open field conditions, from biotic factors like natural enemies to abiotic variables like weather. Even reproduction of experiments can yield inconsistent results.
This source of unknown variability introduces bias that is difficult to account for. Whatever we put, we don't recover everything. Either they die. First, those insects are not used to environment. Second, there could be some natural enemies, but I cannot see with the naked eye, but they might be already on the plant. Sometimes it leads to so many questions. Like is there any cannibalism between them? Are they eating each other or they are just not liking the food, whatever we are providing to them? So that is one of the bias that comes in our experiments. So we just have to assume that. This is always an unknown factor that brings up bias in the experiments in the outcomes.
Whether in academic, industrial or government research, incomplete recovery of test organisms means we must make assumptions that may not reflect real-world insect population dynamics or plant-insect interactions. Addressing these complex, multifaceted influences remains an ongoing challenge across all entomological studies.
Sam: How does this translate to the agriculture industry?
Sajjan: Industry's main goals involve developing effective strategies for insect control, whether genetically engineered crops or chemical pesticides. A major challenge is that lab results don't always translate reliably to field conditions. For example, a transgenic crop may reduce pests by 50% in labs but show lower or inconsistent efficacy across different farm sites.
Understanding performance variability is important for product value. A trait controlling pests in most regions could be worth $100 million versus one only 50% effective in half the areas. Developing tailored solutions acknowledging regional diversity could benefit both farmers and companies through more consistent, sustainable pest management. Continued research aiming to resolve current unknowns holds promise for innovating even more effective solutions over time. Digital monitoring techniques could help reveal currently unknown factors like alternate food sources or natural enemies influencing pest dynamics with crops in situ.
This variability leaves questions around why efficacy differs in real agricultural ecosystems. Potential factors like alternative food sources or natural enemies interacting with plant-insect dynamics could influence outcomes. With better monitoring of field conditions using digital tools, we could gain valuable insights into such discrepancies.
Gaining more location-specific insights into what does or doesn't work would benefit farmers through customized recommendations. For companies, it could improve product value by increasing control consistency. Our research aims to address these knowledge gaps to facilitate sustainable, large-scale solutions supporting both agriculture and business interests.
Sam: What implications does this have for the greater insect community and industry?
Sajjan: Let's look back at the first GMOs (Bt) introduced around 20-30 years ago. At that time, caterpillar populations were high, so these crops helped reduce chemical spraying. This brought environmental benefits by lowering insecticide usage. However, over the following decade, scientists found that with less pressure from these target pests, the agricultural environment had more opportunities for new pest insects to increase.
For example, populations of whiteflies, aphids, stink bugs, and other sap-feeding insects grew, even though they hadn't been major pests previously. These plant-insect community dynamics can shift substantially over time. By the time implications emerge, a decade or more has often passed. These ecosystem shifts aren't evident within a few field seasons of developing the new technology.
If robust monitoring systems had tracked changes from the start, including patterns in insect and environmental factors, early warning signs may have been detected. For instance, increases in certain insect species in particular areas could have been predicted before major problems arose. This would allow for quicker responses rather than reacting to billion-dollar issues down the line.
Sam: When conducting research in controlled environments, is there a risk of results not accurately representing insect behaviors and populations in real world conditions? What value is there in testing both controlled and passive field monitoring approaches?
Sajjan: There is certainly a risk of controlled experiments introducing biases if insect responses differ greatly from natural environmental conditions. Monitoring can help identify sources of variability. For example, if insects placed on plants in chambers don't feed as expected, monitoring could reveal if the plant impacts insect feeding or if starvation is occurring due to the controlled setting, or cannabalism. This would provide valuable insights into factors like plant resistance traits or insect aggression levels.
Combining controlled tests with passive field monitoring allows direct comparison between results. Any discrepancies identified through monitoring real populations could then be addressed in future controlled work. This has significant benefits for industries investing vast resources, helping to reduce risks and inconsistencies when commercializing new products. Monitoring thus complements controlled research by providing more translatable data to inform practical applications.
Sam: How can monitoring be improved to gain a more realistic understanding?
Sajjan: Ideally, we would monitor environmental cues that reveal what insects were present, such as volatile scent signatures emitted during plant-insect interactions. These scents could provide insights into ecosystem dynamics. Advanced detection methods using techniques like environmental DNA sampling also show promise, but no existing system comprehensively monitors insects, plant health, and local conditions. An integrated, multidisciplinary approach leveraging digital monitoring, chemical analysis, and field research holds the most potential for predictive insights.
Sam: What parameters do industries currently look at in field testing?
Sajjan: Industries currently overlook factors beyond basic insect data like climate, other insects including natural enemies, pathogens etc under field testing. Monitoring additional data points could provide insight into why products have varied efficacy levels in different regions. But they are looking at only at the insect data, like little insect data, how many insects were there and then, like, how many survived. All other factors have to be overlooked because it costs so much money, so much resources finding out them. But if there are ways to do that, I think it’d be great.
Sam: What gaps currently exist in our knowledge of complex insect relationships?
Sajjan: Huge gaps remain in understanding less prevalent or unseen insect species, their roles in ecosystems, and how populations may shift over time in response to human and environmental changes. Symbiotic relationships between insects, plants and microbes are another underexplored area. Filling these gaps could help develop more sustainable long-term agricultural strategies rather than reactive, single-target approaches. Novel sensing technologies may help uncover hidden dynamics shaping whole systems in new ways.
Sam: Have any below-ground monitoring techniques proven viable?
Sajjan: Acoustic sensors/insect traps show potential for below-ground insect monitoring but current techniques are still limited. Further developments are needed to achieve reliable, comprehensive monitoring of the diverse insect communities that interact below ground.
Sam: What necessary technological innovations are emerging in this area?
Sajjan: Detection of volatile organic compound signatures emitted during plant-insect interactions shows promise as a monitoring technique. However, databases classifying signatures of different insect species remain incomplete. Fully realizing the potential of techniques like these will require integrating visible and hidden insect data as well as plant response for a full picture. Continued discussion can explore opportunities for collaborative projects to address gaps. Advanced monitoring tools providing spatially and temporally extensive data have great potential. For example, sensors could track otherwise unseen below-ground interactions. Imaging may observe complete pest food webs over agricultural landscapes long-term.
Sam: How could industry and academia collaboration advance this field?
Sajjan: Both would benefit from open data sharing and multidisciplinary projects combining strengths in digital monitoring, chemical analyses, and field-based research. Industry needs scalable solutions to inform product development timelines measured in decades. Early-warning detection of emerging issues through comprehensive monitoring could help redirect investments and minimize unintended impacts. With continued innovation, real-time ecosystem monitoring may optimize balanced, proactive approaches supporting both productivity and biodiversity.
Sam: What are some fun examples of symbiotic relationships between plants and insects?
Sajjan: One is where certain insects feed on plant sap and excrete honeydew, a sugary substance. Other insects are then attracted to come feed on these sugars. This provides benefits to both the insects tapping into the plant's resources and those consuming the honeydew.
Another potential symbiosis involves pollinators like leafcutting bees. While they damage plants by cutting leaves, this activity also triggers plant defense signals. This response could help reduce pest pressures on the plant by deterring other insects. So pollinators may both aid seed production and offer pest control benefits through induced defenses. More research is still needed to fully understand interactions like how pollinator visits impact subsequent herbivore populations. But there are definitely interesting symbiotic relationships being discovered between plants, pollinators, and pest insects.
Sam: Do any examples involve attracting beneficial insects through plant signaling?
Sajjan: Yes, some studies have shown that when insects feed on plants, it can cause the release of volatile organic compounds that act as signals. In many cases, these airborne signals attract other beneficial insects like predators or parasitoids of the herbivores. The incoming "bodyguards" then help control pest populations, creating an indirect mutualism where the plant benefits from reduced herbivory while both plant and natural enemy insects gain from increased prey/food sources. This is an area with numerous opportunities remaining to be explored through further research.
Sam: How can monitoring plant responses to insect feeding provide insights into insect prevalence and relationships?
Sajjan: When insects feed on plants, it can cause the plants to release volatile organic compounds that communicate information. In many cases, these volatiles attract beneficial insects like natural enemies of the herbivores that prey on and help control pest populations. However, some plants may emit deceptive signals that instead attract more herbivores. Over time, insects have also evolved ways to manipulate these signals. If we had better methods to detect and classify the specific volatiles emitted in response to different insects, it could help reveal what insects were present without directly observing them. This approach holds promise as a more comprehensive monitoring technique of the future, but challenges remain in developing reliable detectors for the thousands of potential plant volatiles and signatures.