PIB Spotlight- The Bryan Johnsonification of Agriculture

Every year Bryan Johnson spends $2 million on monitoring all possible biomarkers in his body, adjusting his protocol in real-time based on continuous data streams. His "Don't Die" protocol starts with a fundamental principle: Step 1 is to identify the source of death—biological aging and the cellular processes that lead to mortality. Essentially, the premise is that only by constantly measuring and detecting risks can you intervene before it's too late.

Agriculture is having its Bryan Johnson moment.

As our new climate reality accelerates pest outbreaks, invasive species expansions, and biological risks across farmland, growers are abandoning scheduled spraying and calendar-based treatments and are now beginning to adopt hyper-precise, data driven monitoring approaches that would make the Blueprint founder proud.

This article focuses primarily on the diagnostic (Dx) technologies that detect, identify, and monitor PIB risks, the foundation that enables targeted remediation (Rx) technologies to follow. Just as Johnson's Don't Die protocol would be meaningless without constant biomonitoring to identify which interventions to deploy when, agricultural precision requires sophisticated diagnostic infrastructure before any control strategy can succeed. You can't treat what you can't detect, and you can't deploy precision interventions without precision intelligence about where and when threats are emerging.

We’re moving away from traditional Agtech narratives about biotechnology, decarbonisation and yield optimisation towards adaptation as this is now a story of a survival.

When the Economics of Risk Detection Break Down

For decades, integrated pest management relied on well-established Economic Injury Levels (EIL)—the pest density where damage costs equal control costs—and Economic Thresholds (ET)—the point where you intervene to prevent reaching the EIL. These thresholds were calibrated over decades of predictable pest behaviour.

Our new climate reality is already shattering these calculations. The Fall Armyworm now completes multiple generations per year instead of one, meaning populations spike from below threshold to economically damaging levels in days rather than weeks. Palmer Amaranth can go from undetectable to yield-limiting in warm conditions within days. Traditional thresholds assumed you had weeks to scout and respond and now you have hours.

In specialty crops, spotted Wing Drosophila can destroy entire berry harvests within 48 hours of reaching economic threshold, while Brown Marmorated Stink Bug causes $37 million annually in soybean losses, often spiking unpredictably due to variable winter survival. The economic models underlying decades of IPM strategy are fundamentally broken.

Bringing it back to our earlier analogy, it’s like if Johnson's biomarkers for cardiac stress kept changing, and the time between "elevated risk" and "heart attack" kept shrinking. The old monitoring schedule becomes dangerously inadequate, but crucially given his constant diagnostics and testing he would know exactly when the problem started and where it was.

Diagnostics: Identifying the Source of Crop Death

Just as Johnson's Don't Die protocol begins with identifying biological threats before they become fatal, agriculture's profitability, and indeed survival, now depends on the quick and efficient detection, identification and monitoring of PIB threats before they reach economic injury levels at record speeds in our new climate reality.
 
Traditional methods are falling behind. Sticky trap monitoring requires weekly manual checking by scouts walking fields, it is labor-intensive, delayed, and often missing critical early detection windows. It simply doesn’t cut it with elevated PIB risk and new solutions are needed.

Row Crops: Automated pheromone traps now track corn rootworm emergence patterns across thousands of acres, while satellite imagery analysis identifies early-stage Palmer amaranth infestations. According to Precision Farming Dealer insights, these systems reduce scouting labor by 80% while catching infestations weeks earlier than manual sticky trap checking.

Specialty Crops: Smart traps with AI provide 24/7 monitoring of threats like spotted wing drosophila in berries or codling moth in apple orchards, replacing the need for daily manual trap inspection. Hyperspectral imaging can detect citrus greening disease (HLB) through subtle changes in leaf reflectance before visual symptoms appear.

Lab Services for Agriculture: Environmental DNA testing now allows detection of invasive species from soil or water samples weeks before visual confirmation and absolutely critical for threats like giant salvinia in rice systems or nematode populations in vegetable production. Farmers can mail soil samples and receive species-specific detection results within 48 hours.

PCR-based diagnostics can identify specific Wheat Rust races or bacterial spot strains from leaf samples within hours, transforming pathogen detection from guesswork into precise science, while RNA biomarker analysis can detect plant stress responses to pest feeding or pathogen infection days before visible symptoms appear.

The Investment Case

The Adapt findings estimate PIB risk spending will surge 90% from $103 billion in 2025 to $194 billion by 2030, with investment flowing heavily toward diagnostic and precision technologies that enable targeted interventions rather than broad-spectrum applications.

This shift represents validation of the diagnostic-first approach. The EU's innovation framework, as reported by The Parliament Magazine, recognises that early-detection sensors can substantially reduce both chemical use and crop losses, but only when monitoring infrastructure provides actionable intelligence about WHERE threats are concentrating.

The diagnostic revolution is driving the spending surge because it enables everything else, you can't deploy precision interventions without precision intelligence about threat location and timing.

For VCs tracking climate adaptation, this represents a massive market inflection point. According to PitchBook's AgTech report for Q2 2025, precision agriculture overtook agricultural biotech in funding for the first time since 2017, capturing $580.2M versus biotech's $270.6M, a stunning reversal of recent trends that signals where smart money sees the future.

This shift reflects investor recognition that monitoring and precision technologies are the foundation enabling everything else. Companies like RootWave ($15M for precision weed control), DroneDeploy ($15.2M Series E for crop monitoring) and on the earlier side, TRIC Robotics ($5.5million Seed for UV pests and pathogens) represent surgical, data-driven approaches that agricultural operators now demand but that only function with identification and detection innovations behind them.

Yet, it is the growers who benefit most from this technology-driven approach. Early adopters of precision monitoring and targeted intervention report yield gains of 25–40%, labor cost reductions of 20–40%, and post-harvest loss decreases of up to 60%, underscoring that extreme precision isn't just a tech upgrade—it's a survival strategy.

Notably, 54% of Agtech deals are now late-stage compared to just one-third in 2020, suggesting the precision agriculture thesis has moved beyond speculation into proven commercial demand. It is part of a wider trend seen within Climatetech that investors are shying away from investing purely in green premiums paid for decarbonisation and are falling back on basic principles. If your solution is better, faster and cheaper than what currently exists, then we’ll take a look, and Dx tools for PIB risk certainly fall under this bucket

The New Reality

Agricultural precision protocols signal recognition that traditional farming methods are inadequate for emerging threats. Like Johnson's extreme monitoring reflects his systematic approach to identifying and preventing biological aging, agricultural precision reflects necessity driven by accelerating climate impacts.

The farmers adopting these protocols face existential threats where traditional economic thresholds no longer apply: organophosphate-resistant corn rootworm, bacterial spot appearing in previously safe regions, invasive species establishing faster than historical models predicted. They're following agriculture's version of the Don't Die protocol, first detect and identify the source of crop death, then monitor continuously to prevent it.

For smart money looking to move into the space, this offers a trifecta of compelling dynamics: massive market opportunity, technological differentiation, and genuine necessity. The companies building diagnostic solutions aren't optimising agriculture, in fact it’s possible to argue it’s not a traditional Agtech solution at all, rather an adaptation one.

They're creating the intelligence infrastructure that makes crop survival possible when fundamental assumptions about PIB behaviour have collapsed.

We're living through the Bryan Johnsonification of agriculture, where the focus has shifted to survival. Agricultural PIB threats accelerate faster than traditional responses can evolve, and precision detection, identification and continued monitoring will become the foundation for everything else.

It’s not a question about whether agriculture will adopt these protocols it's how quickly, and which companies will build the diagnostic tools that make targeted survival possible.

Coming next: Rx, Biocontrols vs. biofertilisers—why precision biological technologies will win the investment race in our survival-focused agricultural reality.