Webinar Recap: Microbiome-Driven Precision Agronomy

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2025-10 Boca Raton Presentation.pdf

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Summary (at a glance)

• Scope: Microbiome-Driven Precision Agronomy basics for greens, DNA-based monitoring, algae and disease discussions, and how biological inputs fit with standard programs.

• Why it matters: Knowing how your microbial community shifts with weather, moisture, and management helps you plan ahead, reduce emergency fixes, and maintain consistent surfaces.

• Practical result: Courses are using diagnostics and biological tools to curb surface algae, support recovery through stress, and, when conditions allow, extend some spray and fertility intervals without risking playability.

1) Why Microbiome Agronomy belongs on greens (00:00–00:06)

We opened by explaining that our goal was to use DNA-based, non-invasive testing to see which microbes are present on each green and what they’re likely doing (nutrient cycling or potential pathogen risk).

The point is to time inputs by green, not to follow a fixed calendar. We framed the microbiome across three habitats—leaves, root zone, and inside the plant—and noted that highly managed greens don’t resemble natural grasslands; fungal diversity is typically lower, so our practical aim is stability and function, not “maximum diversity.”

2) Boca Raton case: rapid field response after one application (00:05–00:06)

At the Polo Club of Boca Raton (Celebration bermuda, 18th green), we documented drought-stressed patches pre-application.

Four days after a single application, color and density improved notably—consistent with better root-zone activity and water use—and we used that as a concrete anchor for the rest of the data.

3) What changed in the microbial community (00:07–00:14)

After inoculation, bacterial diversity increased over time, while fungal diversity remained lower, as is typical in intensively managed systems. Root-internal (endophyte) communities looked different from surrounding soil communities and became more similar by Batch 3.

Before application, Xanthomonas was relatively high; later, we saw a strong nitrogen-cycling signal (including ammonia-oxidizing groups). We also verified that Pseudomonas associated with the inoculant increased, and qPCR detected the inoculant species in many plant and rhizosphere samples.

4) Cyanobacteria: spotting bloom conditions early (00:15–00:17)

After drought, rainfall triggered cyanobacteria spikes, especially on shaded greens that stayed wetter. Monitoring showed that risk is shaped by pre-existing species plus shade/tree cover, moisture, and nutrient cycling, so we could shift attention before surface algae became a problem.

In practice, once cyanobacteria were identified as the driver, Jake increased hydrogen-peroxide applications and saw a large drop in surface algae heading into low-light months.

5) Water molds (Pythium, Phytophthora): early warning and placement precision (00:18–00:22)

We highlighted that these are oomycetes (not true fungi), which matters because product choice and placement need to match the organism and where it’s acting (leaf vs. root). With DNA/qPCR screening, we can detect low-abundance signals early and time inputs to biology + weather, rather than only to the calendar.

6) When preventives still fail: what to fix and how to act on the biology (00:22–00:34)

In discussion, we addressed a familiar frustration: breakouts despite preventive programs. The two big failure points are target and placement. If the problem is in leaves but the product/placement is aimed at roots (or the reverse), performance drops; some situations demand watering-in, while others should stay on the surface. Because Pythium is an oomycete, these details matter even more.

Our action step was straightforward: confirm which organism is present and where it’s acting, then match timing and placement to the biology and the weather window. That reduces the mis-targeting and misplacement that often explain “breakthroughs,” and it can prevent unnecessary sprays when pressure is low—site conditions still decide the magnitude.

7) What to take back to your course (00:49–00:50)

Treat each green as its own ecosystem. Use microbial readouts alongside moisture, temperature, and visual cues to determine when and where to act. Read diversity as a signal of function and stability, not as a number to maximize. And for algae and disease, let early detection guide both timing and placement so you’re solving the right problem in the right layer of the plant system.

• Focus on Functional Diversity: Bacterial diversity rose after inoculation in this case; fungal diversity stayed relatively low (typical for managed greens).

• How to Read It: In this talk, more bacterial diversity was presented as a positive signal (ecosystem services, resilience), not as a standalone goal to “maximize at all costs.” The practical goal is stable, functional communities that support nutrient cycling, stress resilience, and consistency.