Upstream Ag Professional - June 8th 2025

Essential news and analysis for agribusiness leaders.

Welcome to the 96th Edition of Upstream Ag Professional!

Index:

  1. Q1 2025 Ag Equipment Manufacturer Results: Themes, Highlights and Analysis

  2. Precision ≠ Less: Rethinking AgTech’s Impact on Input Demand

  3. 10 Insights for Agribusiness Professionals from Mary Meeker and Bond Capital’s AI Report

  4. Resistance Mechanisms to Machine Vision and Optical Precision Spraying

  5. Wallet Launches in Bushel Farm

  6. The Butt Fumble Effect: Why A Lack of Certainty Is Killing Brands in Agriculture

  7. Public Company News

  8. How Spotify Thinks

  9. Other Interesting Ag Content (9 this week)

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This week’s audio edition can be found here and covers the following:

  1. Q1 2025 results and macro themes across ag equipment manufacturers (3:30)

  2. The intersection of machine vision tools and weed resistance mechanisms (8:30)

  3. Ergodicity and why survival, not optimization, explains how farmers and agronomists make decisions (15:20)

Index

  1. Financial Snapshot

  2. Key Takeaways by Company

  3. Themes

    i. Hitting the Bottom of the Cycle?

    ii. Inventory and Production Coming Down

    iii. Precision Ag Insights by Company

    iv. Brazil Bright Spot

    v. Tariffs

  4. Company Overviews

Key Takeaways by Manufacturer

John Deere Key Takeaways

  • Production & Precision Ag sales fell 21% YoY to $5.2B; operating margin declined from 25.1% to 22% due to lower large equipment turnover.

  • Precision ag recurring revenue model is scaling: 10,000+ orders for “Precision Essentials” in H1— exceeding all of FY2024. Renewal rate target set at 70% for first-year subscriptions with ~66% of eligible customers being renewed so far, with more expected.

  • See & Spray demand accelerating: Over 1,000 new orders in 2025 (vs. a few hundred in 2024).

  • Engaged acres on Deere’s digital platform rose 15% YoY to 475M+, with “highly engaged” acres up 25%, now ~30% of total.

CNH Industrial Key Takeaways

  • Agriculture segment net sales fell 23% to $2.58 billion, with adjusted EBIT down 64% to $139 million and margins halving to 5.4%

  • North America tractor sales fell 24% for larger tractors; combine sales dropped a sharp 51%. In contrast for South America, tractor and combine demand grew by 10% and 1% respectively.

  • Q1 2025 production hours for ag were down 43%. Large ag was down 36% versus 2024 and 50% versus 2023.

  • Inventory is $1 billion lower since Q1 2024, with the largest CNH dealer (Titan Machinery) having its inventory down drastically over the last two quarters.

AGCO Key Takeaways

  • Revenues down 30% in the quarter with net sales of $2.1 billion

  • Operating margins were 2.4% for the quarter.

  • Operating income was down over 80%

  • North America had a decline of 34%.

  • Machine production was down 33%, with expectations for the remainder of 2025 to be down between 15% and 20%.

  • PTx Trimble sales are down similar to equipment, but was profitable in the quarter and the AGCO executive team remains optimistic about the future of the segment.

Key Takeaways

  • Precision agriculture does not inherently reduce input usage— it can increase it by uncovering latent demand, reducing uncertainty, and enabling more confident application.

  • Data and decision support tools are complements to inputs. Better information typically drives more targeted and higher total use.

  • The bigger threat to input providers is not reduced volume, but commoditization and profit pool shrinkage— especially when control over key complements like equipment, data, or decision workflows shifts outside their ecosystem.

I recently read AgTech: Are We Still Building for Reaction or Precision? by Mikayla Mooney. It raises an important consideration: are agtech builders solving today’s fire or designing tomorrow’s system? While the article highlights the value of proactive, precision-driven solutions, I think there’s nuance in how precision actually plays out in agronomy, particularly when it comes to input usage, and the risks of product commoditization.

Proactive vs. Reactive

Moving from reactive to proactive is a useful framework for much of crop production. However, it is incomplete as it pertains to agronomy and input usage.

In the article Mikayla Mooney highlights that reactive solutions address problems after they appear offering quicker ROI, clear value, and easier adoption since they meet more burning needs. Proactive solutions on the other hand aim to prevent issues before they arise. They require foresight, education, and behavior change (and systems change), making them harder to implement but often more sustainable and impactful over time.

The suggestion in the article is that Precision = Proactive and Proactive = Less product volumes and treatment intensity. Precision leading to lower volumes is widely accepted in agriculture. But, there is nuance in agronomy and crop inputs.

In practice, “precision” often enables more reactive tactics, not fewer. And even where it supports proactive decision-making, it tends to increase usage intensity, not reduce it.

Consider See & Spray for weed management or fungicides.

The idea of See & Spray is inherently reactive, responding to already emerged weeds that are using nutrients and moisture. Proactive is a broadcast application of residual herbicide, killing the weeds much earlier. Not to mention, being really efficient at reaction can generate more demand, like we see in Jevons Paradox.

Where as fungicides are applied proactively, and because of that they are generally applied in broadcast fashion (not precise). Reacting to visual disease symptoms typically delivers poor results.

Mooney goes on to say:

The traditional ag value chain is built on volume, uniformity, and scale: sell more seed, more fertilizer, more feed, more treatments. Reactive solutions fuel that model.

Proactive solutions challenge it.

- They optimize instead of maximize

- Reduce treatment frequency

- Shrink product volumes

- Shift value from chemical to information

For incumbents, this is existential. Business models built on over-application now face structural headwinds in a world that rewards efficiency.

My estimate is actually that precision technology will increase the volume and treatment intensity of most inputs. However, less inputs will be wasted (applied where they deliver a low return and/or cause harm).

There are two main reasons for my belief:

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