Upstream Ag Professional - April 20th 2025

Welcome to the 89th Edition of Upstream Ag Professional

Index:

1. Are Ag Inputs More like Wine or Diamonds? - Guest Article

2. The Theory of Innovation Adoption in Agriculture

3. Farmers’ Favorite Weedkiller Nears Its End, Bayer Warns

4. Cultura Emphasizing Supply Chain Connectivity: A look at Constellation Software and their Approach in Agriculture

   • Private Equity and Ag Software

5. FMC Corporation receives first product registration in Brazil for Sofero™ Fall pheromone

6. Indigo approaches a megaton of carbon removals stored in US cropland

7. What’s next for precision spraying technology in battling weeds?

8. The Rise of Production Capital

9. Other Interesting Ag Articles (9 this week)

The Upstream Ag Professional audio edition this week includes:

1. Cultura Emphasizing Supply Chain Connectivity: A look at Constellation Software and their Approach in Agriculture + Private Equity and Ag Software (1:08 min)

2. Farmers’ Favorite Weedkiller Nears Its End, Bayer Warns (20:00 min)

3. Indigo approaches a megaton of carbon removals stored in US cropland (29:05 min)

You can find the audio library here.

Thanks for being an Upstream Ag Professional member! And Happy Easter to all of those who celebrate!

1. Are Ag Inputs More like Wine or Diamonds? - Upstream Ag Insights Guest Post by Dan Northrup of Galvanize Climate Solutions

This is a guest post written by Dan Northrup of Galvanize Climate Solutions LLC.

Note: Dan included full references for statements made in his article. I have removed them in the e-mail body to manage sizing and deliverability constraints. The full sourcing and list is available in the article at the above link.

Wine and diamonds have major differences in how they are priced and in consumer buying motivations.  For wine, 85% of people buy based on the label, with less consideration of the quality of the bottle’s content.  Diamonds are priced based on the 4 C's – clarity, cut, carats, and color – quantifiable quality attributes.  

Although ag input decisions appear to be diamond like transactions, purchasing is nuanced, and decisions vary by input category (fertilizers, seeds, crop protection).  Price is a primary reason for choosing fertilizers.  Fertilizers are tested for nutrient composition and unbiased public sector testing ensures product quality.  The correlation between crop yield and fertilizers is reasonably well characterized and supports price-based decisions.

For seeds and crop protection performance is reported as a key reason for purchase, and this attribute takes multiple forms: yield response, weed control, pest control, etc.  Unfortunately, the complexity of these responses and the difficulty in making accurate comparisons between products makes it challenging to achieve the same degree of rigor in ROI calculations at the time of purchase.  This is a challenge to an unproven product and is important for product developers because observability of outcomes is one of the key drivers of adoption.

The datasets that are available to farmers at the point of decision making also vary by input category.  Plant breeders benefit from extensive testing networks.  Commercial varieties and hybrids are typically tested for 4 or more years in 100s of locations before they are advanced to the market.  The result of this testing is a small set of geographically targeted products characterized by extensive datasets that support diamond like, ROI based decision making. 

The 3rd major category of agronomic inputs – chemistries, biologics, stimulants – has a more limited infrastructure for generating performance data.  Unlike seeds, these inputs are expected to perform across wider geographic ranges and conditions even though this may not be a valid assumption.  Without datasets to characterize the performance variation farmers and agronomists do not have the information they need to assess a product’s ROI and this can discourage the adoption of new products and product categories.

Variable Outcomes Challenge ROI based Decision Making and Product Pricing

The challenge of observing returns on a new product is caused by the significant variability in performance which is driven by many interacting parameters (genetics, environment, management).  Prediction accuracy requires observation, and the number of samples needed to achieve a given degree of statistical certainty increases with the variation.  Thus, highly variable outcomes – particularly yield and ROI - require large amounts information to gain statistical confidence of the potential outcomes. 

In addition to the cost, another unfortunate consequence of a high degree of variability is that assessing ROI requires time.  While it is important to prioritize performance-based purchasing and advantageous to price products based on the full value they create, the data gathering and observation challenge to support this value calculation is at odds with a business imperative to advance products quickly.

For the full article, where Dan looks at Variable Outcomes Challenge ROI based Decision Making and Product Pricing and On Farm Testing to Accelerate and Reduce the Cost of Data Collection, check out the link above.

2. The Theory of Innovation Adoption in Agriculture - Upstream Ag Professional

Broadly speaking, there are three sources of consumer-driven product adoption - interest, sign, and hedonic.

Interest concerns the performance of the product or activity in utilitarian, economic and functional terms. Sign concerns the contribution of the product or activity to how they view themselves and impression management (signaling). Hedonic is the extent to which the product or activity satisfies pleasure or experiential goals.

This can similarly be applied to farmers. Farming is not purely B2b.

In The Adoption of Agricultural Innovations, Geoff Kaine introduces five important considerations from previous research that can be used to identify a farmers willingness to adopt:

1. The relative advantage of the innovation over the current standard or other options.

2. Compatibility of the technology within the farmer's operational context.

3. The level of complexity of the innovation.

4. Trialability of the innovation.

5. Observability of the result.

I would add a 6th, based on the work of Ron Adner— adoption chain risk, or value chain incentives that considers how an innovation makes it to the farm.

At a high level, these all make sense, and they are worth breaking down to consider how agribusinesses and agribusiness professionals can leverage these insights as a framework for improving the uptake of their innovations.

For the full Upstream Ag Professional article breaking down all of these in more detail, check out the link above.

Related: Are You Selling a Product - or a Vision? - Linkedin

3. Farmers’ Favorite Weedkiller Nears Its End, Bayer Warns - WSJ

Key Takeaways

• Bayer has $2.8 billion glyphosate revenue and it’s costing them $3+ billion per year to fight lawsuits.

• Bayer is determining within the next 6 months whether they will continue on with glyphosate, or not.

• If Bayer stops manufacturing and supporting the glyphosate label, it sets a precedent that no molecule is legally untouchable (even with approvals from government bodies), raising questions for R&D investment across the crop protection sector.

This article in the WSJ received a significant coverage last week.

I covered the topic 6 weeks ago in the Bayer earnings results.

Over the last ~6 weeks, Bayer has been publicly stating that they may stop producing glyphosate and supporting the label. CEO Bill Anderson is going even further now and positioning the legal pressure as not just as an attack on glyphosate, but as an attack on innovation that benefits farmers and as anti-litigation industry:

Subscribe to Upstream Ag Professional to read the rest.