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Disrupting Digital Agriculture

Here's the text of an article written about the trends in digital agriculture. The article was based on an interview I gave to Disruptor magazine as a result of my company Aglytix Inc. being selected as one of the top Digital Ag companies to look out for in 2018.

1. What’s the history of Aglytix? Where and how did you begin?

GL: Aglytix has been in the Agricultural Digital Ag business since 2011. The original company, Superior Edge, was re-branded Aglytix to better encapsulate the ideas of incorporating analytics into Agriculture. It is based in Mankato, Minnesota, pretty much in the heart of the American corn belt. It was founded by Jerry Johnson; a Minnesota farmer turned farm equipment and implement dealer turned software developer.

Jerry was an early adopter of computer technology and during his farm equipment dealer days he used computers to create detailed proposals for his farmer clients, using software he developed himself. This innovative approach turned into a software company called CWC that sold large enterprise software solutions to the likes of GM, IBM, John Deere, Renault and Mercedes and in 2000 became publicly traded. So Aglytix is coming from a legacy of in-depth understanding of both the agricultural sector as well as the software space.

2. What specific problem does Aglytix solve? How do you solve it?

GL: Aglytix was founded to solve the key issue of how to assure growth in the Agriculture business, knowing that over the next two generations, the world will need to double the amount of food it grows. So, a singular focus on developing solutions for improved yield and reduced inputs application and cost was the driving force in the development of Aglytix’ portfolio of tools that we call Solvers.

After the healthcare business, there is probably no other industry that generates as much data as the ag business. Agronomic data, spatial data, multispectral imagery, equipment data, meteorological data and many other data layers are available for a given singular square meter of land. What to do with this information?

To determine why a particular crop yields a specific amount at harvest is a multidimensional challenge to which we, at Aglytix, have applied our best thinking. By looking at multidimensional causation, we are narrowing in on how to improve yield levels.

We address several basic issues. How does stand influence final yields? How does tillage affect stand? How does equipment performance influence residue spread during tillage? How does implement selection influence equipment performance?

These multifaceted analytics demonstrate the depth of variability and complexity that determines final yield levels. Aglytix Solvers identify the correlations between these complex variables and permit actions to be taken to mitigate further yield loss and to plan for improved yields.

3. What’s the future of agriculture?

GL: Well, Agriculture is not going away, but it will be changing!! With a need to double output over the next 20 plus years, Agriculture has a positive future.

Prediction #1: The drive towards reducing or eliminating the use of fossil fuel powered vehicles will have a disruptive effect on farming within the next generation.

By 2030 many countries in Europe will have banned fossil fuel cars and while the USA has still to develop a national strategy, some states such as California, have already started to think of fossil-free transportation.

Currently, over 40% of all USA corn produced is destined for ethanol production. So, the potential to significantly change the agricultural landscape is certainly there.

The average Iowa cornfield has the potential to deliver more than 15 million calories per acre each year. This is enough to sustain 14 people per acre, with a 3,000 calorie-per-day diet. But since so much corn is destined for ethanol production or animal production, we end up with around 3 million calories of food per acre per year, mainly as dairy and meat products, enough to sustain only three people per acre.

That is lower than the average delivery of food calories per acre from farms in Bangladesh, Egypt and Vietnam.

Prediction #2: Consumer demand will drive reduced inputs and improved food quality resulting in increased demand at the field level for analytics that will pinpoint where and how much nutrients, fertilizer, pesticide, fungicide, and herbicide will be applied to the crop. Farmers will need to become certified and adhere to input management targets to supply the larger food processing companies and supply chain transparency will drive in-field analytics for food traceability.

Prediction #3: Currently, on a global scale, over 30% of the world’s food never gets consumed. In some geographies, the lack of a basic transport infrastructure or a presence of a consistent cold chain is a major barrier to getting fresh food to consumers. In western societies, there are those that throw away vegetables that are not considered aesthetically pleasing… the ugly food syndrome. It is clear that changes to supply chain infrastructure and to consumer behaviour can significantly increase the amount of food that reaches the consumer table.

4. What are the top 3 technology trends you’re seeing in agriculture?

GL: Trends in the agricultural business are hard to see. It is a business where the “proof of concept” timeline is between 9 to 12 months. In the technology business, this is an eternity. In an era where test- fail – pivot- test – succeed is based on speed of execution and validation, many companies cannot survive such an extended validation process.

Additionally, Ag technology solutions are simply too “hard” to gain adoption. Unless we can make it really easy, digital ag will remain a nice idea but with limited adoption.

The farmer does not need a big easy button. The farmer needs NO BUTTON. Technology needs to be unseen and seamless.

Technologies that can help achieve this are:

1. AI and machine learning

A perfect application for these technologies that are now trending in this space. Like the healthcare business, AI is admirably suited to take vast datasets and extract focused decision ready outcomes that are based on solid science. We see AI as the key differentiator going forward for agricultural analytics

2. Machine translation

Like the tower of Babel, agriculture is full of machines speaking foreign tongues. Each manufacturer has felt the need to make their equipment “proprietary”. The emergence of translation software is a much-needed trend that will reap benefits going forward.

3. Geospatial analytics

Agri-centric satellite clusters will significantly change how field level data is accessed, assessed, analysed and consumed. This we see also as a key differentiator for agricultural analytics.

5. Why is the agriculture industry ripe for disruption?

GL: 30% of the world’s landmass is agricultural land and about 60% of people in poorer countries depend on the agricultural sector for their livelihood. Technology can be a positive disruptive factor in improving the lives of millions of people globally while increasing access to safe and quality food to a planet whose population continues to expand. We are convinced that the benign use of technology will contribute to the betterment of the planet in the years to come.

For the entire article go to


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