We recently caught up with Wolfgang van Loeper, Founder and CEO of MySmartFarm. Once a wine farmer himself, he is now using Big Data to transform agriculture. We were keen to learn more about his background and what he is building at MySmartFarm (MSF) ...
Hi Wolfgang, firstly thank you for the interview. Let's start with your background...
Q - What is your 30 second bio?
A - I am South African born, though I finished my last three years of schooling in Germany and then went on to study business economics in Germany as well. Coming back to South Africa I started up a family wine business / farming operation, converted it to organic and won a few wine awards. This saw me using and recording high volumes of technical data over many years. As I was harvesting not only grapes but data (!), I began to transition from farmer to Big Data Entrepreneur.
Q - How did you get interested in working with data?
A - As a farmer you are forced to work with data. I respect the odd organic small holder farmer who doesn't work with data, but for myself, it was the organic farming operational requirements that really got me into collecting farming data. I couldn't imagine doing without. All I now do with the development of MySmartFarm, is to make this whole 'data thing' much easier and quicker for all other farming colleagues.
Q - What was the first data set you remember working with? What did you do with it?
A - We used to receive pages and pages of faxes from the labs, with the analyses of all our soil and leaf samples. Being the structured person I am, I re-typed all the data sets into excel sheets. This helped me understand and structure the data better. We then used my analysis/insights to balance our soils and fertilize appropriately. Very soon thereafter we also started working with soil moisture data, hosted in an independent software package, to further refine our farming techniques.
Q - Was there a specific "aha" moment when you realized the power of data?
A - We were preparing for last pre-harvest irrigations in our vineyards and observed a coming heat wave in combination with already high levels of plant stress. With harvest being eminent, we were looking at obtaining optimum phenolic constitutions within the grapes. It was a major manual exercise combining and understanding all the data - not made for the everyday farmer - but I am glad we did and we were very happy with the results. And I, for one, realized the power of combining all that data.
Wolfgang, very interesting background and context - thank you for sharing! Next, let's talk more about Data Science and Agriculture...
Q - What excites you most about bringing Big Data and Agriculture together?
A - The opportunity to create a move in farming practices - literally being part of a new Green Revolution, which, unlike the last one, potentially has the ability to fix the problems the previous one has bought us.
Q - Which areas of agriculture do you think will be most impacted by Data Science?
A - The application of chemicals and water and the effective use of natural fertilization.
Q - What are the biggest areas of opportunity / questions you would like to tackle?
A - Creating an environment for farmers to farm crops more in tune with nature. And making more use of nature's tricks, to harvest crops that cost less to produce and contain more of the all-important natural phytonutrients, which conventional, heavily chemically treated, farm produce has very little of.
Q - What was your reaction to Monsanto acquiring Climate Corporation last year? How does that deal change the Data Science-Agriculture landscape?
A - Although the Climate Corporation does not cover as many varied sources of data as MySmartFarm (MSF) does, it was inevitable that one of the big players was going to move into agricultural data science. But only recent developments in SaaS systems make it possible to collect data directly from the farmer. So it would have been hard to develop a MSF-like system any earlier, or similarly, for an acquisition of such a scope to be possible. Subsequent to Climate Corporation's acquisition, Du Pont and Deere have also partnered to drive their own move into agricultural data science. Sitting in the middle of this development, I'm first glad to be part of it and second, to have my patents in place!
Definitely sounds like an exciting time to be developing technology in this space! On that note, let's talk more about MySmartFarm...
Q - How did you come to found MySmartFarm?
A - After years of using and fine-tuning my excel sheets - where I manually collected/entered/analyzed all the data - farmers, agronomists and scientists said I should think about solving the problem in a way that I could commercialize it so other farmers could benefit. So creating a SaaS Cloud based platform that automatically collected all the data just made so much sense.
Q - Got it. So what specific problem does MySmartFarm solve? How would you describe it to someone not familiar with it?
A - With MySmartFarm a farmer has all his data (harvesting, fertilization, laboratories, weather, disease and sensor data - such as from local soil or leaf moisture and satellite sensors) alongside his important mapping and GIS data. MSF then combines all that data with climate data and from there generates new intelligence. Added to the secure storage of a farmer's complete set of data, he has the added benefit, by getting a very convenient management dashboard, illustrating what is important to him to make fast and efficient decisions.
Q - Could you tell us a little more about the technology?
A - MSF makes use of a whole host of available high tech services to farmers - basically farmers make use of sensors and laboratory information from these service providers and MSF collects the data from them all onto one platform. All the data that we collect for the farmer on our SaaS systems is hugely valuable in that we can combine that data with forecasted data and help the farmer act on predictions or tendencies we pick up over the years. With these insights the farmer can act in a much more timely manner on an enormous set of parameters, which otherwise would be impossible. In terms of technology stack, IBM is supporting the development of MySmartFarm and we're using business intelligence stacks from their portfolio, this saves us a lot of costs and development money.
Q - What have you been working on most recently?
A - We're busy with beta testing and developing the first version. In the last four weeks we've been busy with the dashboard, for me a very important aspect, as it has very unique patented features that make it literally visually fun for the farmer to interact with all his data - and he will be able to specifically select what is important for him. The feedback to-date from farmers is that they like being able to interact with the data from multiple sources on one dashboard, without being required to change to different platforms or software.
Q - What else should we know about MySmartFarm?
A - MSF will drive farmers to more sustainable farming practices, not only saving water and chemicals, but assisting them on the move to more agro-ecological practices through knowledge transfer of successful and profitable, more ecological practices; especially if it is linked to high tech and data.
Very interesting - look forward to hearing more about MySmartFarm going forward! Finally, it is advice time!...
Q - What does the future of Data Science & Agriculture look like?
A - Rosy!
Q - Any words of wisdom for Data Science students or practitioners starting out?
A - Studies and data collection are nice but of limited use without the wisdom of practical solutions that actually help people achieve new ways of doing things, such that we can still live on this planet in a 100 years time.
Wolfgang - Thank you so much for your time! Really enjoyed learning more about the evolving Data Science - Agriculture landscape and what you are building at MySmartFarm. MySmartFarm can be found online at http://mysmart.farm and on twitter @MySmartFarm.
Readers, thanks for joining us!
P.S.If you enjoyed this interview and want to learn more about
- what it takes to become a data scientist
- what skills do I need
- what type of work is currently being done in the field