In order to have successful crops, farmers and land operators need to fully understand their land and how it performs. They need to know how it has behaved in the past so they can better understand how it will function in the future. Awareness of historical practices, helps growers transition to more sustainable practices with regenerative agriculture for the future.
CIBO hosted a historical land demo webinar where we showed how to find historical land data and information so land operators can make more sustainable choices in the future. The webinar featured CIBO’s VP Land Platform Nitzan Haklai with a live Q&A. We did a live demonstration on our platform and covered historical practices, how CIBO showcases historical information, how to use historical information for regenerative ag and more! Below is some of the information, questions, and answers from the live event.
How do organizations find historical land information today?
The old fashioned way is going in person to evaluate a piece of farmland and trying to get data from different sources. Organizations need to collect data sources and try to make something useful from it in order to gain insight to the land. Today, when you see stakeholders try to expand their businesses they run into many obstacles because it’s an expensive and time consuming process. Farmers get many products that help them learn about their field but other stakeholders – investors, owners, operators, or lenders – who need farmland information for their business operations, aren’t able to get it. This is where CIBO starts to identify a challenge and gap. It’s helping these stakeholders scale and streamline this process.
“Land tells a story.” – Nitzan Haklai, VP Land Platform.
According to the USDA, they tallied 88 million of corn planted acres in 2020. You mention scale and it is nearly impossible to visit even a small fraction of these acres. Can you tell us why understanding historical practices is important?
The condition of farmland today is the result of how it was treated in the past few years. When evaluating a piece of land and figuring out the risk of investing in it, the key is to look at how it has performed in the past and how it has been treated.
By understanding the historical land practices, organizations can discover what potential outcomes the field could produce by doing different practices on the land and having different climate conditions to determine how they could impact productivity.
What we see now and what many farmers have known for years is the benefits of practices like cover crops or tillage practices. It is important to understand the historical uses of cover crops to determine the opportunities for the future. This is especially true for land that has not been treated the best in the past, we can figure out how to improve it. That is when investors see that particular land as an opportunity. The land might not have been treated the way it should have been but by doing cover crops and tillage practices, they can increase the productivity of the land for the future.
“Farmers do what’s best for land to make it more productive.” – Nitzan Haklai, VP Land Platform.
Questions from the audience:
How does CIBO gain such detailed information including elevation and soil type?
We use SSURGO soil samples and publicly available soil maps as well as remote sensing. It allows us to get the details on the infield variability analysis. Our yield simulation is based on a crop modeling approach based on how a crop behaves over a growing season. What is its performance and how is it changing? It is also based on the specific understanding of that field’s conditions.
CIBO combines modeling and simulation as one pillar to benchmark against county averages. Then, we combine AI and remote sensing to detect what is actually happening inside the field in the last day, week or specific time period. By combining both simulation and modeling with computervison and AI, CIBO is able to bring in the public, private, and proprietary data to produce scores, in field variability, crop identification. We blend it all together to make it bigger than the sum of its parts.
What are the specific data layers in the valuation model including soil, weather, etc? How does CIBO differ from other models? Do you use private data in your analysis?
We take a lot of public data sources that are relevant to CIBO like USDA valuation, historical practices, soil maps, etc. We take this data and put it in one place. On top of all this data, we layer it with remote vision, AI and modeling to provide a deeper understanding of the information. Visit CIBO’s blog for more information about our specific valuation approaches.
When we take a look at the publicly available data, we use our own understanding of performance, stability, and valuation to find the difference between each piece of land in order to find its own unique agronomic value. CIBO has built a robust data infrastructure at a county level. We have agronomists who go through public information to validate it. We add our remote sensing data to this information and apply algorithms on top of it about the specific crops (our own IP). Together, with our agronomists, we give validation to our practices and agronomic data.
We do license some data from third parties. This includes our owner information but we do not sell this information to others.
What crop model do you use?
CIBO uses the SALUS model and it was developed by one of our co-founders, Dr. Bruno Basso. It models the growth of a crop over 300 different parameters from planting date, inputs, crop type, etc. Some of the other things that come out of that model are the carbon equivalent to a particular crop growing on a piece of land.
How do growers enroll in CIBO?
We developed a very simple way for a grower to enroll in the CIBO marketplace or join a customer’s enterprise private working space. Growers upload a field and through our simplified process, we can calculate within that moment how many credits they can generate based on their practices. Once a farmer has completed his or her enrollment, we use our own computer vision technology to verify their practices. Our platform gives estimates of how many carbon credits they can sell. Farmers input their practices and we are able to give them a quick and easy number. We make it as simple and easy for farmers to input and access their information in one place. It also gives them access to the full breadth of data about land they just enrolled.
CIBO is continuously updating our baseline and our algorithms to make sure we are providing correct and valuable information.
Each of our algorithms has its own unique story and approach. With valuation, we did our initial work primarily in 2020. On a daily basis, we see an increase in land valuation. We are starting to have new thoughts about how to relate the agronomic value versus the new approach to what is the real estate or market value of the net income of a piece of land using our yield simulation.
Within our carbon algorithm, we are constantly doing work to update our model and protocol. Carbon markets and the perspective of what should be used are evolving quickly. We are matching those changes. We recently launched our new carbon protocol which is based on our approach that looks at annual carbon credit valuation based on practices a farmer is doing on his or her field. Each algorithm is done differently, some are done annually because they are more static meanwhile some are constantly being updated.
To learn more, take a look at CIBO’s Science section within our resources on our website to find out more detailed information about CIBO’s models.
Meet our Speaker
Nitzan Haklai is the VP of the Land Platform at CIBO, leading the company’s product strategy and Go-to-Market. She is an experienced professional in the food and agricultural industries, and passionate about driving tech commercialization in the Ag space. Before joining CIBO, Nitzan worked at Gro Intelligence, a VC-backed agriculture data platform, and Bayer AG. Earlier in her career, she led the Global Open Innovation Initiative at Adama, one of the world’s leading agrochemical companies. Prior to working at Adama, she served as a lieutenant at The National Geospatial-Intelligence Agency in the Israel Defense Forces. Nitzan holds an MBA degree from the Massachusetts Institute of Technology and a law degree (LLB) from the Hebrew University of Jerusalem.
