Curiosity develops Artificial Intelligence (AI) based solutions (hardware/software) to automate microscope image processing. Our current focus is on developing solutions that will automate soil analysis for the presence of various biological organisms (worms, bacteria, fungi, etc.).
Farming is a biological problem. While it is a common practice to evaluate chemical composition of soil, and optimize micronutrient (Nitrogen, Potassium Magnesium, etc.) concentrations with application of fertilizers, we understand very little about how the types of organisms that are found in soil affect crop manufacturing.
High Sampling Frequency
Limited Sample Processing
CHEMICAL ANALYSIS DATA
At the end of each growing season, we collect high resolution data on the yield of your crop. This has to do with the fact that this type of data acquisitions is integrated in the normal operation of the harvesting combine. As a result, it is cheap, and fast.
A farmer can evaluate the chemical composition of his field by hiring a soil consultant who will go out in the field, acquire soil samples, and send them to the lab for analysis. While the cost of sample acquisition is cheap, the cost of chemical analysis greatly limits the number of tests that a farmer can run on his field.
A soil consultant can also perform a series of tests (CO2 burst, PLFA, or DNA) that can create limited information about the types of biological organisms that are found in soil. These can cost up to 150$ per test for each sample, and, as a result, the farmer can afford to perform only a couple of these tests on his field. It is naïve to assume that two samples will provide a comprehensive understanding of the biological diversity of soil in a 1000-acre field.
*This is the same field!
The most comprehensive test for organismal diversity of soil requires manual assessment of samples with a microscope. Manual assessment of these tests requires technicians with highly specialized training in microbiology. This manual assessment is not only slow (1 sample / hour), but is also a subject to human error. Slow processing, high cost, and person to person variability limit our ability to scale this type of testing.
As you can see, the lack of cost effective tools that evaluate the organismal diversity of soil, limits our ability to gather data, and analyze it to develop best farming practices from the biological perspective. If we could develop these best practices, we could improve the yield of our crops, make farming more sustainable, and limit the harmful byproducts of agriculture while keeping our farmers in business.
Curiosity develops AI based solutions that replace manual labor in microscope image processing. Our software identifies different organisms that are found in a microscope image and classifies them. This workflow is much faster and cost effective than manual processing. It is consistent for every sample since it is not subjected to human error.
Our lab will open its doors in the spring of 2020. We will start offering hybrid biological assessment assays (combination of manual and AI) that will replace CO2 burst, PLFA and DNA tests.
Spring 2020 – (1) Grand opening! (2) Seek funding to develop the first comprehensive image database of biological organisms found in Iowa's soil.
Summer 2020 – Develop the database, and first completely autonomous AI based solution for soil analysis.
Fall 2020 – Beta testing, and early adoption phase. Start outfitting conventional soil analysis labs (Midwestern Laboratories and others) with our subscription-based software solution for soil analysis.
Spring 2021 – Achieve complete deployment of our subscription-based system with multiple soil analysis labs for the farming season of Spring/Summer/Fall 2021. (2) Collect the first comprehensive biological diversity dataset in the state of Iowa.
Future – Continue providing AI based solutions for automating microscopic analysis of soil. Expand beyond the state of Iowa. Continue collecting comprehensive biological data on various types of soil in the US, and develop best farming practices that improve the yield of our crops, make farming more sustainable, and limit the harmful byproducts of agriculture while keeping our farmers in business.