A child can draw a stick figure. Two arms. Two legs. A head. A body. Now draw another one exactly like it, except this one has red shoes. If your goal is simply to count people, both drawings are equally useful. Either one can represent a person in a database. The informational resolution is sufficient
Why Agriculture Needs Digitization Through Digital Twins The chart tells a simple story: capital is following AI, but AI does not flow evenly into every industry. It flows into industries that have already become digital. Figure 1. Investment trends show AI-era capital flowing back into more digitized sectors while upstream AgTech continues to lag FinTech
“LandScan’s Root Cause Analytics integrated with our variable‑rate application systems have significantly improved the precision of our input management. By quantifying soil and environmental variability across space and time, we’ve reduced input costs, improved agronomist efficiency, and realized measurable production gains. These combined benefits have yielded an average value of $390 per acre.” Zac Ellis
Executive Summary Today, many otherwise progressive growers and managers of high value crops find themselves with uneven yields and more expensive inputs and are asking what they can do to improve uniformity, reduce risk and take their operations to the next level of profitability and sustainability. Historically, agricultural improvement has focused heavily on genetics and
Soil data needs to be obtained rapidly, digitally, and objectively so that it can be repeatable and transferable. Without this, soil data is not scalable or appropriate for modeling, advanced analytics, and enabling modern engineering solutions. The problem with soil sampling and lab analysis is that they don’t produce the proper or accurate reference to
