Dow AgroSciences, MS Technologies Receive Patent For Unique Gene Insertion In Enlist E3™ Soybeans

Feb 23, 2017

Technology innovation and integration help advance modern agriculture, and an example of this progress comes from Dow AgroSciences LLC, a subsidiary of The Dow Chemical Company (NYSE: DOW), and MS Technologies, LLC, as the companies announce receipt of a significant patent covering soybean plants and seeds containing the innovative Enlist E3™ event. U.S. Patent No. 9,540,655 acknowledges the proprietary work done to develop new soybean products tolerant to three herbicides’ modes of action, providing farmers significantly improved cropping systems to address resistant and hard-to-control weeds. The ability to combine multiple herbicide tolerance genes of interest in a single location in high-performing soybean genetics ultimately benefits farmers through bringing forward improved products like Enlist E3 soybeans.

The Enlist E3 soybean event includes, for the first time, three herbicide tolerance genes combined in a genetic event in the soybean genome. These genes provide tolerance to Dow AgroSciences’ Enlist Duo® with Colex-D® Technology (a combination of new 2,4-D choline and glyphosate) as well as glufosinate herbicide. A product offering of the Enlist system, Enlist E3 soybeans will be brought to market in high-yielding varieties for farmers who want improved weed control and high yields. The innovative product is being developed through a collaboration between MS Technologies and Dow AgroSciences.

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Video: Seeing the Whole Season: How Continuous Crop Modeling Is Changing Breeding

Plant breeding has long been shaped by snapshots. A walk through a plot. A single set of notes. A yield check at the end of the season. But crops do not grow in moments. They change every day.

In this conversation, Gary Nijak of AerialPLOT explains how continuous crop modeling is changing the way breeders see, measure, and select plants by capturing growth, stress, and recovery across the entire season, not just at isolated points in time.

Nijak breaks down why point-in-time observations can miss critical performance signals, how repeated, season-long data collection removes the human bottleneck in breeding, and what becomes possible when every plot is treated as a living data set. He also explores how continuous modeling allows breeding programs to move beyond vague descriptors and toward measurable, repeatable insights that connect directly to on-farm outcomes.

This conversation explores:

• What continuous crop modeling is and how it works

• Why traditional field observations fall short over a full growing season

• How scale and repeated measurement change breeding decisions

• What “digital twins” of plots mean for selection and performance

• Why data, not hardware, is driving the next shift in breeding innovation As data-driven breeding moves from research into real-world programs, this discussion offers a clear look at how seeing the whole season is reshaping value for breeders, seed companies, and farmers, and why this may be only the beginning.