Study Reveals Manitoba Crop Alliance Crop Types Are Major Drivers Of Manitoba Economy

Mar 13, 2024

Today, Manitoba Crop Alliance (MCA) released data highlighting the significant contributions of its crop types to the Manitoba economy.

MCA contracted information services company GlobalData to conduct a study assessing the impact of Manitoba-grown wheat (excluding durum), barley, grain corn, sunflower and flax on the province’s economy.

Together, these five crop types account for a large part of Manitoba’s agriculture industry. Several of these crops are also the foundations for important food industries, both within the province and beyond.

GlobalData found that the total economic impact of MCA’s five crop types averaged roughly $6.9 billion over the past three years, including more than 28,000 Manitoba jobs and $2.5 billion in wages.

“This study shows the major role our crop types play in the economic well-being of the province and the country,” says MCA chair Robert Misko, who farms east of Roblin, MB.

“As farmers, we have long known our position in the system and how we contribute to the province’s success, but it is heartening to see those contributions laid out in a measurable way that anyone can understand.”

For a full breakdown of the study, including summary data and in-depth reports for each crop type, visit mbcropalliance.ca/economic-impact.

This economic assessment was modelled after work done last year by Cereals Canada on wheat, barley, durum and oats. Visit cerealscanada.ca/economic-impact for more information.

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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.