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More work wanted on removing red tape

Canadian farmers risk falling further behind competitors if two main federal agencies don’t become more efficient and responsive to what the industry needs, said witnesses appearing before the House of Commons agriculture committee.

Industry representatives said Canada lags in many areas. Approvals and decisions take too long and rely on old processes, such as paper phytosanitary certificates.

The committee is studying red tape reduction and regulatory modernization at the Canadian Food Inspection Agency and Pest Management Regulatory Agency. The government implemented regulatory reform at both agencies, which fall under the health department, and they issued updates in September.

However, agricultural organizations want more progress to ensure the industry is competitive and sustainable.

Canadian Federation of Agriculture second vice-president Stephanie Levasseur said it wants the cabinet directive on regulation amended to mandate that economic and competitive interests of producers be considered.

“Decisions are made without sufficient consideration of food security in Canada, nor the price of food, and even less of the economic impacts of, or competitiveness of, Canadian agriculture, and this needs to change,” she told the committee earlier this month.

She and others said timelines have to be shorter for many regulatory processes.

“Re-evaluations should not take a decade,” she said.

“Evaluating drone usage, for example, for some crops, should not take over half a decade.”

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

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.