Tax Credit for the 2013 Tax Year Open to Alberta Canola Producers

Mar 05, 2014

Canola growers in Alberta that do not request a refund of their check off from the Alberta Canola Producers Commission (ACPC) qualify for a tax credit for the 2013 tax year.

The Scientific Research and Experimental Development (SR&ED) tax credit allows canola growers to claim the tax credit for that portion of the check off paid that was used to fund qualifying research.

The rate for Alberta canola producers in 2013 is 19.47 percent. For example, for an individual grower that paid $100.00 in check off to the ACPC in 2013, $19.47 is eligible to earn the tax credit.

The tax credit can:

offset federal taxes owing in the current year,
be received as a tax refund,
be carried forward up to 10 years to offset federal taxes owing, or
be carried back 3 years to reduce federal taxes paid in those years.
Individual producers must file a T2038 (IND). Farm corporations must file form T2SCH31.

Source: Alberta Canola Producers Commission

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.