Canola Crush Makes New Monthly High in December

Jan 25, 2024

A Statistics Canada crush report Wednesday pegged the December 2023 canola crush at 943,302 tonnes, up 3.8% from November and more than 14% above the December 2022 crush of 826,445. The previous December high for the crush was in 2022 at 904,577 tonnes.

The cumulative August-December crush for the 2023-24 marketing year now stands at 4.57 million tonnes, up 13.9% from the same period a year earlier and 43.5% of Agriculture Canada’s forecasted annual target of 10.5 million tonnes.

Amid rising demand for canola oil from the North American renewable diesel industry and a flurry of new facility and crush expansion announcements since 2021, Canadian canola processing capacity is expected to increase by 60% from the current 11.1 million tonnes by 2025, according to the Canola Council of Canada. Canadian processors produced 4.15 million tonnes of canola oil in 2022-23, an amount that could rise to around 7 million over the next five years if all the intended new processing capacity eventually comes on stream.

In its initial supply-demand estimates for the upcoming 2024-25 marketing year on Monday, Ag Canada held its crush estimate unchanged from the current year at 10.5 million tonnes. However, the government described its estimate as ‘conservative,’ suggesting it may be revised considerably higher, depending on how quickly the planned new Prairie crush plants are brought into operation.

According to StatsCan, the December crush produced 402,183 tonnes of canola oil, up from 386,867 in November and 345,687 in December 2022.

Source : Syngenta.ca

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.