Historical Data Points to Bad Year for Pulse Root Rots

Feb 21, 2024

Once again, farmers should be on the lookout for root rots in pulse crops. If farmers are practicing proper field crop rotations and haven’t grown pulses in fields since 2020, then root rots could be a problem.

“You want to look back and think ‘Okay, well, what were the weather conditions like in 2020, when you had that pea and lentil crop in the field?’ And unfortunately, 2020 was a fairly wet year. When we look at the past few years of precipitation history, 2020 does stand out as a wetter year. So that means that risk will be higher in those fields that had pea or lentil in 2020 going into 2024,” Syama Chatterton, pulse pathologist at AAFC Lethbridge, says in a phone interview.

Chatterton recommends farmers look back at their yield maps or field notes from the last time pulse crops were grown in a field to check if there were any yellowing spots in the field or if there are any low-lying spots where water can accumulate. Soil tests should be taken from these areas to test for root rots. Possible root rot complexes that can impact pulse crops include Aphanomyces, Fusarium, Rhizoctonia and Pythium.

Bacterial blight incidence should be low for the 2024 growing season as 2023 was a drier year, Chatterton says.

Farmers growing chickpeas should be aware that there has been an unknown chickpea health issue that’s popped up in Saskatchewan, cautions Chatterton. There isn’t much information yet about what’s causing it yet, but farmers should watch out for wilting and yellowing of chickpea plants starting at the growing tips. If it is found farmers should report it.

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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.