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Steve kell: Black Sea War creates price swings both ways

One of the most compelling and dynamic factors influencing world grain markets over the past two years has been the Russian invasion of Ukraine and its impact on global commodity prices.

In the early days of the war, there was a substantial degree of panic in wheat and corn markets as the world’s 4th largest producer of wheat was at war with the world’s 7th largest producer of wheat, and prices rose to reflect the anxiety over supply. Two years later the battle scars of war have changed the export pathways for Ukrainian producers to access international markets, and those changes are now having a negative impact on our domestic grain values.

While not at pre-war levels, Ukraine is still a massive producer and exporter of grains. For 2023, it is estimated that Ukrainian farmers harvested 80-million metric tonnes of grains and oilseeds. They have about 30-million tonnes of internal domestic consumption of these crops, and will export close to 50-million tonnes of grain in the current crop year.

The most important thing to understand about Ukrainian grain logistics is to appreciate the scale of their operations. Prior to the Russian invasion back in 2020 and 2021, the Ukrainian Black Sea Grain terminal could reach a peak capacity of exporting as much as 6 million tonnes of grain each month, (to put that in perspective, the Ontario “Bay Ports” in the Great Lakes and St. Lawrence Seaway export about 3.5 million tonnes per year).

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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.