Heat And Drought Can Cause Flower Abortion

Jul 03, 2015

Hot days (28-30°C and up) and warm nights (16°C and up) from bud to mid-flowering stages can have a devastating effect on canola yield. Cool nights offer some recovery from hot days. Warm nights do not provide a recovery period, and more flowers are aborted, producing blanks along the stem. Even with a few days of heat, it can take a week for hormone balance and regular pod formation to return. Recently opened flowers with shortened stamens that don’t protrude above the petals can be a sign of heat damage. These flowers are not likely to produce pods.

Moisture stress during reproductive stages can cause a hormone imbalance that disrupts pod formation and seed set. In a drought, canola plants will progressively drop later flowers at the top of the main raceme and on branches, and put energy into preserving the pods it has. If moisture returns, plants can start sustaining flowers again, resulting in a stem with pods at the bottom and top but nothing in the middle. Additional symptoms of drought include leaf wilting, and flowers with smaller petals that may be off-color (pale or yellowish-orange), or flower buds that die before fully opening.

Source : AlbertaCanola

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.