Fewer Rainy Days and Earlier Springs Linked in Northern Climates

Mar 30, 2022

By Pam Knox

A recent article from the National Science Foundation describes the result of a study on when new leaves appear on plants in spring by scientists at Ohio State University and published in Nature Climate Change. The study shows that while warmer temperatures are the primary cause of earlier leaf occurrence, the number of days of rain (not the amount of precipitation) also makes a difference, and as the number of rainy days per year has been decreasing in many areas north of 30 degrees latitude, this is also affecting how early the leaves come out. The researchers calculated that a decline in rainfall frequency will lead to spring arriving an additional one to two days earlier each decade through 2100. What would cause this? The researchers think that fewer rainy days means fewer cloudy days, too, and that more sunlight reaching the plants in spring stimulates them to produce leaves earlier in the year.

Source : uga.edu

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.