How changing skies alter plant growth patterns

Sunlight shapes life on Earth, driving photosynthesis, influencing weather patterns, and determining the growth of plants. While many assume that more sunlight directly results in better plant growth, the reality is far more complex.

Plants respond not only to the amount of sunlight they receive but also to its quality, intensity, and distribution. Cloud cover, atmospheric conditions, and seasonal changes all play a role in shaping how plants interact with light.

Understanding these interactions is critical for agriculture, especially in an era where climate change is altering weather patterns.

Researchers at Kyushu University have taken a significant step toward unraveling the mysteries of sunlight behavior. Their study introduces a new numerical model that explains how sunlight behaves under different weather conditions.

Published in the journal Ecological Informatics, the research could help farmers make more informed decisions about crop management and greenhouse farming.

Sunlight and plant growth

Plants rely on sunlight for photosynthesis, but more sunlight does not always mean better growth. Cloudy weather can sometimes be beneficial.

On sunny days, light reaches plants from a single direction, leaving lower leaves in shade. In contrast, clouds scatter sunlight more evenly, allowing lower parts of plants to receive light. This balance influences plant development in ways that are not immediately obvious.

Study first author Amila Siriwardana is a PhD student at Kyushu University’s Faculty of Agriculture.

“Plants also respond to different wavelengths of sunlight. If you have ever seen a rainbow, you know that sunlight is made up of many wavelengths. Plants sense these different wavelengths of light and alter their growth responses,” explained Siriwardana.

Plants adapt to different sunlight types

Plants detect the ratio of light wavelengths to gauge their environment. This ratio depends on cloud cover, atmospheric conditions, and the sun’s altitude.

However, little research had categorized this information in terms of plant physiology and ecology. To bridge this gap, the research team collected yearlong sunlight data to examine daily variations in light quality.

“While many projects look at only the ‘energy’ produced by the sun, our methods set out to categorize both the ‘energy’ and ‘quality’ of light,” said Professor Atsushi Kume, who led the team.

“By sorting sunlight into five categories, from clear skies to overcast, we can better understand how plants can adjust and respond to different light conditions.”

Collecting and categorizing sunlight data

To measure sunlight under different weather conditions, the researchers used a spectroradiometer. This device captures the entire spectrum of sunlight.

The spectroradiometer was installed on top of Kyushu University’s Faculty of Agriculture building on Ito campus. The device recorded data from sunrise to sunset throughout 2021.

Using this information, the team built a machine learning model to analyze and predict sunlight variations. The model recognized patterns in weather conditions, including light intensity, scattering, air clarity, and humidity.

Based on these factors, it classified sunlight into five groups. A clear sunny day belonged to group one, while overcast conditions fell into group five.

Sunlight changes across weather patterns

The team observed clear patterns in how sunlight behaves and affects plants.

On bright, cloudless days, more light energy reaches the ground. However, as cloud cover increases, light intensity decreases while ultraviolet levels rise.

Additionally, sunlight shifts in color from red tones on sunny days to blue hues under cloudy skies. Once trained, the model could predict sunlight patterns with high accuracy.

“Our method achieved 94% accuracy in predicting sunlight category without the need for expensive advanced equipment,” said Siriwardana.

“Our model is especially relevant for regions experiencing four distinct seasons similar to Japan’s.”

Applications in agriculture

The research team sees potential applications for modern farming. Their model can help farmers adjust greenhouse conditions and optimize planting schedules throughout the year.

“We hope our model can be used to address the challenges in modern agriculture. Farmers can use this information to improve greenhouse conditions and planting schedules throughout the year,” explained Kume.

”For instance, during Japan’s cloudy rainy season in June, farmers might adjust their greenhouse operations or crop spacing to maximize available light. Even in the fall and winter, when sunlight patterns change, farmers can adapt their strategies based on our model.”

Expanding the research scope

Looking ahead, the team plans to extend their research to different climates, including tropical and high-altitude environments.

This would allow them to refine the model and explore broader environmental impacts of sunlight variations.

By deepening the understanding of how sunlight interacts with plants, the researchers aim to provide more tools for sustainable agriculture and climate adaptation.

The study is published in the journal Ecological Informatics.

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