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NEW SMART AGRICULTURE TECHNOLOGY FOR MONITORING PLANTS

This unobtrusive, leaf-mounted sensor saves time and improves productivity by
remotely monitoring the health of plants in real-time.


209_NEW_SMART_AGRICULTURE_TECHNOLOGY_FOR_MONITORING_PLANTS_T.JPG



Sensor attached directly to the underside of a plant leaf. By attaching it to
the underside, light is not obstructed, allowing for accurate measurements. Data
observed outdoors can be viewed in real-time from a terminal.

Kohzuma and Miyamoto

With growing concerns over climate change and overpopulation, we urgently need
to boost agricultural productivity. With the goal of creating a way to easily
tell whether a plant is thriving or dying, a leaf-mounted sensor was created by
researchers at Tohoku University. This small but mighty technology could help
improve crop yields and resource management in order to meet ever-growing
demands.

Extreme weather events like heatwaves, heavy rain, and droughts stress plants,
which can reduce crop yields and threaten the long-term health of our farms,
forests, and biodiversity. There is an unmet need to monitor precisely how
plants respond to these changes. While drones and aircrafts have improved plant
monitoring from above, they only capture more macro, surface-level information.
They also need adjustments to be able to track plants accurately over time.
Other small sensors that can capture changes at the individual plant level are
inconvenient since they often require on-site personnel to install and manually
check each sensor.

"The traditional methods may work well for some purposes, but they are difficult
to operate and quite expensive," explains Kaori Kohzuma, "In order to
continuously monitor small changes, we needed a new solution."

To address these issues, a team of researchers developed a novel sensor that
attaches directly to the underside of plant leaves. This small device uses a
spectroscopic sensor and light source to measure leaf color without blocking
sunlight, and it can track changes in the same spot over time. Powered by a
battery, with Wi-Fi data transfer and waterproofing, the sensor can work
outdoors for over a month, allowing for extended data collection.

"Smart agriculture is a huge time-saver," says Ko-ichiro Miyamoto, "Farmers
don't have time to manually check every single plant. This sensor is able to
provide fine-tuned readings for what's going on in real time. Then, they can
react accordingly to areas where plants are experiencing high levels of stress."

This sensor performed well when compared with a commercial spectrometer on about
90 leaves from 30 different plant species. It accurately distinguished colors
across seven out of its eight detectable wavelengths, and its readings at 620 nm
were highly similar to commercial chlorophyll meters. Further tests with a
stress-sensitive Arabidopsis thaliana mutant showed that changes at 550 nm in
the sensor's readings matched the plant's stress responses, which aligned with
the commonly used Photochemical Reflectance Index (PRI).


FIG.2.JPG



Approximately 30 types of plant leaves used in the sensor's functional test.

Kohzuma and Miyamoto

In an outdoor trial to test performance under real life conditions, they
attached the sensor to birch leaves to track changes in leaf color during
autumn, leaf fall, and aging over two weeks. They were able to observe a
decrease in chlorophyll (an indicator of plant stress) and how the plant's
response fluctuated with sunlight intensity.

"This affordable sensor is a promising tool for accurately monitoring plant
health and stress through leaf color and light reflection data. Its low cost
makes it possible to place multiple sensors across various locations, creating a
network for simultaneous monitoring in many spots," summarizes Kohzuma.

This smart diagnosis technology allows for support to be provided in the areas
it's needed most. This sensor could be used widely in smart farming, forest
health studies, and other areas where detailed plant health tracking is
important.

The research was published in Sensing and Bio-Sensing Research on September 24,
2024.


FIG.3.JPG



Observations of birch leaves in the autumn foliage stage over a two-week period.
(Top) Time-course changes across eight wavelengths. (Middle) Variation in
sunlight intensity. (Bottom) Actual changes in leaf color. As the green color
shifts to yellow and brown, changes in reflectance can be observed.

Kohzuma and Miyamoto



Published: 26 Nov 2024

Institution:
Tohoku University


CONTACT DETAILS:

Public Relations Division

Tohoku University Public Relations Division 2-1-1, Katahira, Aoba-ku, Sendai,
980-8577

public_relations@grp.tohoku.ac.jp
+81-22-217-6038
Country: 
Japan
Journal:
Sensing and Bio-Sensing Research
News topics: 
Innovation
Plants & Animals
Science
Technology
Academic disciplines: 
Engineering & Technology
Biology
Content type: 
Peer Reviewed
Website: 
New Smart Agriculture Technology for Monitoring Plants
Reference: 

Title: Analysis of plant physiological responses based on leaf color changes
through the development and application of a wireless plant sensor
Authors: Kaori Kohzuma, Ko-ichiro Miyamoto
Journal: Sensing and Bio-Sensing Research
DOI: 10.1016/j.sbsr.2024.100688






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