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Scientists have developed a nasal sensor for plant leaves

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Credit: ACS.

Plants cannot speak when thirsty.

And visual signs, such as wrinkling or browning of the leaves, do not appear until most of the water has gone.

To detect water loss earlier, researchers at ACS Applied Materials & Interfaces have created a nasal sensor for plant leaves.

The wireless system transmits data to a smartphone app that allows you to remotely manage drought stress in gardens and crops.

New wearables are more than just step counters.

Some smart watches now monitor the electrical activity of the wearer’s heart with electrodes adjacent to the skin.

And because many devices can share collected data wirelessly, doctors can monitor and assess the health of their patients remotely.

Similarly, plant-based devices can help farmers and gardeners remotely monitor the health of their plants, including the water content in the leaves – a key marker of metabolism and drought stress.

Previously, researchers developed metal electrodes for this purpose, but the electrodes had problems with attachment, which reduced the accuracy of the data.

Thus, Renato Lima and his colleagues wanted to identify an electrode design that would be reliable for long-term water stress monitoring in plants and also remained in place.

The researchers created two types of electrodes: one made of nickel applied in a narrow, wavy pattern, and the other cut out of partially burnt paper covered with a wax film.

When the team attached both electrodes to individual soybean leaves with clear duct tape, the nickel-based electrodes worked better, producing larger signals when the leaves dried.

The metal ones also held stronger in the wind, which is probably because the thin construction of the metal film allowed most of the tape to bond to the surface of the sheet.

Next, the researchers created a device for carrying plants with metal electrodes and attached it to a live plant in a greenhouse.

The wireless data transfer device is a smartphone app and website, and a simple, fast machine learning technique has successfully turned that data into a percentage of lost water.

Researchers say that monitoring the water content of the leaves can indirectly provide information about the effects of pests and toxic agents.

Because the wearable device provides reliable indoor data, they now plan to test the devices in outdoor gardens and crops to determine when plants need watering, which can save resources and increase yields.

The authors acknowledge support from the Sao Paulo Research Foundation and the Brazilian Synchrotron Light Laboratory. Two study authors are listed in the application for technology.

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