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Offbeat These Fake Flowers Could Help Scientists Study At-Risk Bees

07:16  14 february  2018
07:16  14 february  2018 Source:   mentalfloss.com

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Fake flowers designed to look like real orchids, for example, could encourage the pollination of endangered orchid species. But for people studying dwindling bee populations, orchids are low on the list of concerns: 30 percent of all the world's crops are pollinated by bees [PDF].

Similar from the Web. These Fake Flowers Could Help Scientists Study At - Risk Bees - mentalfloss.com. Fake flowers designed to look like real orchids, for example, could encourage the pollination of endangered orchid species.

a close up of a yellow flower: These Fake Flowers Could Help Scientists Study At-Risk Bees© iStock These Fake Flowers Could Help Scientists Study At-Risk Bees If you haven't heard, the world's bees are having a crisis. According to one recent study, bee populations in some areas have plummeted by 75 percent in a quarter of a century. Some countries have introduced legislation banning certain pesticides in response to the news, but solving the complicated problem will likely require much more research. In order to gather better data on bee behavior, one new media artist has developed a machine that can give scientists a bug's-eye view.

As Co.Design reports, Michael Candy's Synthetic Pollenizer is designed to blend into a bee's natural environment. Yellow circles bolted around the opening of the device imitate the petals on a flower. Tubes pump real nectar and pollen into the center of the fake flower, so when bees land on it to feed, they're collecting real reproductive materials they can spread to the next plant they visit.

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Scientists at Newcastle University found that nectar laced with caffeine helps bees remember where the flower is, increasing the chances of a return visit. To understand how this “buffer zone” works, scientists studied bee behavior and wrote up a few algorithms. Their findings improved computer

Candy, who's based in Brisbane, Australia, originally conceived the apparatus as a way for scientists to track the pollinating behaviors of bees. The synthetic flower is outfitted with cameras and dyes, and with enough of them distributed in the wild, researchers could see which bees travel to certain places and how long they stay.

After his concept reached the final round of the Bio Art and Design awards in the Netherlands, Candy decided to create his own prototype with help from an urban beekeeper in Melbourne, Australia. The invention worked: Bees mistook it for real flora and carried pollen from it to their next destination. But to use it for tracking and studying bees on a larger scale, Candy would need to build a lot more of them. The pollinators would also need to be scattered throughout the bees' natural habitats, and since they would each come equipped with a camera, privacy (for nearby residents, not the bees) could become a concern.

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Scientists report that bees and flowers appear to have a charged communication. In addition to a flower ’s color and scent, its electric field may also bring A scientist who studies bugs, he works at the University of Arizona in Tucson. Robert and his coworkers showed that bees notice electric fields

“We hope this will help to counter the problem of bee declines,” says Miyako. “But importantly, bees and drones should be used together.” Saul Cunningham at the Australian National University in Canberra says that using drones to pollinate flowers is an intriguing idea but may not be economically

Even if the concept never gets the funding it needs to expand, Candy says it could still be used in smaller applications. Fake flowers designed to look like real orchids, for example, could encourage the pollination of endangered orchid species. But for people studying dwindling bee populations, orchids are low on the list of concerns: 30 percent of all the world's crops are pollinated by bees [PDF].

[h/t Co.Design]

Google’s new AI algorithm predicts heart disease by looking at your eyes .
Experts say it could provide a simpler way to predict cardiovascular risk more simply by using scans of the retina. Scientists from Google and its health-tech subsidiary Verily have discovered a new way to assess a person’s risk of heart disease using machine learning. By analyzing scans of the back of a patient’s eye, the company’s software is able to accurately deduce data, including an individual’s age, blood pressure, and whether or not they smoke.

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