Drone strikes botanical gold

Thanks to a new tool, botanists have the power to observe and operate in even more remote parts of the world than before.
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When drones (also known as unmanned aerial vehicles, and Remotely Piloted Aerial Systems) are mentioned without qualification, one’s knee-jerk thought is of remotely-operated weaponised aircraft that deal death from the skies as various governments or their agents ‘liquidate’ enemies of the state. Well, we at Cuttings HQ shun such barbarism and are pleased to look at some of the less harmful ways in which drones have been used – for the benefit of humanity – in the plant sciences. Although botanists are known for their derring-do and death-defying escapades in their search for plants, if such antics can be avoided, then so much the better (and safer!). And drones can help botanists reach places that are inaccessible – or otherwise dangerous to get to. In that regard, members of Hawaii’s National Tropical Botanical Garden (NTBG) have used drones* to discover new populations of several plants listed as critically endangered on the International Union for Conservation of Nature (IUCN) Red List on the vertical cliff face of Mauna Pulou on Kauai.

The rarest plant spotted by this botanical ‘eye in the sky’ was laukahi (Plantago princeps var. anomala), which has been used in traditional Hawaiian healing to disinfect wounds, as well as to treat boils and high blood pressure. Prior to this discovery, fewer than 25 individuals were known to exist in the wild, making this Hawaiian Islands’ endemic one of the rarest plants in the world.

This proof of principle gives high hopes that the aerial technology can be further exploited to identify more sites for rare species in inaccessible places (which locations, because of their ‘out-of-the-wayness’, may also help to protect these rare botanics). It is also envisaged that, in future, drones with arms (as opposed to a military-style ‘armed’ drone!) could be used to collect seeds from these precious plants. Germination and propagation of these collected seeds should help to ensure the plant’s multiplication and survival so that their ethnobotanical promise can be studied without harming the native populations. However, there is apparently a race against time to do this because the Plant Extinction Prevention Program (PEPP) involved in this important work is under threat from cuts to its funding.

Elsewhere in the world, the maize breeders of southern Africa are poised to benefit from drone technology. Pilot studies suggest that use of drones could cut labour and costs spent in collecting data for maize breeding by at least 10%; for example, drones can collect data from 1,000 plots in 10 minutes which would take eight hours to do manually. However, it is important to stress that drones will not replace humans in data collection, and it is still a matter of some urgency that Africa trains more plant breeders and field technicians needed to develop improved varieties of the staple crops to boost productivity in farmers’ fields.

And drones appear to be the next big technological breakthrough in soya agriculture. Their use as early detection systems for diseases can also help protect crops from devastating infections, and have a key role in predicting potato yields.

Indeed, drones along with robots, are touted as the way ahead in plant agriculture more widely. Although it should be noted that farmers don’t always want to use the new technology in ways you might expect; for example some are keen to employ the ‘spy-in-the-sky’, aerial viewing platform to check that farm workers are doing the jobs they are paid for, and to chase away unwelcome representatives from animal feed companies!

*For the technically-minded the drone used in Hawaii was a DJI Mavic Pro

References

Palmer, C. (2004). Plantago spp. and Bidens spp.: A case study of change in Hawaiian herbal medicine. Journal of Ethnobiology, 24, (1), 13-31. http://direct.biostor.org/reference/175101

Yu, N., Li, L., Schmitz, N., Tian, L. F., Greenberg, J. A., & Diers, B. W. (2016). Development of methods to improve soybean yield estimation and predict plant maturity with an unmanned aerial vehicle based platform. Remote Sensing of Environment, 187, 91–101. https://doi.org/10.1016/j.rse.2016.10.005


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