July 10, 2019

Good Morning,

So it seems that a vegetable-picking robot has been created. Vegebot, as it's known, is not as efficient as a human who's picking vegetables, but how long until they replace us like so many other automated machine have already done. It makes you think.

Learn about this and more interesting stories from the scientific community in today's issue.

Until Next Time,
Erin

Questions? Comments? Scientific Discoveries? Email Us

*-- Gene-editing enzymes imaged in 3D --*

Scientists have for the first time captured high-definition, 3D images of enzymes in the process of cutting DNA strands.

The breakthrough -- described Monday in the journal Nature Structural and Molecular Biology -- helped scientists see exactly how the gene-editing technology called CRISPR-Cas9 works, and could, in the future, help researchers design a more efficient and precise version of the technology.

The findings could also help scientists better understand -- and eventually, treat and prevent -- diseases caused by DNA mutations, including cancer, sickle cell anemia, Tay-Sachs disease, Huntington's disease and many others.

"It is exciting to be able to see at such a high level of detail how Cas9 actually works to cut and edit DNA strands," lead study author Sriram Subramaniam, researcher at the University of British Columbia, said in a news release. "These images provide us with invaluable information to improve the efficiency of the gene-editing process so that we can hopefully correct disease-causing DNA mutations more quickly and precisely in the future."

CRISPR-Cas9, or CRISPR for short, relies on the creation of double-strand breaks, or DSBs, in the genomic regions targeted for manipulation. CRISPR deploys enzymes that act as molecular scissors. Once the DNA is cut, the sequence can be altered.

But CRISPR isn't perfect. Previous studies have shown the technology regularly creates unwanted mutations.

To better understand how CRISPR works, scientists deployed an imaging technique called cryogenic electron microscopy, or cryo-EM. The images revealed the step-by-step molecular movements during the DNA-cutting process.

"One of the main hurdles preventing the development of better gene-editing tools using Cas9 is that we didn't have any images of it actually cutting DNA," said University of Illinois researcher Miljan Simonovic, co-author of the new study. "But now we have a much clearer picture, and we even see how the major domains of the enzyme move during reaction and this may be an important target for modification."

*--- Engineers design robot to pick iceberg lettuce ---*

Scientists have finally automated the job of picking iceberg lettuce. As detailed in a newly published study, the vegetable-picking robot designed by engineers at the University of Cambridge proved itself a capable hand in the field.

The picking of dozens of fruit and vegetable crops has been automated, but engineers have struggled to design a robot and the necessary algorithms to effectively harvest iceberg lettuce.

The so-called Vegebot has previously picked iceberg lettuce in the lab, but the latest test results -- published this week in the Journal of Field Robotics -- mark the first time the robot has successfully picked iceberg lettuce under field conditions.

Though Vegebot isn't yet as efficient as a human, the breakthrough marks an important step in the development of sophisticated agricultural robotics.

Some crops like potatoes and wheat are relatively easy for robots to harvest. But lettuce presents unique problems for robots. Lettuce heads are relatively flat and are low to the ground. Lettuce is also easily damaged.

Automated machines plant lettuce seeds and tend to their needs as they grow, but harvesting still requires manual labor. Picking lettuce is difficult work, but with a few tweaks, it could soon be the work of a robot.

"Every field is different, every lettuce is different," Cambridge engineer Simon Birrell said in a news release. "But if we can make a robotic harvester work with iceberg lettuce, we could also make it work with many other crops."

Harvesting lettuce presents two main challenges to a robot: selecting and cutting. Vegebot relies on a computerized vision system to identify the target crop and determine whether a head of lettuce is ready to be harvested. Vegebot's cutting system allows the robot to slice the head from the roots without damaging the lettuce.

A machine learning algorithm perfected in the lab helps Vegebot determine what a ready-to-cut head of iceberg lettuce looks like. One camera, coupled with its machine learning software, helps Vegebot find ready-to-pick lettuce, while a second camera guide's the robots blade, ensuring a clean cut. A gripping arm holds the head with just the right amount of pressure, so as to allow an efficient slice without bruising or crushing the lettuce.

Researchers suggest the Vegebot can adjust its software and gripping-cutting technique to harvest other types of lettuce and above-ground crops.

Vegebot could help reduce food waste by ensuring only ripe lettuce heads are picked. The robot could also help farmers improve their farming strategies.

"We're also collecting lots of data about lettuce, which could be used to improve efficiency, such as which fields have the highest yields," said lead researcher Josie Hughes. "We've still got to speed our Vegebot up to the point where it could compete with a human, but we think robots have lots of potential in agri-tech."