The human dependency on the animals is just climbing the stairs. Thus, an American company has thought something out of the box and using the gene-editing technique for cutting or adding genes in the animals for bringing about a total change in the animal’s farm. This may sound mindboggling but there is a possibility that it can be fruitful.
The process of gene-editing is currently being put to practice by the company named Recombinetics so as to help remove the faulty genetic traits and replace it with the beneficial ones in certain animals so as to enhance animal husbandry. The process lets the company produce cows without horns along with the breeding cows that can sustain the hot climate. The gene-cutting procedure can help change the traits in animals such as retaining their small size, characteristics, features, and more. For example, the grown pigs tend to have a bad smelling meat which is not the case when they are small. One of the challenges for the company is to convince United States government officials regarding the benefits and safety of genetically modified animals with no much of a difference in comparison to the traditional bred ones.
At the moment, not a single gene-edited animal has been sold in the country. For the first time, the U.S. Food and Drug Administration has given a green card to a specific salmon that has been genetically engineered to grow quickly but this fish has not yet been marketed. The biggest question is whether people will accept genetically modified animals and it is quite a diplomatic matter. The FDA plans on putting forth stringent norms for supporting plant and animal biotechnology’s advancement along with safeguarding public health. Recombinetics is trying to change animals using technology for increasing productivity and growth without making them seem strange to people. As per Paul Thompson at Michigan State University, changing the animals for ones benefit is like playing with god.
Recently, the University of Wyoming researchers Michael Tabak and Ryan Miller have educated a deep neural network to categorize wildlife species by means of 3.37 Million camera-trap imagery of 27 species of animals acquired from 5 states across the US. The model showed 97.6% accuracy which is the highest one achieved using machine learning for wildlife imagery categorization.