{"id":14664,"date":"2019-04-03T23:22:21","date_gmt":"2019-04-03T23:22:21","guid":{"rendered":"https:\/\/rsoftsolution.com\/blog\/mits-cyber-agriculture-optimizes-basil-flavors.html"},"modified":"2019-04-03T23:22:21","modified_gmt":"2019-04-03T23:22:21","slug":"mits-cyber-agriculture-optimizes-basil-flavors","status":"publish","type":"post","link":"https:\/\/www.rbsitsoftwaresolution.in\/blog\/mits-cyber-agriculture-optimizes-basil-flavors.html","title":{"rendered":"MIT\u2019s \u2018cyber-agriculture\u2019 optimizes basil flavors"},"content":{"rendered":"

The days when you could simply grow a basil plant from a seed by placing it on your windowsill and watering it regularly are gone \u2014 there\u2019s no point now that machine learning-optimized hydroponic \u201ccyber-agriculture\u201d has produced a superior plant with more robust flavors. The future of pesto is here.<\/p>\n

This research didn\u2019t come out of a desire to improve sauces, however. It\u2019s a study from MIT\u2019s Media Lab and the University of Texas at Austin aimed at understanding how to both improve and automate farming.<\/p>\n

In the study, published today in PLOS ONE<\/a>, the question being asked was whether a growing environment could find and execute a growing strategy that resulted in a given goal \u2014 in this case, basil with stronger flavors.<\/p>\n

Such a task is one with numerous variables to modify \u2014 soil type, plant characteristics, watering frequency and volume, lighting and so on \u2014 and a measurable outcome: concentration of flavor-producing molecules. That means it\u2019s a natural fit for a machine learning model, which from that variety of inputs can make a prediction as to which will produce the best output.<\/p>\n

\u201cWe\u2019re really interested in building networked tools that can take a plant\u2019s experience, its phenotype, the set of stresses it encounters, and its genetics, and digitize that to allow us to understand the plant-environment interaction,\u201d explained MIT\u2019s Caleb Harper in a news release<\/a>. The better you understand those interactions, the better you can design the plant\u2019s lifecycle, perhaps increasing yield, improving flavor or reducing waste.<\/p>\n

In this case the team limited the machine learning model to analyzing and switching up the type and duration of light experienced by the plants, with the goal of increasing flavor concentration.<\/p>\n

\"\"<\/a>A first round of nine plants had light regimens designed by hand based on prior knowledge of what basil generally likes. The plants were harvested and analyzed. Then a simple model was used to make similar but slightly tweaked regimens that took the results of the first round into account. Then a third, more sophisticated model was created from the data and given significantly more leeway in its ability to recommend changes to the environment.<\/p>\n

To the researchers\u2019 surprise, the model recommended a highly extreme measure: Keep the plant\u2019s UV lights on 24\/7.<\/p>\n

Naturally this isn\u2019t how basil grows in the wild, since, as you may know, there are few places where the sun shines all day long and<\/em> all night strong. And the arctic and antarctic, while fascinating ecosystems, aren\u2019t known for their flavorful herbs and spices.<\/p>\n

Nevertheless, the \u201crecipe\u201d of keeping the lights on was followed (it was an experiment, after all), and incredibly, this produced a massive increase in flavor molecules, doubling the amount found in control plants.<\/p>\n

\u201cYou couldn\u2019t have discovered this any other way,\u201d said co-author John de la Parra. \u201cUnless you\u2019re in Antarctica, there isn\u2019t a 24-hour photoperiod to test in the real world. You had to have artificial circumstances in order to discover that.\u201d<\/p>\n

But while a more flavorful basil is a welcome result, it\u2019s not really the point. The team is more happy that the method yielded good data, validating the platform and software they used.<\/p>\n

\u201cYou can see this paper as the opening shot for many different things that can be applied, and it\u2019s an exhibition of the power of the tools that we\u2019ve built so far,\u201d said de la Parra. \u201cWith systems like ours, we can vastly increase the amount of knowledge that can be gained much more quickly.\u201d<\/p>\n

If we\u2019re going to feed the world, it\u2019s not going to be done with amber waves of grain, i.e. with traditional farming methods. Vertical, hydroponic, computer-optimized \u2014 we\u2019ll need all these advances and more to bring food production into the 21st century.<\/p>\n

Article source: https:\/\/techcrunch.com\/2019\/04\/03\/mits-cyber-agriculture-optimizes-basil-flavors\/<\/p>","protected":false},"excerpt":{"rendered":"

The days when you could simply grow a basil plant from a seed by placing it on your windowsill and watering it regularly are gone \u2014 there\u2019s no point now <\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"jetpack_post_was_ever_published":false,"_jetpack_newsletter_access":"","_jetpack_dont_email_post_to_subs":false,"_jetpack_newsletter_tier_id":0,"_jetpack_memberships_contains_paywalled_content":false,"_jetpack_memberships_contains_paid_content":false,"footnotes":"","jetpack_publicize_message":"","jetpack_publicize_feature_enabled":true,"jetpack_social_post_already_shared":true,"jetpack_social_options":{"image_generator_settings":{"template":"highway","default_image_id":0,"font":"","enabled":false},"version":2}},"categories":[17],"tags":[23],"class_list":["post-14664","post","type-post","status-publish","format-standard","hentry","category-networking-and-communication","tag-network-and-communication"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t