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Wednesday, July 11, 2012

Cosmic Connectivity in the Quest for a Tender Steak











Two month's ago I posted about an emerging trend called the “Internet of Cows”; the convergence of digital sensors, networks, and advanced analytics intending to improve the way meat gets from farm-to-fork.

In that post I describe that clearly; not everyone who is excited about beef is excited about such an Internet of Cows. I implored then – as now – to put emotion on the particulars aside – and instead ask:

How do we understand the real-world, non-digital - interconnected network between human, cow, and earth?

But... What the hell does that even mean?!? Isn't that just hippie hogwash; a cosmidelic vision based on little more than wishful thinking about a highly interconnected world? Not at all!

I've been a casual, if mildly eccentric student of chaos & complexity theories for about a decade now; and I gotta say – it's kind of been a lot work with seemingly little in the way of tangible gains - till  recently.  Somehow, up until now, I'd missed the explosion in Network Sciences that are finally allowing us a glimpse into the ineffably complex, fractaline universe of meats - and so much more.

Pictured above is an adapted image from Lim et.al (2011); graphing the specific individual protein to protein interactions within beef cells that, along with good forages and low stress, lead to the tenderness of a steak. This isn't an amalgamation of human knowledge over the centuries; this isn't biochemistry. It's the cutting edge in molecular biology, and essentially the real-time quantification of a non-stop intra-cellular fiesta-del-mundo; the end result of which (in this case); is simply amazing beef.

Now, my friends and readers in the world of small-scale and grass-based beef might argue: so what! Many farmers produce outstanding beef products without ever having the aid of such technological frizz-a-frazz. They might even argue that such a techy approach diminishes from the 'real' research we need into agro-ecological production methods. Indeed – here in Madagascar the meat of the Zebu cattle is most generally, and perhaps surprisingly - superb. We can be quite sure these farmers have never seen, and feel no need, to contend with such Proteomic Network Graphs;  and surely they would benefit far greater in the short-term from an agro-ecological research agenda.

So what indeed! It's a good question. To say such data-intensive maps are the “future of beef”, as it may appear I am arguing here, is to miss a critical lesson regarding the evolutionary nature of technology and change in food and farming.

The proteomic graph above was created through the very cutting edge in technology – millions upon millions of research dollars; thousands upon thousands of human hours; even centuries upon centuries of knowledge building up to this current crescendo of progress......a barely intelligible, if cool-looking, network of cellular activity that no farmer can directly put to use. Shit!

But all this – the money, the time, the centuries of toil – all of this was done with little or no interest in creating a melt-in-your-mouth tenderloin.  Rather - it's a result of what can be called Information Technology (IT) spillover.

IT is truly an evolutionary force to be reckoned with. Genes, neurons, and yes – computer chips flicker on and off;  yes or no, 1 or 0 – in direct relationship to their environment in the unending, unfurling binary dance from the ultimacy of the micro to the complexity of the macro. From genes emerged neurons; from neurons emerged computer chips; and today – from computer chips emerge better computer chips.

Mapping the incomprehensible network of protein to protein interactions became possible because of evolutionary exponential growth in IT. It became desirable because it fuels a revolution in health care (Loscalzo & Barbasi 2011); but it only became applied to the luxurious domain of beef tenderness because it became practical. An emergent property of a constellation of convergence among sensing and thinking cybernetics; it strikes me as unreasonable to assume that IT spillover will stop any time soon.

Network science plays the role of both beneficiary and master to this endless spilling over of information into the world. Transforming medicine, ecology, economics, transportation, and now – food and farming. While the proteomic graph may seem – no matter how much you enjoy tender beef - like a banal example of this technological trend. And while farmers may not make direct use of this data – network analysts can; and the results will undoubtedly guide the evolution of healthier, more delicious cows. This story isn't about proteins and tenderness however, it's about new approaches to complexity.....and complexity is what abounds and confounds as we try to feed the growing population without harming the earth, our animals, or our selves.

The global (and local) systems that put beef on your table are no less complex, adaptive, or seemingly incomprehensible than the proteomic graph above. As the Internet of Cows, or so-called Smart Agri-Food systems, begin to apply these very same networked sensors and analytics to the “network of networks” we call meat; Farmers and Consumers should expect anything but a lack of change. Information Technology is spilling over into food and farming at astonishing rates. We  can either prepare for this and guide the turbulent flows of data to our collective wishes; or ignore these trends - and be washed away in a flood of dynamic change.  The farming, slaughter, processing, and distribution of meats are all currently on the plate for  network analysts. What this will mean - no one can say. The technology of illuminating network complexity is a technology cleaner than tractors and with perhaps greater promise for yielding a new agricultural revolution!



Loscalzo & Barbasi; (2011) Systems Biology and the Future of Medicine. http://www.barabasilab.com/pubs/CCNR-ALB_Publications/201111-00_WIREs-SysBiology/201111-00_WIREs-SysBiology.pdf


Lim et.al ; (2011) Identification of Candidate Genes Related to Bovine Marbling Using Protein-Protein Interaction Networks; http://www.ncbi.nlm.nih.gov/pmc/articles/pmc3164149/

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