Could Quantum Computing Help Feed the World?

How the Agtech Revolution will Change with Quantum Computing

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One in three men, women, and children around the world suffers from malnutrition of some sort. Food security is one of the greatest problem we face; so much so, that the United Nations has named Zero Hunger Goal 2 of its 17 sustainable development goals, second only to complete eradication of poverty. One of the promises of quantum computing has been that it could help solve world hunger. Could those whirling qubits really put food into the bellies of 821 million hungry people every day?

Perhaps it isn’t clear exactly how quantum computing could end world hunger. The answer lies in the way fertilizer is made – principally from ammonia. The Haber-Boschprocess, by which this chemical compound is made, is long due for an upgrade since its creation in the early 1900s. It is expensive, like most high pressure high heat processes, and the catalysts used have changed little in industry since its nascence. The ammonia industry is not only important to the way we grow food in America and around the world but also represents a substantial segment of the economy. The global ammonia market is projected to grow to USD 76.64 billion by 2025 in a recent estimate.

Quantum computing comes into play by providing a new way to improve the catalysts used in the production of ammonia. A catalyst, by definition, lowers the activation energy of a reaction, meaning it takes less energy input (generally in the form of heat) to cause the forward reaction. Finding a better catalyst could dramatically reduce the cost of Haber-Bosch process by reducing the overhead necessary for heat and pressure in the reaction. In a hunt for a better catalyst, a researcher might proceed by first categorizing families of catalysts, then further subcategorizing them, then using heuristics to select a few ideal candidates to test in the process. Besides labor intensive laboratory experiments, these catalysts could be tested by molecular dynamics simulations to collect data on the probabilistic interactions between molecules involved in a given reaction and calculate the activation free energy. The problem is that there aren’t just a few catalysts. There are thousands. Working through all of these compounds is time intensive, to say the least. These modeling studies may run for hours or days at a time. An iron catalyst has been used in the Haber-Bosch process for the past century, and finding a better one would take another, even on the world’s fastest computers. A quantum computing modeling ability will make uber-difficult modeling calculation relatively inexpensive, in terms of time to compute, and will increase the number of catalysts testable in a short amount of time.

That said, no amount of fertilizer or technological advancement will “feed the world,” given how we as a global economy manage food demand currently. Agricultural subsidy in the U.S. results in 60 million tons of produce (that’s a whopping half of American produce) being thrown out every single year. As one of the largest producers of staple crops like maize (Zea mays L., corn), wheat, and soy, the U.S is responsible for a devastating amount of waste, representing a third of all food stuffs in the world. Without delving into the ethical and environmental dilemma of agricultural incentives, suffice it to say this sets a precedent for future advancements in ag tech made possible by quantum computing. Who will benefit from the discovery of a better Haber-Bosch catalyst? It won’t be the starving people in third world countries or even those who go hungry in developed nations; more likely, those to benefit from this kind of discovery are unfamiliar with the immediacy of true hunger.

Before quantum computing, it could be argued the last major, paradigm shifting advancement in agriculture was the advent of genetically modified (GM) crops, or as they are commonly referred to, GMOs – genetically modified organisms. One of the great promises of these GM crops was to feed the world by increasing crop yield. (Yield is produce per acre.) Scientists created super crops that would allegedly grow more robustly: faster, plumper, and more resistant to natural stressors. A 2014 paper by Heinemann in the International Journal of Agricultural Sustainability, however, challenged claims of higher yield in GM crops. Maize, rapeseed (Brassica napus L., canola), soybean and cotton yield data were compiled and modeled, and Heinemann demonstrated that the United States and Canada did not experience improved yield when compared to the same non-GM crops in Western Europe countries of Austria, Belgium-Luxembourg, France, Germany, Netherlands and Switzerland. In fact, the growth in yield trended lower than that of the European countries. While these conclusions may be controversial, it is clear that GM crops are not the sweeping solution to world hunger that was sold to consumers.

Although farmable land is a resource not equally available to all regions of the world, the problem with world hunger has never lie primarily with a dearth of food. Rather, the problem is in how we gratuitously waste food. Perhaps with the change of our approach to the AG industry in general and how we, as global citizens, manage food security, the use of quantum computing can develop in a way that leads to feeding more hungry people.

QC will solve problems in ways we probably cannot even imagine yet. Still, we should be pragmatic in our hopes for humankind’s use of technology, given our track record. As we launch into a new era, where quantum technology is pitted as a saviour of men, it may be helpful to reframe the problem statement. In the final analysis, new tech rarely, if ever, solves a long-standing social problem without socio-political change preceding it.

Could quantum computing help feed the world? The answer is yes, it could – if we let it.