Could smarter sensors, big data and automation bring about the second revolution in agricultural yields and food production? Many smart people working in IT, robotics and drone technology think so.
While the first “Green Revolution” (called that by USAID director William Gaud, who was describing the peaceful yet productive “revolution” brought about by agricultural improvements in the developing world) of the mid-20th century increased yields through biology and chemistry (better fertilizers, better pesticides and new crop strains), the second one could both boost production and reduce losses with the aid of better, more data-driven insights. That could be critical in a world of 9 billion-plus people that needs to see crop yields grow by 70 percent or more.
Is it possible the global food supply is really that sensitive to improvements wrought by better data and smarter machines? IBM offers some numbers to show that the answer is yes.
“‘Precision agriculture’ techniques and technologies can maximize food production, minimize environmental impact and reduce cost,” notes IBM Research. “By collecting real-time data on weather, soil and air quality, crop maturity and even equipment and labor costs and availability, predictive analytics can be used to make smarter decisions.”
Better modeling and predictions, for example, could cut weather-related crop damage by 25 percent — a significant improvement when you consider that a full 90 percent of all crop losses are caused by weather damage. Similarly, improved decision-making during food transport could help speed up deliveries, avoid weather-related delays and put a dent in the 30 percent figure of food that’s harvested but never reaches the people it’s meant for.
Autonomous systems, drones and robotics also have the potential to improve yields and reduce problems caused by weeds, insects, nutrient deficiencies in soil and other farming challenges. By making it easier to take aerial pictures of fields, develop better maps and pinpoint trouble spots, for instance, drones could help farmers monitor germinating corn and determine where replanting or a spot treatment of fertilizer might be needed.
“Plants with too little nitrogen, for example, tend to turn pale green or yellow, whereas those with enough appear dark green,” notes an essay on precision agriculture in the current issue of the journal Foreign Affairs. “Several US and European companies have developed sensors that detect greenness, generating measurements that can be used to generate a map recommending various amounts of nitrogen to be applied later.
Alternatively, the measurements can be linked directly to the nitrogen applicator to change the application rate on the go. A tractor may have a sensor mounted on the front and an applicator on the back; by the time the applicator reaches a point that the sensor has just passed, an algorithm has converted the readings into settings for how much fertilizer to apply.”
Global positioning systems have already brought a level of mapping precision to farming that was unimaginable only a decade or two ago (think about all those cool corn mazes that have now become a Halloween-time staple in many parts of the US). Just imagine how much smarter — as well as efficient and productive — agriculture might become with the aid of high-tech sensors, big data, analytics and drones. The developed world is already producing far more food with far less human labor that at any time in the past. Just imagine what it might be able to do with the addition of super-human computing power.