Embracing Disruption
Precision agriculture yielding
According to the USDA, total U.S. farm output tripled from 1984 to 2021, largely driven by advancements in technology such as precision agriculture, automation, and improved crop genetics. This remarkable achievement occurred despite declines in land use, and other traditional inputs, highlighting the growing efficiency of modern farming systems.
With that said, farming continues to face challenges, with climate change impacting crop yields through shifts in temperature and rainfall. Some estimate that even in the lowest warming scenario where we keep warming levels below 2C, global yields will decline by about 6%. At the same time, labor shortages are driving up product costs as farmers struggle to find the necessary workforce, further straining the agriculture sector. Automation and biological enhancements are poised to play a critical role in addressing these issues with companies like John Deere, Kubota, Bioceres and Lindsay leading the next wave of innovation through precision technologies.
Image 1: How could climate change affect global crop yields?
The modeled impact of climate change on global crop yields in two scenarios:
RCP2.6 – in blue – a low warming scenario, and RCP8.5 – an extreme (and unrealistic) scenario in red.
Our current emissions pathway is between these two scenarios. Temperature and carbon fertilization effects are included. Each dot is one individual crop model; the thick solid line is the mean across the 12 crop models.
Source: Adapted from Jonas Jägermeyr et al. (2021). Climate impacts on global agriculture emerge earlier in new generation of climate and crop models. OurWorldinData.org – Research and data to make progress against the world’s largest problems. Licensed under CC-BY by the author Hannah Ritchie.
Source: Image 1: https://ourworldindata.org/will-climate-change-affect-crop-yields-future#:~:text=This%20temperature%20increase%20esulted%20in,yields%20increase%20by%20around%2035%25
Geopolitics at a nano scale
Precision Farming is a key component of the modern agriculture revolutions and continues to be one of the most significant trends in contemporary farming. Early examples of precision in agriculture include using GPS to help farmers to correlate yield data with spraying and planting data to optimize crop planting and management across small subsections of their fields. Since then, geo-location has improved drastically, to the point where one can use GPS for everything from tractor guidance which helps to optimize routes, to creating detailed fertilizer application maps to allow farmers to input what exactly the plants need, reducing runoff and overfertilization, reducing costs and increasing plant yields. John Deere, a leader within the space has even gone one step further to use machine vision technology to spot green weeds againts the backdrop of brown soil and activate nozzles to spray only the weeds, also allowing farmers to reduce the amount of herbicide they use, saving money and lessening their impact on the environment. Kubota, a Japanese agricultural leader, has developed precision farming technologies like the KSAS “taste-yield combine harvester,” which measures yield, protein, and water content in rice fields during harvesting. This data allows for optimized fertilizer application, enhancing the taste and nutritional value of rice while reducing reliance on traditional, intuition-based farming methods.
The technologies used in farming are constantly evolving and the Internet of Things (IoT), Big Data analysis and AI are all being used to make more informed decisions. For example, smart irrigation systems can use IoT sensors to monitor soil moisture, temperature and humidity, and communicate with an irrigation controller to adjust watering schedules based on real-time data, ensuring crops receive the right amount of water. Lindsay is a leader in smart irrigation through its FieldNet platform which uses real-time weather data and field-specific conditions to adjust irrigation schedules, allowing farmers to efficiently manage water use from their phone without manual intervention. Big Data analysis aggregates data from satellites, drones, and field sensors to generate actionable insights. For example, farmers can use historical yield data, weather patterns, and soil conditions to predict optimal planting times and crop rotations. AI takes this further by processing vast amounts of data to detect patterns and provide recommendations. AI-powered tools, such as autonomous tractors or pest detection systems, can adjust operations dynamically, enhancing productivity while minimizing waste. Bioceres advances precision agriculture through its HB4® droughttolerant crops, a breakthrough that enables farmers to optimize their resource use, particularly water, in water-scarce environments. These precision crops, genetically designed for higher resilience to droughts, help farmers improve yield while reducing environmental impact, further enhancing farm efficiency and sustainability. Together, these advancements make farming more precise, efficient, and sustainable.
