Smart Farming technologies hold the promise to bring on the next (fourth) agricultural revolution. The first agricultural revolution occurred roughly 12.000 years ago, with humans farming for the first time. The second revolution came with the reorganization of the farmland during the 17th century, while the third revolution, aka “The green revolution” or modern farming as we know it today, started in the 50s and 60s with the introduction of chemical fertilizers, pesticides, heavy agricultural machinery and novel high-yield and disease tolerant crop breeds. Now with AI being the tip of the spear, smart farming technologies promise to reduce manual labor and time spent in the field and optimize the use of resources/inputs.
Several solutions at various resolutions and scales are already available commercially, while others are at the MVP and prototype stages. Camera-based solutions enable real-time monitoring of weeds, pests, and diseases, thus allowing timely intervention and reducing the need for multiple treatments. Moreover, they can locate and quantify the size of the problem, thus adjusting the dose and the region to be targeted. Additionally, the use of spectral cameras allows for the calculation of several vegetation indexes that enable stress monitoring before being visible to the human eye, as well as the identification of important quality characteristics enabling the grower to transition from a universal approach to a more plant-specific one adjusting the use of inputs accordingly.
Besides camera-based systems, AI technologies are also used by Decision Support Systems (DSS), which include irrigation, crop, economic, environmental, meteorological models, and others, to suggest the best way of action to increase the efficiency and efficacy of resources used under the specific constraints and particularities. Through the use of DSS, the grower not only limits the resources used but also maximizes the potential of its crop.
Autonomous machinery such as sprayers and tractors enable 24/7 monitoring and action no matter the time of day and labor availability. Decoupling labor availability with agricultural tasks allows for the optimization of all tasks as they can be performed based on the crop status, even if this means that the same tasks should be repeated for each parcel/tree over an extended period.
FMIS Farm Management Information System (FMIS) takes DSS a step further by automating the recording and storage of farm data and monitoring and analyzing tasks and consumption while simultaneously recording farm expenses and the total budget. Through such software, input usage is optimized as all decision-making transitions to a data-driven approach rather than one based on farmers’ previous knowledge and intuition.
In summary, combining smart farming technologies will allow modern agriculture to produce more with less by increasing work and fuel efficiency, reducing consumables, and increasing yields. While also provides substantial benefits to the farmers themselves by reducing stress and facilitating the use of machinery and modern technology in general, as well as enabling them to make easier and more accurate forecasts.