By Adrian Gracia Romero PhD in Plant Phenotyping and Remote Sensing. AESA certified Drone Pilot.
One of the biggest challenges facing agriculture today is to meet the high food demand of a growing population, with the added challenge of improving crop productivity under the pressures of climate change. Among the main factors that will contribute most to crop yields are changes in precipitation and temperature patterns through periods of drought and heat waves, as well as loss of soil fertility.
To improve crop productivity under these conditions, it is vital to adopt better agricultural practices that offer resource optimization such as adjustments in irrigation systems. The digitization of this process is known as precision agriculture and encompasses activities that use information about the variability of a crop within a single plot to improve its management. These strategies work by grouping data from different sources in order to detect the presence of an irregularity in a field, study the reason for it and thus help the farmer in making decisions. Some examples of these situations are uneven application of resources such as fertilizers or irrigation system, differences in soil structure and composition, variability in crop density due to planting problems, or the appearance of weeds or diseases in the crop. This knowledge allows to better address problems in a localized manner, reducing costs and avoiding unnecessary use of excess resources. In this way, the application of precision farming strategies not only aims at agronomic benefits, but an improvement in the efficiency of resource management will reduce costs to the farmer and produce a lower environmental impact. In addition, in the long term, the farmer will have a large amount of data that will allow him to know his plot better and thus plan better.
Almost by definition, today’s precision agriculture strategies use remote sensing tools and methodologies, ranging from information extracted from satellites and light aircraft to cameras loaded on drones. These technologies can be used in conjunction with other climatic or soil-related sensors to monitor the main environmental constants.
The development of these technologies plays a vital role in the current objectives of meeting food demands in a more sustainable manner. For this reason, governments and large companies are paying close attention and funding the development of innovative precision farming technologies to better manage and maintain competitiveness in the agricultural sector. One example is the Canadian government, which this year has invested $875,000 in projects aimed at improving disease and pest control in different crops. [ https://www.canada.ca/en/agriculture-agri-food/news/2022/02/government-invests-in-precision-agriculture-to-enhance-competiveness-and-efficiency.html ].
At present, the application of artificial intelligence systems and machine learning to all this large amount of data helps to better understand the heterogeneity of the plot with high precision and thus develop predictive models of production and quality. At HEMAV we work on the development of models based on historical information combined with real-time satellite and meteorological data to offer our customers the highest accuracy in forecasting productivity throughout the crop cycle. In this way, the Ag-Tech digital platform provides updated information on the development of the crop, supporting the farmer in making decisions and optimizing the harvest.