The concept of precision agriculture, in its current form, appeared in the United States in the early 1980s. In 1985, researchers from the University of Minnesota varied the contributions of calcium fertilizers in agricultural plots. It was at this time that the practice of grid-sampling (collection of samples on a fixed network of one point per hectare) appeared. Towards the end of the 80s and thanks to the extractions carried out through samples, the first recommendation maps for modulated contributions of fertilized elements and for pH corrections appeared. The evolution of technologies allowed the development of performance sensors and their use, together with the appearance of GPS, has not stopped growing until currently reaching several million hectares covered by these systems.

Throughout the world, precision agriculture is developing at different rates depending on the country. Among the pioneering countries we find, of course, the United States, Canada and Australia. The Latin American country most involved with this crop management methodology, both in adoption rate and in the development of highly complex agro-components, is without a doubt the Argentine Republic, a country that, thanks to the efforts of the private sector and official research institutions, today has a large amount of area planted under this modality and a significant number of very well-trained professionals for this new paradigm of modern agriculture. In 1995, technological innovation was applied for the first time in grain production at the EEA Manfredi of the National Institute of Agricultural Technology INTA, who created an Argentine map of the yield of a grain harvest.[5] Another Latin American country that is emerging as a great demander of this type of technology is Brazil. The current scenario of agriculture in Brazil is moving towards efficient production with environmental protection, therefore, Embrapa established the Brazilian Precision Agriculture Research Network, with the objective of generating knowledge, tools and technologies for precision agriculture applied to soybean, corn, wheat, rice, cotton, grasses, eucalyptus, pine trees, grapes, peaches, oranges and sugar cane crops.

In Europe, the precursors were the English, closely followed by the French. In France, precision agriculture appeared in 1997-1998. The development of GPS and modular recreation techniques helped to entrench these practices. Currently, less than 10% of the French agricultural population is equipped with modulation tools of this type. GPS is more widespread. But this does not prevent them from using services, which provide recommendation maps by plots, considering their heterogeneity.[6]​.

The reduction in the amounts of nitrogen supplied is significant, which usually generates better performance. Therefore, the return on investment is achieved at several levels: savings in the purchase of phytosanitary products and fertilizers, and better valorization of the crops.[7]​.

The second positive effect, on a larger scale, of these targeted contributions, geographically, temporally and quantitatively, refers to the environment. In fact, providing the correct dose in the ideal place and at the optimal time can only benefit the crop, the soil and the water tables, and, in this way, the entire agricultural cycle.

Therefore, precision agriculture has become one of the pillars of sustainable agriculture, since it is respectful of crops, lands and farmers. Sustainable agriculture is understood as an agricultural production device that aims to guarantee perennial food production, respecting the ecological, economic and social limits that guarantee the maintenance of this production over time.

Therefore, precision agriculture does nothing more than put high technology at the service of this respectable and laudable ambition.[8]​.

Precision agriculture is a field of application of new digital technologies:

• - Robots.

• - Autonomous vehicles[9]​.

• - Satellite and drone images.

• - Internet of Things (IoT, Internet of Things).

• - Mobile applications.

• - Machine Learning.

• - Nax precision agriculture.

• - Bioo 100% sustainable sensor: It does not require batteries of any kind, since it has plants that work as a biological switch. They generate a bacteria from organic substances found in the soil, which then gives energy to said device.[10]​.

• - InfoAg Conference.

• - European conference on Precision Agriculture (ECPA) (biennial, in odd years).

• - International Conference on Precision Agriculture (ICPA) (biennial, in even years).

• - Chronology of agriculture and food technologies.

• - Geographic information system.

• - DSSAT.

• - Embrapa, precision agriculture in Brazil.

• - Precision Agriculture Manual.

• - Precision Viticulture Manual.

• - https://www.ispag.org/.

• - Research Group on Agrotics and Precision Agriculture, University of Lérida.

• - Precision Agriculture Argentina Site.

• - Site of Argentina Industrialization of the countryside.

Contenido

Se puede distinguir cuatro etapas en la implementación de técnicas de agricultura de precisión que tome en consideración la heterogeneidad espacial:.

Geolocation of information

The geolocation of the plot allows the available information to be superimposed on the latter: soil analysis, analysis of nitrogenous remains, previous crops, soil resistivity. Geolocation is carried out in two ways:

• - physical delimitation with the help of an on-board GPS, which requires the operator to travel to the plot;

• - cartographic delimitation based on an aerial or satellite image. To ensure geolocation accuracy, these background images must be adapted in terms of resolution and geometric quality.

Characterization of heterogeneity

The origins of variability are diverse: climate (hail, drought, rain, etc.), soil (texture, depth, nitrogen phosphorus and potassium content), cultivation practices (no-till sowing), weeds, diseases.

Several permanent indicators (mainly related to the soil) allow the farmer to stay informed about the main constants of the environment.

Other specific indicators keep you informed about the current state of the crop (development of diseases, water stress, nitrogen stress, lodging, damage caused by frost, etc.).

The information can come from weather stations, sensors (soil electrical resistivity, naked-eye detection, satellite images, etc.).

The measurement of resistivity, completed by pedological analysis, results in precise agropedological maps that allow the environment to be taken into account.

Decision making: two strategies that can be adopted in the face of this heterogeneity

Based on the agro-pedological maps, the decision on the modulation of inputs in the plot is made based on two strategies:

• - the preventive approach: it is based on an analysis of static indicators during the campaign (soil, resistivity, plot history, etc.).

• - the management approach: the preventive approach is updated thanks to periodic measurements during the campaign. These measurements are carried out:

• through physical samples: weight of biomass, chlorophyll content of leaves, weight of fruits, etc.,

• through proxy-detection: sensors on board the machines to measure the state of the foliage but that require total surveying of the plot,

• through aerial or satellite remote sensing: multispectral images are acquired and treated so that maps can be created that represent different biophysical parameters of the crops.

The decision can be based on Decision Support Systems (agronomic crop simulation models and recommendation models, for example DSSAT), but it depends above all on the farmer, depending on the economic interest and the impact on the environment.

Implementation of practices to compensate for these variabilities

Information and communication technologies (ICT) allow the modulation of cultivation operations within the same plot to be more operational and facilitate use by the farmer.

The technical application of modulation decisions requires the availability of appropriate agricultural material. In this case we speak of VRT or variable index technology (example of modulation: sowing with variable density, application of nitrogen, application of phytosanitary products).

The implementation of precision agriculture is easier thanks to the equipment installed on tractors:.

• - Global positioning system (for example, GPS receivers that use satellite transmissions to determine an exact position on the globe).

• - Geographic information system (GIS): programs that help manipulate all available data.

• - Agricultural material that can practice variable index technology (seeder, fertilizer spreader).

The concept of precision agriculture, in its current form, appeared in the United States in the early 1980s. In 1985, researchers from the University of Minnesota varied the contributions of calcium fertilizers in agricultural plots. It was at this time that the practice of grid-sampling (collection of samples on a fixed network of one point per hectare) appeared. Towards the end of the 80s and thanks to the extractions carried out through samples, the first recommendation maps for modulated contributions of fertilized elements and for pH corrections appeared. The evolution of technologies allowed the development of performance sensors and their use, together with the appearance of GPS, has not stopped growing until currently reaching several million hectares covered by these systems.

Throughout the world, precision agriculture is developing at different rates depending on the country. Among the pioneering countries we find, of course, the United States, Canada and Australia. The Latin American country most involved with this crop management methodology, both in adoption rate and in the development of highly complex agro-components, is without a doubt the Argentine Republic, a country that, thanks to the efforts of the private sector and official research institutions, today has a large amount of area planted under this modality and a significant number of very well-trained professionals for this new paradigm of modern agriculture. In 1995, technological innovation was applied for the first time in grain production at the EEA Manfredi of the National Institute of Agricultural Technology INTA, who created an Argentine map of the yield of a grain harvest.[5] Another Latin American country that is emerging as a great demander of this type of technology is Brazil. The current scenario of agriculture in Brazil is moving towards efficient production with environmental protection, therefore, Embrapa established the Brazilian Precision Agriculture Research Network, with the objective of generating knowledge, tools and technologies for precision agriculture applied to soybean, corn, wheat, rice, cotton, grasses, eucalyptus, pine trees, grapes, peaches, oranges and sugar cane crops.

In Europe, the precursors were the English, closely followed by the French. In France, precision agriculture appeared in 1997-1998. The development of GPS and modular recreation techniques helped to entrench these practices. Currently, less than 10% of the French agricultural population is equipped with modulation tools of this type. GPS is more widespread. But this does not prevent them from using services, which provide recommendation maps by plots, considering their heterogeneity.[6]​.

The reduction in the amounts of nitrogen supplied is significant, which usually generates better performance. Therefore, the return on investment is achieved at several levels: savings in the purchase of phytosanitary products and fertilizers, and better valorization of the crops.[7]​.

The second positive effect, on a larger scale, of these targeted contributions, geographically, temporally and quantitatively, refers to the environment. In fact, providing the correct dose in the ideal place and at the optimal time can only benefit the crop, the soil and the water tables, and, in this way, the entire agricultural cycle.

Therefore, precision agriculture has become one of the pillars of sustainable agriculture, since it is respectful of crops, lands and farmers. Sustainable agriculture is understood as an agricultural production device that aims to guarantee perennial food production, respecting the ecological, economic and social limits that guarantee the maintenance of this production over time.

Therefore, precision agriculture does nothing more than put high technology at the service of this respectable and laudable ambition.[8]​.

Precision agriculture is a field of application of new digital technologies:

• - Robots.

• - Autonomous vehicles[9]​.

• - Satellite and drone images.

• - Internet of Things (IoT, Internet of Things).

• - Mobile applications.

• - Machine Learning.

• - Nax precision agriculture.

• - Bioo 100% sustainable sensor: It does not require batteries of any kind, since it has plants that work as a biological switch. They generate a bacteria from organic substances found in the soil, which then gives energy to said device.[10]​.

• - InfoAg Conference.

• - European conference on Precision Agriculture (ECPA) (biennial, in odd years).

• - International Conference on Precision Agriculture (ICPA) (biennial, in even years).

• - Chronology of agriculture and food technologies.

• - Geographic information system.

• - DSSAT.

• - Embrapa, precision agriculture in Brazil.

• - Precision Agriculture Manual.

• - Precision Viticulture Manual.

• - https://www.ispag.org/.

• - Research Group on Agrotics and Precision Agriculture, University of Lérida.

• - Precision Agriculture Argentina Site.

• - Site of Argentina Industrialization of the countryside.