The stages of precision agriculture don’t necessarily develop individually, but as an integrated and synchronized system.

 

The term “precision agriculture” gained ground in Brazil from 1995, following the importation of mechanical harvest equipment with productivity mapping systems - a revolution at the time for enabling a deep investigation of the spatial variability in the crops' productivity. 

However, as Embrapa Milho e Sorgo researcher Evandro Mantovani presented at the round table on Precision Agriculture of the 1st Northeast Regional Symposium on Geoprocessing and Remote Sensing - promoted by Embrapa Tabuleiros Costeiros em 2002 -, “this technological innovation, besides being an excellent management tool for production fields, is only the first stage of precision agriculture’s cycle. Collecting information in the field is essential because the data allows the systematization and analysis of the diagnoses, supporting the decision-making process about the appropriate management and how to apply it in the crop.

However, data collecting is only the first step.Which and how many are all the steps of precision agriculture is exactly the subject of this article. Here you will get to know about:

Step 1 - Data collection in precision agriculture
Step 2 - Compilation and analysis of precision agriculture data
Step 3 - Planning and decision-making in precision agriculture
Step 4 - Specific located application in the field

Have a good read!

Step 1 - Data collection in precision agriculture

In conventional agriculture, the variabilities of a crop are disregarded in planning and defining the management practices to be implemented, and the inputs are applied uniformly based on an average. 

This practice can lead to crop mismanagement, since input applications are made in larger or smaller doses than necessary in many regions of the farm, resulting in higher costs, lower productivity, and consequently, lower rentability in agribusiness.  

With precision agriculture, it began to be considered that the management of heterogeneity in crops must be constantly carried out through four stages.

Therefore, the first step is collecting agricultural information, responsible for investigating the variability, both in production factors (soil, water presence, plant nutrition, etc.) and productivity (bags per hectare).

Thus, the fundamental strategy of precision agriculture is to previously recognize the variability in production or even in plantation development through sensing techniques, in order to identify the responsible agents for non-uniformity.

However, before we move on to explain the next stages of precision agriculture, it is important to understand that those do not have a direct correlation with the phases of the crop, and each step can be used at different points of the plantation. 

That being so, the step 1 of data collection can - and should - be carried out both in the soil preparation phase and during plant development - or even so in harvesting. 

Step 2 - Compilation and analysis of precision agriculture data

As we explained, the data collection in precision agriculture is constant and at all crop’s phases. Yet, merely collecting data does not mean diagnosing a problem, let alone that the solution is given.

To precision agriculture makes sense for those who invested in it, the collected data needs to be compiled, analyzed, and understood so that the agronomist can propose an appropriate management.

At this stage, tables, graphs, and georeferenced diagnostic maps are generated with information and image processing through softwares, systems, and applications especially developed for precision agriculture, where it is possible to cross and interpolate a large amount of data and produce high-density maps.

Again, it is important to emphasize: this compilation and analysis of data occurs constantly and at all stages of a crop.

From diagnostic maps, using the knowledge obtained with data analysis, agronomists and farmers can optimize their agriculture practices to increase yield, reduce waste, and minimize environmental impact. This can lead to significant cost savings, as well as higher profitability and sustainability. 

The compilation and analysis of data in precision agriculture are critical components of modern agricultural practices, as there is still a lack of qualified professionals to process, understand, and propose data-based management. 

Step 3 - Planning and decision-making in precision agriculture

Agronomic diagnostic maps, whether of fertility, soil compaction, NDVI index, or others, are the “X-Ray of the crop” - the most complete information that the agronomist and the producer have to support decisions.

It is from the analysis and interpolation of the data obtained in the field that these maps are generated, and then the agronomist or directly the producer can plan the adequate management for each point of the crop.

It is at this moment that the agronomist’s technical knowledge allows them to interpret the diagnostic maps and quickly identify the variability of the area, proposing the most adequate and precise management for every region of the crop through variable rate recommendation maps.

The action proposed by the agronomist through these recommendation maps can be either of localized management of more or less seeds, irrigation, fertilizers, amendments, or agrochemicals. In short, everything with the aim of optimizing costs and ensuring that each area of the crop has the maximum possible productivity.

Just like all the stages of precision agriculture, the recommendations can be made by the agronomist either before or during the planting, or even in plants’ development.

Step 4 - Specific located application in the field

As discussed, data collection and analysis are the foundation of precision agriculture. However, it is in the application stage that all of the investment in it turns into real gain for the agribusiness. 

In traditional agriculture, the process of irrigation, fertilization, and phytosanitary pesticides, for example, are carried out equally throughout all areas. On the other hand, in precision agriculture it is considered that the regions of a crop are not homogeneous and have variabilities that can - and should - be taken into account.

From this understanding, a widely used term in all precision agriculture applications emerged: variable rates.

To obtain it, all data collected in the first stage are processed and georeferenced in order to identify crop areas that require more or less interference. 

The result is a more efficient application. Regions less fertile or with higher incidence of pests and diseases receive fertilizers, agrochemicals, irrigation, and even differentiated doses according to the local needs.

It is important to emphasize that the stages of precision agriculture do not necessarily develop individually, but rather as an integrated system where the application of a management (step 4) can often occur simultaneously with a data collection (step 1).  

This is what happens, for example, in harvesting grains, in which modern harvesters already collect data regarding location (GPS) and productivity as they harvest in each plot. 

Other examples happen in irrigation, which can occur simultaneously with soil moisture measurement, or in the spraying of agricultural chemicals, which can be carried out at the same time as measuring the NDVI index. 

As we have observed, steps 1 (collection of crop information) and 2 (compilation and analysis of data) are the foundation of precision agriculture, without which no localized or variable management is possible.

Without these steps, all agronomic management would still be based on the general average of the crop, and this would not characterize precision agriculture.