ARTIFICIAL INTELLIGENCE IN AGRICULTURE: BOOSTING PRODUCTIVITY AND EFFICIENCY

Artificial intelligence (AI) in agriculture has had a great growth and positive impact on current production processes. 

Technology is advancing more and more every day and it is a great opportunity to make processes more efficient and increase productivity in the field to gain competitiveness and, therefore, generate a better return on investment. 

In this article, we will explain what artificial intelligence in agriculture is, what technologies you can use and all the benefits it offers. 

WHAT IS ARTIFICIAL INTELLIGENCE IN AGRICULTURE?

Artificial intelligence in agriculture consists of applying all the technology available, with the main objective of optimizing and improving the tasks performed during the cultivation processes. 

These are advances that are created from computer programs to execute actions comparable to those that would be carried out by a person and to be able to solve problems more efficiently, also increasing productivity. 

INFLUENCE OF ARTIFICIAL INTELLIGENCE IN AGRIBUSINESS

Artificial intelligence technologies provide the possibility of improving a large number of tasks performed during agribusiness processes, such as:

• Real-time change monitoring
• Pest control and elimination
• Soil quality check
• NDVI (Normalized Difference Vegetation Index) formula application
• Real-time data analysis

Artificial intelligence in agriculture can help in upstream, midstream and downstream processes, i.e. from data collection to data analysis and implementation of actions or changes according to what is detected to be needed.

This has helped agribusinesses to become much more efficient and profitable, being able to provide better products at lower prices, without losing quality. 

WHAT IA TECHNOLOGIES CAN BE APPLIED IN AGRIBUSINESS?

Currently, there are several artificial intelligence technologies that can be implemented in agribusiness. 

The three main areas where AI can be applied in agriculture are:

• Predictive capabilities
• Agriculture-oriented robotics
• Soil and crop monitoring and assessment via IoT

Let's look at each one specifically so you know how to leverage this technology within agribusiness.

1. IoT y Big Data

IoT (internet of things) and Big Data are two of the main areas where AI can help farmers and experts in this sector. 

The scope of big data applications is very broad, as it can provide relevant information on rainfall patterns, fertilizers, crops to be monitored or planted, harvest dates, and so on. 

In terms of IoT, the most important advances are in the use of sensors, drones and other technologies to know soil quality, moisture levels, nutrients, irrigation and much more. 

One example is the German-based technology company PEAT, which developed the Plantix app, based on AI, which can identify nutrient deficiencies in the soil, pests, plant diseases and more so that farmers have information on which fertilizers to use on each crop to improve crop quality.

2. Deep Learning

Deep Learning is a recent and innovative AI technique that has been developed to process images and analyze data in order to identify and solve problems in time or prevent them. 

This has particular relevance for meeting the challenges of agriculture, in terms of production, productivity, impact on the environment and sustainability. 

One of the advantages of Deep Learning is that it focuses on function learning, i.e., automation in raw data mining, which can help solve more complex problems faster. 

In application, one of the great functions of Deep Learning is in species breeding, because from field data, the performance of crops in different climatic conditions is analyzed and it is possible to predict which genes could contribute more to a plant. 

3. Robots

In the near future, robots are expected to play an important role in artificial intelligence in agriculture. 

Companies such as John Deere already use AI in their processes and machine learning in their equipment, which has helped farmers to be more successful in their crops and reduce environmental impact. 

Some of the functions that robots can currently perform in agriculture are:

• Identify crop conditions and apply corresponding products (chemicals, fertilizers, irrigation).
• Manipulate products through collaborative arms, for example, to harvest fruits.
• Collecting and converting or analyzing information useful for agribusiness experts
• Avoid food waste

4. Machine Learning

Machine Learning is an AI technology that continues to grow and improve. In agriculture, it is used to create and understand algorithms that can help farmers in terms of weather conditions. 

With this, it is possible to foresee when there will be storms or any situation that could affect crops, and in this way, reduce the losses that could occur. 

Machine Learning algorithms can help in:

• Soil management (studying evaporation, temperature and soil moisture processes and their impact).
• Water management
• Livestock production (predictions to optimize the economic efficiency of livestock production systems).

ADVANTAGES OF ARTIFICIAL INTELLIGENCE IN AGRICULTURE

Implementing artificial intelligence in agriculture offers many advantages and benefits to producers at all stages of the production and cultivation process, as it allows everything to be directed towards precision agriculture in a more efficient way.

Among these advantages, the following stand out:

1. POSSIBILITY OF PREDICTING FUTURE SCENARIOS.

The use of algorithms such as Big Data, Deep Learning and Machine Learning helps predict future production scenarios.

Thanks to this, farmers can foreshadow crop conditions and conditions, i.e., know what their crop will be like, crop yields and techniques that could make their results more efficient.

2. INCREASED EFFICIENCY

AI technology also has a very important positive impact on precision agriculture, as it allows the detection of specific problems and provides concrete solutions based on them.

One example is artificial intelligence sensors, which are responsible for detecting weeds and attacking them so that they do not grow. They also provide solutions, such as information on the herbicides that should be applied.

3. INCREASES PRODUCTIVITY

Soil has different behaviors and characteristics according to the environment in which it is cultivated. 

In this sense, technology has advanced greatly and artificial intelligence in agriculture makes it possible to determine what to plant, where, and when and it is even possible to predict the volume of harvests. 

In addition, AI allows robots to carry out repetitive and optimization tasks to make everything more automated and without human intervention, streamlining many processes. 

With this data and assistance, it is much easier to achieve good crop results, respond to consumer demands and achieve more with less effort.

4. GREATER CERTAINTY

Artificial intelligence makes it possible to process a large amount of data, process it and convert it into useful and valuable information for farmers and experts, providing greater certainty about all processes: pre-harvest, harvest and post-harvest. 

Applying AI in agriculture offers the possibility of performing tasks with greater precision than humans can. Some machines can even make automated decisions.

In addition, there are factors or elements that may be undetectable to the human eye. This is solved by AI technology. 

In this way, there can be more guarantees and security about the investments that should be made from data analysis.

DISADVANTAGES OF ARTIFICIAL INTELLIGENCE IN AGRICULTURE

The advantages of artificial intelligence in agriculture are very important and worthwhile, but it is also important to consider the disadvantages for everything to work properly. 

These disadvantages, in reality, are not specific to AI, but rather have to do with the lack of training or knowledge of those who wish to implement this technology in their agribusiness.

1. DEFICIENCIES IN DATA PROCESSING

Often, the data obtained from AI is provided in isolation or is not interpreted and is believed to be of low quality, which can be a major challenge for agribusinesses. 

This can only be avoided with a well-designed strategy to extract AI data in an organized, consistent way and to help interpret it in a professional, expert manner.

Otherwise, the information will not be useful and will not help companies in the different production processes. 

2. UNQUALIFIED PROFILES FOR IA USE

Another obstacle often encountered in the implementation of AI in agriculture is the shortage of personnel with the skills and experience to handle the technology to be implemented. 

It is very important to study the profiles for a successful implementation. In the event that trained personnel are not available, the most effective solution is business consulting. 

With the help of experts, it will be much simpler and more productive to implement AI in agribusinesses, in addition to having greater guarantees and ensuring that it is a good investment.

3. COST AND IMPLEMENTATION TIME

The cost and time to implement artificial intelligence in agriculture is a key factor that must be taken into account when taking this step. 

Companies that do not have experience in this process and need external help, have to evaluate the price and the time that this change will take to be profitable and successful. 

It should be considered the option of receiving advice for the implementation, but also for the maintenance of the technologies if there is no area of expertise in this type of AI tool.

Many times, it is not considered and problems arise at the time of use and exploitation, so there must be clarity in this aspect so that there are no misunderstandings or a bad experience in the use of AI in agriculture.

Conclusion

Artificial intelligence in agriculture makes the work carried out in this sector more efficient, dictating precise orders to machines on how to treat the soil, conserve and obtain higher quality products with greater efficiency.

Thanks to these technologies, it is possible to monitor and pay attention to crops 24 hours a day, generating incredible results. It not only helps farmers to automate processes, but also helps in precision and to obtain higher yields with fewer resources without sacrificing quality. 

AI has become a key resource for companies to become more competitive and to achieve higher returns on investment in production environments. 

For this reason, it is very important to take the step towards the use of more recent technologies, but always in the hands of experts, who guarantee a correct transition to make the most of the resources and the investment made in this process.