Agrosavia and Adintelo developed an application to analyze soil samples in record time. Thanks to this new IA solution, Agrosavia now has a faster response time and can reach many more farmers with their fertilizer recommendations.
The Colombian Corporation for Agricultural Research, AGROSAVIA:
The purpose of the institution is to work in the generation of scientific knowledge and agricultural technological development in order to improve the competitiveness of production and equity in the distribution of the benefits of sustainability in the use of natural resources.
How we created a better way of understanding the soil:
Challenge:
How we improved the way Agrosavia was processing the lab result data. One of the main difficulties faced by the farmers at the time of knowing what is the best option for their soils in terms of minerals and fertilizers.
Given the large number of recommendation requests saturated the team at Agrosavia, making it impossible to fulfill the farmers’ needs in an efficient manner.
For this reason, Agrosavia looked for an ally that would allow it to facilitate and maximize these processes so that the farmers could have the soil samples quickly and efficiently, to achieve this, the following challenges had to be overcome:
- This application had to be faster than the agricultural engineers, in order to reduce critical times in the analysis of soil samples.
- Be able to obtain and provide information that would expose the reality of the soils and thus have accurate data.
Adintelo had in his hands the challenge of making millions of farms more fertile and improve the Agrosavia’s soil research process.
The solution:
Adintelo help to improve the research and development process to find the best strategy to give solutions to Agro Savia’s needs:
- A user-friendly web application: This application allows the expert scientist to see a prediction based on the data entered, giving him the option to accept or reject it.
- The application uses artificial intelligence to predict the elements and minerals needed for the sample to grow the desired type of crop.
- Hardware-Software: Adintelo team brought expert programmers in Python, Scikitlearn, XGboost, Kubernetes, Fast API, and NoSQL databases.
The Results:
The application developed by Adintelo yielded the following results for the improvement of the soil analisis process at Agrosavia:
- Accelerated and automated the process of fertilizer prediction using AI.
- Automatic generation of results in pdf format
- Increase the number of samples processed by 200 percent.
- Facilitate the cycle of verification of fertilizers for use on the land.
In summary, Adintelo developed a web application that through machine learning allows to give indications on land use to Agrosavia scientist, significantly reducing the delivery times of results and making more efficient the process of land use.
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