As we discussed in the Machine Learning: A Primer to Laboratory Applications blog, artificial intelligence (AI) and machine learning (ML) are helping researchers across many different industries uncover meaning in the massive amounts of data they collect and produce. The agriculture market is rapidly adopting these technologies. MarketsandMarkets forecasts the AI in agriculture market will grow from $600 million in 2018 to $2.6 billion by 2025.
What’s driving this market growth? Research suggests the leading factor could be population growth. The global agriculture sector is facing major challenges from the lack of sufficient production with respect to the growing population. In the Artificial Intelligence: Applications and Global Markets report, BCC Research projects that the agriculture sector needs to improve its production levels by over 70 percent to meet the demand of an expected global population of 9 billion by 2050. AI and ML are expected to play a key role in overcoming this challenge.
AGROSAVIA Brings AI to the Field
One organization implementing AI to address these challenges is AGROSAVIA (Colombian Corporation for Agricultural Research). AGROSAVIA’s mission is to contribute to technical change and improve productivity and competitiveness of the Colombian agricultural sector. As a public organization that operates independent of the Colombian government, AGROSAVIA uses research to drive scientific knowledge and development of agricultural technology in Colombia. Their network of laboratories is among the most comprehensive and modern infrastructures in the country.
Working with the government of Colombia through the agency Ministry of Information Technologies and Communications (Ministerio de Tecnologías de la Información y Comunicaciones), AGROSAVIA launched an initiative to optimize the soil analysis process. The project provides farmers with data-driven recommendations for crop fertilization before the planting season, with the goal of increasing crop output.
To execute this ambitious project, AGROSAVIA implemented Thermo Scientific™ SampleManager LIMS™ software to manage their network of laboratories, centralize the soil data and make it accessible to the farming community. SampleManager LIMS software connects with IBM Watson™ to utilize its AI capabilities. IBM Watson uses soil analysis data from SampleManager LIMS software and predicts which nutrients each crop needs. IBM Watson analyzes more than 10,000 fertilization plans and 10,000 soil studies when obtaining its model and algorithm. The fertilization plans detail the amount of nutrients that will be provided (e.g., Nitrogen, Phosphorus, Potassium, Calcium, Magnesium, Sulfur, Iron, Manganese, Zinc and Boron). The plans specify the amendment dose needed, fertilizer dose, and time to apply. The fertilization plans are also validated by an agronomist. The agronomist’s interaction with IBM Watson enables the tool to learn from revisions and improve its prediction. 
Early Results help Farmers Embrace AI
By using SampleManager LIMS software with IBM Watson, AGROSAVIA has doubled the agronomists’ ability to carry out fertilization plans. Before the project, agronomists completed 18 recommendations/day. Using the new system, they’re completing 36 recommendations/day. AGROSAVIA has convinced farmers of the importance of the project, and provided the tools needed to help farmers participate.
Farmers from around the country are sending their soil samples to AGROSAVIA, with the information captured and managed in SampleManager LIMS software. Automation from SampleManager LIMS software has made sample collection easier, improved the presentation of the fertilization plans, and increased sample traceability.
AGROSAVIA expects even greater results as the program matures. The program currently includes fertilization plans for more than 200 crops. As additional plans are developed for each crop, the prediction models will continue to improve.
This blog is the second in a series detailing how Thermo Fisher software applications can support the use of advanced digital technologies, such as AI, to accelerate science. For more information about how AGROSAVIA is advancing agricultural technology in Colombia, read the SampleManager LIMS Agrosavia case study.
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