Data Science and Agriculture

This new Scicrop blog is intended to introduce data science concepts to the agricultural audience. Data science is an important addition to the farmers’ armory to improve yields, reduce costs and increase profitability. Especially in the era of global warming where advances from traditional sources are expected to level off around 2050. Plateauing food production will be a global disaster because of increasing population, and the rise of popularity in gasoline alternatives such as sugar ethanol which will make demands upon agricultural lands.

Data science allows farmers and farm managers to make optimal decisions about many farm processes. This can lead to large gains which can be through the aggregation of small gains through out the farm or through the identification of poor decision making. Data science gives the farmer not only evidence for their own intuitions, but provide insights for decisions that may seem counter intuitive to even the most experienced farm manager.

Data science is simply a mix of techniques from computer and information science as well mathematics and statistics. These techniques are used to analyze data that has been collected from variety of sources which may be: open or proprietary , local or global. Inferences then can be made, and these insights are turned into actions and decisions. There is nothing mystical about the techniques used, and despite the best marketing efforts of a number of companies the techniques are open and available to all. The “secret sauce” is the method selection, its application and access to data. A haphazard approach to data science can produce disastrous results.

In the coming weeks and months this blog will address issues in data science and agriculture, and if you have any questions about what is covered in this blog, please contact us at:

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