Data science in agriculture

Today, generating digital data is a huge deal, from using social networks to communicate with others to consulting our card balance. The data we produce can be direct, such as sharing a note on social networks or indirectly, requesting a GPS location on a cell phone, each of these data serves companies, to define our tastes and characteristics, and to provide us with better services and applications in our life I say.

The digitization of our data is constant, and the agricultural sector is no exception, for example at the international level, integrating monitoring devices and sensors into agricultural operations, and determining the optimal moment for remote harvesting. In Mexico, an application of censuses and agricultural data from the National Weather Service provides valuable information for decision-making for both the government and the country’s small producers. However, this general data only reaches the municipal level, it is necessary to create new mechanisms for generating agricultural data at the local level and includes the social and cultural characteristics of societies.

The vast amount of data leads us to search for new ways to manage and benefit from it, the so-called data science, which is a system based on statistical methodology and computer science, using various tools such as machine learning, mining data and artificial intelligence, to extract useful information for making comprehensive decisions including dimensions Economic, social, cultural and environmental sustainable development of agricultural societies. You can even enroll in any Data Science Training in London and get ahead in your career.

To know the agricultural situation in Hidalgo State, we need digital data for small-scale producers, as well as the first step is to collect data at the local level, and government programs in cooperation with research institutions are currently making it possible to generate new data. Databases for identifying social, environmental and economic problems. In particular, the research conducted at the CIAD-Hidalgo Center for Food Research and Development seeks to assess agricultural sustainability in the municipalities of El Cardonal and Ixmiquilpan. Identifying the ability of crops to adapt to climate change in the region as critical points, as well as the related impact on the transfer of traditional knowledge to new generations, mainly due to the migration of young people in the region.

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Globally, data science is a tool that allows us to define problems in the agricultural sector with high accuracy, as well as potential decision-making scenarios, and provide comprehensive information for both product and government institutions. It should be noted that the use of data science necessarily exerts a real overlap with the work of agricultural engineers, social researchers, engineers, biotechnologists, physicists, mathematicians in the academic field, agricultural producers and their families in the social segment, entrepreneurs and entrepreneurs. In the economic sector, developing common strategies to achieve true sustainability in the agricultural sector.

The author is a researcher in the regional Hidalgo unit of the AC Food and Development Research Center.

Yaxquin Coronado

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