Profitability, the environment, food sovereignty, but also farmers’ comfort are at the heart of the promises of Big Data in agriculture. More concretely, what is Big Data based on and where are we today?
What is Big Data?
The explosion of data at the origin of Big Data
Big Data means the storage, organization, development and dissemination of data from digital tools such as software or applications. This term was coined at the end of the 90s, a period marked by the arrival of the digital data explosion. Researchers then had to find new ways of seeing and analyzing this new emerging digital world and its new orders of magnitude. The concept of “Big Data” was born, with the objective of storing mega digital information, i.e. “data”. Today, Big Data is presented as the last step towards the third industrial revolution, namely the information revolution.
Volume, Variety, Velocity: the rule of mass data
Imagined as a solution allowing everyone to access giant databases in real time, Big Data relies on various tools dedicated to the massive analysis of data, responding to the 3V rule. Massive volume of data to be processed, variety of information coming from multiple sources, and speed to be reached, i.e. the speed to create, collect and share these data. The arrival of Cloud Computing, which can be summarized by remote storage and no longer on servers, has of course facilitated the massive storage of data to give birth to Big Data. The agricultural sector and the increasingly massive use of connected tools will therefore give rise to Big Data in agriculture, also known as “Big Agro Data”.
What are the challenges of Big Data in agriculture?
Enhancing agricultural practices with agricultural data
Farmers generate a lot of data on their farms without necessarily taking advantage of it. The development of their agricultural practices is based on the exploitation of this agricultural data. Whether it’s to improve farming practices, save time, rationalize costs, or implement more efficient and sustainable precision agriculture… The use of agricultural data can also help guarantee the traceability of production, predict harvest levels, better protect the environment, or simply sell production better.
Tracking a batch of wheat from the field to the bakery with the help of computerized data collection tools can, for example, increase the value of a loaf of bread and of course increase the price paid to the producer. Agricultural data can therefore add value to products throughout their journey.
Agricultural data: essential for traceability
Also known as “food tracking”, the traceability of a food product makes it possible to find its origin and to retrace the entire route taken before it is marketed “from the farm to the fork”. Or from the field to the consumer’s plate! Accentuated by the increasing mobility of goods on a global scale, traceability also responds to health and regulatory concerns, such as for GMOs.
The traceability thus ensures all the follow-up of the origin of its production upstream by the farmers, with its transport, its transformation with the factory, until its distribution near the consumers. Now a legal obligation, the traceability of agricultural production began in France in 1969, at the time within the meat industry for the improvement of breeds. At the end of the 90’s, this principle became more precise and thorough, to respond to the fall in consumer confidence following the mad cow crisis.
Today, traceability has become an essential lever for guaranteeing the quality and origin of food products, and is also essential for promoting their cultivation practices and production, right up to the consumer.
Source : smag.tech