Precision agriculture is all about optimizing the agricultural practice according to the various factors like, weather pattern, soil characteristics, location etc. which inputs are carefully analyzed to optimize raw material use and at the same time increase the yield. With lots of technology lying around data collection is not a problem, thus making the smart farming a need rather than a choice. In precision farming, farmers are more interested in designing a farming protocol conceiving all aspects of nature, thanks to computing supports like GPS, drone monitoring, rain tracking etc. Data-driven agriculture has tons of data generated, which needs to be sorted, analyzed, and stored. This is why data management in agriculture needs an extra reinforcement to handle it better.
Data driven agriculture is the basis of a modern farming practice that combines computing technology into conventional farming practice to improve efficiency. Various data are collected starting from the earth till sky that influences the growth of a crop. This data is analyzed using the software, and the manual interpretation is implemented, thus making this more of a ‘data farming’ than crop farming. Since lots of data is involved managing, it has a big-time relevance, and that’s why an organization and understating about data management is critical. As far as crop science is concerned, precision agriculture is the best chance, for which data management is a vital part.
Precision farming means different in field crop and in greenhouse segments. In a greenhouse you can have more possibility to intervene in technology (irrigation, climate, etc.).
In precision farming, all possible environmental cum plant data are collected using a variety of sensors. For example, sensor and/or satellite data provides information about weather pattern, rain tracking, wind profile, etc. Likewise, a farmer can collect lots of data that helps in fine-tuning the crop needs. In the early days of digitization in farming, the data flow was discreet and limited to a fewer audience. But in the current scenario, the data accessibility has improved a lot, making farm data management a separate science. Thus, individuals have a far wider reach to vital data.
In the past, farmers had very limited associability to digital data, and so did a few of them would employ sensors or other sophisticated tools for improving the quality of farming. Only the flow of information might come from a local body or agricultural office who collects data from respective institutes /authorities. Over time more and more communication devices came into play resulting in the improved data flow, which still had a lesser impact.
It is when sensors and computers stepped into agriculture, the era of smart farming had begun. Now the data flow can directly be synched to the farmer on a real-time basis, and also the farmer can choose to share his data to a community to help others grow.
Data flows from various sources, and storing it is the major challenge. There are two ways you could store the enormous data that are being collected in the precision farming context.
Crop cultivation is influenced by hundreds of factors, and only a few of them can be controlled by the farmer. Rest has to be blessed by nature for a successful harvest. This context is not entirely true, at least in this era and all the credits go to agricultural science. Precision farming is the leading tech that is by far the most successful approach in modern agriculture. Having a load of data that directly and indirectly influence the plant growth is an agricultural asset. These agri data can be analyzed using specialized software, for instance, ‘Trutina’ by Gremon Systems, and thereby helping you in the decision-making process. Remote sensing can help farmers carefully plan fertilization procedure to reduce wastage. Farm data management will be crucial in case of crop insurance. Likewise, data management has many benefits and very crucial sometimes, especially because new sensor technologies are providing millions of data, that could not managed only by human intervention.
Agricultural data can be classified into four categories. All modern farmers have to depend on these data to some degree depending on the type of farming, duration, crop, etc. thus making data driven farming the need for modern agriculture.
Four categories include:
Gremon Systems is one of the pioneers in the field of precision agriculture, focusing on greenhouses. Their deep insight about future farming led them to design state of the art technologies to help farmers. All the products like ’Insight Manager’, ‘Trutina,’ ‘Trutina Soil’ and ‘Crop Monitor’ are data intensive and help the farmer in the decision making process with no margin for error. Plus scientific backing in the design philosophy of each of these products helped GS to develop a true extension of future farm technology into the conventional farming world.
One excellent demonstration of technological superiority by GS is with how they evaluate and analyze the solar irradiation. They employ a sophisticated algorithm that collects data like local sunrise, sunset, and pyranometer output to determine the level of irrigation and climate strategy. This one tiny data can influence the yield by up to 15 % by saving water and fertilizer! All their data management is synched to a cloud-based central server so that it can be used in two different parts of the world by adjusting local parameters, making GS products versatile.
Precision farming is the next big thing in the horti-world, and Gremon Systems had made a commendable contribution in this data driven farming technique with their series of sensor-based products and cloud server-based data management system. Rather than being a technique, it is a novel farming strategy concocting the ‘IoT’ and computing technology to make farming more efficient than ever before. So, precision farming will be the smartest investment in the agriculture that you can make now because the computer integration into our daily lives has just started its race.