Archaic farming practices, like excessive use of fertilisers and using large volumes of water, are no longer seen as viable farming methods. To compensate, agribusinesses are turning to sustainable farming practices powered by fourth industrial technology, like IoT and agricultural analytics.
In our latest blog, we explain how agricultural analytics plays a huge role in sustainable farming.
Sustainable farming refers to farming practices that can meet the needs of the present, without compromising the needs of future generations.
Sustainable farming is not just a mantra, it is a set of policies and procedures that have proven to be effective in improving farming productivity, and reducing food waste.
In fact, studies show that sustainable farming practices, powered by IoT and agricultural analytics, can save approximately $155-$405 billion a year by 2030.
One excellent example is the Wangree Plant Factory, which used IoT and agricultural analytics to make farming practices more sustainable. The end result was significant gains in reducing resource consumption and improving yield.
For example, the Thai-based agribusiness reduced the cost of infrastructure by 50 per cent, reduced the cost of fertiliser by over 80 per cent, while also increasing product weight per unit by 33 per cent to 75 per cent. Furthermore, they were able to reduce water consumption by over 99 per cent and cut plant defects by 30-50 per cent.
Sustainable agriculture is a key practice for the future and many farmers and agribusiness are looking to make that a reality using modern technology.
Fourth industrial revolution technology, like IoT devices and sensors, are perfect for making sustainable farming a reality. This is because these sensors can measure farming equipment. IoT devices are a key part of sustainable farming because they are able to make precise measurements on fertiliser usage, water consumption, and energy use.
However, while IoT sensors collect a wide variety of data and measure different KPIs, all of it wouldn’t mean much if there are no devices to convert the data into useful information. This is where agricultural analytics comes into play.
Agricultural analytics serves as the missing link between IoT sensors and sustainable farming. The data analytics platform can sift through the large volumes of data looking for trends and irregularities in the use of farming resources.
IoT sensors are constantly collecting data on resource consumption. Trying to make sense of data from different devices, like drones, crop sensors, and automated equipment is challenging because the data comes in different formats. Agricultural analytics make sustainable farming a reality because of its ability to measure resource use right down to the minute detail.
Furthermore, agricultural analytics can simplify the management of big data. IoT sensors can collect a lot of data but if it is difficult to understand, then it becomes difficult to manage. If data is not collected and analysed, then it becomes difficult to achieve some of the more sustainable farming practices, like smart spraying, seeding, and harvesting. Agricultural analytics can work around this problem by analysing the data and presenting the findings in a way that works.
Agricultural analytics dashboards can automate and visualise the presentation of data, making it far more accessible than before. Data is set up in a way that makes for easy assessment and collaboration between different analytics professionals, which means higher quality analysis and findings for everyone involved.
Most importantly, agricultural analytics allows agribusinesses to be more proactive in their cultivation practices. Data analytics can collect data on different conditions related to weather, soil quality, and pesticide use. Agricultural analytics can draw data from a variety of sources, including satellites, drones, and robots. The analytics software can generate useful information about future weather conditions and plan their farming practices around that. In other words, they can proactively manage farm yields.
Agricultural analytics can take the complexity out of data collection and analysis by automating and visualizing the process, which means lower operating costs.
Agricultural analytics can help transform the farming industry for the better. While we have only tapped into sustainable farming, analytics placed a host of other benefits as well. For example, data analytics can optimise supply chain management and better anticipate demand in the future through automated demand sensing to better mitigate the risks of farming in the future.
Agriculture is the world’s largest industry! As smart machines and sensors crop up on farms and data grows in quantity, farming processes become increasingly data-driven. Rapid developments in data analytics solutions, Internet of Things (IoT) and cloud computing is propelling the industry forward.
With the development of data analytics solutions today, we can monitor farms, soil, plant activity and water levels to understand agricultural systems in a way that we were never able to before. With the use of wireless sensors, we can gather and analyse this data to discover patterns that will allow farmers to make more educated decisions that will increase the output, and ultimately, grow a better product.
Read on to see how data analytics solutions are shaping the farming industry’s trajectory.
Smart farming, also called the Third Green Revolution, is the innovation of the agriculture sector through the adoption of smart technologies. In the years to come, it promises to bridge the gap between the latest tech solutions and the agricultural sector – a realm that is used to relying on more traditional farming methods.
Farmers are using data to calculate harvest yields, fertiliser demand, cost savings, and even identifying optimisation strategies for future crops. Smart farming uses data analytics solutions to gather information from multiple farming practices to create algorithms that can be utilised by different farms to create a crop yield that is both fruitful and sustainable. With this knowledge, farmers will be able to better predict activity in the farm and utilise methods that are not only better for their crops but more environmentally sound.
Research predicts the global smart farming market to reach around $23 billion by 2022 and grow at a compound annual growth rate (CAGR) of almost 20% from 2017 to 2022, such as accelerated development triggered by the increasing demand for crop yield and food production with the same resources.
A significant risk factor in farming and agriculture is the external variables we have no control over. Pest and crop diseases, for example, can decimate entire harvests, as can natural disasters, like storms or extreme weather. Before data analytics solutions existed, it was almost impossible to predict such events.
Machine learning and algorithmic tools can be designed to factor in any number of external insights or information. Farmers can then use predictive modeling techniques to plan or act accordingly – Think weather patterns, consumer demand and even industry trends. This data will help workers in the agriculture industry understand how the surrounding world affects their business.
What should they plant? When is the best time? What earnings can they expect? Are the cost of supplies rising? How does this affect profits? All these questions can be answered using data analytics solutions.
By using sophisticated computer algorithms to analyse decades, and sometimes, centuries of weather and crop data, today’s farmers can predict crop yields with shocking accuracy, before planting a single seed. The insight provided by data analytics allows farmers to start and harvest their crops at an optimum time, which maximises crop yields and minimises stress.
Rather than filling up an entire plot, farmers can account for the fluctuations in demand. Farmers can see how much they produced in previous years, what that meant for customers, how this affected market forces and how to improve operations going forward. They could cut excess waste by producing fewer crops for a lower demand season to complete certain objectives, like saving money or clearing space to grow alternative crops.
Thanks to recent advances in drone technology, the internet and data analytics, automation has reached staggering new heights. Farmers are using drones with advanced sensors to survey their crops, update their data and notify them of areas that need improvement. As technology continues to progress, you can expect drones to move from surveying to planting and harvesting.
Chemists and agricultural scientists have been analysing plant data for years, in the hopes of developing crops that can grow in any environment. Chemically engineered seeds designed with data analytics solutions may sound like a bad thing on the surface, and the news usually portrays it that way. However, seeds engineered with the aid of data analytics could put an end to world hunger.
Visit our website for more information on how data analytics solutions are transforming the trajectory of the farming industry.
Agriculture is the backbone of most countries and with the advent of big data analytics, we see a shift in the operation of the agricultural sector. With agricultural analytics paving the way for innovation, the sector is able to make much-needed changes by deriving effective key data insights.
According to McKinsey & Company, about a third of food produced is lost or wasted every year. Globally, that’s a $940 billion economic hit. Inefficiencies in planting, harvesting, water use, and trucking, as well as uncertainty about the weather, pests, consumer demand, and other intangibles, contribute to the loss. These are problems desperately in need of solutions and many of those solutions can be found in emerging technologies.
Big data is moving into agriculture in a big way with investors recently dropping a combined $40 million into Farmers Business Network. Venture capital has flooded the agricultural tech space, with investment increasing 80% annually since 2012, as investors realise big data can revolutionise the food chain from farm to table.
Read on to find out more on how agricultural analytics is paving the way for much-needed innovation in the farming sector.
Improved crop forecasts and utilising sensors for data collation
The farmers spend a lot of their time worrying about how the crops will turn out to be. Crop predictions during the course of years have been anything but correct, until now.
With the help of high-end and useful computer algorithms to review the years and sometimes decades of weather and crop information, present-day farmers can foresee their yield with absolute accuracy, and that too, before even planting a single seed in the soil. The insight offered by big data and agricultural analytics enable the farmers to initiate and harvest their yield at the best time, and this helps to maximise the harvests. Farmers are also compelled to spend a lot of time worrying about their crop. However, accurate crop forecasting saves them from the stress of worrying about their crop from time to time.
Sensors on fields and crops are starting to provide literally granular data points on soil conditions, as well as detailed information on wind, fertilizer requirements, water availability and pest infestations. GPS units on tractors, combines and trucks can help determine optimal usage of heavy equipment. Data analytics can help prevent spoilage by moving products faster and more efficiently. Unmanned aerial vehicles, or drones, can patrol fields and alert farmers to crop ripeness or potential problems.
Precision farming with agricultural analytics
Precision agriculture or automated farming is the new way to grow crops. Though, there is no doubt about the fact that, for years, farmers have been using several varied solutions to automate and keep track of a plethora of agricultural procedures. Now, big data analytics solutions completely separate the commercial agriculturalists from the pack.
With recent and exponential developments in big data, AI, internet, and drone technology, agricultural automation has reached a new level! Farmers are now even using drones with cutting-edge sensors to survey the crops, keep their data updated, and inform them about the areas that require improvement. The technology is growing at a rapid speed and it is anticipated to move from gauging to even planting and harvesting.
Big data analytics is all about looking for the tiniest of errors in a system and rectifying them, thus the technology helps the farmers to check the quality of their crops to a new height!
Big data analytics has made a noteworthy impact in the agricultural industry, however, it’s hard to pin down all of its effects and even tougher to forecast just how much more transformation it might bring about. However, one thing is for certain – the impact of big data on farming has, is, and will surely continue to be refreshing and beneficial for the farmers and actors throughout the agricultural space.
By adopting newer big data-enabled technologies to make full use of big data analytics, farmers can leverage these insights to increase efficiency, reduce waste, leverage predictive capabilities, and manage yield better – all with the power of greater insights!
For more information on how agricultural analytics is paving the way for innovation in the agricultural sector and for services that can help you manage your operations with SAS, visit our site and check out our services.