Modern agriculture technologies such as crop monitoring drones, farm management software and livestock measuring sensors are just some of the tools improving crop production in a world full of depleting resources.
The cleaned asparagus is transported to optical quality recognition station and from there to the appropriate collecting container, which is subdivided into different quality levels. Images of asparagus were captured by cameras and transmitted by Firewire signals.
New propane flame weeding technology uses heat to rupture the internal cells of plants for a clean, highly effective solution for weed control that reduces reliance on herbicides and combats increasing weed resistance issues.
IDTechEx believes that the digitalization of agriculture will be more and more widely adopted. The transformation will not be overnight, and although the technology evolution is already underway, we can expect the pace of adoption to increase rapidly over the coming years.
Before using MagGrow, Sparrow could cover an average of 500 acres a day. Now, he can cover 800-1,000 acres in the same amount of time.
Security is a crucial yet often overlooked consideration for modern agriculture facilities. While people most commonly associate crime with large cities, not the rural farmland, farms are popular targets.
Today's agriculture is facing an increasing number of challenges - high production and labor cost despite the lack of skilled workers is only one out of many. To face these challenges, machine vision has become an integral part of many applications used in agriculture.
In the South of Russia, XAG's agricultural drone has been introduced to the full cycle of rice cultivation. It brings new hope to farmers as the use of drone demonstrates the potential to reduce the cost of rice production.
We are moving to a world where robots need to make intelligent decisions about what to do based on what they see. Hence the need for machine learning, vision and AI.
The lettuce's outer, or 'wrapper', leaves will be mechanically removed to expose the stem. Machine vision and artificial intelligence are then used to identify a precise cut point on the stem to neatly separate the head of lettuce.
It analyses recent challenges in the agriculture industry and how robotics and technology developments will change the business of agriculture, enabling ultra-precision farming, helping to mitigate the challenges, and maintaining sustainable developments.
Cover crops. No-till. Biological diversity. Microbial health. You've heard it all before. The techniques and principles of good soil health practices are well known but not widely adopted. Why?
Contrary to popular belief, we consistently find that growers are in fact open to adopting new technologies. That said, several criteria need to be met.
The Startup Collaborator program helps John Deere deepen its interaction with startup companies whose technology could add value for John Deere customers in the future.
After 10 years' existence, Naïo Technologies is consolidating its status as the agricultural robotics leader by being the first company in the world to certify that its large scale agricultural robots will be operating unsupervised in fields from the spring of 2022!
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Precision Farming - Featured Product
Artificial intelligence can be used, for example, to classify fruit varieties or to identify damaged parts, e.g. apples with marks or color deviations. To cover all possible variances with classical image processing would be very time-consuming and costly. With artificial intelligence, however, these challenges can be solved in no time at all. IDS NXT ocean is a user-friendly all-one-one system which requires neither special knowledge in deep learning nor camera programming. Only sample images and knowledge on how to evaluate them (e.g. "good apples" / "bad apples") are needed. This makes the start into AI-based image processing particularly easy. Camera hardware, software, infrastructure and support come from a single company. For beginners, IDS offer the IDS NXT ocean Creative Kit, which includes all components and workflows to create, train and run a neural net.