Artificial Intelligence in Agriculture: Understanding Crop Growth
There are many different types of potential applications of AI in agriculture -- ranging from machine control, to image analysis, to improving our understanding of where, when, and how a crop might respond toparticular environmental conditions.
Some Deep Learnings from Applying Deep Learning
To build a robust deep learning model, it can be much more than training or fine tuning some existing models (e.g. inception v3, resnet, LSTM, etc.) with your own dataset. These winning models are your best friend and can usually serve as base models.
It is Agriculture's Turn to Put the Next Generation of Digital Technologies to Work
It is exciting to see the technologies that have made a life-saving difference in medicine now being applied to producing more food from every acre with the best quality.
A Tale of Two Sciences-Artificial Intelligence Meets Agronomy
If 29-year-old me were here in the present day looking at whats going on in agriculture, I cant help but wonder what would be going through my mind-"Do I believe what I am seeing?" or "Am I inside a Sci-Fi movie?"
Beyond the Hype: AI in Agtech
With Agrilyst, growers can understand which of their crops are the highest performers based on yield, growth rate, or both and run production scenarios with higher performers having more space allocation. These recommendations help growers optimize the space on their farm and drive significantly higher revenues.
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X-Rail: reliability and resistance to environmental impurities
Rollon's X-Rail linear rails are a reliable solution in environments susceptible to impurities. Equipped with rolling elements with shaped and flat raceways, they are available in several versions: galvanized, nitrided or stainless-steel sheet metal. The latter version ensures total corrosion resistance, which is critical for hostile environments such as those found in vertical farming.
Particularly innovative is the T + U configuration of the X-Rail linear rails, which can compensate for the parallelism errors of mounting surfaces. This simplifies installation and reduces costs.
