Matt Hickman for Mother Nature Network: Seawater is pumped to the greenhouse installation where it's used to cool and humidify the hot desert air drawn into the structure's growing area using fans before going through an evaporation process that distills saltwater
It's the underlying science tools and heroes of the digital agriculture movement - specifically, machine learning and predictive modeling - that are central to the success of delivering a digital transformation.
Last year recorded groundbreaking technological advances in agriculture, even as the ag giants focused on consolidation. In looking back over the trends that shaped 2017, we can locate the signs pointing to the big stories we anticipate this year.
The biogas generated from the waste streams is powering a 300 kW gen-set which delivers renewable electricity to the local grid.
Presentations and interactive panel discussions will address investment opportunities in upstream agtech advancements - where global investments have grown to $4.2 billion from $2.36 billion in the past three years, according to AgFunder.
By interconnecting crops, tools and vehicles to smart devices and sensors, farmers will be able to produce more while saving money and conserving natural resources by making the right decision at the right time based on data.
Though there exists a corridor across the northwestern Corn Belt in which there appears to be some truth to this belief, there are as many other corn growing areas where there is no discernible relationship, or even an inverse relationship
AgShift is building world's first autonomous food inspection system using Deep learning and they plan to use the funding to strengthen product development and expand customer reach.
Dan Charles for NPR: Any 4-year old can pick a strawberry, but machines, for all their artificial intelligence, can't seem to figure it out. Pitzer says the hardest thing for them is just finding the fruit. The berries hide behind leaves in unpredictable places.
Black Swift Technologies and NASA Partner to Push Agricultural Drone Technology Beyond NDVI and NDRE (Red Edge)
Next-Generation UAS-Borne Sensors Proving More Effective at Vegetation Health and Growth Monitoring Than Existing Alternatives
Launch customer ISight RPV Services achieves transformative results during beta tests
ABI Research gives comparatively conservative estimates at the valuation of the drone-ag market for many reasons, including an increasingly consolidated market, and the actual needs of the farming industry
Wefarm's peer-to-peer network connects over 660,000 small-scale farmers to vital agricultural information
As the autonomous capabilities of the M220 develop, turf farmers will have the ability to create maps of their fields, assign multiple mowers to separate fields and dispatch them to mow, unmanned, all with the click of a mouse or tap on the screen.
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.
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