Amid growing shortage of farm workers, making smart tractors, agribots and robotics remains an essential option
By Kiran N. Kumar
By next spring, a small army of PhytoPatholoBots (PPB) developed by Cornell AgriTech with a new AI and robotics technology called VitisGen will be dispatched to four grape breeding programs across the United States.
These bots will engage in studying highly susceptible grapevines to powdery mildew and downy mildew diseases and gather data to nurture new disease-resistant varieties.
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“Adoption of these new varieties alone has potential to reduce pesticide use by 90%,” revealed Lance Cadle-Davidson, co-project director at Cornell AgriTech.
Katie Gold, who specializes in using imaging spectroscopy for disease detection, is gearing up to conduct field trials to design disease detection programs using the latest imaging spectroscopy, a technology that was first developed by NASA to study the solar system’s electromagnetic radiation.
Named BlackBird, the scientists have a new automated phenotyping RGB microscopy robot that has increased seedlings by 60-fold and is helpful to quantify disease in their lab more accurately than humans to ‘see’ plants at the chemical level.
“Much of the true variation in foliage is captured in wavelengths we can’t see that primarily correspond to chemistry and physiology,” Gold said. “Hyperspectral has truly shown its ability.”
Once commercialized, the PPB robots can help growers monitor disease in their vineyards on a larger-than-ever scale, paving the way for next generation agrifood systems.
In New York state, where the $15 billion industry is struggling, can now heave a sigh of relief to see the disease and pest pressure in grapevines is drastically brought down with the VitisGen.
Cornell AgriTech has released 59 juice, table and wine grape varieties so far, which have become backbones of the New York grape and wine industry, valued at $6.65 billion. Beyond grapes, the research institute has more than 280 varieties of fruits and vegetables to its credit.
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Automation in agriculture
The increasing number of robotics applications in agriculture has also accelerated automation in the sector, reducing costs and optimizing harvests.
For instance, 99% of phytosanitary products are currently wasted as they cover the entire field but with the help of agricultural robotics, farmers can spray pesticides only to the plants that need them, thus saving on cost and time.
Another example is of BACCHUS intelligent mobile robotic system that is fast replacing manual harvesting operations, at every level in Europe. Several collaborative robots are now common in fruit harvesting or insect grafting and cultivation, while Artificial Intelligence provides predictive data to optimize farms and plantations.
Explaining the combination of innovative technology and artificial intelligence, Cadle-Davidson says, “Over the course of VitisGen, more than 65 co-investigators have worked together at the cutting edge of technology… What we can accomplish now is going to be so exciting, powerful and probably revolutionary.”
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Revolutionary, indeed, as the R&D expenditure on AI technologies in the field of agriculture is predicted to grow from $1 billion in 2020 to $4 billion in 2026.
BI Intelligence Research estimates that the global spending on smart, connected agricultural technologies and systems, including AI and machine learning, will triple in revenue by 2025, reaching $15.3 billion.
As the global population reached 8 billion already and projected to reach around 8.5 billion in 2030 and 9.7 billion in 2050, as per the United Nations, a 60% increase in food productivity is required to feed them by then.
With the growing shortage of agricultural workers, making AI and machine learning-based smart tractors, agribots and robotics remains an essential option.