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Council Post: Artificial Intelligence And Precision Farming: The Dawn Of The Next Agricultural Revolution

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Co-Founder and CTO of Prospera Technologies, leading the company's vision to transform the way food is grown using data science and AI. The human race has come a long way in our ability to produce food at scale. Historian and author Yuval Noah Harari refers to it in his book Sapiens as "an agricultural revolution," using wheat as an example. Ten thousand years ago, wheat was a wild grass that grew in a relatively small region in the Middle East. Today, wheat can be considered one of the most successful plants in history, according to the evolutionary criteria of survival and reproduction. In regions where wheat never existed, such as the Great Plains of North America, you can drive for hundreds of miles without seeing anything else but wheat fields.


Deere's Farm Version of Facial Recognition Coming to Fields in 2021

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Agricultural equipment giant Deere & Co. next summer will debut in farm fields a solution that combines machine vision and machine learning, to distinguish weeds from plants. Agriculture giant Deere & Co. plans to roll out a system next summer that combines machine vision and machine learning to improve the identification of individual plants and weeds. Deere's Jahmy Hindman said neural network models could be trained to only spray weeds in crop fields, killing everything except genetically modified plants designed to survive chemical applications. Said Hindman, "We are interested in being able to manage each plant over the course of its life, minimizing inputs and maximizing productivity." The technology would take pictures of plants, and a machine cruising the field would make the decision to spray in just seconds.


9 Agritech startups making Indian farmers self-reliant - Agriculture Post

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Agritech in India has seen a skyrocketing growth with numerous startups emerging with new technologies and advanced methods such as data analytics, machine learning and satellite imaging, among others to cater to the needs of Indian farmers and maximise their output. India with 118.7 million farmer households, accounting for more than half of the population is heavily dependent on agriculture as a primary source of income. But Indian agriculture is plagued by several problems both man made and natural such as; unavailability of seeds, small and fragmented land-holdings, problems with irrigation due to uncertain monsoon, shortage of finance among other necessities, leaving farmers helpless and with no option but to let their produce go at dirt cheap prices. Therefore, Agritech is clearly one of the most needed industries in India and here is a list of top 9 agritech startups helping Indian farmers by providing agronomic intelligence. Started in 2016 by Nishant Vats and Tauseef Khan, Gramophone is a one-stop e-commerce platform for farmers delivering agricultural inputs in more than 10,000 villages.


Inquiry says technology could boost the value of Australia's agriculture sector by AU$20b

ZDNet

An inquiry into growing Australia's agriculture sector to AU$100 billion by 2030 has highlighted that digital technology will be key to driving growth in Australia's agriculture. The inquiry, conducted by the House of Representatives Standing Committee on Agriculture and Water Resources and chaired by Liberal MP Rick Wilson, estimated that digital agriculture could add AU$20 billion to the value of the sector. "A boost of this size would, by itself, cover the projected shortfall required to reach the AU$100 billion by 2030 target," the Growing Australia report [PDF] said. The inquiry was launched last September to investigate whether the National Farmers' Federation's goal to grow the country's agriculture sector to AU$100 billion by 2030 would be attainable. Read: CSIRO using artificial intelligence to map 1.7m Australian grain paddocks In releasing the findings, Wilson described the target as ambitious but achievable.


IoT Applications in Agriculture

#artificialintelligence

Despite a growing population, now predicted to reach 9.6 billion by 2050, the agriculture industry must rise to meet demand, regardless of environmental challenges like unfavorable weather conditions and climate change. To meet the needs of that growing population, the agriculture industry will have to adopt new technologies to gain a much-needed edge. New agricultural applications in smart farming and precision farming through IoT will enable the industry to increase operational efficiency, lower costs, reduce waste, and improve the quality of their yield. So, what is smart farming? Smart farming is a capital-intensive and hi-tech system of growing food cleanly and sustainable for the masses.


Salinas company FarmWise has weeder on Time's list of Best Inventions of 2020

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A behemoth of a worker, recently recognized by a national publication, that can meticulously and precisely remove weeds growing between sprouting crops is being employed on farms in California and Arizona. Time magazine recently placed the FarmWise Titan FT-35 on its list of Best Inventions of 2020. It is an automated mechanical weeder that can help substitute the pass of a hand-weeding crew, which usually has 10 to 15 people. FarmWise has its operations headquarters, or home base for its team and machines, in Salinas and an office in San Francisco that houses most of its engineers. The company works with farming operations in the Salinas Valley such as Dole and Braga Fresh, plus dozens of other customers.


Facial recognition for pigs: Is it helping Chinese farmers or hurting the poorest?

The Guardian > Technology

Like humans, pigs have idiosyncratic faces, and new players in the Chinese pork market are taking notice, experimenting with increasingly sophisticated versions of facial recognition software for pigs. China is the world's largest exporter of pork, and is set to increase production next year by 9%. As the nation's pork farms grow in scale, more farmers are turning to AI systems like facial recognition technology – known as FRT – to continuously monitor, identify, and even feed their herds. This automated style of farming has the potential to be safer, cheaper and generally more effective: In 2018, pig farmers in China's Guangxi province trialling FRT found that it slashed costs, cut down on breeding time, and improved welfare outcomes for the pigs themselves. But it also has the potential to leave behind independent, small-scale farmers, who cannot afford to introduce this kind of technology to their operations.


Facial recognition for pigs: Is it helping Chinese farmers or hurting the poorest?

The Guardian

Like humans, pigs have idiosyncratic faces, and new players in the Chinese pork market are taking notice, experimenting with increasingly sophisticated versions of facial recognition software for pigs. China is the world's largest exporter of pork, and is set to increase production next year by 9%. As the nation's pork farms grow in scale, more farmers are turning to AI systems like facial recognition technology – known as FRT – to continuously monitor, identify, and even feed their herds. This automated style of farming has the potential to be safer, cheaper and generally more effective: In 2018, pig farmers in China's Guangxi province trialling FRT found that it slashed costs, cut down on breeding time, and improved welfare outcomes for the pigs themselves. But it also has the potential to leave behind independent, small-scale farmers, who cannot afford to introduce this kind of technology to their operations.


Microsoft at GITEX: Tech titan cultivates interest in AI-powered agricultural innovation

#artificialintelligence

How to boost agriculture to ensure food security in a country where deserts cover 80% of the land? Sounds like a tough task, but planting seeds of tech-based innovation and a data-driven future, can unlock growth. The Emirates has already witnessed tremendous progress in strengthening healthcare and tourism, via apps and digital platforms. Emerging as a regional tech-hub, Dubai is now hosting tech giants like Microsoft at the GITEX tech week. On its part, Microsoft is demonstrating how AI and cloud storage can engineer an agricultural revolution in the desert.


Fusing Optical and SAR time series for LAI gap filling with multioutput Gaussian processes

arXiv.org Machine Learning

The availability of satellite optical information is often hampered by the natural presence of clouds, which can be problematic for many applications. Persistent clouds over agricultural fields can mask key stages of crop growth, leading to unreliable yield predictions. Synthetic Aperture Radar (SAR) provides all-weather imagery which can potentially overcome this limitation, but given its high and distinct sensitivity to different surface properties, the fusion of SAR and optical data still remains an open challenge. In this work, we propose the use of Multi-Output Gaussian Process (MOGP) regression, a machine learning technique that learns automatically the statistical relationships among multisensor time series, to detect vegetated areas over which the synergy between SAR-optical imageries is profitable. For this purpose, we use the Sentinel-1 Radar Vegetation Index (RVI) and Sentinel-2 Leaf Area Index (LAI) time series over a study area in north west of the Iberian peninsula. Through a physical interpretation of MOGP trained models, we show its ability to provide estimations of LAI even over cloudy periods using the information shared with RVI, which guarantees the solution keeps always tied to real measurements. Results demonstrate the advantage of MOGP especially for long data gaps, where optical-based methods notoriously fail. The leave-one-image-out assessment technique applied to the whole vegetation cover shows MOGP predictions improve standard GP estimations over short-time gaps (R$^2$ of 74\% vs 68\%, RMSE of 0.4 vs 0.44 $[m^2m^{-2}]$) and especially over long-time gaps (R$^2$ of 33\% vs 12\%, RMSE of 0.5 vs 1.09 $[m^2m^{-2}]$).