Autonomous Spore Sensors Assist With Accurate Decision Making

Autonomous Spore Sensors Assist With Accurate Decision Making CROPS New Techniques Diseases reduce yield waste herbicides and pesticides and negatively damage plant ecosystems Many of these challenges stem from fungal pathogens that cause diseases such as gray leaf spot northern corn leaf blight stem rot soybean rust white mold and powdery mildews Scanit Technologies Inc a California company is addressing these issues with its new technological sensors and equipment The Spore-Cam 100 Sensor essentially a miniature digital microscope captures the ground truth of actual disease presence in a greenhouse or outdoor field Using optics and light fusion it autonomously detects 100 000 to 1 million airborne particles daily Collected particle data is transferred to the cloud for classification and analysis “We capture the most elusive data points in a field to help farmers make a confident decision about whether to spray or not ” says company co-founder Jaydeep Rane “Many farmers make decisions based on the disease triangle or whether they’re likely or estimates and probabilities of thresholds With our technology they don’t have to guess The equipment detects signs of disease when they’re still invisible weeks before they cause physical damage to crops ” Powered by solar panels and batteries for outdoor use or standard electrical grids indoors the Spore-Cam continuously sucks air through a small inlet Particles are deposited onto a sticky cassette media inside the component The images are sent to the cloud for analysis and the data reaches the farmer through a dashboard email text alerts or integration into an existing management app A single outdoor unit mounted close to the harvest canopy height covers anywhere from about 40 to a few hundred acres depending on the terrain and crop type They can be installed at any location for indoor use even near doorways to detect spore entry sources One cam can simultaneously detect up to three or four crop pathogen combinations as farmers often grow crops like corn and soybeans beside each other For example each Spore-Cam can detect white mold for soybeans and other corn diseases They work well with almost unlimited crops including corn soybeans wheat strawberries and grapes “Going forward if we can put these out in strategic areas and they work they’ll provide real-time information for making chemical-application decisions ” says Brad Koch a Syngenta agronomist and corn soybean and wheat farmer near Quincy Illinois who oversaw the project on the three farms in his area “For example if we can accurately predict southern corn rust and treat it accordingly growers could see a 20 to 30 bushel per acre yield increase ” The Spore-Cam 100 is commercially available across North America The data derived from the technology is sold through a flexible subscription model Interested parties should contact Scanit Technologies through the website or email to determine the best process for their situation “The most common method of spore identification is still manual trapping which takes two to seven days for results ” Rane says “Our data is accurate in two to five hours without manual intervention This allows time to take preventative action and apply less aggressive chemicals as disease threats are known weeks in advance It’s real-time accurate sustainable and better for the environment ” Contact: FARM SHOW Followup Scanit Technologies Inc 323 Whitney Pl Fremont Calif 94539 ph 408-930-1779; info@scanit-tech com; www scanittech com

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