Over the past 40 years agricultural scanning technology has developed rapidly from sprayers with only the capability to recognize brown bare soil from very green growing plant material to machines capable of guiding moving sprayers to target individual plants or “visually” sampling a load of grain for moisture content.

The latter examples are based on technology developed by the defense industry using shortwave infrared (SWIR) frequencies for intelligence, surveillance and reconnaissance, and are increasingly finding their way onto the farm to detect water stress, plant disease, and other conditions affecting food and fiber production.

Mike Grodski, product manager for Canadian firm, Teledyne DALSA’s SWIR products says the imaging technology is beginning to yield real benefits in agriculture, including increased crop production, lower-cost produce, and reduced food waste.

He explains the SWIR band (high above the frequency of visible light) includes frequencies from 1 to 3 nanometers, and compared with imaging sensors operating at longer wavelengths SWIR sensors deliver images with higher resolution and stronger contrast.

“SWIR imaging can also highlight features and defects that visual imaging cannot,” Grodski says. “For example, (using SWIR scans) water vapor and other materials become either more or less reflective or transmissive than they would appear under visible wavelengths. This allows colors that appear almost identical in visible light to be clearly differentiated in the SWIR image.”

Grodski says water’s strong absorption at SWIR wavelengths make objects with a high moisture content appear nearly black in images captured using SWIR cameras. As a result, by applying appropriate filters or light source can help make moisture content highly evident in well-irrigated crops, bruised fruit or bulk grain.

“This also enables scientists to precisely follow water absorption from a plant’s roots into its leaves, or conversely, to monitor evaporation or desiccation,” he explains.

Most practical farm applications of SWIR observations use LIDAR (Light or Laser Detection and Ranging), and can be found in “smart sprayers” that observe weeds within crops on-the-go and target herbicide sprays to defeat the identified weeds. Also, the irrigation industry is developing sprinkler-mounted LIDAR sensors to monitor crop condition and water-use throughout the growing season.

In addition, grain handling facilities use similar technology to monitor bulk grains for moisture content in real time – eliminating the need for manual sampling and laboratory analysis.

In these examples, generally the distance between observed plants or products are very near the monitoring devices, usually no further away than roughly 4 feet. Still, like most technology driven by the marketplace, improvements in the use of SWIR are continual.

Case in point: France-based IRIDESENSE, a pioneer in 3D SWIR Multispectral perception, introduced its new laser-based LIDAR sensor recently at the Consumer Technology Association’s annual CES trade event in Las Vegas.

Company officials say the product is, “the first 3D Multispectral LIDAR sensor capable of analyzing plant health and soil humidity levels remotely in real time and in all light conditions.”

The product is also capable of monitoring plant growth and boasts a sensing range of up to 300 meters.

“Prior to this sensor, no technology could measure plant health or soil moisture levels in outdoor conditions without resorting to sampling, while alternative technologies can only detect these factors at a distance of 1.5 meters under conditions in which lighting can be carefully controlled,” explains Nadine Buard, company co-founder and CEO. Further, she says in the future IRIDESENCE’s sensors could be fit as standard equipment on agricultural machinery to interact with systems using artificial intelligence to react to needs of crops in real time.

Product information further describes the new sensor as differentiating infrared images in 5 colors and providing high-resolution images superior to standard 2D cameras. The system is completely independent of lighting and meteorological conditions and can be used night or day.

The technology also offers enhanced “sorting” or inspection capabilities for agriculture and other industries by analyzing different image “signatures” using AI to distinguish various materials such as plastics, rocks, oil, wood, plant species and water, as well as the water content of scanned materials.