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WWW.POTATOGROWER.COM 43 devices can detect nutrient deficiencies at the plant scale. Although these units are easy to use, their data collection is labor- and time-intensive. Most importantly, collected data is prone to human error and influenced by environmental variability. Handheld sensors, accompanied by specialized portable computers, are also available to capture hyperspectral information. However, these units are expensive and primarily used for research purposes to identify spectral signatures associated with various plant traits or stress factors. Handheld sensors and sensors of similar capabilities, can also be mounted on manned vehicles (e.g., four-wheelers, tractors and combines) or unmanned equipment (e.g., wheel lines and center pivots) to collect data at the canopy level—data averaged across many plants as opposed to one, which provide a continuous measurement across an area. DRONES Unmanned aerial vehicles (UAVs), also known as drones, provide effective platforms to carry spectral sensors and acquire ultra-high-resolution images of crop spectral responses at plant/ canopy and field scales. Operating Canopy reflectance measured using a handheld spectrophotometer in small research plots. drones, however, requires permits from the Federal Aviation Administration (FAA). Professional expertise may also be needed to process images and interpret the output. As an alternative to obtaining and operating personal drones and sensors, there are imagery companies that also provide such services at a medium cost. Similar measurements can also be recorded through sensors mounted on manned aircrafts. Flying aircraft, however, is usually relatively more expensive and not justifiable for frequent monitoring. SATELLITES Satellite remote sensing is perhaps one of the most affordable approaches, and it is gaining popularity among producers. Both low- and high- resolution images of fields may be ordered through various satellite imagery companies. Compared to drones and aircraft, satellite imaging is somewhat limited in resolution and influenced by air quality and cloudiness. Examples of acquired information include NDVI, leaf area index, crop water stress index, and nitrogen nutrition index. Remote sensing offers a powerful tool to monitor crop health and to detect deficiencies in a timely manner to minimize yield and economic losses. Although each of the above- mentioned approaches may be marked by some disadvantages, they will still provide improved monitoring of large- scale potato production (and that of other crops). To minimize shortfalls associated with individual approaches, the University of Idaho potato research team is geared to develop remotely sensed monitoring protocols, based on a combination of approaches to maximize the efficiency of its crop and pest management practices. Arash Rashed is an associate professor of entomology, Sanaz Shafian an assistant professor of precision agriculture, and Xi Liang an assistant professor of cropping systems, all with University of Idaho Extension. 4073-11IndustrialVentilation12h.indd 1 12/23/19 10:38 AM