An ultra-low-cost active multispectral crop diagnostics device

Abstract

Abstract-A multispectral imaging system is presented, using components that will support its deployment within the world of small-holder agriculture. An active narrowband illumination setup was selected, which allowed a low-cost broadband image sensor to be used. The preliminary set-up has been demonstrated with droughted tomato plants as a proof of concept. The results demonstrated a 5, 28 and 90% deterioration after day 1, 2 and 3 respectively; calculated by the disease/water stress index. Initial analysis showed that for specific applications the device be used in lieu of high-cost diffraction gratings, however additional innovation is required to negate unwanted sensing phenomena.

Remote Sensing of Wetlands in the Prairie Pothole Region of North America

“…Hyperspectral imaging spectrometers are available in airborne and satellite forms and operate within the governance of optical sensors. In contrast to multispectral sensors, which acquire data at a subset of targeted, broad spectral bands within a range, hyperspectral sensors acquire data in narrow spectral bands along continuous and contiguous ranges of wavelengths at equal intervals [128], typically between 400 nm to 2500 nm (blue to infrared). The large number of spectral bands allows for detailed analysis to be performed on each pixel, enabling the determination of atmospheric constituents, surface compositions, and biogeochemical elements (ideal for wetland vegetation discrimination) [71].…”

Spectral Deconvolution for Dimension Reduction and Differentiation of Seagrasses: Case Study of Gulf St. Vincent, South Australia

“…Remote sensing has become a useful alternative, particularly due to advances in spaceborne and airborne detection sensors [2,[23][24][25][26][27]. Spectral imaging remote sensing has proven to be a useful tool, regardless of whether spectral imaging is passive with very high spectral resolution over contiguous bands (hyperspectral), or active with lower spectral resolution in discrete narrow bandwidths (multispectral) [28,29]. This is so because its reflectance responses vary along the light spectrum, often providing distinct optical signatures that can be repeatedly measured to provide multi-dimensional information [2,25,28,30,31].…”

“…Spectral imaging remote sensing has proven to be a useful tool, regardless of whether spectral imaging is passive with very high spectral resolution over contiguous bands (hyperspectral), or active with lower spectral resolution in discrete narrow bandwidths (multispectral) [28,29]. This is so because its reflectance responses vary along the light spectrum, often providing distinct optical signatures that can be repeatedly measured to provide multi-dimensional information [2,25,28,30,31]. In addition, underwater communities can only be detected with wavelengths in the visible light spectrum (≈350-750 nm), where light can penetrate the water column without being easily absorbed and get reflected to the sensor [5,24,32].…”

Proximal Methods for Plant Stress Detection Using Optical Sensors and Machine Learning

“…Multispectral imaging involves data collection using a camera or other sensing device to produce image data in specified wavelength or waveband regions, while multispectral spectroscopy produces spectral data for specified wavebands. Both multispectral imaging and multispectral spectroscopy have been successfully used to identify plant stresses; for example, multispectral imaging was used to detect leaf spot disease in oilseed rape [54], gray mold in tomato leaves [55], and nutrient deficiencies in tomato plants [56], while multispectral spectroscopy was used to detect nitrogen deficiency stress in maize [57], drought stress in tomato plants [58], and nitrogen deficiency in canola plants [59]. Multispectral techniques offer more affordable sensors than their hyperspectral counterparts; however, they do not provide as much information about the plant and its environment due to the broader wavebands.…”