Hyperspectral imaging involves capturing and processing images at a large number of wavelengths. Although multispectral imaging can use three or four colors (red, green, blue, and near infrared) to assess the process, hyperspectral imaging breaks the image into tens or hundreds of colors. By using spectroscopy technology, which is used to identify materials based on the behavior of objects that illuminate the light, hyperspectral images acquire more spectral data for each pixel in the scene image.
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This technology has promoted many advancements in precision agriculture, which requires more than basic red green blue (RGB) information. Unlike radiography, hyperspectral imaging is a non-destructive, non-contact technology that can be used without damaging the object under analysis. For example, drones with hyperspectral cameras can detect plant diseases, weeds, soil erosion problems, and estimate crop yields. Hyperspectral imaging has been used in agriculture for a wide range of purposes, including estimating crop biochemical properties and biophysical properties for understanding vegetation physiological status and predicting yield, evaluating crop nutrient status, monitoring crop disease, and investigating soil properties.
Hyperspectral imaging is a technology that has applications in multiple industries such as healthcare, defense, and security. The applications of the technology in the agricultural industry entail a wide range of benefits that can help in reducing global agricultural problems. The growth in the global hyperspectral imaging in agriculture market is expected to be primarily driven by increased awareness of the technology in regions where the agricultural industry plays a huge role in the economy of countries such as Asia-Pacific and China.
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Hyperspectral imaging has the ability to address major issues of global food safety and food demand. With better adoption of the technology in the agricultural industry, issues such as crop failure, pathogen attack, and plant stress can be managed. Due to the constant monitoring and control over plant health, the agricultural yield can be efficiently maximized by incorporating hyperspectral imaging in agriculture. Also, with constant monitoring of crops, soil conditions can be improved by reducing pesticide and fertilizer input to the soil to manage soil health.
A major factor driving hyperspectral imaging in the agriculture market is the increasing crop failure incidents throughout the world. This is primarily caused by the plants being damaged, destroyed, or affected in some way that they fail to form edible fruit, seeds, or leaves in their expected abundance. Crop failure causes a lot of problems and primarily disrupts the supply chain. Through hyperspectral imaging, plant health will be maintained, and crop failure incidents will decrease. A key challenge for better growth and adoption of hyperspectral imaging in agriculture is the high initial investment. In order to have hyperspectral imaging in the field, specific equipment such as hyperspectral imaging cameras, image processing software, and artificial light sources are required. The high initial investment required for achieving hyperspectral imaging might play a major hindrance in the adoption of technology by small and medium-scale farmers.
