The global hyperspectral imaging in agriculture market size was valued at USD 35.86 million in 2022. It is estimated to reach USD 97.30 million by 2031, growing at a CAGR of 13.73% during the forecast period (2023–2031).
Hyperspectral imaging entails collecting and analyzing pictures from a wide range 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. Hyperspectral images use spectroscopy technology to gather more spectral information for each pixel in the scene image, which is used to identify materials based on the behavior of objects that illuminate the light. In addition, hyperspectral imaging technology has applications in multiple industries, such as healthcare, defense, and security. The applications of technology in the agricultural industry entail a wide range of benefits that can help in reducing global agricultural problems.
Hyperspectral imaging can address major issues of global food safety and food demand. With better technology adoption in the agricultural industry, issues such as crop failure, pathogen attack, and plant stress can be managed. In agriculture, hyperspectral imaging has been utilized for various applications, such as measuring crop biochemical and biophysical properties to understand vegetation physiological health and anticipate yield, assessing crop nutritional status, keeping track of crop disease, and analyzing soil qualities.
Increased Global Food Safety Concerns
Food safety is one of the major global concerns at present. Crop quality monitoring inadequacies are to blame for the escalating food safety issues. Detection is usually carried out by random testing combined with chemical analysis, which inevitably prolongs the detection time and decreases the exactness of the result. Therefore, improper crop quality checks have significantly increased food-borne disease outbreaks.
Hyperspectral imaging technology is being used to monitor crop health to address the issues of global food insecurity and reduce food-borne disease outbreaks. Changes in the physiology and health of crops can change their reflective properties. In addition, hyperspectral imaging can detect these small changes, identifying conditions such as plant stress arising from various factors, including disease, nutrient deficiency, and water stress. Thus, hyperspectral imaging is a suitable solution to global food insecurity, and the technology can control food-borne disease outbreaks, driving market growth.
Increased Crop Failure Incidents in Conventional Farming
Crop failure or harvest failure is a diminished crop yield relative to expectation. Crop failure causes a lot of problems and primarily disrupts the supply chain. For the farmers, the expected yield is not achieved, and a large-scale crop failure affects the nation's economy. Crop failure occurs for various reasons, such as adverse climatic conditions, unpredictable weather conditions, poor farming practices, pests, and diseases.
The increase in global large-scale crop failures is expected to be a driver for global hyperspectral imaging in the agriculture market; as with hyperspectral imaging, crop health can be well maintained with constant monitoring and detection of pathogens and pests present in the crop soil. With the information available on plant health, the correct actions can be taken to maintain and improve plant health and reduce the chances of crop failure, boosting market growth.
High Cost of Equipment
Equipment cost plays a major role in any technological equipment's growth, development, and adoption. In agriculture, technological solutions are primarily used to increase the yield and decrease the chances of crop failure. Hyperspectral imaging is a technology that is being used in a wide range of industries. In agriculture, the adoption of technology is still low, and one of the reasons for the slow adoption of hyperspectral imaging in agriculture is the high equipment cost.
Hyperspectral imaging equipment comes under both hardware and software segments. The hardware equipment comprises cameras, scanners, sensors, and image processors. Since the technology is quite new and offers a wide range of solutions for the agricultural industry, the hardware cost is high. This might be a major hindrance in adopting the technology, especially in developing countries where the farmers do not possess the capital to invest in these technologies. Therefore, the high cost of hyperspectral imaging equipment can restrict the market growth over the forecast period.
Increased Emphasis on Precision Farming
The development of technologically advanced tools for agriculture is essential to help farmers make decisions related to crop health and resource management. Hyperspectral imaging solutions have made many advances in precision agriculture, requiring more than basic RGB information. In addition, hyperspectral imaging in precision agriculture can help farmers efficiently use resources such as herbicides and pesticides and provide information on crops' current growth stage and health.
Precision agriculture is a science that uses high-tech sensors and analysis tools to increase crop yields and aid in management decision-making. Regardless of the data source, the goal of precision agriculture is always the same: to help farmers run their businesses efficiently. Such assistance comes in various forms, but the result usually reduces the required resources. Therefore, there would be a huge increase in precision agriculture with the development and greater uptake of hyperspectral imaging solutions in the agricultural sector, which is greatly needed to tackle the existing difficulties in the agricultural sector.
Study Period | 2020-2032 | CAGR | 11.73% |
Historical Period | 2020-2022 | Forecast Period | 2024-2032 |
Base Year | 2023 | Base Year Market Size | USD XX Billion |
Forecast Year | 2032 | Forecast Year Market Size | USD XX Billion |
Largest Market | Fastest Growing Market |
Based on region, the global hyperspectral imaging in agriculture market is bifurcated into North America, South America, Europe, the U.K., China, Asia-Pacific, and the Middle East and Africa.
North America is the most significant global hyperspectral imaging in agriculture market shareholder and is anticipated to exhibit a CAGR of 12.96% during the forecast period. North America is one of the leading areas for the growth and development of hyperspectral imaging in the agricultural industry. The high growth in the North American region for hyperspectral imaging in the agricultural industry is attributed to the region's high technological developments and the potential of incorporating high-investment equipment in the agricultural industry. Hyperspectral imaging can increase agricultural productivity in North America with its constant plant health monitoring.
Furthermore, yield detection capability through hyperspectral imaging in agriculture will enable a forecast for production. Accordingly, the plantation can be done to meet the food demands for self-consumption in the region and export throughout the world. In addition, many leading hyperspectral imaging equipment providers are operating in the North American region, such as Surface Optics Corporation, Corning Incorporated, and Headwall Photonics, Inc., thereby fueling the growth of the regional market.
China is projected to exhibit a CAGR of 11.29% over the forecast period. China is among the largest countries in the world and the largest country in terms of population. Due to the country's high population, the country's food demand is also high. Since China is a developing country with a severe shortage of arable land, China's agriculture has always been labor-intensive. Nevertheless, numerous methods have been developed or employed throughout history to increase agricultural output and efficiency. Technological advancement in the country is quite high, which is expected to play a prominent role in the better adoption of hyperspectral imaging in agriculture in China.
In the past decade, agricultural activities in the South American region have grown and developed into a huge agricultural produce exporter. Major agricultural products offered by the region are coffee, sugar, soybeans, manioc, rice, maize, cotton, edible beans, and wheat. In addition, the agricultural development in the region is pushing the precision agriculture market and the adoption of new technologies. Due to the increase in the adoption of the precision agriculture market in the country, hyperspectral imaging in the agriculture market is poised to grow during the forecast period.
Europe has been advancing its technological capabilities since 2010 along with other continents. Due to the increased technological advancements, the region is growing steadily, especially in countries such as Germany and France. In addition, Europe is one of the regions in the world with a high emphasis on food safety and security. Hyperspectral imaging in agriculture can increase agricultural yield and decrease the chances of crop failure. This acts as a driver for the growth of hyperspectral imaging in the agriculture market in the region.
In the Middle East and Africa, most people reside in rural areas and rely on agriculture-related activities for their livelihood. Since the majority of the population in the region relies on agriculture for its livelihood, the scope of hyperspectral imaging in the agriculture market is high in the region. The region faces high demand for food and decreasing availability of water and other natural resources. Hyperspectral imaging helps increase agricultural yield and is expected to be adopted in the Middle East and Africa region.
Asia-Pacific nations are investing in digitizing their agriculture industries to boost agricultural productivity and efficiency due to the region's rapid technological development. India is the country with the second-largest population in the world, and 40% of its people are employed in agriculture. In addition, the agricultural sector in the region is an important contributor to the overall GDP of the region, recording extraordinary growth during the years 2008-2019. Therefore, Asia-Pacific has a huge potential for hyperspectral imaging in agriculture.
We can customize every report - free of charge - including purchasing stand-alone sections or country-level reports
The global hyperspectral imaging in agriculture market is segmented by product and application.
Based on the product, the global market is divided into the camera, artificial light source, image processor, and others.
The camera segment is responsible for the most significant market share and is anticipated to exhibit a CAGR of 11.75% over the forecast period. Cameras are the primary equipment required for achieving hyperspectral imaging in the agricultural industry. A hyperspectral imaging camera plays a vital role as it captures the plant characteristics to measure the plant stress levels. Primarily, hyperspectral imaging cameras can scan visible, ultraviolet, and near-infrared spectral ranges. These cameras measure microscopic plant characteristics, providing excellent image quality and low distortion. Further, there are two types of hyperspectral imaging cameras, namely, line scan cameras and area scan cameras. The line scan camera integrates a one-dimensional linear sensor. It provides the advantage of a high frame rate, exceeding 40,000 lines per second, making it suitable for online inspection on the assembly line. Combined with artificial intelligence (AI) for defect recognition or pattern recognition, it is an important part of the inspection system because the high collection speed enables artificial intelligence-based defect recognition and classification tasks.
Light sources used for spectral imaging applications can generally be divided into two categories, namely, illumination light sources and excitation light sources. Broadband light is generally used as an illumination source for transmitting reflection and transmission images, while narrowband light is generally used as an excitation source. Therefore, lighting is a key part of a hyperspectral imaging system. Compared to the naked eye, the visual system is affected by the level and quality of light. The light generated by the lighting equipment illuminates the target object being inspected; therefore, the lighting system's performance can greatly affect the image quality and play a vital role in the overall accuracy and efficiency of the system.
Based on application, the global market is segmented into yield estimation, crop disease monitoring, impurity detection, stress detection, vegetation mapping, and others.
The stress detection segment owns the highest market share and is estimated to exhibit a CAGR of 11.09% during the forecast period. The ability of hyperspectral imaging to offer valuable data on the status and health of crops depends on the interaction and relationship between electromagnetic radiation (EMR) and leaves. EMR can be absorbed, transmitted, or reflected. Although vegetation's internal and external physical structure will affect this, the main influence on EMR is various photosynthetic pigments.
Furthermore, drought is important in predicting crop yield and eventual success. Early detection of water-related pressures in field crops allows growers to identify specific irrigated areas, saving water, energy, and time. Early detection also allows growers to supply water to crops before drought stress causes yield losses. A higher pressure level ultimately establishes itself as a change in photosynthetic pigment. When the reflectance of the red wavelength increases to match that of the green, these changes can cause the common symptoms of chlorosis, resulting in a typical yellow. Long before the human eye sees any changes, hyperspectral imaging can detect these changes much earlier.
Soil contamination is among the serious problems that cause crop failure. The presence of impurities in the soil creates an issue for plant nourishment and decreases the yield quality. Hyperspectral satellite images provide potentially powerful tools for soil contamination detection and mapping. Generally, there is a small number of contaminants in the soil, so the contribution to the entire reflectance spectrum is negligible. Spectral separation technology is used to detect this small impurity. The coarse spatial resolution of hyperspectral imagers leads to the possibility of co-capturing multiple different spectra, leading to their separation errors. If there are many spectral samples, different spectra can be separated even in the joint field of view.