Close range hyperspectral imaging of plants: A review (original) (raw)
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Background: Although hyperspectral imaging was originally introduced for military, remote sensing, and astrophysics applications, the use of analytical hyperspectral imaging techniques has been expanded to include monitoring of agricultural crops and commodities due to the broad range and highly specific and sensitive spectral information that can be acquired. Combining hyperspectral imaging with remote sensing expands the range of targets that can be analyzed. Results: Hyperspectral imaging technology can rapidly provide data suitable for monitoring a wide range of plant conditions such as plant stress, nitrogen status, infections, maturity index, and weed discrimination very rapidly, and its use in remote sensing allows for fast spatial coverage. Conclusions: This paper reviews current research on and potential applications of hyperspectral imaging and remote sensing for outdoor field monitoring of agricultural crops. The instrumentation and the fundamental concepts and approaches of hyperspectral imaging and remote sensing for agriculture are presented, along with more recent developments in agricultural monitoring applications. Also discussed are the challenges and limitations of outdoor applications of hyperspectral imaging technology such as illumination conditions and variations due to leaf and plant orientation.
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In-field hyperspectral imaging: An overview on the ground-based applications in agriculture
Journal of Agricultural Engineering
The measurement of vegetation indexes that characterise the plants growth, assessing the fruit ripeness or detecting the presence of defects and diseases, is a key factor to gain high quality of fruit or vegetables. Such evaluation can be carried out using both destructive and non destructive techniques. Among non-destructive techniques, hyperspectral imaging (HSI), combining image analysis and visible/near-infrared spectroscopy, looks particularly useful. Many studies have been published concerning the use of hyperspectral cameras in the agronomic and food field, especially in controlled laboratory conditions. Conversely, few studies described the application of HSI technology directly in field, especially involving ground-based systems. Results suggest that this technique could be particularly useful, even if the role of environmental variables has to be considered (e.g., intensity and incidence of solar radiation, wind or the soil in the background). In this paper, recent in-fiel...
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Hyperspectral imaging is an emerging technique in the agriculture sector to obtain spectral and spatial data of plant without destruction of plant parts. Traditional sampling ways are a destructive method that damages the plant parts and required more time. This is the best method to get results from a large area within minimum time. We can obtain our research goals without physically effecting the plant parts. Nowadays, its application includes mapping of vegetation, crop diseases and pest attack, crop stress and yield analysis, plant parts identification, nutrients measurements and exposure of impurities. Agriculture elements consist of different chemical and physical compositions, in the response with near-infrared spectroscopy, plant parts will reflect, absorb, scatter or emit waves in different ways at a specific wavelength. These variations are characterizing with spectral signs of that part. The purpose of literature is to provide basic information about the role of hyperspectral imaging and its application in the agriculture sector.
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Hyperspectral imaging techniques have been expanding considerably in recent years. The cost of current solutions is decreasing, but these high-end technologies are not yet available for moderate to low-cost outdoor and indoor applications. We have used some of the latest compressive sensing methods with a single-pixel imaging setup. Projected patterns were generated on Fourier basis, which is well-known for its properties and reduction of acquisition and calculation times. A low-cost, moderate-flow prototype was developed and studied in the laboratory, which has made it possible to obtain metrologically validated reflectance measurements using a minimal computational workload. From these measurements, it was possible to discriminate plant species from the rest of a scene and to identify biologically contrasted areas within a leaf. This prototype gives access to easy-to-use phenotyping and teaching tools at very low-cost.
2014
Much progress has been made on optimizing plant water supply based on several methods of irrigation scheduling, in both open-field and greenhouse cultivations, such as real-time measurements of solar radiation and soil or substrate moisture. However, only a limited number of such methods use plant-based physiological indicators to detect plant water stress and adapt irrigation scheduling accordingly. In addition, even fewer indicators can be estimated by non-contact, remote sensors (RS) that do not affect plant development. Hyperspectral imaging technology could be an accurate remote way to detect moisture content of plants, taking into account crop characteristics. In this work, a methodology of hyperspectral imaging calibration and acquisition is presented. The method uses the reflectance characteristics in hyperspectral bands from 400 to 1000 nm and incorporates the appropriate radiometric and geometric corrections. The basic statistical parameters of mean and standard deviation ...
Hyperspectral Imaging: A Tool for Plant Disease Detection
Agri Articles - ISSN: 2582-9882, 2024
Detecting and identifying plant diseases is crucial for sustainable crop production. Accurately assessing disease impact on yield quality and quantity is vital in various agricultural areas. Hyperspectral imaging of afflicted plants provides valuable insights into pathogenesis processes. Integrating this method with data analysis enables timely and precise identification and quantification of plant diseases. This approach, applicable across different scales, enhances our understanding of plant-pathogen interactions. It contributes to proactive disease management, particularly in precision crop production, horticulture, plant breeding, fungicide screening, and both basic and applied plant research.
Ground Based Hyperspectral Imaging to Characterize Canopy-Level Photosynthetic Activities
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Improving plant photosynthesis provides the best possibility for increasing crop yield potential, which is considered a crucial effort for global food security. Chlorophyll fluorescence is an important indicator for the study of plant photosynthesis. Previous studies have intensively examined the use of spectrometer, airborne, and spaceborne spectral data to retrieve solar induced fluorescence (SIF) for estimating gross primary productivity and carbon fixation. None of the methods, however, had a spatial resolution and a scanning throughput suitable for applications at the canopy and sub-canopy levels, thereby limiting photosynthesis analysis for breeding programs and genetics/genomics studies. The goal of this study was to develop a hyperspectral imaging approach to characterize plant photosynthesis at the canopy level. An experimental field was planted with two cotton cultivars that received two different treatments (control and herbicide treated), with each cultivar-treatment com...