Article
Environmental Sciences
Dennis D. Langer, Milica Orlandic, Sivert Bakken, Roger Birkeland, Joseph L. Garrett, Tor A. Johansen, Asgeir J. Sorensen
Summary: Hyperspectral imaging is a valuable technology for remote sensing, but its application in space is limited by the large amount of data it generates and the subsequent bottleneck in data transmission. To overcome this limitation, an on-board processing pipeline for the HYPSO-1 cube-satellite is developed, providing flexible image processing, reliability, and resilience. The performance of the pipeline, including processing time and compression rate, is analyzed, and the implications for the HYPSO-1 mission are discussed.
Article
Plant Sciences
Dominic Williams, Alison Karley, Avril Britten, Susan McCallum, Julie Graham
Summary: Monitoring plant responses to stress is a challenge, especially below-ground stress. Hyperspectral imaging can help identify stress responses in plants by analyzing the relationship between plant spectral data and specific stresses.
Article
Chemistry, Multidisciplinary
Mohammad Akbar Faqeerzada, Eunsoo Park, Taehyun Kim, Moon Sung Kim, Insuck Baek, Rahul Joshi, Juntae Kim, Byoung-Kwan Cho
Summary: Ginseng has been widely consumed for medicinal and dietary purposes, but climate warming and rising heat waves are negatively impacting its productivity and yield quality. This study demonstrated the potential of fluorescence hyperspectral imaging for early detection and prediction of chlorophyll composition in heat-stressed ginseng plants. The results showed high accuracy in discriminating heat-stressed plants and predicting chlorophyll concentration.
APPLIED SCIENCES-BASEL
(2023)
Article
Chemistry, Analytical
Takanori Iino, Kenji Hashimoto, Takuya Asai, Kazuyuki Kuchitsu, Yasuyuki Ozeki
Summary: Stimulated Raman scattering (SRS) microscopy enables label-free biological imaging with chemical specificity and discrimination of multiple components. Hyperspectral SRS imaging can identify up to six components in plant tissues without labeling, showcasing its efficacy as a tool for label-free multicolour imaging analysis of various biomolecules.
Review
Instruments & Instrumentation
Zhixin Wang, Peng Xu, Bohan Liu, Yankun Cao, Zhi Liu, Zhaojun Liu
Summary: This paper demonstrates the principle and practical applications of hyperspectral object detection, as well as discussing the challenges faced in this field. By summarizing the current research status of hyperspectral techniques and exploring the development of underwater hyperspectral techniques, the paper presents a conclusion of applications and future research directions. Various methods for underwater object detection with hyperspectral imaging are compared, highlighting the importance of these methods in the future of this technology.
Article
Spectroscopy
Jiaying Wang, Laijun Sun, Guojun Feng, Hongyi Bai, Jun Yang, Zhaodong Gai, Zhide Zhao, Guanghui Zhang
Summary: In this study, accurate detection of hard seeds in snap beans was achieved using hyperspectral imaging technology. By processing characteristic spectra and wavelengths, an intelligent detection model was established with a detection accuracy rate of 89.32%.
SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
(2022)
Article
Chemistry, Analytical
Mangalraj Poobalasubramanian, Eun-Sung Park, Mohammad Akbar Faqeerzada, Taehyun Kim, Moon Sung Kim, Insuck Baek, Byoung-Kwan Cho
Summary: This study aims to detect early heat and water stress in strawberry plants using fluorescence images and chlorophyll-fluorescence indices, and develop machine-learning models to assess their performance. The proposed workflow performs well in terms of accuracy and has significant implications for strawberry plant management.
Article
Plant Sciences
Muhammad Akbar Andi Arief, Hangi Kim, Hary Kurniawan, Andri Prima Nugroho, Taehyun Kim, Byoung-Kwan Cho
Summary: Chlorophyll fluorescence imaging (CFI) is the latest method used to measure the efficiency of photosynthesis in strawberry plants, providing non-destructive spatiotemporal data. A CFI system was developed in this study to measure the maximum quantum efficiency of photochemistry (Fv/Fm), using a dark adaptation chamber, blue LED light sources, and a monochrome camera with a lens filter. The Fv/Fm values obtained from different treatment groups showed a correlation with a chlorophyll meter, indicating the accuracy of the developed CFI system in capturing the response of strawberry plants to abiotic stresses.
Article
Biochemical Research Methods
Eleni Aloupogianni, Takaya Ichimura, Mei Hamada, Masahiro Ishikawa, Takuo Murakami, Atsushi Sasaki, Koichiro Nakamura, Naoki Kobayashi, Takashi Obi
Summary: This study proposes a framework for tumor segmentation of pigmented skin lesions based on hyperspectral imaging (HSI). Pixel-wise processing and simultaneous use of spatio-spectral features are shown to improve segmentation performance and produce more comprehensive tumor masks. A three-dimensional Xception-based network achieves good performance in tumor border detection, but has difficulty detecting margins in some cases of basal cell carcinoma.
JOURNAL OF BIOMEDICAL OPTICS
(2022)
Article
Engineering, Chemical
Bartosz Blonski, Slawomir Wilczynski, Anna Stolecka-Warzecha
Summary: This study aims to assess the homogeneity of distribution of active pharmaceutical ingredients in chocolate using computed microtomography, and proposes image analysis algorithms for this purpose. These methods allow for quantitative assessment of the distribution of components in chocolate samples without the need for 3D reconstruction.
Article
Plant Sciences
Anne M. Ruffing, Stephen M. Anthony, Lucas M. Strickland, Ian Lubkin, Carter R. Dietz
Summary: Industrial accidents release harmful chemicals into the environment, impacting natural flora and potentially causing metal contamination. This study uses hyperspectral reflectance imaging and MCR analysis to identify unique spectral signatures of different stresses in plants, providing a method to distinguish stress phenotypes. The research demonstrates that this approach can be effective in detecting metal contamination across large geographical areas.
FRONTIERS IN PLANT SCIENCE
(2021)
Article
Agronomy
Zhenfeng Yang, Juncang Tian, Zhi Wang, Kepeng Feng
Summary: Photosynthesis is a critical indicator for predicting crop yield and quality, and accurately monitoring its dynamics is of great importance in field management. This study developed a Bayesian neural network model to predict photosynthetic performance parameters in grape leaves by quantifying spectral response indices of photosynthetic pigments and water status. The results showed that the developed model had better predictive performance compared to other models, and it could simplify the complex photosynthetic reaction process and provide a rapid and accurate method for monitoring photosynthetic performance.
EUROPEAN JOURNAL OF AGRONOMY
(2022)
Article
Environmental Sciences
Shuowen Yang, Xiang Yan, Hanlin Qin, Qingjie Zeng, Yi Liang, Henry Arguello, Xin Yuan
Summary: This paper introduces a novel mid-infrared compressive hyperspectral imaging system that combines an improved MIR-DMD with an off-the-shelf infrared spectroradiometer to capture hyperspectral images in the mid-infrared spectral range. The development of a dual-stage image reconstruction method and the use of measurement without coding as side information has improved the quality of reconstruction for infrared hyperspectral images. This system represents a less expensive alternative to conventional mid-infrared hyperspectral imaging systems.
Article
Horticulture
Marius Ruett, Laura Verena Junker-Frohn, Bastian Siegmann, Jan Ellenberger, Hannah Jaenicke, Cory Whitney, Eike Luedeling, Peter Tiede-Arlt, Uwe Rascher
Summary: This study introduces a new method for assessing the health status of ornamental plants, using hyperspectral imaging technology combined with expert experience for plant performance monitoring. Reflectance in the green and red-edge regions of the spectrum was identified as crucial for classifying plants as healthy or stressed.
SCIENTIA HORTICULTURAE
(2022)
Article
Environmental Sciences
Jordi Cristobal, Patrick Graham, Anupma Prakash, Marcel Buchhorn, Rudi Gens, Nikki Guldager, Mark Bertram
Summary: A pilot study for mapping Arctic wetlands was conducted in the Yukon Flats National Wildlife Refuge in Alaska, using hyperspectral images and various classification methods to achieve the best classification performance. Recommendations for future work include the acquisition of LiDAR or RGB photo-derived digital surface models to improve classification efforts.