Review
Plant Sciences
Rijad Saric, Viet D. Nguyen, Timothy Burge, Oliver Berkowitz, Martin Trtilek, James Whelan, Mathew G. Lewsey, Edhem Custovic
Summary: Our ability to manipulate the genome exceeds our capacity to measure genetic changes on plant traits. Plant scientists have been using imaging approaches, specifically hyperspectral imaging, to define plant responses to environmental conditions and optimize crop management.
TRENDS IN PLANT SCIENCE
(2022)
Article
Agronomy
Ieva Urbanaviciute, Luca Bonfiglioli, Mario A. Pagnotta
Summary: The study analyzed the diversity of root systems in six durum wheat accessions under drought conditions and evaluated root traits using a high-throughput phenotyping scanner. The results showed significant variability in root development, distribution, and architecture among the different genotypes. Interestingly, the two drought-tolerant genotypes exhibited different root system ideotypes and rooting patterns. Furthermore, a positive correlation was found between the root angle of plants grown in greenhouse conditions and plants grown in the field.
Article
Engineering, Electrical & Electronic
Yang Xu, Zebin Wu, Jocelyn Chanussot, Zhihui Wei
Summary: This paper proposes a new reconstruction algorithm based on collaborative Tucker3 tensor decomposition for dual-camera compressive hyperspectral imaging systems. The algorithm models similar nonlocal patches and introduces a spectral quadratic variation constraint while maintaining spatial structure consistency, achieving promising experimental results.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO TECHNOLOGY
(2021)
Article
Agriculture, Multidisciplinary
Ahmed Islam ElManawy, Dawei Sun, Alwaseela Abdalla, Yueming Zhu, Haiyan Cen
Summary: Hyperspectral imaging is a popular technique for plant phenotyping, but extracting useful traits from the images is challenging. This study introduces HSI-PP, a standalone software platform that can process and analyze hyperspectral images for high-throughput plant phenotyping. The results demonstrate its efficiency and accuracy in extracting phenotypic traits from large image datasets.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
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.
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)
Review
Plant Sciences
Pooja Tripathi, Sangita Subedi, Abdul Latif Khan, Yong-Suk Chung, Yoonha Kim
Summary: Silicon is a common element in soil that enhances root morphological traits in various crop species, promoting plant growth. Advanced image analysis methods utilizing machine learning technologies allow for comprehensive study of root functions and the effects of Si application on roots.
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
Andrea Genangeli, Giovanni Avola, Marco Bindi, Claudio Cantini, Francesco Cellini, Stefania Grillo, Angelo Petrozza, Ezio Riggi, Alessandra Ruggiero, Stephan Summerer, Anna Tedeschi, Beniamino Gioli
Summary: Recent developments in low-cost imaging hyperspectral cameras have opened up new possibilities for high-throughput phenotyping. This study integrated a low-cost hyperspectral camera into an HTP platform to evaluate the drought stress resistance and physiological response of four tomato genotypes. The study collected over 120 gigabytes of hyperspectral data and developed an innovative segmentation method to reduce the dataset. The results showed the better capacity of the hyperspectral index to describe the dynamic of drought stress trend compared to optical indices, while the selected optical indices were capable of describing structural changes during plant growth.
Article
Plant Sciences
Arianna Latini, Fabio Fiorani, Patrizia Galeffi, Cristina Cantale, Annamaria Bevivino, Nicolai David Jablonowski
Summary: This study investigated the effects of biochar incorporation into potting soil substrate on the early growth stages of five elite varieties of durum wheat. The results showed that specific genotypes and different biochar treatments significantly influenced plant growth traits. The use of different biochar sources also resulted in distinct changes in plant responses.
FRONTIERS IN PLANT SCIENCE
(2021)
Article
Environmental Sciences
Dongdong Ma, Tanzeel U. Rehman, Libo Zhang, Hideki Maki, Mitchell R. Tuinstra, Jian Jin
Summary: This study proposed a modeling method to understand and model the environmental influences on hyperspectral imaging data by constructing a fixed hyperspectral imaging gantry at Purdue University's research farm. The results showed that an artificial neural network (ANN) model accurately predicted the environmental effects in remote sensing results and effectively eliminated the environment-induced variation in the phenotyping features. The variance in NDVI was reduced by 79% and similar performance was confirmed with the relative water content (RWC) predictions.
Article
Multidisciplinary Sciences
Fernando Tateo, Monica Bononi, Giulia Castorina, Salvatore Antonio Colecchia, Stefano De Benedetti, Gabriella Consonni, Filippo Geuna
Summary: This study provides a characterization of a wheat landrace called 'TB2018' and compares it with other cultivars. The results show that 'TB2018' exhibits visual and genetic similarities with the traditional variety 'Senatore Cappelli'. Several genes potentially linked to the distinctive traits of 'TB2018' were identified. This study lays the foundation for the potential utilization of 'TB2018' in cultivation and breeding of traditional cultivars.
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
Agronomy
P. Euteneuer, H. Wagentristl, S. Pauer, M. Keimerl, C. Schachinger, G. Bodner, H. -p. Piepho, S. Steinkellner
Summary: Cover cropping did not affect the decay of sclerotia, but sclerotia declined faster in larger mesh size. Under sufficient moisture and temperature conditions, certain cover crops may stimulate early germination of sclerotia.
ACTA AGRICULTURAE SCANDINAVICA SECTION B-SOIL AND PLANT SCIENCE
(2022)
Article
Agronomy
Mouhannad Alsalem, Aliyeh Salehi, Jiangsan Zhao, Boris Rewald, Gernot Bodner
Summary: Root traits are crucial for plant resilience under stress. Image-based phenotyping can reveal relevant datasets on root traits, but faces challenges in methodology. This study proposes a strategy for analyzing root images and identifies inter-related root descriptors.
INTERNATIONAL AGROPHYSICS
(2021)
Article
Environmental Sciences
Cong Wang, Christoph Schuerz, Ottavia Zoboli, Matthias Zessner, Karsten Schulz, Andrea Watzinger, Gernot Bodner, Bano Mehdi-Schulz
Summary: Quantifying N2O emissions from agroecosystems is challenging due to the lack of measured data and high spatial variability. A submodule based on the SWAT model was developed to simulate N2O emissions and emission factors, capturing the impact of N fertilizer application on N2O emissions through simulated water balance.
Article
Plant Sciences
Deepanshu Khare, Tobias Selzner, Daniel Leitner, Jan Vanderborght, Harry Vereecken, Andrea Schnepf
Summary: Researchers have found that traditional models for plant root water uptake tend to overestimate the water absorption in dry soil conditions. To address this issue, they have proposed a more accurate and computationally efficient multi-scale model that can better simulate water uptake in dry soil conditions.
FRONTIERS IN PLANT SCIENCE
(2022)
Editorial Material
Plant Sciences
Andrea Schnepf, Daniel Leitner, Gernot Bodner, Mathieu Javaux
FRONTIERS IN PLANT SCIENCE
(2022)
Article
Agronomy
Christoph Rosinger, Gernot Bodner, Luca Giuliano Bernardini, Sabine Huber, Axel Mentler, Orracha Sae-Tun, Bernhard Scharf, Philipp Steiner, Johannes Tintner-Olifiers, Katharina Keiblinger
Summary: Tackling the global carbon deficit through soil organic carbon sequestration in agricultural systems has been a recent focus. However, there is still a lack of comprehensive understanding of on-farm SOC sequestration potentials in order to derive effective strategies.
Article
Soil Science
Panpan Ma, Shuzhen Nan, Xinguang Yang, Yan Qin, Tao Ma, Xilai Li, Yang Yu, Gernot Bodner
Summary: This study conducted a meta-analysis to investigate the effects of different fertilizers on soil aggregates. The results revealed that the composition of soil aggregates was significantly influenced by different fertilizer treatments and environmental conditions.
SOIL & TILLAGE RESEARCH
(2022)
Article
Soil Science
Orracha Sae-Tun, Gernot Bodner, Christoph Rosinger, Sophie Zechmeister-Boltenstern, Axel Mentler, Katharina Keiblinger
Summary: Reducing soil tillage intensity can increase soil organic carbon and nitrogen stocks, improve soil aggregate stability, promote microbial growth, and enhance soil organic carbon sequestration.
APPLIED SOIL ECOLOGY
(2022)
Article
Agronomy
Orracha Sae-Tun, Katharina M. Keiblinger, Christoph Rosinger, Axel Mentler, Herwig Mayer, Gernot Bodner
Summary: The study aims to assess the structure-related dissolved organic matter (DOM) patterns in conservation farming systems and investigate the underlying bio-chemical drivers. A novel method combining ultrasonication aggregate breakdown and continuous UV-Vis measurement was used to characterize DOM release from soil. The results showed significant differences in DOM release dynamics between land-use and agricultural management systems.
Article
Agronomy
Gernot Bodner, Mouhannad Alsalem
Summary: Water stress is the main risk for sugar beet production in Europe and its management is crucial for future growth. In a climate chamber experiment, the study found that stomatal conductance and root characteristics varied among sugar beet cultivars in response to water limitations, with longer roots buffering the reduction in stomatal conductance.
Proceedings Paper
Optics
Thomas Arnold, Martin De Biasio, Tibor Bereczki, Marcus Baumgart, Arnold Horn
Summary: This study presents the development of a detection and analysis system for solid particles and oil droplets in the process water of the petrochemical industry. A hyperspectral imaging system is used for particle material analysis, while a fluorescence imaging system is used for oil droplet detection. The results of the laboratory demonstrator show the potential application value of the system.
ALGORITHMS, TECHNOLOGIES, AND APPLICATIONS FOR MULTISPECTRAL AND HYPERSPECTRAL IMAGING XXVIII
(2022)
Proceedings Paper
Optics
T. Bereczki, T. Arnold, M. De Biasio, G. Kroupa, N. Cselyuszka
Summary: This study demonstrates the development of a compact, low-cost, high-energy Q-switched Nd:YAG laser using commercially available components, with a static, non-circulated liquid cooling system.
LASER TECHNOLOGY FOR DEFENSE AND SECURITY XVII
(2022)
Proceedings Paper
Optics
M. De Biasio, T. Arnold
Summary: This paper presents the impact of stresses introduced during semiconductor processing on silicon devices and proposes the use of Raman spectroscopy for stress measurement. The research findings demonstrate that micro-Raman spectroscopy is a powerful tool for quantitatively measuring stress levels and distributions on entire productive wafers as well as on the final chip.
ALGORITHMS, TECHNOLOGIES, AND APPLICATIONS FOR MULTISPECTRAL AND HYPERSPECTRAL IMAGING XXVIII
(2022)
Article
Plant Sciences
Sabine Julia Seidel, Thomas Gaiser, Amit Kumar Srivastava, Daniel Leitner, Oliver Schmittmann, Miriam Athmann, Timo Kautz, Julien Guigue, Frank Ewert, Andrea Schnepf
Summary: Accurate prediction of root growth and resource uptake is crucial for accurately simulating crop growth, especially under unfavorable environmental conditions. In this study, a 1D field-scale crop-soil model was coupled with a 3D architectural root model to simulate the effects of soil conditions on root growth. The model was tested and validated using field data, and the results showed that mechanical strip-wise subsoil loosening significantly enhanced root length densities and improved crop productivity, particularly under dry conditions.
FRONTIERS IN PLANT SCIENCE
(2022)