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hyperspectral imaging

Xuping Feng, Yiying Zhao, Chu Zhang, Peng Cheng, Yong He
There are possible environmental risks related to gene flow from genetically engineered organisms. It is important to find accurate, fast, and inexpensive methods to detect and monitor the presence of genetically modified (GM) organisms in crops and derived crop products. In the present study, GM maize kernels containing both cry1Ab/cry2Aj-G10evo proteins and their non-GM parents were examined by using hyperspectral imaging in the near-infrared (NIR) range (874.41-1733.91 nm) combined with chemometric data analysis...
August 17, 2017: Sensors
Ziyu Wang, Rui Zhu, Kazuhiro Fukui, Jing-Hao Xue
Hyperspectral images (HSIs) possess non-negative properties for both hyperspectral signatures and abundance coefficients, which can be naturally modelled using cone-based representation. However, in hyperspectral target detection, conebased methods are barely studied. In this paper, we propose a new regularised cone-based representation approach to hyperspectral target detection, as well as its two working models by incorporating into the cone representation l2-norm and l1- norm regularisations, respectively...
August 16, 2017: IEEE Transactions on Image Processing: a Publication of the IEEE Signal Processing Society
Gernot Bodner, Mouhannad Alsalem, Alireza Nakhforoosh, Thomas Arnold, Daniel Leitner
Better understanding of plant root dynamics is essential to improve resource use efficiency of agricultural systems and increase the resistance of crop cultivars against environmental stresses. An experimental protocol is presented for RGB and hyperspectral imaging of root systems. The approach uses rhizoboxes where plants grow in natural soil over a longer time to observe fully developed root systems. Experimental settings are exemplified for assessing rhizobox plants under water stress and studying the role of roots...
August 8, 2017: Journal of Visualized Experiments: JoVE
Christian Rogass, Friederike M Koerting, Christian Mielke, Maximilian Brell, Nina K Boesche, Maria Bade, Christian Hohmann
Proximal sensing as the near field counterpart of remote sensing offers a broad variety of applications. Imaging spectroscopy in general and translational laboratory imaging spectroscopy in particular can be utilized for a variety of different research topics. Geoscientific applications require a precise pre-processing of hyperspectral data cubes to retrieve at-surface reflectance in order to conduct spectral feature-based comparison of unknown sample spectra to known library spectra. A new pre-processing chain called GeoMAP-Trans for at-surface reflectance retrieval is proposed here as an analogue to other algorithms published by the team of authors...
August 11, 2017: Sensors
Maximilian Lange, Benjamin Dechant, Corinna Rebmann, Michael Vohland, Matthias Cuntz, Daniel Doktor
Quantifying the accuracy of remote sensing products is a timely endeavor given the rapid increase in Earth observation missions. A validation site for Sentinel-2 products was hence established in central Germany. Automatic multispectral and hyperspectral sensor systems were installed in parallel with an existing eddy covariance flux tower, providing spectral information of the vegetation present at high temporal resolution. Normalized Difference Vegetation Index (NDVI) values from ground-based hyperspectral and multispectral sensors were compared with NDVI products derived from Sentinel-2A and Moderate-resolution Imaging Spectroradiometer (MODIS)...
August 11, 2017: Sensors
Paulo Cartaxana, Erik Trampe, Michael Kühl, Sónia Cruz
Several sacoglossan sea slug species feed on macroalgae and incorporate chloroplasts into tubular cells of their digestive diverticula. We investigated the role of the "stolen" chloroplasts (kleptoplasts) in the nutrition of the sea slug Elysia viridis and assessed how their abundance, distribution and photosynthetic activity were affected by light and starvation. Elysia viridis individuals feeding on the macroalga Codium tomentosum were compared with starved specimens kept in dark and low light conditions...
August 10, 2017: Scientific Reports
Hongyan Zhu, Bingquan Chu, Yangyang Fan, Xiaoya Tao, Wenxin Yin, Yong He
We investigated the feasibility and potentiality of determining firmness, soluble solids content (SSC), and pH in kiwifruits using hyperspectral imaging, combined with variable selection methods and calibration models. The images were acquired by a push-broom hyperspectral reflectance imaging system covering two spectral ranges. Weighted regression coefficients (BW), successive projections algorithm (SPA) and genetic algorithm-partial least square (GAPLS) were compared and evaluated for the selection of effective wavelengths...
August 10, 2017: Scientific Reports
Desheng Zheng, Liyang Lu, Kevin F Kelly, Steven Baldelli
Sum frequency generation microscopy is a label-free optical imaging technique with intrinsic molecular vibrational contrast for surface studies. Recent developments of compressive sensing broad-band hyperspectral SFG microscopy have demonstrated the potential application for imaging monolayer at metal surfaces with micrometer spatial resolution. Here is presented the capability of chemical imaging of spatially patterned monolayers of 1-octadecanethiol (ODT) and 16-methoxy-1-hexadecanethiol (MeOHT) molecules assembled on a copper surface...
August 10, 2017: Journal of Physical Chemistry. B
Hui Feng, Guoxing Chen, Lizhong Xiong, Qian Liu, Wanneng Yang
Pigments absorb light, transform it into energy, and provide reaction sites for photosynthesis; thus, the quantification of pigment distribution is vital to plant research. Traditional methods for the quantification of pigments are time-consuming and not suitable for the high-throughput digitization of rice pigment distribution. In this study, using a hyperspectral imaging system, we developed an integrated image analysis pipeline for automatically processing enormous amounts of hyperspectral data. We also built models for accurately quantifying 4 pigments (chlorophyll a, chlorophyll b, total chlorophyll and carotenoid) from rice leaves and determined the important bands (700-760 nm) associated with these pigments...
2017: Frontiers in Plant Science
Chunhui Zhao, Weiwei Deng, Yiming Yan, Xifeng Yao
The Kernel-RX detector (KRXD) has attracted widespread interest in hyperspectral image processing with the utilization of nonlinear information. However, the kernelization of hyperspectral data leads to poor execution efficiency in KRXD. This paper presents an approach to the progressive line processing of KRXD (PLP-KRXD) that can perform KRXD line by line (the main data acquisition pattern). Parallel causal sliding windows are defined to ensure the causality of PLP-KRXD. Then, with the employment of the Woodbury matrix identity and the matrix inversion lemma, PLP-KRXD has the capacity to recursively update the kernel matrices, thereby avoiding a great many repetitive calculations of complex matrices, and greatly reducing the algorithm's complexity...
August 7, 2017: Sensors
A Nkengne, J Robic, P Seroul, S Gueheunneux, M Jomier, K Vie
BACKGROUND: An accurate way to determine skin pigmentation is to acquire the spectral reflectance of a skin sample and to quantify chromophores by reverse calculation from physical models of light propagation. Therefore, we tested a new hyperspectral imaging device and software suite, the SpectraCam(®) system, and evaluated its accuracy to quantify skin chromophores. METHODS: Validation of the SpectraCam(®) system was performed by, firstly, comparing the known and the acquired reflectance spectra of color phantoms...
August 2, 2017: Skin Research and Technology
Abelardo Montesinos-López, Osval A Montesinos-López, Jaime Cuevas, Walter A Mata-López, Juan Burgueño, Sushismita Mondal, Julio Huerta, Ravi Singh, Enrique Autrique, Lorena González-Pérez, José Crossa
BACKGROUND: Modern agriculture uses hyperspectral cameras that provide hundreds of reflectance data at discrete narrow bands in many environments. These bands often cover the whole visible light spectrum and part of the infrared and ultraviolet light spectra. With the bands, vegetation indices are constructed for predicting agronomically important traits such as grain yield and biomass. However, since vegetation indices only use some wavelengths (referred to as bands), we propose using all bands simultaneously as predictor variables for the primary trait grain yield; results of several multi-environment maize (Aguate et al...
2017: Plant Methods
Arjun Chennu, Paul Färber, Glenn De'ath, Dirk de Beer, Katharina E Fabricius
We developed a novel integrated technology for diver-operated surveying of shallow marine ecosystems. The HyperDiver system captures rich multifaceted data in each transect: hyperspectral and color imagery, topographic profiles, incident irradiance and water chemistry at a rate of 15-30 m(2) per minute. From surveys in a coral reef following standard diver protocols, we show how the rich optical detail can be leveraged to generate photopigment abundance and benthic composition maps. We applied machine learning techniques, with a minor annotation effort (<2% of pixels), to automatically generate cm-scale benthic habitat maps of high taxonomic resolution and accuracy (93-97%)...
August 2, 2017: Scientific Reports
Yang Chen, Xiangyong Cao, Qian Zhao, Deyu Meng, Zongben Xu
Hyperspectral image (HSI) denoising has been attracting much research attention in remote sensing area due to its importance in improving the HSI qualities. The existing HSI denoising methods mainly focus on specific spectral and spatial prior knowledge in HSIs, and share a common underlying assumption that the embedded noise in HSI is independent and identically distributed (i.i.d.). In real scenarios, however, the noise existed in a natural HSI is always with much more complicated non-i.i.d. statistical structures and the under-estimation to this noise complexity often tends to evidently degenerate the robustness of current methods...
July 27, 2017: IEEE Transactions on Cybernetics
Sébastien Angelliaume, Xavier Ceamanos, Françoise Viallefont-Robinet, Rémi Baqué, Philippe Déliot, Véronique Miegebielle
Remote sensing techniques are commonly used by Oil and Gas companies to monitor hydrocarbon on the ocean surface. The interest lies not only in exploration but also in the monitoring of the maritime environment. Occurrence of natural seeps on the sea surface is a key indicator of the presence of mature source rock in the subsurface. These natural seeps, as well as the oil slicks, are commonly detected using radar sensors but the addition of optical imagery can deliver extra information such as thickness and composition of the detected oil, which is critical for both exploration purposes and efficient cleanup operations...
August 2, 2017: Sensors
Víctor Olmos, Mònica Marro, Pablo Loza-Alvarez, Demetrio Raldúa, Eva Prats, Francesc Padrós, Benjamin Piña, Romà Tauler, Anna de Juan
Changes on an organism by the exposure to environmental stressors may be characterized by hyperspectral images (HSI), which preserve the morphology of biological samples, and suitable chemometric tools. The approach proposed allows assessing and interpreting the effect of contaminant exposure on heterogeneous biological samples monitored by HSI at specific tissue levels. In this work, the model example used consists of the study of the effect of the exposure of chlorpyrifos-oxon on zebra fish tissues. To assess this effect, unmixing of the biological sample images followed by tissue-specific classification models based on the unmixed spectral signatures is proposed...
August 2, 2017: Journal of Biophotonics
Ni Zhang, Xu Liu, Xiaoduo Jin, Chen Li, Xuan Wu, Shuqin Yang, Jifeng Ning, Paul Yanne
Phenolics contents in wine grapes are key indicators for assessing ripeness. Near-infrared hyperspectral images during ripening have been explored to achieve an effective method for predicting phenolics contents. Principal component regression (PCR), partial least squares regression (PLSR) and support vector regression (SVR) models were built, respectively. The results show that SVR behaves globally better than PLSR and PCR, except in predicting tannins content of seeds. For the best prediction results, the squared correlation coefficient and root mean square error reached 0...
December 15, 2017: Food Chemistry
Aiping Gong, Susu Zhu, Yong He, Chu Zhang
Fast and accurate grading of Chinese Cantonese sausage is an important concern for customers, organizations, and the industry. Hyperspectral imaging in the spectral range of 874-1734 nm, combined with chemometric methods, was applied to grade Chinese Cantonese sausage. Three grades of intact and sliced Cantonese sausages were studied, including the top, first, and second grades. Support vector machine (SVM) and random forests (RF) techniques were used to build two different models. Second derivative spectra and RF were applied to select optimal wavelengths...
July 25, 2017: Sensors
Jiyong Shi, Wu Chen, Xiaobo Zou, Yiwei Xu, Xiaowei Huang, Yaodi Zhu, Tingting Shen
Hyperspectral images (431-962nm) and partial least squares (PLS) were used to detect the distribution of triterpene acids within loquat (Eriobotrya japonica) leaves. 72 fresh loquat leaves in the young group, mature group and old group were collected for hyperspectral imaging; and triterpene acids content of the loquat leaves was analyzed using high performance liquid chromatography (HPLC). Then the spectral data of loquat leaf hyperspectral images and the triterpene acids content were employed to build calibration models...
July 19, 2017: Spectrochimica Acta. Part A, Molecular and Biomolecular Spectroscopy
Stuart O J Crichton, Sascha M Kirchner, Victoria Porley, Stefanie Retz, Gardis von Gersdorff, Oliver Hensel, Barbara Sturm
Initial quality grading of meat is generally carried out using invasive and occasionally destructive sampling for the purposes of pH testing. Precise pH and thresholds exist to allow the classification of different statuses of meat, e.g. for detection of dry, firm, and dark (DFD) (when dealing with cattle and sheep), or pale, soft exudative meat (when dealing with pork). This paper illustrates that threshold detection for pH level in beef with different freshness levels (fresh, fresh frozen-thawed, matured, and matured frozen-thawed)...
July 18, 2017: Meat Science
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