Mining hyperspectral data for non-destructive and rapid prediction of nitrite content in ham sausages

2021 ◽  
Vol 14 (2) ◽  
pp. 182-187
Author(s):  
Yadong Zhu ◽  
◽  
Hongju He ◽  
Shengqi Jiang ◽  
Hanjun Ma ◽  
...  
Keyword(s):  
Hyperspectral Data ◽  
Rapid Prediction ◽  
Non Destructive ◽  
Nitrite Content

scholarly journals INFORMATION EXTRACTION IN TOMB PIT USING HYPERSPECTRAL DATA

2018 ◽  
Vol XLII-3 ◽  
pp. 2107-2111
Author(s):  
X. Yang ◽  
M. Hou ◽  
S. Lyu ◽  
S. Ma ◽  
Z. Gao ◽  
...  
Keyword(s):  
Hyperspectral Imaging ◽  
Visual Experience ◽  
Hyperspectral Data ◽  
Shanxi Province ◽  
Bottom Surface ◽  
Archaeological Research ◽  
Reference Images ◽  
Research Findings ◽  
And Storage ◽  
Non Destructive

Hyperspectral data has characteristics of multiple bands and continuous, large amount of data, redundancy, and non-destructive. These characteristics make it possible to use hyperspectral data to study cultural relics. In this paper, the hyperspectral imaging technology is adopted to recognize the bottom images of an ancient tomb located in Shanxi province. There are many black remains on the bottom surface of the tomb, which are suspected to be some meaningful texts or paintings. Firstly, the hyperspectral data is preprocessing to get the reflectance of the region of interesting. For the convenient of compute and storage, the original reflectance value is multiplied by 10000. Secondly, this article uses three methods to extract the symbols at the bottom of the ancient tomb. Finally we tried to use morphology to connect the symbols and gave fifteen reference images. The results show that the extraction of information based on hyperspectral data can obtain a better visual experience, which is beneficial to the study of ancient tombs by researchers, and provides some references for archaeological research findings.

scholarly journals Retrieval of Hyperspectral Information from Multispectral Data for Perennial Ryegrass Biomass Estimation

Sensors ◽  
2020 ◽  
Vol 20 (24) ◽  
pp. 7192
Author(s):  
Gustavo Togeiro de Alckmin ◽  
Lammert Kooistra ◽  
Richard Rawnsley ◽  
Sytze de Bruin ◽  
Arko Lucieer
Keyword(s):  
Perennial Ryegrass ◽  
Cross Validation ◽  
Parametric Method ◽  
Vegetation Indices ◽  
Performance Comparison ◽  
Hyperspectral Data ◽  
Biomass Estimation ◽  
Canopy Reflectance ◽  
Multispectral Data ◽  
Non Destructive

The use of spectral data is seen as a fast and non-destructive method capable of monitoring pasture biomass. Although there is great potential in this technique, both end users and sensor manufacturers are uncertain about the necessary sensor specifications and achievable accuracies in an operational scenario. This study presents a straightforward parametric method able to accurately retrieve the hyperspectral signature of perennial ryegrass (Lolium perenne) canopies from multispectral data collected within a two-year period in Australia and the Netherlands. The retrieved hyperspectral data were employed to generate optimal indices and continuum-removed spectral features available in the scientific literature. For performance comparison, both these simulated features and a set of currently employed vegetation indices, derived from the original band values, were used as inputs in a random forest algorithm and accuracies of both methods were compared. Our results have shown that both sets of features present similar accuracies (root mean square error (RMSE) ≈490 and 620 kg DM/ha) when assessed in cross-validation and spatial cross-validation, respectively. These results suggest that for pasture biomass retrieval solely from top-of-canopy reflectance (ranging from 550 to 790 nm), better performing methods do not rely on the use of hyperspectral or, yet, in a larger number of bands than those already available in current sensors.

scholarly journals Gossypium Plant Health Detection from Hyperspectral Data using Various Disease Indices

2019 ◽  
Vol 9 (1) ◽  
pp. 7129-7135
Keyword(s):  
Vegetation Indices ◽  
Hyperspectral Data ◽  
Economic Losses ◽  
Treatment Technique ◽  
Linear Regression Models ◽  
Plant Composition ◽  
Personal Loss ◽  
Spectral Vegetation Indices ◽  
Non Destructive ◽  
Hyperspectral Sensor

Cotton is the world's most prevalent beneficial non-food crop, producing revenue for over 250 million people globally and employing nearly 7% of all workers in developing nations. About half of all fabrics are produced with cotton. In such a case if the cotton plant gets affected due to disease can lead to economic and personal loss. These diseases may be one of the reasons that could significantly reduce the supply of cotton to the market, which result in a low agricultural economy. Faster and more accurate prediction of leaf diseases in crops could help to develop an early treatment technique while significantly reducing economic losses. The traditional monitoring system is time-consuming and expensive. In this paper, we have discussed hyperspectral sensor ASD FieldSpec4 which are less time consuming and non-destructive. Spectral Vegetation Indices (SVI) is strongly linked to the chemical composition of the plant leaf such as chlorophyll, nitrogen, carotenoid, and anthocyanin. The linear regression models were developed for the calculation of correlations between spectral indices and plant composition using MATLAB 2018.

Recent advances in the rapid acoustic screening of deoxynivalenol in wheat grains

2014 ◽  
Vol 7 (4) ◽  
pp. 517-525 ◽  
Author(s):  
G. Juodeikiene ◽  
D. Vidmantiene ◽  
L. Basinskiene ◽  
D. Cernauskas ◽  
D. Klupsaite ◽  
...  
Keyword(s):  
Moisture Content ◽  
Ultrasonic Transducer ◽  
Acoustic Method ◽  
Cereal Grains ◽  
Toxic Metabolite ◽  
Acoustic Frequency ◽  
Wheat Grains ◽  
Acoustic Technique ◽  
Rapid Prediction ◽  
Non Destructive

Deoxynivalenol (DON) is a natural and ubiquitous toxic metabolite produced by filamentous fungi of the genus Fusarium. Approximately one quarter of the world's food crops (mainly cereals) are affected by mycotoxins such as DON. A rapid and non-destructive method to evaluate the quality and safety of grains is therefore required to eliminate these toxins from the food chain. The first portable acoustic device that predicts the concentration of DON in cereal grains has been developed using a broadband capacitive ultrasonic transducer. An acoustic method was optimised for the rapid prediction of DON in wheat. To measure the performance of this method, a model system comprising 0-100% scabby wheat grains was prepared and a single laboratory validation was carried out. The best regression model between DON concentrations determined by the reference ELISA method and the acoustic technique was obtained at an acoustic frequency of 32.2 kHz, with a correlation coefficient of 0.9852 and a repeatability coefficient of variation of 2.1-9.3%, which is much better than the results achieved by prototype acoustic spectrometers. These data show that acoustic technology allows the online monitoring of DON in cereal grains, such as wheat, because it is possible to analyse multilayer grain beds. Sound absorption depends on the grain size and moisture content, so it is advisable to use the equipment at the point of harvest, where one strain of cereals usually dominates and the grains have a more homogeneous morphology and uniform moisture content.

Luminescence from individual dislocations in II-VI and III-V semiconductors

1991 ◽  
Vol 49 ◽  
pp. 834-835
Author(s):  
J W Steeds
Keyword(s):  
Group Iv ◽  
Luminescence Properties ◽  
Carrier Recombination ◽  
Transmission Electron ◽  
Wide Range ◽  
Basic Physics ◽  
Semiconducting Compounds ◽  
Diamond Group ◽  
Non Destructive ◽  
Technological Significance

There is a wide range of experimental results related to dislocations in diamond, group IV, II-VI, III-V semiconducting compounds, but few of these come from isolated, well-characterized individual dislocations. We are here concerned with only those results obtained in a transmission electron microscope so that the dislocations responsible were individually imaged. The luminescence properties of the dislocations were studied by cathodoluminescence performed at low temperatures (~30K) achieved by liquid helium cooling. Both spectra and monochromatic cathodoluminescence images have been obtained, in some cases as a function of temperature.There are two aspects of this work. One is mainly of technological significance. By understanding the luminescence properties of dislocations in epitaxial structures, future non-destructive evaluation will be enhanced. The second aim is to arrive at a good detailed understanding of the basic physics associated with carrier recombination near dislocations as revealed by local luminescence properties.

Forensic Identifications Aided by Scanning Electron Microscopy of Silicone-Epoxy Microreplicas of Calcified and Cornified Structures

1975 ◽  
Vol 33 ◽  
pp. 678-679 ◽  
Author(s):  
R.F. Sognnaes
Keyword(s):  
Electron Microscopy ◽  
Scanning Electron Microscopy ◽  
Forensic Science ◽  
George Washington ◽  
Epithelial Surface ◽  
Extended Application ◽  
Tissue Surfaces ◽  
Non Destructive ◽  
Scanning Electron ◽  
Surface Changes

Sufficient experience has been gained during the past five years to suggest an extended application of microreplication and scanning electron microscopy to problems of forensic science. The author's research was originally initiated with a view to develop a non-destructive method for identification of materials that went into objects of art, notably ivory and ivories. This was followed by a very specific application to the identification and duplication of the kinds of materials from animal teeth and tusks which two centuries ago went into the fabrication of the ivory dentures of George Washington. Subsequently it became apparent that a similar method of microreplication and SEM examination offered promise for a whole series of problems pertinent to art, technology and science. Furthermore, what began primarily as an application to solid substances has turned out to be similarly applicable to soft tissue surfaces such as mucous membranes and skin, even in cases of acute, chronic and precancerous epithelial surface changes, and to post-mortem identification of specific structures pertinent to forensic science.

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