Rapid and non-destructive detection of chicken adulteration in minced beef using visible near-infrared hyperspectral imaging and machine learning

This paper proposes the use of Near Infrared Hyperspectral Imaging (NIR-HSI) as a new strategy for fast and non-destructive classification of cotton seeds with respect to variety.

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Near-infrared hyperspectral imaging in tandem with partial least squares regression and genetic algorithm for non-destructive determination and visualization of Pseudomonas loads in chicken fillets

Talanta ◽

10.1016/j.talanta.2013.01.057 ◽

2013 ◽

Vol 109 ◽

pp. 74-83 ◽

Cited By ~ 131

Author(s):

Yao-Ze Feng ◽

Da-Wen Sun

Keyword(s):

Genetic Algorithm ◽

Least Squares ◽

Partial Least Squares ◽

Hyperspectral Imaging ◽

Partial Least Squares Regression ◽

Near Infrared ◽

Least Squares Regression ◽

Non Destructive

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Near-infrared spectroscopy and hyperspectral imaging: non-destructive analysis of biological materials

Chemical Society Reviews ◽

10.1039/c4cs00062e ◽

2014 ◽

Vol 43 (24) ◽

pp. 8200-8214 ◽

Cited By ~ 219

Author(s):

Marena Manley

Keyword(s):

Infrared Spectroscopy ◽

Hyperspectral Imaging ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Nir Spectroscopy ◽

Biological Materials ◽

Destructive Analysis ◽

Non Destructive

Principles, interpretation and applications of near-infrared (NIR) spectroscopy and NIR hyperspectral imaging are reviewed.

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Use of infrared hyperspectral imaging as an aid for paint identification

Journal of Spectral Imaging ◽

10.1255/jsi.2016.a2 ◽

2016 ◽

Cited By ~ 1

Author(s):

A. Polak ◽

T. Kelman ◽

P. Murray ◽

S. Marshall ◽

D. Stothard ◽

...

Keyword(s):

Hyperspectral Imaging ◽

Near Infrared ◽

Imaging System ◽

Classification Problem ◽

Extensive Study ◽

Electromagnetic Spectrum ◽

New Techniques ◽

Art Authentication ◽

Infrared Spectral ◽

Non Destructive

Art authentication is a complicated process that often requires the extensive study of high value objects. Although a series of non-destructive techniques is already available for art scientists, new techniques, extending current possibilities, are still required. In this paper, the use of a novel mid-infrared tunable imager is proposed as an active hyperspectral imaging system for art work analysis. The system provides access to a range of wavelengths in the electromagnetic spectrum (2500–3750 nm) which are otherwise difficult to access using conventional hyperspectral imaging (HSI) equipment. The use of such a tool could be beneficial if applied to the paint classification problem and could help analysts map the diversity of pigments within a given painting. The performance of this tool is demonstrated and compared with a conventional, off-the-shelf HSI system operating in the near infrared spectral region (900–1700 nm). Various challenges associated with laser-based imaging are demonstrated and solutions to these challenges as well as the results of applying classification algorithms to datasets captured using both HSI systems are presented. While the conventional HSI system provides data in which more pigments can be accurately classified, the result of applying the proposed laser-based imaging system demonstrates the validity of this technique for application in art authentication tasks.

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Distinction of surgically resected gastrointestinal stromal tumor by near-infrared hyperspectral imaging

Scientific Reports ◽

10.1038/s41598-020-79021-7 ◽

2020 ◽

Vol 10 (1) ◽

Author(s):

Daiki Sato ◽

Toshihiro Takamatsu ◽

Masakazu Umezawa ◽

Yuichi Kitagawa ◽

Kosuke Maeda ◽

...

Keyword(s):

Machine Learning ◽

Gastrointestinal Stromal Tumor ◽

Hyperspectral Imaging ◽

Near Infrared ◽

Submucosal Tumor ◽

Stromal Tumor ◽

Training Data ◽

Support Vector ◽

Gastric Gist ◽

Mucosal Layer

AbstractThe diagnosis of gastrointestinal stromal tumor (GIST) using conventional endoscopy is difficult because submucosal tumor (SMT) lesions like GIST are covered by a mucosal layer. Near-infrared hyperspectral imaging (NIR-HSI) can obtain optical information from deep inside tissues. However, far less progress has been made in the development of techniques for distinguishing deep lesions like GIST. This study aimed to investigate whether NIR-HSI is suitable for distinguishing deep SMT lesions. In this study, 12 gastric GIST lesions were surgically resected and imaged with an NIR hyperspectral camera from the aspect of the mucosal surface. Thus, the images were obtained ex-vivo. The site of the GIST was defined by a pathologist using the NIR image to prepare training data for normal and GIST regions. A machine learning algorithm, support vector machine, was then used to predict normal and GIST regions. Results were displayed using color-coded regions. Although 7 specimens had a mucosal layer (thickness 0.4–2.5 mm) covering the GIST lesion, NIR-HSI analysis by machine learning showed normal and GIST regions as color-coded areas. The specificity, sensitivity, and accuracy of the results were 73.0%, 91.3%, and 86.1%, respectively. The study suggests that NIR-HSI analysis may potentially help distinguish deep lesions.

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Non-Destructive Assessment of Edible Seed Chemical Content by Near-Infrared Hyperspectral Imaging for the Improvement of Nutritional Traits in Bottle Gourd (Lagenaria Siceraria)

Journal of Agricultural Science and Food Technology ◽

10.36630/jasft_19060 ◽

2021 ◽

Vol 7 (5) ◽

pp. 75-81

Author(s):

Nadège Aurelie N’dri-Aya ◽

◽

Irié Vroh-Bi ◽

◽

Keyword(s):

Hyperspectral Imaging ◽

Near Infrared ◽

Principal Component ◽

Bottle Gourd ◽

Lagenaria Siceraria ◽

Absorption Bands ◽

Tropical Regions ◽

Nutrition Security ◽

Chemical Content ◽

Non Destructive

The edible seeds of bottle gourd [Lagenaria siceraria (Molina) Standl.] are rich in oils, proteins and minerals of high nutritional quality. They are highly prized in pan tropical regions where they constitute valuable resources for food and nutrition security. In this study, near-infrared hyperspectral imaging (NIR-HSI) was combined with chemometrics to assess the variability of seed chemical content of African cultivars for the selection of nutritional traits. Six hundred seeds of four accessions belonging to two cultivars were collected from the Ivory Coast (West Africa) and analysed. The NIR-HSI spectra collected on whole seeds in the 1100-2400 nm range revealed that the main absorption bands of the seed chemical content were associated with water, lipids and proteins. The absorbance values between seeds of the same accession in these spectral regions varied up to 1.8 folds. Among the two chemometric tools used, principal component analysis (PCA) did not separate the accessions while Partial Least Squares Discriminant Analysis (PLS-DA) discriminated the accessions with 87.33 % to 94.67 %, and the cultivars with 90 % to 92 % correct classification. Seed oils from bottle gourd are for instance rich in linoleic acid which is an essential fatty acid for human health. The non-destructive and qualitative determination of the content of single seeds was demonstrated in the study and provides the opportunity to select superior seeds for the improvement of key nutritional traits in bottle gourd. Lagenaria siceraria, near-infrared hyperspectral imaging, seed chemical content, PCA, PLS-DA, nutrition security

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Applications of Visible and near-Infrared Hyperspectral Imaging for Non-Destructive Detection of the Agricultural Products

Advanced Materials Research ◽

10.4028/www.scientific.net/amr.317-319.909 ◽

2011 ◽

Vol 317-319 ◽

pp. 909-914

Author(s):

Ying Lan Jiang ◽

Ruo Yu Zhang ◽

Jie Yu ◽

Wan Chao Hu ◽

Zhang Tao Yin

Keyword(s):

Hyperspectral Imaging ◽

Near Infrared ◽

Imaging System ◽

Imaging Technique ◽

Agricultural Products ◽

Quality Inspection ◽

Hyperspectral Reflectance ◽

Imaging And Spectroscopy ◽

Non Destructive

Agricultural products quality which included intrinsic attribute and extrinsic characteristic, closely related to the health of consumer and the exported cost. Now, imaging (machine vision) and spectrum are two main nondestructive inspection technologies to be applied. Hyperspectral imaging, a new emerging technology developed for detecting quality of the food and agricultural products in recent years, combined techniques of conventional imaging and spectroscopy to obtain both spatial and spectral information from an objective simultaneously. This paper compared the advantage and disadvantage of imaging, spectrum and hyperspectral imaging technique, and provided a description to basic principle, feature of hyperspectral imaging system and calibration of hyperspectral reflectance images. In addition, the recent advances for the application of hyperspectral imaging to agricultural products quality inspection were reviewed in other countries and China.

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