Non-destructively sensing pork quality using near infrared multispectral imaging technique

RSC Advances ◽  
2015 ◽  
Vol 5 (116) ◽  
pp. 95903-95910 ◽  
Author(s):  
Qiping Huang ◽  
Huanhuan Li ◽  
Jiewen Zhao ◽  
Gengping Huang ◽  
Quansheng Chen
Keyword(s):  
Near Infrared ◽  
Multispectral Imaging ◽  
Imaging System ◽  
Imaging Technique ◽  
Water Holding Capacity ◽  
Pork Quality ◽  
Water Holding ◽  
Non Destructive

Near infrared multispectral imaging system based on three wavebands—1280 nm, 1440 nm and 1660 nm—was developed for the non-destructive sensing of the tenderness and water holding capacity of pork.

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

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.

scholarly journals Non-Destructive Detection Pilot Study of Vegetable Organic Residues Using VNIR Hyperspectral Imaging and Deep Learning Techniques

Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2899
Author(s):  
Youngwook Seo ◽  
Giyoung Kim ◽  
Jongguk Lim ◽  
Ahyeong Lee ◽  
Balgeum Kim ◽  
...  
Keyword(s):  
Deep Learning ◽  
Hyperspectral Imaging ◽  
Near Infrared ◽  
Imaging System ◽  
Imaging Technique ◽  
Support Vector ◽  
Organic Residues ◽  
Efficient Detection ◽  
Non Destructive

Contamination is a critical issue that affects food consumption adversely. Therefore, efficient detection and classification of food contaminants are essential to ensure food safety. This study applied a visible and near-infrared (VNIR) hyperspectral imaging technique to detect and classify organic residues on the metallic surfaces of food processing machinery. The experimental analysis was performed by diluting both potato and spinach juices to six different concentration levels using distilled water. The 3D hypercube data were acquired in the range of 400–1000 nm using a line-scan VNIR hyperspectral imaging system. Each diluted residue in the spectral domain was detected and classified using six classification methods, including a 1D convolutional neural network (CNN-1D) and five pre-processing methods. Among them, CNN-1D exhibited the highest classification accuracy, with a 0.99 and 0.98 calibration result and a 0.94 validation result for both spinach and potato residues. Therefore, in comparison with the validation accuracy of the support vector machine classifier (0.9 and 0.92 for spinach and potato, respectively), the CNN-1D technique demonstrated improved performance. Hence, the VNIR hyperspectral imaging technique with deep learning can potentially afford rapid and non-destructive detection and classification of organic residues in food facilities.

A rapid and non-destructive method for detecting the water-holding capacity of pork using composite film

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Xing Li ◽  
Xiaodan Wang ◽  
Dengyong Liu ◽  
Yanli Dong ◽  
Feng Hu
Keyword(s):  
Service Life ◽  
Composite Film ◽  
Water Holding Capacity ◽  
Detection Methods ◽  
Important Indicator ◽  
Discriminant Model ◽  
Fisher Discriminant ◽  
Water Holding ◽  
Non Destructive ◽  
Pork Samples

Abstract Water-holding capacity (WHC) is an important indicator of pork quality, but the existing detection methods of WHC are either expensive or time-consuming. In this study, a new method of pork WHC detection was developed by a composite film. The preparation method, mechanical properties and service life of the composite film were studied. The result showed that composite film was 0.46 ± 0.06 mm thick and had a service life of 21 days, tensile strength of 7.72 ± 0.11 MPa and the elongation at break of 28.54 ± 0.15%. Thirty groups of pork samples were randomly selected to build the model and another twenty groups were used to verify the model accuracy. Results showed that the accuracy of composite film coupled with Fisher discriminant model to detect the WHC of pork is 90%. This study demonstrates the high value of composite film as a detection tool to classify WHC of pork.

scholarly journals Rapid identification of shallow inundation for mosquito disease mitigation using drone-derived multispectral imagery

2020 ◽  
Vol 15 (1) ◽  
Author(s):  
Tasya Vadya Sarira ◽  
Kenneth Clarke ◽  
Philip Weinstein ◽  
Lian Pin Koh ◽  
Megan Lewis
Keyword(s):  
Vegetation Index ◽  
Near Infrared ◽  
Multispectral Imaging ◽  
Imaging System ◽  
South Australia ◽  
Rapid Identification ◽  
Breeding Habitat ◽  
Mapping Accuracy ◽  
Normalised Difference Vegetation Index ◽  
Mosquito Breeding

Mosquito breeding habitat identification often relies on slow, labour-intensive and expensive ground surveys. With advances in remote sensing and autonomous flight technologies, we endeavoured to accelerate this detection by assessing the effectiveness of a drone multispectral imaging system to determine areas of shallow inundation in an intertidal saltmarsh in South Australia. Through laboratory experiments, we characterised Near-Infrared (NIR) reflectance responses to water depth and vegetation cover, and established a reflectance threshold for mapping water sufficiently deep for potential mosquito breeding. We then applied this threshold to field-acquired drone imagery and used simultaneous in-situ observations to assess its mapping accuracy. A NIR reflectance threshold of 0.2 combined with a vegetation mask derived from Normalised Difference Vegetation Index (NDVI) resulted in a mapping accuracy of 80.3% with a Cohen’s Kappa of 0.5, with confusion between vegetation and shallow water depths (< 10 cm) appearing to be major causes of error. This high degree of mapping accuracy was achieved with affordable drone equipment, and commercially available sensors and Geographic Information Systems (GIS) software, demonstrating the efficiency of such an approach to identify shallow inundation likely to be suitable for mosquito breeding.

Non-destructive determination of total polyphenols content and classification of storage periods of Iron Buddha tea using multispectral imaging system

2015 ◽  
Vol 176 ◽  
pp. 130-136 ◽  
Author(s):  
Chuanwu Xiong ◽  
Changhong Liu ◽  
Wenjuan Pan ◽  
Fei Ma ◽  
Can Xiong ◽  
...  
Keyword(s):  
Multispectral Imaging ◽  
Imaging System ◽  
Total Polyphenols ◽  
Non Destructive

scholarly journals ACTIVE SPECTRAL IMAGING NONDESTRUCTIVE EVALUATION (SINDE) CAMERA

2016 ◽  
Vol 5 (1) ◽  
pp. 121-125 ◽  
Author(s):  
Eli Simova ◽  
Paul A. Rochefort
Keyword(s):  
Nondestructive Evaluation ◽  
Near Infrared ◽  
Multispectral Imaging ◽  
Light Emitting Diodes ◽  
Imaging Technique ◽  
Spectral Imaging ◽  
Video Camera ◽  
Proof Of Concept ◽  
Light Emitting

A proof-of-concept video camera for active spectral imaging nondestructive evaluation has been demonstrated. An active multispectral imaging technique has been implemented in the visible and near infrared by using light emitting diodes with wavelengths spanning from 400 to 970 nm. This shows how the camera can be used in nondestructive evaluation to inspect surfaces and spectrally identify materials and corrosion.

scholarly journals Use of infrared hyperspectral imaging as an aid for paint identification

2016 ◽  
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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