Jia et al., 2017 - Google Patents
Prediction of pH of fresh chicken breast fillets by VNIR hyperspectral imagingJia et al., 2017
- Document ID
- 10222427875864440497
- Author
- Jia B
- Yoon S
- Zhuang H
- Wang W
- Li C
- Publication year
- Publication venue
- Journal of Food Engineering
External Links
Snippet
Visible and near-infrared (VNIR) hyperspectral imaging (400–900 nm) was used to evaluate pH of fresh chicken breast fillets (pectoralis major muscle) from the bone (dorsal) side of individual fillets. After the principal component analysis (PCA), a band threshold method was …
- 238000000701 chemical imaging 0 title abstract description 44
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/35—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infra-red light
- G01N21/3577—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry using infra-red light for analysing liquids, e.g. polluted water
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
- G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
- G01N21/25—Colour; Spectral properties, i.e. comparison of effect of material on the light at two or more different wavelengths or wavelength bands
- G01N21/31—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry
- G01N21/314—Investigating relative effect of material at wavelengths characteristic of specific elements or molecules, e.g. atomic absorption spectrometry with comparison of measurements at specific and non-specific wavelengths
- G01N2021/3155—Measuring in two spectral ranges, e.g. UV and visible
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0012—Biomedical image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/30—Subject of image; Context of image processing
- G06T2207/30004—Biomedical image processing
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using infra-red, visible or ultra-violet light
- G01N21/84—Systems specially adapted for particular applications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by the preceding groups
- G01N33/02—Investigating or analysing materials by specific methods not covered by the preceding groups food
- G01N33/12—Investigating or analysing materials by specific methods not covered by the preceding groups food meat; fish
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10024—Color image
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/40—Analysis of texture
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/20—Special algorithmic details
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Jia et al. | Prediction of pH of fresh chicken breast fillets by VNIR hyperspectral imaging | |
Kamruzzaman et al. | Parsimonious model development for real-time monitoring of moisture in red meat using hyperspectral imaging | |
Cheng et al. | Integration of spectral and textural data for enhancing hyperspectral prediction of K value in pork meat | |
Yang et al. | Development of simplified models for nondestructive hyperspectral imaging monitoring of TVB-N contents in cured meat during drying process | |
Ivorra et al. | Detection of expired vacuum-packed smoked salmon based on PLS-DA method using hyperspectral images | |
Pu et al. | Selection of feature wavelengths for developing multispectral imaging systems for quality, safety and authenticity of muscle foods-a review | |
ElMasry et al. | Chemical-free assessment and mapping of major constituents in beef using hyperspectral imaging | |
Kamruzzaman et al. | Online monitoring of red meat color using hyperspectral imaging | |
Xiong et al. | Application of visible hyperspectral imaging for prediction of springiness of fresh chicken meat | |
Kamruzzaman et al. | Hyperspectral imaging for real-time monitoring of water holding capacity in red meat | |
Kamruzzaman et al. | Introduction to hyperspectral imaging technology | |
Ma et al. | Spectral absorption index in hyperspectral image analysis for predicting moisture contents in pork longissimus dorsi muscles | |
Dai et al. | Prediction of total volatile basic nitrogen contents using wavelet features from visible/near-infrared hyperspectral images of prawn (Metapenaeus ensis) | |
ElMasry et al. | Meat quality evaluation by hyperspectral imaging technique: an overview | |
Xiong et al. | Non-destructive prediction of thiobarbituric acid reactive substances (TBARS) value for freshness evaluation of chicken meat using hyperspectral imaging | |
Cheng et al. | Non-destructive and rapid determination of TVB-N content for freshness evaluation of grass carp (Ctenopharyngodon idella) by hyperspectral imaging | |
Kamruzzaman et al. | Application of NIR hyperspectral imaging for discrimination of lamb muscles | |
Cheng et al. | Suitability of hyperspectral imaging for rapid evaluation of thiobarbituric acid (TBA) value in grass carp (Ctenopharyngodon idella) fillet | |
Wu et al. | Application of visible and near infrared hyperspectral imaging for non-invasively measuring distribution of water-holding capacity in salmon flesh | |
Xiong et al. | Combination of spectra and texture data of hyperspectral imaging for differentiating between free-range and broiler chicken meats | |
Barbin et al. | Non-destructive determination of chemical composition in intact and minced pork using near-infrared hyperspectral imaging | |
Wu et al. | Novel non-invasive distribution measurement of texture profile analysis (TPA) in salmon fillet by using visible and near infrared hyperspectral imaging | |
Jiang et al. | Tenderness classification of fresh broiler breast fillets using visible and near-infrared hyperspectral imaging | |
Cheng et al. | Data fusion and hyperspectral imaging in tandem with least squares-support vector machine for prediction of sensory quality index scores of fish fillet | |
Yang et al. | Combination of spectral and textural information of hyperspectral imaging for the prediction of the moisture content and storage time of cooked beef |