http://chineseinput.net/에서 pinyin(병음)방식으로 중국어를 변환할 수 있습니다.
변환된 중국어를 복사하여 사용하시면 됩니다.
Differentiation of Beef and Fish Meals in Animal Feeds Using Chemometric Analytic Models
Yang, Chun-Chieh,Garrido-Novell, Cristobal,Perez-Marin, Dolores,Guerrero-Ginel, Jose E.,Garrido-Varo, Ana,Cho, Hyunjeong,Kim, Moon S. Korean Society for Agricultural Machinery 2015 바이오시스템공학 Vol.40 No.2
Purpose: The research presented in this paper applied the chemometric analysis to the near-infrared spectral data from line-scanned hyperspectral images of beef and fish meals in animal feeds. The chemometric statistical models were developed to distinguish beef meals from fish ones. Methods: The meal samples of 40 fish meals and 15 beef meals were line-scanned to obtain hyperspectral images. The spectral data were retrieved from each of 3600 pixels in the Region of Interest (ROI) of every sample image. The wavebands spanning 969 nm to 1551 nm (across 176 spectral bands) were selected for chemometric analysis. The partial least squares regression (PLSR) and the principal component analysis (PCA) methods of the chemometric analysis were applied to the model development. The purpose of the models was to correctly classify as many beef pixels as possible while misclassified fish pixels in an acceptable amount. Results: The results showed that the success classification rates were 97.9% for beef samples and 99.4% for fish samples by the PLSR model, and 85.1% for beef samples and 88.2% for fish samples by the PCA model. Conclusion: The chemometric analysis-based PLSR and PCA models for the hyperspectral image analysis could differentiate beef meals from fish ones in animal feeds.
( Chun Chieh Yang ),( Cristobal Garrido Novell ),( Dolores Perez Marin ),( Jose E Guerrero Ginel ),( Garrido Varo ),( Hyun Jeong Cho ),( Moon S. Kim ) 한국농업기계학회 2015 바이오시스템공학 Vol.40 No.2
Purpose: The research presented in this paper applied the chemometric analysis to the near-infrared spectral data fromline-scanned hyperspectral images of beef and fish meals in animal feeds. The chemometric statistical models weredeveloped to distinguish beef meals from fish ones. Methods: The meal samples of 40 fish meals and 15 beef meals wereline-scanned to obtain hyperspectral images. The spectral data were retrieved from each of 3600 pixels in the Region ofInterest (ROI) of every sample image. The wavebands spanning 969 nm to 1551 nm (across 176 spectral bands) wereselected for chemometric analysis. The partial least squares regression (PLSR) and the principal component analysis (PCA)methods of the chemometric analysis were applied to the model development. The purpose of the models was to correctlyclassify as many beef pixels as possible while misclassified fish pixels in an acceptable amount. Results: The results showedthat the success classification rates were 97.9% for beef samples and 99.4% for fish samples by the PLSR model, and 85.1%for beef samples and 88.2% for fish samples by the PCA model. Conclusion: The chemometric analysis-based PLSR and PCAmodels for the hyperspectral image analysis could differentiate beef meals from fish ones in animal feeds.
Oxidative stress is associated with the number of components of metabolic syndrome: LIPGENE study
Elena Maria Yubero-Serrano,Javier Delgado-Lista,Patricia Pena-Orihuela,Pablo Perez-Martine,Francisco Fuentes,Carmen Marin,Isaac Tunez,Francisco Jose Tinahones,Francisco Perez-Jimenez,Helen M Roche,Jos 생화학분자생물학회 2013 Experimental and molecular medicine Vol.45 No.6
Previous evidence supports the important role that oxidative stress (OxS) plays in metabolic syndrome (MetS)-related manifestations. We determined the relationship between the number of MetS components and the degree of OxS in MetS patients. In this comparative cross-sectional study from the LIPGENE cohort, a total of 91 MetS patients (43 men and 48women; aged between 45 and 68 years) were divided into four groups based on the number of MetS components: subjects with 2, 3, 4 and 5 MetS components (n¼20, 31, 28 and 12, respectively). We measured ischemic reactive hyperemia (IRH),plasma levels of soluble vascular cell adhesion molecule-1 (sVCAM-1), total nitrite, lipid peroxidation products (LPO), hydrogen peroxide (H2O2), superoxide dismutase (SOD) and glutathione peroxidase (GPx) plasma activities. sVCAM-1, H2O2 and LPO levels were lower in subjects with 2 or 3 MetS components than subjects with 4 or 5 MetS components. IRH and total nitrite levels were higher in subjects with 2 or 3 MetS components than subjects with 4 or 5 MetS components. SOD and GPx activities were lower in subjects with 2 MetS components than subjects with 4 or 5 MetS components. Waist circumference,weight, age, homeostatic model assessment-b, triglycerides (TGs), high-density lipoprotein and sVCAM-1 levels were significantly correlated with SOD activity. MetS subjects with more MetS components may have a higher OxS level. Furthermore, association between SOD activity and MetS components may indicate that this variable could be the most relevant OxS biomarker in patients suffering from MetS and could be used as a predictive tool to determine the degree of the underlying OxS in MetS.
Fu, X.,Kim, M.S.,Chao, K.,Qin, J.,Lim, J.,Lee, H.,Garrido-Varo, A.,Perez-Marin, D.,Ying, Y. Applied Science Publishers 2014 Journal of food engineering Vol.124 No.-
Melamine (2,4,6-triamino-1,3,5-triazine) contamination of food has become an urgent and broadly recognized topic as a result of several food safety scares in the past five years. Hyperspectral imaging techniques that combine the advantages of spectroscopy and imaging have been widely applied for a variety of food quality and safety evaluations. In this study, near-infrared (NIR) hyperspectral imaging technique was investigated to detect low levels (≤1.0%) of melamine particles in milk powders. Following image preprocessing (normalization and background removal), the spectrum of each pixel in the sample images was compared to the pure melamine spectrum by spectral similarity measures including spectral angle measure (SAM), spectral correlation measure (SCM), and Euclidian distance measure (EDM). The three similarity analysis methods provided comparable results for melamine particle detection where imaging allowed visualization of the distribution of melamine particles within images of milk powder mixture samples that were prepared with various melamine concentrations. The classification results were verified by spectral feature comparison between separated mean spectra of melamine pixels and milk powder pixels. The study demonstrated that a combination of NIR hyperspectral imaging technique and spectral similarity analyses was an effective method for melamine adulteration discrimination in milk powders. The method described in this study can also be applied to other chemicals or multi-chemicals adulterant detection in milk powders.