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Anwar H, Anwar T, Murtaza S. Review on food quality assessment using machine learning and electronic nose system. BIOSENSORS AND BIOELECTRONICS: X 2023; 14:100365. [DOI: 10.1016/j.biosx.2023.100365] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/01/2023]
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2
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Tian H, Wu D, Chen B, Yuan H, Yu H, Lou X, Chen C. Rapid identification and quantification of vegetable oil adulteration in raw milk using a flash gas chromatography electronic nose combined with machine learning. Food Control 2023. [DOI: 10.1016/j.foodcont.2023.109758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
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3
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Roy M, Doddappa M, Yadav BK, Jaganmohan R, Sinija VR, Manickam L, Sarvanan S. Detection of soybean oil adulteration in cow ghee (clarified milk fat): an ultrafast study using flash gas chromatography electronic nose coupled with multivariate chemometrics. JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE 2022; 102:4097-4108. [PMID: 34997578 DOI: 10.1002/jsfa.11759] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 11/15/2021] [Accepted: 01/08/2022] [Indexed: 06/14/2023]
Abstract
BACKGROUND Cow ghee is one of the expensive edible fats in the dairy sector. Ghee is often adulterated with low-priced edible oils, like soybean oil, owing to its high market demand. The existing adulteration detection methods are time-consuming, requiring sample preparation and expertise in these fields. The possibility of detecting soybean oil adulteration (from 10% to 100%) in pure cow ghee was investigated in this study. The fingerprint information of volatile compounds was collected using a flash gas chromatography electronic nose (FGCEN) instrument. The classification results were studied using the pattern recognition chemometric models principal component analysis (PCA), soft independent modelling of class analogy (SIMCA), and discriminant function analysis (DFA). RESULTS The most powerful fingerprint odor of all the samples identified from FGCEN analysis was acetaldehyde (Z)-4-heptenal, 2-propanol, ethyl propanoate, and pentan-2-one. The odor analysis investigation was accomplished with an average analysis time of 90 s. A clear differentiation of all the samples with an excellent classification accuracy of more than 99% was achieved with the PCA and DFA chemometric methods. However, the results of the SIMCA model showed that SIMCA could only be used to detect ghee adulteration at higher concentration levels (30% to 100%). The validation study shows good agreement between FGCEN and gas chromatography-mass spectrometry methods. CONCLUSION The methodology demonstrated coupled with PCA and DFA methods for adulteration detection in ghee using FGCEN apparatus has been an efficient and convenient technique. This study explored the capability of the FGCEN instrument to tackle the adulteration problems in ghee. © 2022 Society of Chemical Industry.
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Affiliation(s)
- Mrinmoy Roy
- Planning and Monitoring Cell, Indian Institute of Food Processing Technology, Thanjavur, India
| | - Manoj Doddappa
- Planning and Monitoring Cell, Indian Institute of Food Processing Technology, Thanjavur, India
| | - Binod K Yadav
- Liaison Office, Indian Institute of Food Processing Technology, Thanjavur, India
| | - Rangarajan Jaganmohan
- Department of Food Product Development, Indian Institute of Food Processing Technology, Thanjavur, India
| | - Vadakkepulppara Rn Sinija
- Food Processing Business Incubation Centre, Indian Institute of Food Processing Technology, Thanjavur, India
| | - Loganathan Manickam
- Department of Academics and Human Resource Development, Indian Institute of Food Processing Technology, Thanjavur, India
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Han L, Chen M, Li Y, Wu S, Zhang L, Tu K, Pan L, Wu J, Song L. Discrimination of different oil types and adulterated safflower seed oil based on electronic nose combined with gas chromatography-ion mobility spectrometry. J Food Compost Anal 2022. [DOI: 10.1016/j.jfca.2022.104804] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
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5
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Roy M, Doddappa M, Yadav BK, Shanmugasundaram S. A novel technique for detection of vanaspati (
hydrogenated fat
) in cow ghee (
clarified butter fat
) using flash gas chromatography electronic nose combined with chemometrics. J FOOD PROCESS PRES 2022. [DOI: 10.1111/jfpp.16667] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Mrinmoy Roy
- Planning and Monitoring Cell National Institute of Food Technology, Entrepreneurship and Management Thanjavur India
- Department of Food Technology and Nutrition, School of Agriculture Lovely Professional University Phagwara Punjab India
| | - Manoj Doddappa
- Planning and Monitoring Cell National Institute of Food Technology, Entrepreneurship and Management Thanjavur India
| | - Binod Kumar Yadav
- Liaison Office—Bathinda National Institute of Food Technology, Entrepreneurship and Management Thanjavur India
| | - Sarvanan Shanmugasundaram
- Planning and Monitoring Cell National Institute of Food Technology, Entrepreneurship and Management Thanjavur India
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Tian H, Chen B, Lou X, Yu H, Yuan H, Huang J, Chen C. Rapid detection of acid neutralizers adulteration in raw milk using FGC E-nose and chemometrics. JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION 2022. [DOI: 10.1007/s11694-022-01403-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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7
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Electronic nose for detection of food adulteration: a review. JOURNAL OF FOOD SCIENCE AND TECHNOLOGY 2022; 59:846-858. [PMID: 35185196 PMCID: PMC8814237 DOI: 10.1007/s13197-021-05057-w] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Revised: 02/24/2021] [Accepted: 02/26/2021] [Indexed: 10/21/2022]
Abstract
The food products may attract unscrupulous vendors to dilute it with inexpensive alternative food sources to achieve more profit. The risk of high value food adulteration with cheaper substitutes has reached an alarming stage in recent years. Commonly available detection methods for food adulteration are costly, time consuming and requires high degree of technical expertise. However, a rapid and suitable detection method for possible adulterant is being evolved to tackle the aforesaid issues. In recent years, electronic nose (e-nose) system is being evolved for falsification detection of food products with reliable and rapid way. E-nose has the ability to artificially perceive aroma and distinguish them. The use of chemometric analysis together with gas sensor arrays have shown to be a significant procedure for quality monitoring in food. E-nose techniques with numerous provisions are reliable and favourable for food industry in food fraud detection. In the present review, the contributions of gas sensor based e-nose system are discussed extensively with a view to ascertain the adulteration of food products.
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8
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Food forensics: techniques for authenticity determination of food products. Forensic Sci Int 2022; 333:111243. [DOI: 10.1016/j.forsciint.2022.111243] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 02/23/2022] [Accepted: 02/24/2022] [Indexed: 12/21/2022]
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9
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Mohd Ali M, Hashim N. Non-destructive methods for detection of food quality. FUTURE FOODS 2022. [DOI: 10.1016/b978-0-323-91001-9.00003-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/01/2022] Open
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10
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Karami H, Rasekh M, Mirzaee‐Ghaleh E. Identification of olfactory characteristics of edible oil during storage period using metal oxide semiconductor sensor signals and ANN methods. J FOOD PROCESS PRES 2021. [DOI: 10.1111/jfpp.15749] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Affiliation(s)
- Hamed Karami
- Department of Biosystems Engineering University of Mohaghegh Ardabili Ardabil Iran
| | - Mansour Rasekh
- Department of Biosystems Engineering University of Mohaghegh Ardabili Ardabil Iran
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11
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Khorramifar A, Rasekh M, Karami H, Malaga-Toboła U, Gancarz M. A Machine Learning Method for Classification and Identification of Potato Cultivars Based on the Reaction of MOS Type Sensor-Array. SENSORS 2021; 21:s21175836. [PMID: 34502725 PMCID: PMC8434104 DOI: 10.3390/s21175836] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Revised: 08/24/2021] [Accepted: 08/27/2021] [Indexed: 01/03/2023]
Abstract
In response to one of the most important challenges of the century, i.e., the estimation of the food demands of a growing population, advanced technologies have been employed in agriculture. The potato has the main contribution to people’s diet worldwide. Therefore, its different aspects are worth studying. The large number of potato varieties, lack of awareness about its new cultivars among farmers to cultivate, time-consuming and inaccurate process of identifying different potato cultivars, and the significance of identifying potato cultivars and other agricultural products (in every food industry process) all necessitate new, fast, and accurate methods. The aim of this study was to use an electronic nose, along with chemometrics methods, including PCA, LDA, and ANN as fast, inexpensive, and non-destructive methods for detecting different potato cultivars. In the present study, nine sensors with the best response to VOCs were adopted. VOCs sensors were used at various VOCs concentrations (1 to 10,000 ppm) to detect different gases. The results showed that a PCA with two main components, PC1 and PC2, described 92% of the total samples’ dataset variance. In addition, the accuracy of the LDA and ANN methods were 100 and 96%, respectively.
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Affiliation(s)
- Ali Khorramifar
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran; (A.K.); (H.K.)
| | - Mansour Rasekh
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran; (A.K.); (H.K.)
- Correspondence: (M.R.); (M.G.); Tel.: +98-451-551-2081-9 (M.R.); +48-81-744-50-61 (M.G.); Fax: +48-81-744-50-67 (M.G.)
| | - Hamed Karami
- Department of Biosystems Engineering, University of Mohaghegh Ardabili, Ardabil 56199-11367, Iran; (A.K.); (H.K.)
| | - Urszula Malaga-Toboła
- Faculty of Production and Power Engineering, University of Agriculture in Kraków, Balicka 116B, 30-149 Kraków, Poland;
| | - Marek Gancarz
- Faculty of Production and Power Engineering, University of Agriculture in Kraków, Balicka 116B, 30-149 Kraków, Poland;
- Institute of Agrophysics, Polish Academy of Sciences, Doświadczalna 4, 20-290 Lublin, Poland
- Correspondence: (M.R.); (M.G.); Tel.: +98-451-551-2081-9 (M.R.); +48-81-744-50-61 (M.G.); Fax: +48-81-744-50-67 (M.G.)
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12
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HAZRA TANMAY, SINDHAV ROHITG, SUDHEENDRA CHAGANTIVENKATAKARTIKEYA, RAMAN VIMALM. Simple chromogenic test for detection of adulterated milk with vegetable oil at village milk collection center- A preliminary study. THE INDIAN JOURNAL OF ANIMAL SCIENCES 2021. [DOI: 10.56093/ijans.v91i3.114148] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
In the present investigation, a novel chromogenic test has been developed to ascertain the presence of vegetable oil in milk. This standardized protocol did not show any false-positive results in the genuine milk samples. Adulteration of milk with vegetable oil @ 1% level could be detected by this chromogenic test protocol. This said protocol is convenient to use in the rural dairy industry especially rural-based milk collection centers; as no costly instrument or trained manpower is required for this said test.
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Khodamoradi F, Mirzaee-Ghaleh E, Dalvand MJ, Sharifi R. Classification of basil plant based on the level of consumed nitrogen fertilizer using an olfactory machine. FOOD ANAL METHOD 2021. [DOI: 10.1007/s12161-021-02089-y] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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14
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Galvan D, Aquino A, Effting L, Mantovani ACG, Bona E, Conte-Junior CA. E-sensing and nanoscale-sensing devices associated with data processing algorithms applied to food quality control: a systematic review. Crit Rev Food Sci Nutr 2021; 62:6605-6645. [PMID: 33779434 DOI: 10.1080/10408398.2021.1903384] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Devices of human-based senses such as e-noses, e-tongues and e-eyes can be used to analyze different compounds in several food matrices. These sensors allow the detection of one or more compounds present in complex food samples, and the responses obtained can be used for several goals when different chemometric tools are applied. In this systematic review, we used Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, to address issues such as e-sensing with chemometric methods for food quality control (FQC). A total of 109 eligible articles were selected from PubMed, Scopus and Web of Science. Thus, we predicted that the association between e-sensing and chemometric tools is essential for FQC. Most studies have applied preliminary approaches like exploratory analysis, while the classification/regression methods have been less investigated. It is worth mentioning that non-linear methods based on artificial intelligence/machine learning, in most cases, had classification/regression performances superior to non-liner, although their applications were seen less often. Another approach that has generated promising results is the data fusion between e-sensing devices or in conjunction with other analytical techniques. Furthermore, some future trends in the application of miniaturized devices and nanoscale sensors are also discussed.
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Affiliation(s)
- Diego Galvan
- Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), Federal University of Rio de Janeiro (UFRJ), Cidade Universitária, Rio de Janeiro, RJ, Brazil.,Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), Cidade Universitária, Rio de Janeiro, RJ, Brazil.,Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil
| | - Adriano Aquino
- Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), Federal University of Rio de Janeiro (UFRJ), Cidade Universitária, Rio de Janeiro, RJ, Brazil.,Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), Cidade Universitária, Rio de Janeiro, RJ, Brazil.,Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil
| | - Luciane Effting
- Chemistry Department, State University of Londrina (UEL), Londrina, PR, Brazil
| | | | - Evandro Bona
- Post-Graduation Program of Food Technology (PPGTA), Federal University of Technology Paraná (UTFPR), Campo Mourão, PR, Brazil
| | - Carlos Adam Conte-Junior
- Center for Food Analysis (NAL), Technological Development Support Laboratory (LADETEC), Federal University of Rio de Janeiro (UFRJ), Cidade Universitária, Rio de Janeiro, RJ, Brazil.,Laboratory of Advanced Analysis in Biochemistry and Molecular Biology (LAABBM), Department of Biochemistry, Federal University of Rio de Janeiro (UFRJ), Cidade Universitária, Rio de Janeiro, RJ, Brazil.,Nanotechnology Network, Carlos Chagas Filho Research Support Foundation of the State of Rio de Janeiro (FAPERJ), Rio de Janeiro, RJ, Brazil
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15
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Peng S, Huang T, Peng Y, Zhang P, Liao L, Wu W. Combining GC-MS and chemometrics to assess the quality of camellia seed oils. CYTA - JOURNAL OF FOOD 2021. [DOI: 10.1080/19476337.2021.1933196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Affiliation(s)
- Simin Peng
- College of Food Science and Technology, Hunan Agricultural University, Changsha, P. R. China
| | - Tianzhu Huang
- Research and Development Department, Zhongzhan Camellia Oil Co. Ltd, Changsha, P. R. China
| | - Yali Peng
- Research and Development Department, Shenzhen Total-Test Technology Co. Ltd, Shenzhen, P. R. China
| | - Pengfei Zhang
- Research and Development Department, Huaihua Institute for Food and Drug Control, Huaihua, P. R. China
| | - Luyan Liao
- College of Food Science and Technology, Hunan Agricultural University, Changsha, P. R. China
| | - Weiguo Wu
- College of Food Science and Technology, Hunan Agricultural University, Changsha, P. R. China
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16
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Karami H, Rasekh M, Mirzaee‐Ghaleh E. Application of the E‐nose machine system to detect adulterations in mixed edible oils using chemometrics methods. J FOOD PROCESS PRES 2020. [DOI: 10.1111/jfpp.14696] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Hamed Karami
- Department of Biosystems Engineering University of Mohaghegh Ardabili Ardabil Iran
| | - Mansour Rasekh
- Department of Biosystems Engineering University of Mohaghegh Ardabili Ardabil Iran
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17
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Karami H, Rasekh M, Mirzaee-Ghaleh E. Qualitative analysis of edible oil oxidation using an olfactory machine. JOURNAL OF FOOD MEASUREMENT AND CHARACTERIZATION 2020. [DOI: 10.1007/s11694-020-00506-0] [Citation(s) in RCA: 32] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
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18
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Mohd Ali M, Hashim N, Abd Aziz S, Lasekan O. Principles and recent advances in electronic nose for quality inspection of agricultural and food products. Trends Food Sci Technol 2020. [DOI: 10.1016/j.tifs.2020.02.028] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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19
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A novel approach to detect highly manipulated fat adulterant as Reichert-Meissl value-adjuster in ghee (clarified butter) through signature peaks by gas chromatography of triglycerides. Journal of Food Science and Technology 2020; 57:191-199. [PMID: 31975722 DOI: 10.1007/s13197-019-04047-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Revised: 08/13/2019] [Accepted: 08/19/2019] [Indexed: 10/26/2022]
Abstract
Ghee, the clarified butter fat being the costliest fat among other edible oils and fats in India, prone to adulteration with highly manipulated cheaper oils/fats, especially during lean season. The present investigation carried on triglycerides profile of one of the latest components of the adulterant fat i.e. RM (Reichert-Meissl)-adjuster, has been exploited to check the adulteration of ghee with a newly emerged highly manipulated fat. Using standardized (S)-limits specified by the ISO/IDF for cow milk fat, the minimum level of detection of the adulterant fat was observed as 7.5%. However, in case of buffalo ghee, due to non-availability of the ISO/IDF limits, the detection of this adulterant fat in buffalo ghee was not possible. Gas chromatograms showed specific signature peaks of large size in the retention time region of 4.5 to 6.5 min for RM-adjuster and adulterant fat, whereas no such peaks were observed in pure cow and buffalo ghee samples. The new approach of zooming in and superimposing of selected peaks in the chromatograms of triglycerides of suspected ghee has been used as a strategy to find adulterant fat's presence. Through this approach, the addition of RM-adjusted highly manipulated foreign fat (adulterant fat) to the tune of even 0.5% could be achieved in both cow as well as buffalo ghee.
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Saleem M. Fluorescence Spectroscopy Based Detection of Adulteration in Desi Ghee. J Fluoresc 2020; 30:181-191. [PMID: 31940104 DOI: 10.1007/s10895-019-02483-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Accepted: 12/26/2019] [Indexed: 10/25/2022]
Abstract
Desi ghee, obtained by buffalo and cow milk, is highly expensive because it contains valuable vitamins and conjugated linoleic acid (CLA). Its high demand and cost result in to its adulteration with inferior banaspati ghee. In this study, Fluorescence spectroscopy along with multivariate analysis has been utilised for the detection and quantification of adulteration. Spectroscopic analysis showed that buffalo ghee contains more vitamins and CLA than cow, whereas cow ghee is enriched with beta-carotene. For multivariate analysis, principle component analysis (PCA) and partial least square regression (PLSR) have been applied on the spectral data for the determination of adulteration. PLSR model was authenticated by predicting 23 unknown samples including 3 commercial brands of desi ghee. The root mean square error in prediction (RMSEP) of unknown samples was found to be 1.7 which is a reasonable value for quantitative prediction. Due to non-destructive and requiring no sample pre-treatment, this method can effectively be employed as on line characterization tool for the food safety assurance.
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Affiliation(s)
- M Saleem
- Agri. & Biophotonics Division, National Institute of Lasers and Optronics College, Pakistan Institute of Engineering and Applied Sciences (NILOP-C, PIEAS), Nilore, Islamabad, Pakistan.
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Identification of Fresh-Chilled and Frozen-Thawed Chicken Meat and Estimation of their Shelf Life Using an E-Nose Machine Coupled Fuzzy KNN. FOOD ANAL METHOD 2019. [DOI: 10.1007/s12161-019-01682-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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22
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Piña MDLN, Gutiérrez MS, Panagos M, Duel P, León A, Morey J, Quiñonero D, Frontera A. Influence of the aromatic surface on the capacity of adsorption of VOCs by magnetite supported organic-inorganic hybrids. RSC Adv 2019; 9:24184-24191. [PMID: 35527864 PMCID: PMC9069820 DOI: 10.1039/c9ra04490f] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2019] [Accepted: 07/31/2019] [Indexed: 11/21/2022] Open
Abstract
It has been recently evidenced that hybrid magnetic nanomaterials based on perylene diimide (PDI) dopamine and iron oxide nanoparticles are useful for the adsorption and determination of volatile organic compounds (VOCs). However, NDI compounds are expensive and difficult to handle compared to smaller size diimides. Therefore, in this manuscript a combined experimental and theoretical investigation is reported including the analysis of the effect of changing the aromatic surface on the ability of these magnetite supported organic-inorganic hybrid nanoparticles (NPs) to adsorb several aromatic and non-aromatic VOCs. In particular, two new hybrid Fe3O4NPs are synthesized and characterized where the size of organic PDI dopamine linker is progressively reduced to naphthalene diimide (NDI) and pyromellitic diimide (PMDI). These materials were utilized to fill two sorbent tubes in series. Thermal desorption (TD) combined with capillary gas chromatography (GC)/flame detector (FID) was used to analyze both front and back tubes. Adsorption values (defined as % VOCs found in the front tube) were determined for a series of VOCs. The binding energies (DFT-D3 calculations) of VOC-Fe3O4NP complexes were also computed to correlate the electron-accepting ability of the arylene diimide (PDI, NDI or PMDI) with the adsorption capacity of the different tubes. The prepared hybrids can be easily separated magnetically and showed great reusability.
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Affiliation(s)
- María de Las Nieves Piña
- Department of Chemistry, Universitat de les Illes Balears Crta. de Valldemossa km 7.5 07122 Palma de Mallorca Spain
| | - María Susana Gutiérrez
- Department of Chemistry, Universitat de les Illes Balears Crta. de Valldemossa km 7.5 07122 Palma de Mallorca Spain
| | - Mario Panagos
- Department of Chemistry, Universitat de les Illes Balears Crta. de Valldemossa km 7.5 07122 Palma de Mallorca Spain
| | - Paulino Duel
- Department of Chemistry, Universitat de les Illes Balears Crta. de Valldemossa km 7.5 07122 Palma de Mallorca Spain
| | - Alberto León
- Department of Chemistry, Universitat de les Illes Balears Crta. de Valldemossa km 7.5 07122 Palma de Mallorca Spain
| | - Jeroni Morey
- Department of Chemistry, Universitat de les Illes Balears Crta. de Valldemossa km 7.5 07122 Palma de Mallorca Spain
| | - David Quiñonero
- Department of Chemistry, Universitat de les Illes Balears Crta. de Valldemossa km 7.5 07122 Palma de Mallorca Spain
| | - Antonio Frontera
- Department of Chemistry, Universitat de les Illes Balears Crta. de Valldemossa km 7.5 07122 Palma de Mallorca Spain
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Gancarz M, Nawrocka A, Rusinek R. Identification of Volatile Organic Compounds and Their Concentrations Using a Novel Method Analysis of MOS Sensors Signal. J Food Sci 2019; 84:2077-2085. [PMID: 31339559 DOI: 10.1111/1750-3841.14701] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2019] [Revised: 04/28/2019] [Accepted: 05/23/2019] [Indexed: 12/12/2022]
Abstract
Volatile organic compounds (VOCs) are natural markers useful in rapid assessment of adverse changes occurring in biological material. The use of an electronic nose seems to be a good, fast, and cheap method to determine particular VOCs. This paper presents a new method determination for VOCs and their concentration based on three sensorgram parameters: maximum of normalized sensor response, reaction time, and cleaning time measured from the end of the test to the half value of the maximum of normalized sensor response. The novelty of the method consists in the use for the first time of two parameters: reaction time and cleaning time measured from the end of the test to the half value of the maximum of normalized sensor response. The VOC sensorgrams at different VOC concentrations (26 to 3,842 ppm) were measured by an electronic nose Food Volatile Compound Analyzer (Agrinose) equipped with eight metal oxide semiconductor sensors dedicated to detect different gases. In the present studies, only six sensors that best respond to the VOCs were used. The highest responses to VOCs were obtained for two sensors-TGS2602 and AS-MLV-P2. The results showed that the dependence between the sensorgram parameters on VOC concentration was well described by a logarithmic curve in the whole range of concentrations. Detailed analysis revealed that the cleaning time increases with an increase in the number of carbon atoms in aliphatic molecules. The principal component analysis (PCA) was used to verify the utility of the new three parameters method in VOCs differentiation. The PCA analysis of these parameters showed that maximum of the normalized sensor response alone, which has been used for identification of particular VOCs so far, could not be regarded as a good parameter used for this purpose. Application of all the three parameters gave the best results in VOC identification. The research indicates that the use of three parameters of a volatile compound instead of only one parameter can allow precise determination of substances. Moreover, the results indicate that the analyzed parameters depend on the chemical structure of VOCs.
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Affiliation(s)
- Marek Gancarz
- Inst. of Agrophysics, Polish Academy of Sciences, Do´swiadczalna 4, 20-290, Lublin, Poland
| | - Agnieszka Nawrocka
- Inst. of Agrophysics, Polish Academy of Sciences, Do´swiadczalna 4, 20-290, Lublin, Poland
| | - Robert Rusinek
- Inst. of Agrophysics, Polish Academy of Sciences, Do´swiadczalna 4, 20-290, Lublin, Poland
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