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Lužaić T, Kravić S, Stojanović Z, Grahovac N, Jocić S, Cvejić S, Pezo L, Romanić R. Investigation of oxidative characteristics, fatty acid composition and bioactive compounds content in cold pressed oils of sunflower grown in Serbia and Argentina. Heliyon 2023; 9:e18201. [PMID: 37519709 PMCID: PMC10372673 DOI: 10.1016/j.heliyon.2023.e18201] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 07/10/2023] [Accepted: 07/11/2023] [Indexed: 08/01/2023] Open
Abstract
Background In this work, the chemical composition analysis was performed for cold pressed oils obtained from the 15 sunflower hybrids grown in Serbia and Argentina, as well as the determination of their oxidative quality. The fatty acid composition and bioactive compounds including total tocopherols, phenols, carotenoids, and chlorophyll contents were investigated. The oxidation products were monitored through the peroxide value (PV), anisidine value (AnV), conjugated dienes (CD) and conjugated trienes (CT) content, and total oxidation index (TOTOX) under accelerated oxidation conditions by the oven method. Results Linoleic acid was the most abundant fatty acid in investigated oil samples, followed by oleic and palmitic acids. The mean contents of total tocopherols, phenols, carotenoids, and chlorophyll were 518.24, 9.42, 7.54 and 0.99 mg/kg, respectively. In order to obtain an overview of sample variations according to the tested parameters Principal Component Analysis (PCA) was applied. Conclusion PCA indicated that phenols, chlorophyll, linoleic and oleic acid were the most effective variables for the differentiation of sunflower hybrids grown in Serbia and Argentina. Furthermore, based on the fatty acid composition and bioactive compounds content in the oils, a new Artificial Neural Network (ANN) model was developed to predict the oxidative stability parameters of cold pressed sunflower oil.
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Affiliation(s)
- Tanja Lužaić
- Faculty of Technology Novi Sad, University of Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia
| | - Snežana Kravić
- Faculty of Technology Novi Sad, University of Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia
| | - Zorica Stojanović
- Faculty of Technology Novi Sad, University of Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia
| | - Nada Grahovac
- Institute of Field and Vegetable Crops, National Institute of the Republic of Serbia, Maksima Gorkog 30, 21000 Novi Sad, Serbia
| | - Siniša Jocić
- Institute of Field and Vegetable Crops, National Institute of the Republic of Serbia, Maksima Gorkog 30, 21000 Novi Sad, Serbia
| | - Sandra Cvejić
- Institute of Field and Vegetable Crops, National Institute of the Republic of Serbia, Maksima Gorkog 30, 21000 Novi Sad, Serbia
| | - Lato Pezo
- Institute of General and Physical Chemistry, University of Belgrade, Studentski trg 12/V, 11000 Belgrade, Serbia
| | - Ranko Romanić
- Faculty of Technology Novi Sad, University of Novi Sad, Bulevar Cara Lazara 1, 21000 Novi Sad, Serbia
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Silver-miang nanocomposites: A green, rapid and simple approach for selective determination of nitrite in water and meat samples. Microchem J 2021. [DOI: 10.1016/j.microc.2020.105879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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3
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Vakula A, Pavlić B, Pezo L, Tepić Horecki A, Daničić T, Raičević L, Ljubojević M, Šumić Z. Vacuum drying of sweet cherry: Artificial neural networks approach in process optimization. J FOOD PROCESS PRES 2020. [DOI: 10.1111/jfpp.14863] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Affiliation(s)
- Anita Vakula
- Faculty of Technology University of Novi Sad Novi Sad Serbia
| | - Branimir Pavlić
- Faculty of Technology University of Novi Sad Novi Sad Serbia
| | - Lato Pezo
- Institute of General and Physical Chemistry University of Belgrade Belgrade Serbia
| | | | - Tatjana Daničić
- Faculty of Technology University of Novi Sad Novi Sad Serbia
| | | | | | - Zdravko Šumić
- Faculty of Technology University of Novi Sad Novi Sad Serbia
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Rapid quantification of polysaccharide and the main onosaccharides in Dendrobium huoshanense by near-infrared attenuated total reflectance spectroscopy. J Pharm Biomed Anal 2018; 151:331-338. [DOI: 10.1016/j.jpba.2018.01.027] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Revised: 01/13/2018] [Accepted: 01/15/2018] [Indexed: 11/20/2022]
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Xiong Z, Sun DW, Pu H, Gao W, Dai Q. Applications of emerging imaging techniques for meat quality and safety detection and evaluation: A review. Crit Rev Food Sci Nutr 2017; 57:755-768. [PMID: 25975703 DOI: 10.1080/10408398.2014.954282] [Citation(s) in RCA: 39] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
With improvement in people's living standards, many people nowadays pay more attention to quality and safety of meat. However, traditional methods for meat quality and safety detection and evaluation, such as manual inspection, mechanical methods, and chemical methods, are tedious, time-consuming, and destructive, which cannot meet the requirements of modern meat industry. Therefore, seeking out rapid, non-destructive, and accurate inspection techniques is important for the meat industry. In recent years, a number of novel and noninvasive imaging techniques, such as optical imaging, ultrasound imaging, tomographic imaging, thermal imaging, and odor imaging, have emerged and shown great potential in quality and safety assessment. In this paper, a detailed overview of advanced applications of these emerging imaging techniques for quality and safety assessment of different types of meat (pork, beef, lamb, chicken, and fish) is presented. In addition, advantages and disadvantages of each imaging technique are also summarized. Finally, future trends for these emerging imaging techniques are discussed, including integration of multiple imaging techniques, cost reduction, and developing powerful image-processing algorithms.
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Affiliation(s)
- Zhenjie Xiong
- a School of Food Science and Engineering , South China University of Technology , Guangzhou , China.,b Academy of Contemporary Food Engineering, South China University of Technology , Guangzhou Higher Education Mega Center , Guangzhou , China
| | - Da-Wen Sun
- a School of Food Science and Engineering , South China University of Technology , Guangzhou , China.,b Academy of Contemporary Food Engineering, South China University of Technology , Guangzhou Higher Education Mega Center , Guangzhou , China.,c Food Refrigeration and Computerised Food Technology , Agriculture and Food Science Centre, University College Dublin, National University of Ireland , Belfield , Dublin , Ireland
| | - Hongbin Pu
- a School of Food Science and Engineering , South China University of Technology , Guangzhou , China.,b Academy of Contemporary Food Engineering, South China University of Technology , Guangzhou Higher Education Mega Center , Guangzhou , China
| | - Wenhong Gao
- a School of Food Science and Engineering , South China University of Technology , Guangzhou , China.,b Academy of Contemporary Food Engineering, South China University of Technology , Guangzhou Higher Education Mega Center , Guangzhou , China
| | - Qiong Dai
- a School of Food Science and Engineering , South China University of Technology , Guangzhou , China.,b Academy of Contemporary Food Engineering, South China University of Technology , Guangzhou Higher Education Mega Center , Guangzhou , China
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Xiong Z, Xie A, Sun DW, Zeng XA, Liu D. Applications of hyperspectral imaging in chicken meat safety and quality detection and evaluation: a review. Crit Rev Food Sci Nutr 2016; 55:1287-301. [PMID: 24689678 DOI: 10.1080/10408398.2013.834875] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Currently, the issue of food safety and quality is a great public concern. In order to satisfy the demands of consumers and obtain superior food qualities, non-destructive and fast methods are required for quality evaluation. As one of these methods, hyperspectral imaging (HSI) technique has emerged as a smart and promising analytical tool for quality evaluation purposes and has attracted much interest in non-destructive analysis of different food products. With the main advantage of combining both spectroscopy technique and imaging technique, HSI technique shows a convinced attitude to detect and evaluate chicken meat quality objectively. Moreover, developing a quality evaluation system based on HSI technology would bring economic benefits to the chicken meat industry. Therefore, in recent years, many studies have been conducted on using HSI technology for the safety and quality detection and evaluation of chicken meat. The aim of this review is thus to give a detailed overview about HSI and focus on the recently developed methods exerted in HSI technology developed for microbiological spoilage detection and quality classification of chicken meat. Moreover, the usefulness of HSI technique for detecting fecal contamination and bone fragments of chicken carcasses are presented. Finally, some viewpoints on its future research and applicability in the modern poultry industry are proposed.
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Affiliation(s)
- Zhenjie Xiong
- a College of Light Industry and Food Sciences , South China University of Technology , Guangdong 510641 , P. R. China
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Rahman UU, Shahzad T, Sahar A, Ishaq A, Khan MI, Zahoor T, Aslam S. Recapitulating the competence of novel & rapid monitoring tools for microbial documentation in food systems. Lebensm Wiss Technol 2016. [DOI: 10.1016/j.lwt.2015.11.041] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
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Effect of temperature, high pressure and freezing/thawing of dry-cured ham slices on dielectric time domain reflectometry response. Meat Sci 2015; 100:91-6. [DOI: 10.1016/j.meatsci.2014.10.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2013] [Revised: 10/02/2014] [Accepted: 10/05/2014] [Indexed: 11/20/2022]
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Kamruzzaman M, Makino Y, Oshita S. Non-invasive analytical technology for the detection of contamination, adulteration, and authenticity of meat, poultry, and fish: A review. Anal Chim Acta 2015; 853:19-29. [DOI: 10.1016/j.aca.2014.08.043] [Citation(s) in RCA: 77] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2014] [Revised: 07/22/2014] [Accepted: 08/20/2014] [Indexed: 10/24/2022]
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Wei Y, Fan W, Zhao X, Wu W, Lu H. Rapid Authentication ofDendrobium officinaleby Near-Infrared Reflectance Spectroscopy and Chemometrics. ANAL LETT 2014. [DOI: 10.1080/00032719.2014.963595] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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Xiong Z, Sun DW, Zeng XA, Xie A. Recent developments of hyperspectral imaging systems and their applications in detecting quality attributes of red meats: A review. J FOOD ENG 2014. [DOI: 10.1016/j.jfoodeng.2014.02.004] [Citation(s) in RCA: 112] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Ma J, Sun DW, Qu JH, Liu D, Pu H, Gao WH, Zeng XA. Applications of Computer Vision for Assessing Quality of Agri-food Products: A Review of Recent Research Advances. Crit Rev Food Sci Nutr 2014; 56:113-27. [DOI: 10.1080/10408398.2013.873885] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
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He HJ, Wu D, Sun DW. Rapid and non-destructive determination of drip loss and pH distribution in farmed Atlantic salmon (Salmo salar) fillets using visible and near-infrared (Vis-NIR) hyperspectral imaging. Food Chem 2014; 156:394-401. [PMID: 24629986 DOI: 10.1016/j.foodchem.2014.01.118] [Citation(s) in RCA: 74] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2012] [Revised: 04/15/2013] [Accepted: 01/31/2014] [Indexed: 11/30/2022]
Abstract
Drip loss and pH are important indices in quality assessment of salmon products. This work was carried out for rapid and non-destructive determination of drip loss and pH distribution in salmon fillets using near-infrared (Vis-NIR) hyperspectral imaging. Hyperspectral images were acquired for salmon fillet samples and their spectral signatures in the 400-1700nm range were extracted. Partial least square regression (PLSR) was used to correlate the spectra with reference drip loss and pH values. Important wavelengths were selected using the regression coefficients method to develop new PLSR models, leading to a correlation coefficient of cross-validation (rCV) of 0.834 with root-mean-square errors by cross-validation (RMSECV) of 0.067 for drip loss and a rCV of 0.877 with RMSECV of 0.046 for pH, respectively. Distribution maps of drip loss and pH were generated based on the new PLSR models using image processing algorithms. The results showed that Vis-NIR hyperspectral imaging technique combined with PLSR calibration analysis offers an effective quantitative capability for determining the spatial distribution of drip loss and pH in salmon fillets.
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Affiliation(s)
- Hong-Ju He
- Food Refrigeration and Computerised Food Technology (FRCFT), School of Biosystems Engineering, University College Dublin, National University of Ireland, Agriculture & Food Science Centre, Belfield, Dublin 4, Ireland
| | - Di Wu
- Food Refrigeration and Computerised Food Technology (FRCFT), School of Biosystems Engineering, University College Dublin, National University of Ireland, Agriculture & Food Science Centre, Belfield, Dublin 4, Ireland
| | - Da-Wen Sun
- Food Refrigeration and Computerised Food Technology (FRCFT), School of Biosystems Engineering, University College Dublin, National University of Ireland, Agriculture & Food Science Centre, Belfield, Dublin 4, Ireland.
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Makky M, Soni P. In situ quality assessment of intact oil palm fresh fruit bunches using rapid portable non-contact and non-destructive approach. J FOOD ENG 2014. [DOI: 10.1016/j.jfoodeng.2013.08.011] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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Gomes JFS, Leta FR. Applications of computer vision techniques in the agriculture and food industry: a review. Eur Food Res Technol 2012. [DOI: 10.1007/s00217-012-1844-2] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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18
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Automated identification and visualization of food defects using RGB imaging: Application to the detection of red skin defect of raw hams. INNOV FOOD SCI EMERG 2012. [DOI: 10.1016/j.ifset.2012.09.008] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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Menesatti P, Angelini C, Pallottino F, Antonucci F, Aguzzi J, Costa C. RGB color calibration for quantitative image analysis: the "3D thin-plate spline" warping approach. SENSORS 2012; 12:7063-79. [PMID: 22969337 PMCID: PMC3435966 DOI: 10.3390/s120607063] [Citation(s) in RCA: 55] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/12/2012] [Revised: 05/14/2012] [Accepted: 05/22/2012] [Indexed: 11/27/2022]
Abstract
In the last years the need to numerically define color by its coordinates in n-dimensional space has increased strongly. Colorimetric calibration is fundamental in food processing and other biological disciplines to quantitatively compare samples' color during workflow with many devices. Several software programmes are available to perform standardized colorimetric procedures, but they are often too imprecise for scientific purposes. In this study, we applied the Thin-Plate Spline interpolation algorithm to calibrate colours in sRGB space (the corresponding Matlab code is reported in the Appendix). This was compared with other two approaches. The first is based on a commercial calibration system (ProfileMaker) and the second on a Partial Least Square analysis. Moreover, to explore device variability and resolution two different cameras were adopted and for each sensor, three consecutive pictures were acquired under four different light conditions. According to our results, the Thin-Plate Spline approach reported a very high efficiency of calibration allowing the possibility to create a revolution in the in-field applicative context of colour quantification not only in food sciences, but also in other biological disciplines. These results are of great importance for scientific color evaluation when lighting conditions are not controlled. Moreover, it allows the use of low cost instruments while still returning scientifically sound quantitative data.
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Affiliation(s)
- Paolo Menesatti
- Agricultural Engineering Research Unit of the Agricultural Research Council (CRA-ING), Via della Pascolare 16, Monterotondo scalo (Rome) 00015, Italy; E-Mails: (P.M.); (C.A.); (F.P.); (F.A.)
| | - Claudio Angelini
- Agricultural Engineering Research Unit of the Agricultural Research Council (CRA-ING), Via della Pascolare 16, Monterotondo scalo (Rome) 00015, Italy; E-Mails: (P.M.); (C.A.); (F.P.); (F.A.)
| | - Federico Pallottino
- Agricultural Engineering Research Unit of the Agricultural Research Council (CRA-ING), Via della Pascolare 16, Monterotondo scalo (Rome) 00015, Italy; E-Mails: (P.M.); (C.A.); (F.P.); (F.A.)
| | - Francesca Antonucci
- Agricultural Engineering Research Unit of the Agricultural Research Council (CRA-ING), Via della Pascolare 16, Monterotondo scalo (Rome) 00015, Italy; E-Mails: (P.M.); (C.A.); (F.P.); (F.A.)
| | - Jacopo Aguzzi
- Instituto de Ciencías del Mar (ICM-CSIC), Paseo Marítimo de la Barceloneta 37-49, Barcelona 08003, Spain; E-Mail:
| | - Corrado Costa
- Agricultural Engineering Research Unit of the Agricultural Research Council (CRA-ING), Via della Pascolare 16, Monterotondo scalo (Rome) 00015, Italy; E-Mails: (P.M.); (C.A.); (F.P.); (F.A.)
- Author to whom correspondence should be addressed; E-Mail: ; Tel.: +39-06-9067-5214; Fax: +39-06-9062-5591
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Mathiassen JR, Misimi E, Bondø M, Veliyulin E, Østvik SO. Trends in application of imaging technologies to inspection of fish and fish products. Trends Food Sci Technol 2011. [DOI: 10.1016/j.tifs.2011.03.006] [Citation(s) in RCA: 80] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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Valous NA, Drakakis K, Sun DW. Detecting fractal power-law long-range dependence in pre-sliced cooked pork ham surface intensity patterns using Detrended Fluctuation Analysis. Meat Sci 2010; 86:289-97. [DOI: 10.1016/j.meatsci.2010.04.017] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2009] [Revised: 04/12/2010] [Accepted: 04/15/2010] [Indexed: 10/19/2022]
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