Academic literature on the topic 'Food spoilage detection'
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Journal articles on the topic "Food spoilage detection"
Joshi, Atharva, Abhishek Bokil, Ashish Chhajed, Tejas Choudhari, and Atharva Kalamkar. "Food Spoilage Detection System using ESP-8266." International Journal for Research in Applied Science and Engineering Technology 10, no. 12 (December 31, 2022): 1013–16. http://dx.doi.org/10.22214/ijraset.2022.48087.
Full textLeite, Liliana, Inês Boticas, Miguel Navarro, Luís Nobre, João Bessa, Fernando Cunha, Pedro Neves, and Raúl Fangueiro. "Halochromic Inks Applied on Cardboard for Food Spoilage Monitorization." Materials 15, no. 18 (September 16, 2022): 6431. http://dx.doi.org/10.3390/ma15186431.
Full textGenovese, Maria E., Sinoj Abraham, Gianvito Caputo, Gabriele Nanni, Surjith K. Kumaran, Carlo D. Montemagno, Athanassia Athanassiou, and Despina Fragouli. "Photochromic Paper Indicators for Acidic Food Spoilage Detection." ACS Omega 3, no. 10 (October 18, 2018): 13484–93. http://dx.doi.org/10.1021/acsomega.8b02570.
Full textDainty, R. H. "Chemical/biochemical detection of spoilage." International Journal of Food Microbiology 33, no. 1 (November 1996): 19–33. http://dx.doi.org/10.1016/0168-1605(96)01137-3.
Full textAMMOR, MOHAMMED SALIM, CHRISTOS MICHAELIDIS, and GEORGE-JOHN E. NYCHAS. "Insights into the Role of Quorum Sensing in Food Spoilage." Journal of Food Protection 71, no. 7 (July 1, 2008): 1510–25. http://dx.doi.org/10.4315/0362-028x-71.7.1510.
Full textHam, Mirim, Soohyun Kim, Wonmok Lee, and Hyunjung Lee. "Fabrication of Printable Colorimetric Food Sensor Based on Hydrogel for Low-Concentration Detection of Ammonia." Biosensors 13, no. 1 (December 23, 2022): 18. http://dx.doi.org/10.3390/bios13010018.
Full textSkandamis, Panagiotis N., and George-John E. Nychas. "Quorum Sensing in the Context of Food Microbiology." Applied and Environmental Microbiology 78, no. 16 (June 15, 2012): 5473–82. http://dx.doi.org/10.1128/aem.00468-12.
Full textKim, Hongki, Ba Thong Trinh, Kyung Ho Kim, Jeong Moon, Hyunju Kang, Kwanghyeon Jo, Rashida Akter, et al. "Au@ZIF-8 SERS paper for food spoilage detection." Biosensors and Bioelectronics 179 (May 2021): 113063. http://dx.doi.org/10.1016/j.bios.2021.113063.
Full textGARCÍA, TERESA, BELÉN MAYORAL, ISABEL GONZÁLEZ, INÉS LÓPEZ-CALLEJA, AMANDA SANZ, PABLO E. HERNÁNDEZ, and ROSARIO MARTÍN. "Enumeration of Yeasts in Dairy Products: A Comparison of Immunological and Genetic Techniques." Journal of Food Protection 67, no. 2 (February 1, 2004): 357–64. http://dx.doi.org/10.4315/0362-028x-67.2.357.
Full textVENKITANARAYANAN, K. S., M. I. KHAN, C. FAUSTMAN, and B. W. BERRY. "Detection of Meat Spoilage Bacteria by Using the Polymerase Chain Reaction." Journal of Food Protection 59, no. 8 (August 1, 1996): 845–48. http://dx.doi.org/10.4315/0362-028x-59.8.845.
Full textDissertations / Theses on the topic "Food spoilage detection"
Chang, Su-Sen. "Guaiacol producing Alicyclobacillus spp. differentiation, detection, and control /." Pullman, Wash. : Washington State University, 2008. http://www.dissertations.wsu.edu/Dissertations/Fall2008/S_Chang_090208.pdf.
Full textHobday, Duncan Stuart. "Development of polyaniline as a sensor for food quality and spoilage detection." Thesis, Cranfield University, 2009. http://dspace.lib.cranfield.ac.uk/handle/1826/4482.
Full textKershri, G. "Novel food applications of electronic nose technology for detection of spoilage fungi." Thesis, Cranfield University, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.392743.
Full textBester, Linka. "Detection and identification of wine spoilage microbes using PCR-based DGGE analysis." Thesis, Stellenbosch : University of Stellenbosch, 2009. http://hdl.handle.net/10019.1/1558.
Full textGrape juice is transformed into wine through the complex processes of alcoholic and malolactic fermentation that is performed by yeasts, lactic acid bacteria and acetic acid bacteria. However, the microbes involved in these processes do not only take part in ensuring the successful production of wine, but also cause spoilage of the wine if their growth is not controlled. Conventional, culture-dependent methods of microbiology have been used as the main technique in detecting and identifying these spoilage microbes. Cultureindependent techniques of molecular biology have recently become more popular in detecting possible spoilage microbes present in must and wine, since it allows the detection and identification of viable, but non-culturable microbes and are not as timeconsuming as conventional microbiological methods. The aim of this study was to investigate the sustainability of polymerase chain reaction (PCR)-based denaturing gradient gel electrophoresis (DGGE) analysis in detecting wine spoilage microbes inoculated into sterile saline solution (SSS) (0.85% (m/v) NaCl) and sterile white wine and red wine as single microbial species and as part of mixed microbial populations. Three methods of DNA isolation from SSS, sterile white wine and sterile red wine inoculated with reference microbial strains were compared in terms of DNA concentration and purity, as well as simplicity of the technique. These three DNA isolation methods were the TZ-method, the proteinase K-method and the phenol extraction method. DNA could not successfully be isolated from red wine using any of the three DNA isolation methods. The TZ-method was the method of choice for the isolation of DNA from inoculated SSS and sterile white wine as this technique gave the best results in terms of simplicity, DNA concentration and purity. PCR and DGGE conditions were optimised for the universal primer pair, HDA1-GC and HDA2, the wine-bacteria specific primer pair, WBAC1-GC and WBAC2, and the yeast specific primer pair, NL1-GC and LS2. DNA from Acetobacter pasteurianus, Lactobacillus plantarum, Pediococcus pentosaceus, Oenococcus oeni, Brettanomyces bruxellensis and Saccharomyces cerevisiae were amplified with the appropriate primers and successfully resolved with DGGE analysis. PCR and DGGE detection limits were successfully determined when 106 cfu.ml-1 of the reference microbes, A. pasteurianus, Lb. plantarum, Pd. pentosaceus and B. bruxellensis were separately inoculated into SSS and sterile white wine. It was possible to detect low concentrations (101 cfu.ml-1) with PCR for A. pasteurianus, Lb. plantarum, Grape juice is transformed into wine through the complex processes of alcoholic and malolactic fermentation that is performed by yeasts, lactic acid bacteria and acetic acid bacteria. However, the microbes involved in these processes do not only take part in ensuring the successful production of wine, but also cause spoilage of the wine if their growth is not controlled. Conventional, culture-dependent methods of microbiology have been used as the main technique in detecting and identifying these spoilage microbes. Cultureindependent techniques of molecular biology have recently become more popular in detecting possible spoilage microbes present in must and wine, since it allows the detection and identification of viable, but non-culturable microbes and are not as timeconsuming as conventional microbiological methods. The aim of this study was to investigate the sustainability of polymerase chain reaction (PCR)-based denaturing gradient gel electrophoresis (DGGE) analysis in detecting wine spoilage microbes inoculated into sterile saline solution (SSS) (0.85% (m/v) NaCl) and sterile white wine and red wine as single microbial species and as part of mixed microbial populations. Three methods of DNA isolation from SSS, sterile white wine and sterile red wine inoculated with reference microbial strains were compared in terms of DNA concentration and purity, as well as simplicity of the technique. These three DNA isolation methods were the TZ-method, the proteinase K-method and the phenol extraction method. DNA could not successfully be isolated from red wine using any of the three DNA isolation methods. The TZ-method was the method of choice for the isolation of DNA from inoculated SSS and sterile white wine as this technique gave the best results in terms of simplicity, DNA concentration and purity. PCR and DGGE conditions were optimised for the universal primer pair, HDA1-GC and HDA2, the wine-bacteria specific primer pair, WBAC1-GC and WBAC2, and the yeast specific primer pair, NL1-GC and LS2. DNA from Acetobacter pasteurianus, Lactobacillus plantarum, Pediococcus pentosaceus, Oenococcus oeni, Brettanomyces bruxellensis and Saccharomyces cerevisiae were amplified with the appropriate primers and successfully resolved with DGGE analysis. PCR and DGGE detection limits were successfully determined when 106 cfu.ml-1 of the reference microbes, A. pasteurianus, Lb. plantarum, Pd. pentosaceus and B. bruxellensis were separately inoculated into SSS and sterile white wine. It was possible to detect low concentrations (101 cfu.ml-1) with PCR for A. pasteurianus, Lb. plantarum, iv Pd. pentosaceus, and B. bruxellensis in SSS when amplified with the HDA1-GC and HDA2 primer pair. A PCR detection limit of 102 cfu.ml-1 was determined in sterile white wine for Pd. pentosaceus and 103 cfu.ml-1 for B. bruxellensis using this primer pair. The results obtained from the PCR amplification with the WBAC1-GC and WBAC2 primer pair compared well with the results of the HDA1-GC and HDA2 primer pair. The results from the DGGE detection limits indicated that it was possible to detect lower concentrations (101 – 102 cfu.ml-1) of A. pasteurianus, Lb. plantarum and Pd. pentosaceus with the HDA1-GC and HDA2 primer pair than the WBAC-GC and WBAC2 primer pair (102 – 104 cfu.ml-1). Lower detection limits were also determined for B. bruxellensis amplified with the HDA1-GC and HDA2 primer pair (103 – 104 cfu.ml-1) than with the NL1-GC and LS2 primer pair (105 cfu.ml-1). PCR and DGGE detection limits for the inoculation of A. pasteurianus, Lb. plantarum and B. bruxellensis at an inoculum of 108 cfu.ml-1 as part of mixed populations in SSS and sterile white wine compared well with the results obtained from the reference microbes inoculated as single microbial species. PCR detection limits of 101 cfu.ml-1 were determined for all three reference microbes inoculated as part of mixed populations when amplified with the HDA1-GC and HDA2 and the WBAC1-GC and WBAC2 primer pairs. It was observed that similar or higher DGGE detection limits were obtained for the reference microbes inoculated in sterile white wine (101 – 107 cfu.ml-1) than when inoculated into SSS (101 – 105 cfu.ml-1). PCR-based DGGE analysis proved to be a technique that could be used successfully with the universal, wine-bacteria and yeast specific primer pairs for the detection of A. pasteurianus, Lb. plantarum, Pd. pentosaceus and B. bruxellensis. The culture-independent technique makes the early detection of possible spoilage microbes at low concentrations in wine possible.
Xiao, Linlin. "Detection of Viable Foodborne Pathogens and Spoilage Microorganisms by Nucleic Acid Amplification Based Platforms." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1308284180.
Full textBotha, Janita J. "Sensory, chemical and consumer analysis of Brettanomyces spoilage in South African wines." Thesis, Stellenbosch : University of Stellenbosch, 2010. http://hdl.handle.net/10019.1/4141.
Full textENGLISH ABSTRACT: This study focussed on the sensory effects of the main volatile compounds produced by Brettanomyces yeast causing spoilage in wine. This research firstly aimed to determine the detection thresholds of eight Brett-related spoilage compounds in wine. The second aim was to determine the sensory effect of the four most important Brett-related compounds when present individually in wine. The third aim was to determine the sensory effects of these four compounds when present in wine in a range of combinations, and to further investigate their effect on consumer liking. Finally, this project aimed to investigate the incidence of these compounds in a small range of South African wines. The sensory detection thresholds of 4-ethylphenol, 4-ethylguaiacol, 4-ethylcatechol, 4- vinylphenol, 4-vinylguaiacol, isovaleric acid, isobutyric acid and acetic acid were determined. Apart from 4-ethylcatechol, these values generally agreed well with recent literature where values determined in wine are available. However, the discrepancies highlighted the importance of the effect of the medium (wine) when determining sensory detection thresholds. The use of the median as alternative calculation method was also investigated, and it was found that this method gives more insightful results than the standard American Society of Testing Materials (ASTM E679-04) method. Four compounds, namely 4-ethylphenol, 4-ethylguaiacol, 4-ethylcatechol and isovaleric acid were profiled individually in wine using a trained sensory panel. It was found that all four compounds caused a suppression of the natural berry-like character in the wine, which induced a sick-sweet character. 4-ethylphenol contributed Elastoplast™ and leather aromas in the wine, both of which are commonly associated with Brettanomyces taint. 4-ethylguaiacol added a medicinal aroma to the wine, and 4-ethylcatechol and isovaleric acid were responsible for savoury and pungent aromas, respectively. 4-ethylphenol, 4-ethylguaiacol, 4-ethylcatechol and isovaleric acid were also profiled in combination according to the central composite design. Several univariate and multivariate methods were applied to the dataset obtained. PARAFAC, a multiway method not widely utilized regarding sensory data, was applied to the data, the results of which were complementary to those obtained during univariate and multivariate analyses. It was found that there is a great deal of interaction between the four compounds profiled in terms of sensory effects. The most notable was the Elastoplast™ attribute, the intensity of which was affected by all four compounds. The pungent attribute was also affected by the 4-ethylphenol concentration. Consumer analysis revealed that some of the samples spiked with Brettanomyces-spoilage compounds were preferred to the unspiked (control sample). However, no further relationship could be found between consumer liking and either chemical composition or sensory profile. It is therefore speculated that consumer liking of Brettanomyces infected wine is driven by more complex sensory or socio-demographic factors. Finally, the concentration of 4-ethylphenol, 4-ethylguaiacol, 4-ethylcatechol, 4-vinylphenol, 4- vinylguaiacol, isovaleric acid, isobutyric acid and acetic acid was determined in a small set of South African wines, selected to contain a high proportion of wines spoiled by Brettanomyces. Significant correlations were found between 4-ethylphenol and 4-ethylguaiacol, as well as 4- ethylphenol and isovaleric acid. However, no correlation could be found between 4-ethylphenol and 4-ethylcatechol. It is speculated that this lack of relationship is due to the different precursor profiles present in the analysed wines. This study paved the way for future investigations on the sensory effects of Brettanomyces spoilage in Pinotage red wine.
AFRIKAANSE OPSOMMING: Hierdie studie het gefokus op die sensoriese invloed van die belangrikste vlugtige komponente wat deur die Brettanomyces gis geproduseer word en bederf veroorsaak in wyn. Eerstens is gefokus op die bepaling van die deteksiedrempelwaardes van agt Brett-verwante bederwende komponente. Die tweede doelwit was om die sensoriese invloed van vier van die mees belangrike Brett-komponente te bepaal wanneer hulle individueel in wyn voorkom. Die derde doelwit was om die sensoriese invloed van hierdie vier komponente te bepaal wanneer hulle in verskillende kombinasies in wyn voorkom, asook die effek daarvan op verbruikervoorkeur. Laastens is gepoog om die voorkoms van hierdie komponente in ‘n klein seleksie van Suid- Afrikaanse wyne te bepaal. Die sensoriese deteksiedrempelwaardes vir 4-etielfenol, 4-etielguaiacol, 4-etielcatechol, 4- vinielfenol, 4-vinielguaiacol, isovaleraatsuur, isobuteraatsuur en asynsuur is bepaal. Met die uitsondering van 4-etielcatechol het die waardes oor die algemeen goed ooreengestem met waardes wat onlangs in die wetenskaplike literatuur gepubliseer is. Die uitsonderings het egter die belangrikheid van die medium (wyn) gedurende die bepaling van sensoriese deteksiedrempelwaardes uitgelig. Die gebruik van die mediaan as ‘n alternatiewe berekeningsmetode is ook ondersoek en daar is gevind dat hierdie metode meer insiggewende resultate lewer as die standaard American Society of Testing Materials (ASTM E679-04) metode. Vier komponente naamlik 4-etielfenol, 4-etielguaiacol, 4-etielcatechol en isovaleraatsuur is individueel in wyn geprofileer met behulp van ‘n opgeleide sensoriese paneel. Daar is gevind dat al vier die komponente die natuurlike bessiekarakter in die wyn onderdruk terwyl dit aanleiding gee tot ‘n onnatuurlike soet karakter. 4-etielfenol is gekenmerk aan Elastoplast™ en leeragtige aromas in die wyn en beide van hulle word algemeen geassosieer met Brettanomyces bederf. 4-etielguaiacol het ‘n medisinale aroma tot die wyn toegevoeg en 4- etielcatechol en isovaleraatsuur het respektiewelik souterige (“savoury”) en sterk (“pungent”) aromas tot gevolg gehad. 4-etielfenol, 4-etielguaiacol, 4-etielcatechol en isovaleraatsuur is ook in verskeie kombinasies geprofileer volgens die sentrale saamgestelde ontwerp (“central composite design”). Verskeie enkelveranderlike en meerveranderlike statistiese analisemetodes is ook op die datastel uitgevoer. PARAFAC, ‘n meerrigtingsmetode wat nie normaalweg vir sensoriese analise data gebruik word nie, is ook uitgevoer op die data en die resultate was komplimentêr tot die van die enkelveranderlike en meerveranderlike analisemetodes. Daar is gevind dat, met betrekking tot sensoriese effekte, daar noemenswaardige interaksie tussen die vier komponente plaasvind. Die mees opmerklike hiervan was die Elastoplast™ aroma, waarvan die intensiteit deur al vier die ander komponente geaffekteer is. Verder is die sterk (“pungent”) aroma beïnvloed deur die 4-etielfenol konsentrasie. Verbruikersvoorkeur-analise het aangedui dat sommige van die monsters waarby Brettanomyces bederwende komponente gevoeg is, verkies word bó die kontrole-wyn. Daar kon egter geen verdere verband gevind word tussen die verbruiker se voorkeur en, nog die chemise komposisie of sensoriese profiele, van die wyn nie. Daar kan dus gespekuleer word dat verbruiker voorkeur van Brettanomyces bederfde wyn gedryf word deur meer komplekse en sosio-demografiese faktore. Laastens is die konsentrasies van 4-etielfenol, 4-etielguaiacol, 4-etielcatechol, 4-vinielfenol, 4- vinielguaiacol, isovaleraatsuur, isobuteraatsuur en asynsuur in ‘n seleksie van Suid-Afrikaanse wyne bepaal. Dié wyne is spesifiek so gekies sodat ‘n aansienlike aantal van hulle met Brettanomyces bederf was. Betekenisvolle korrelasies is gevind tussen 4-etielfenol and 4- etielguaiacol, sowel as 4-etielfenol en isovaleraatsuur. Daar is egter geen korrelasie tussen 4- etielfenol and 4-etielcatechol gevind nie. Daar word vermoed dat hierdie gebrek aan korrelasie te wyte is aan die voorloperkomponent profiele teenwoordig in die wyne. Hierdie studie het die weg gebaan vir verdere ondersoeke na die sensoriese effekte van Brettanomyces bederf in Pinotage rooi wyn.
Raut, Nilesh G. "BIOSENSING SYSTEMS FOR THE DETECTION OF BACTERIAL QUORUM SENSING MOLECULES: A TOOL FOR INVESTIGATING BACTERIA-RELATED DISORDERS AND FOOD SPOILAGE PREVENTION." UKnowledge, 2012. http://uknowledge.uky.edu/chemistry_etds/13.
Full textBook chapters on the topic "Food spoilage detection"
Fathima, Aksa, Tafadzwa Justin Chiome, Archer Ann Catherine, Chukwuebuka Egbuna, Raghu Ram Achar, and Asha Srinivasan. "Smart Use of Nanomaterials as Sensors for Detection and Monitoring of Food Spoilage." In Application of Nanotechnology in Food Science, Processing and Packaging, 169–88. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-98820-3_11.
Full textPrathyusha, A. M. V. N., Harish Annavarapu, and Pallaval Veera Bramhachari. "Methods for the Detection and Quantification of Quorum-Sensing Signals in Food Spoilage." In Implication of Quorum Sensing and Biofilm Formation in Medicine, Agriculture and Food Industry, 251–67. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-32-9409-7_16.
Full textDantas Vanetti, Maria Cristina, and Solimar Gonçalves Machado. "Spoilage Detection." In Handbook of Dairy Foods Analysis, 699–711. 2nd ed. Second edition. | Boca Raton : CRC Press, 2021.: CRC Press, 2021. http://dx.doi.org/10.1201/9780429342967-38.
Full textKurtzman, C. "Detection, identification and enumeration methods for spoilage yeasts." In Food spoilage microorganisms. CRC Press, 2006. http://dx.doi.org/10.1201/9781439824573.ch2.
Full textCousin, M. "Detection, enumeration and identification methods for spoilage molds." In Food spoilage microorganisms. CRC Press, 2006. http://dx.doi.org/10.1201/9781439824573.ch3.
Full textGoodacre, R., and D. Ellis. "Quantitative detection and identification methods for microbial spoilage." In Food spoilage microorganisms. CRC Press, 2006. http://dx.doi.org/10.1201/9781439824573.pt1.
Full textKurtzman, C. P. "Detection, identification and enumeration methods for spoilage yeasts." In Food Spoilage Microorganisms, 28–54. Elsevier, 2006. http://dx.doi.org/10.1533/9781845691417.1.28.
Full textEllis, D. I., and R. Goodacre. "Quantitative detection and identification methods for microbial spoilage." In Food Spoilage Microorganisms, 3–27. Elsevier, 2006. http://dx.doi.org/10.1533/9781845691417.1.3.
Full textCousin, M. A. "Detection, enumeration and identification methods for spoilage molds." In Food Spoilage Microorganisms, 55–85. Elsevier, 2006. http://dx.doi.org/10.1533/9781845691417.1.55.
Full text"Detection and Enumeration." In Handbook of Food Spoilage Yeasts, Second Edition, 203–20. CRC Press, 2007. http://dx.doi.org/10.1201/9781420044942.ch8.
Full textConference papers on the topic "Food spoilage detection"
Fang, Sun. "Design of Intelligent Detection System for Food Spoilage." In 2018 11th International Conference on Intelligent Computation Technology and Automation (ICICTA). IEEE, 2018. http://dx.doi.org/10.1109/icicta.2018.00050.
Full textPaul, Rinika, Sanketh B. Prabhu, and Sudha Yadav. "FPGA based Intelligent Food Spoilage Detection for Commercial Storage." In 2022 International Conference on Edge Computing and Applications (ICECAA). IEEE, 2022. http://dx.doi.org/10.1109/icecaa55415.2022.9936415.
Full textMegalingam, Rajesh Kannan, Gadde Sakhita Sree, Gunnam Monika Reddy, Inti Rohith Sri Krishna, and L. U. Suriya. "Food Spoilage Detection Using Convolutional Neural Networks and K Means Clustering." In 2019 3rd International Conference on Recent Developments in Control, Automation & Power Engineering (RDCAPE). IEEE, 2019. http://dx.doi.org/10.1109/rdcape47089.2019.8979114.
Full textNadeem, F., J. Mandon, S. M. Cristescu, and F. J. M. Harren. "External Cavity-Quantum Cascade Laser for Sensitive Detection of Volatiles Emitted During Food Spoilage." In Laser Applications to Chemical, Security and Environmental Analysis. Washington, D.C.: OSA, 2016. http://dx.doi.org/10.1364/lacsea.2016.lm4g.5.
Full textArampongpun, R., P. Ounsawatdipong, K. Trakoontiwakorn, C. Thanachayanont, and P. Pungetmongkol. "Modified Co-doped ZnO nanostructures on SPCE for Xanthine detection in early food spoilage." In 2022 IEEE 22nd International Conference on Nanotechnology (NANO). IEEE, 2022. http://dx.doi.org/10.1109/nano54668.2022.9928589.
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