Rapid Screening of Alicyclobacillus acidoterrestris Spoilage of Fruit Juices by Electronic Nose: A Confirmation Study

Early screening of Alicyclobacillus spp. in fruit juices is a major applicative goal for the food industry, since juice contamination can lead to considerable loss of quality, and subsequently, to economic damages for juice producers. This paper presents an accurate study to assess and confirm the EOS507 electronic nose's (EN) ability of diagnosing Alicyclobacillus acidoterrestris spoilage in artificially contaminated fruit juices. The authors experimental results have shown that the EOS507 can early identify, just after 24 hours from inoculation, contaminated orange and pear juices with an excellent classification rate close to 90% and with a detection threshold as low as 103 cfu/ml. In apple juice the detection threshold was about 105 cfu/ml, thus requiring longer incubation times (72 hours). PLS regression of EOS507 data can be also used to predict with fair accuracy the colony-forming units concentration of the bacteria. These results were supported by the GC/MS/MS measurements of specific chemical markers, such as guaiacol.

[1]  B. D. Malhotra,et al.  Recent developments in bio-molecular electronics techniques for food pathogens. , 2006, Analytica chimica acta.

[2]  G. Sberveglieri,et al.  Electronic Olfactory Systems Based on Metal Oxide Semiconductor Sensor Arrays , 2004 .

[3]  K Yamazaki,et al.  Isolation and identification of Alicyclobacillus acidoterrestris from acidic beverages. , 1996, Bioscience, biotechnology, and biochemistry.

[4]  F. B. Whitfield,et al.  Role of Alicyclobacillus acidoterrestris in the development of a disinfectant taint in shelf‐stable fruit juice , 2003, Letters in applied microbiology.

[5]  Gerhard Cerny,et al.  Fruchtsaftverderb durch Bacillen: Isolierung und Charakterisierung des Verderbserregers , 1984 .

[6]  Su-Sen Chang,et al.  Alicyclobacillus spp. in the Fruit Juice Industry: History, Characteristics, and Current Isolation/Detection Procedures , 2004, Critical reviews in microbiology.

[7]  Giorgio Sberveglieri,et al.  Alicyclobacillus spp.: Detection in soft drinks by Electronic Nose , 2010 .

[8]  Naresh Magan,et al.  Early detection and differentiation of spoilage of bakery products , 2005 .

[9]  Alphus D. Wilson,et al.  Applications and Advances in Electronic-Nose Technologies , 2009, Sensors.

[10]  Giorgio Sberveglieri,et al.  Solid state gas sensing , 2009 .

[11]  M. Peris,et al.  A 21st century technique for food control: electronic noses. , 2009, Analytica chimica acta.

[12]  Johanna Smeyers-Verbeke,et al.  Handbook of Chemometrics and Qualimetrics: Part A , 1997 .

[13]  A J Ramos,et al.  Use of a MS-electronic nose for prediction of early fungal spoilage of bakery products. , 2007, International journal of food microbiology.

[14]  H. T. Nagle,et al.  Handbook of Machine Olfaction , 2002 .

[15]  E. Gobbi,et al.  Early detection of microbial contamination in processed tomatoes by electronic nose. , 2009 .

[16]  Suranjan Panigrahi,et al.  Evaluation of an artificial olfactory system for grain quality discrimination , 2007 .

[17]  Changsheng Xie,et al.  Spoiling and formaldehyde-containing detections in octopus with an E-nose , 2009 .

[18]  Roberto Paolesse,et al.  Detection of fungal contamination of cereal grain samples by an electronic nose , 2006 .

[19]  G. Fox,et al.  Comparative sequence analyses on the 16S rRNA (rDNA) of Bacillus acidocaldarius, Bacillus acidoterrestris, and Bacillus cycloheptanicus and proposal for creation of a new genus, Alicyclobacillus gen. nov. , 1992, International journal of systematic bacteriology.

[20]  N. Magan,et al.  Potential for detection and discrimination between mycotoxigenic and non-toxigenic spoilage moulds using volatile production patterns: A review , 2007, Food additives and contaminants.

[21]  Amalia Berna,et al.  Metal Oxide Sensors for Electronic Noses and Their Application to Food Analysis , 2010, Sensors.

[22]  M. J. Saxby Food Taints and Off-Flavours , 1995 .

[23]  Giorgio Sberveglieri,et al.  Electronic nose and Alicyclobacillus spp. spoilage of fruit juices: An emerging diagnostic tool , 2010 .

[24]  G. Downey,et al.  Recent technological advances for the determination of food authenticity , 2006 .

[25]  Mahdi Ghasemi-Varnamkhasti,et al.  Biomimetic-based odor and taste sensing systems to food quality and safety characterization: An overview on basic principles and recent achievements , 2010 .

[26]  Knut Rudi,et al.  Application of gas-sensor array technology for detection and monitoring of growth of spoilage bacteria in milk: A model study , 2006 .

[27]  Suranjan Panigrahi,et al.  Independent component analysis-processed electronic nose data for predicting Salmonella typhimurium populations in contaminated beef , 2008 .

[28]  M. Pardo,et al.  Classification of electronic nose data with support vector machines , 2005 .

[29]  K. Poralla,et al.  [Spoilage of fruit juice by bacilli: isolation and characterization of the spoiling microorganisms]. , 1984, Zeitschrift fur Lebensmittel-Untersuchung und -Forschung.

[30]  Giorgio Sberveglieri,et al.  Detection of toxigenic strains of Fusarium verticillioides in corn by electronic olfactory system , 2005 .

[31]  E. Vicini,et al.  Caratterizzazione di Alicyclobacillus, batteri sporigeni termofili e acidofili , 1995 .

[32]  J. Haugen,et al.  Recalibration of a gas-sensor array system related to sensor replacement , 2004 .

[33]  Suranjan Panigrahi,et al.  Neural-network-integrated electronic nose system for identification of spoiled beef , 2006 .

[34]  Giorgio Sberveglieri,et al.  Exploratory data analysis for industrial safety application , 2008 .

[35]  Carol A Phillips,et al.  Alicyclobacillus acidoterrestris: an increasing threat to the fruit juice industry? , 2007 .