Use of a MS-electronic nose for prediction of early fungal spoilage of bakery products.
A MS-based electronic nose was used to detect fungal spoilage (measured as ergosterol concentration) in samples of bakery products. Bakery products were inoculated with different Eurotium, Aspergillus and Penicillium species, incubated in sealed vials and their headspace sampled after 2, 4 and 7 days. Once the headspace was sampled, ergosterol content was determined in each sample. Different electronic nose signals were recorded depending on incubation time. Both the e-nose signals and ergosterol levels were used to build models for prediction of ergosterol content using e-nose measurements. Accuracy on prediction of those models was between 87 and 96%, except for samples inoculated with Penicillium corylophilum where the best predictions only reached 46%.
Marín
S
S
Food Technology Department, Lleida University, CeRTA-UTPV, Alcalde Rovira Roure, 191, 25198 Lleida, Spain. smarin@tecal.udl.es
Vinaixa
M
M
Brezmes
J
J
Llobet
E
E
Vilanova
X
X
Correig
X
X
Ramos
A J
AJ
Sanchis
V
V
D001230:Aspergillus / Q000254:growth & development / Q000302:isolation & purification; D001939:Bread / Q000382:microbiology*; D004875:Ergosterol / Q000032:analysis*; D032641:Eurotiales / Q000254:growth & development / Q000302:isolation & purification; D005506:Food Contamination / Q000032:analysis*; D005658:Fungi / Q000254:growth & development* / Q000302:isolation & purification; D010407:Penicillium / Q000254:growth & development / Q000302:isolation & purification; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012903:Smell; D013997:Time Factors
D004875:Ergosterol