Response evaluation of an E-nose towards contaminated wheat by Fusarium poae fungi

Presicce, D.S.; Forleo, A.; Taurino, A.M.; Zuppa, M.; Siciliano, P.; Laddomada, Barbara; Logrieco, A.; Visconti, Angelo

doi:10.1016/j.snb.2006.04.045

Cited by 41 publications

(23 citation statements)

References 12 publications

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“…A wide variety of compounds belonging to various functional groups including alcohols, aldehydes, esters, ketones, acetates, and furans were identified from the headspace of the wheat samples. The results are consistent with those of other authors (Presicce et al, 2006). Based on visual observations of chromatograms, the volatile compounds of three wheat varieties were quite similar, but the content of each compound was different according to peak profiles and the W9023 had a unique peak which labeled with '*' (compound: 2, 6, 10-dodecatrien-1-ol, 3, 7, 11-trimethyl).…”

Section: Resultssupporting

confidence: 91%

“…Nowadays, E-nose has already been used in various field, such as: pork (O'Sullivan et al, 2003), mandarin (Gomez et al, 2007), peach (Benedetti et al, 2008;Di Natale et al, 2001), apple (Li and Heinemann, 2007), pear (Oshita et al, 2000), wine (Garcia et al, 2006) and grain (Balasubramanian et al, 2007;Evans et al, 2000). Moreover, E-nose and GC-MS have also been used for detection of spoilage of grain and mycotoxins, ergosterol, and odour volatiles in durum wheat (Abramson et al, 2005;Presicce et al, 2006). However, most of them are on qualitative identification of stored grains, no information has been available on the applicability of an electronic nose for the identification different varieties of wheat seeds.…”

Section: Bo Zhoumentioning

confidence: 99%

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Identification of different wheat seeds by electronic nose

Zhang¹,

Wang²,

2012

International Agrophysics

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A b s t r a c t. The potential of electronic nose to distinguish of wheat seeds was studied. The reproducibility and practicability of electronic nose data was evaluated by repeating the analysis of samples with a time difference of two months. The principle components analysis and linear discriminant analysis were applied to the generated patterns to distinguish the varieties of wheat seeds. The results showed that they could distinguish the wheat varieties properly. The stepwise discriminant analysis and a three-layer backpropagation neural network were developed for pattern prediction models. The results showed that both models could identify the wheat varieties, the back-propagation neural network presented the higher percent of correct classifications in comparison to stepwise discriminant analysis. Moreover, gas chromatography mass spectrometry analysis of the headspaces of same samples confirmed that electronic nose as a powerful tool is able to identify the wheat seeds.K e y w o r d s: electronic nose, wheat seeds, identification, gas chromatography mass spectrometry INTRODUCTIONThe usual methods for identification of wheat seeds are seed protein electrophoresis, DNA molecular markers techniques, morphological identification and field evaluation (Li et al., 2006). In most cases, these methods are expensive and time-consuming, have low reproducibility, both in their commercial as well as in their technological implications. Several attempts have been made recently to classify wheat varieties using nondestructive methods such as machine vision (Douik and Abdellaoui, 2008;, near infrared spectrometer (Li et al., 2008) and thermal imaging (Manickavasagan et al., 2010). Most of them used kernel morphological features of a single grain for variety identification. It would be highly desirable to have an alternative method for classification of wheat varieties, which may use some characteristics of the kernels other than morphological features. A simple variety identification system with less complexity for bulk sample testing (not single grain analysis) would be most desirable in the grain-handling facilities.Electronic nose (E-nose) is instrument which mimics the sense of smell. These devices are typically array of sensors used to detect and distinguish odours precisely in complex samples and at low cost (Peris and EscuderGilabert, 2009). In contrast to the well known analytical gas chromatography mass spectrometry (GC-MS) and sensory techniques that have been used for the analysis of flavour compounds, the E-nose does not give any information about the compounds causing the investigated aroma; neither about the identity of the compounds nor their sensorial properties. Using E-nose the aroma is judged by the so-called 'aroma pattern', which should be characteristic to the investigated substrate (O'Sullivan et al., 2003). With the use of appropriate mathematical methods, E-nose should be capable of recognizing the aroma pattern or of distinguishing it from aroma patterns of other samples (Peris and EscuderGilab...

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Section: Resultssupporting

confidence: 91%

Section: Bo Zhoumentioning

confidence: 99%

Identification of different wheat seeds by electronic nose

Zhang¹,

Wang²,

2012

International Agrophysics

View full text Add to dashboard Cite

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“…Some are advanced enough for field studies and have already reached the stage of commercialization, some are at a transition phase between research and application to analysis of food/feed samples, other still have to face the challenge of validation by multiple laboratories. A list of the emerging rapid methods for mycotoxin analysis is reported in Table 2 Keshri & Magan, 2000;Olsson et al, 2002;Presicce et al, 2006;Cheli et al, 2009b;Campagnoli et al, 2011. (Maragos, 2004;Krska & Welzig, 2006;Zeng et al, 2006;Goryacheva et al, 2007;Maragos & Busnam, 2010). The most known rapid screening methods for mycotoxin detection, especially for the screening of raw materials, are antibody-based methods, ELISA test.…”

Section: Rapid Methods For Mycotoxin Analysismentioning

confidence: 99%

“…Detection and differentiation between mycotoxigenic and non-mycotoxigenic strains of Fusarium spp. using volatile production profiles evaluated by EN has been also reported (Keshri & Magan, 2000;Magan & Evans, 2000;Falasconi et al, 2005;Presicce et al, 2006;Sahgal et al, 2007). Further developments of studies carried out with EN technology have been made in order to evaluate the possibility of using fungal volatile metabolites as indicators of mycotoxin presence (Campagnoli et al, 2009b).…”

Section: The Analytical Approaches Miming Senses: the Example Of Elecmentioning

confidence: 99%

Rapid Methods as Analytical Tools for Food and Feed Contaminant Evaluation: Methodological Implications for Mycotoxin Analysis in Cereals

Cheli¹,

Campagnoli²,

Pinotti³

et al. 2012

Food Production - Approaches, Challenges and Tasks

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“…Odours and volatiles are produced by a wide range of organisms including those causing deterioration of plant granular materials (Presicce et al, 2006). Volatile metabolites produced by fungi during the spoilage process can be characteristic markers of fungal presence.…”

Section: Introductionmentioning

confidence: 99%

Electronic nose with polymer-composite sensors for monitoring fungal deterioration of stored rapeseed

Gancarz

Wawrzyniak

Gawrysiak‐Witulska

et al. 2017

International Agrophysics

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A b s t r a c t. Investigations were performed to examine the possibility of using an electronic nose to monitor development of fungal microflora during the first eighteen days of rapeseed storage. The Cyranose 320 device manufactured by Sensigent was used to analyse volatile organic compounds. Each sample of infected material was divided into three parts and the degree of spoilage was measured in three ways: analysis of colony forming units, determination of ergosterol content, and measurement of volatile organic compounds with the e-nose. Principal component analysis was performed on the generated patterns of signals and six groups of different spoilage levels were isolated. An analysis of sensorgrams for a few sensors with a strong signal for each group of rapeseed spoilage was performed. The ratio of the association time to the steady state was calculated. This ratio was different for the low level and the highest level of ergosterol and colony forming units. The results have shown that the e-nose can be a useful tool for quick estimation of the degree of rapeseed spoilage.

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Response evaluation of an E-nose towards contaminated wheat by Fusarium poae fungi

Cited by 41 publications

References 12 publications

Identification of different wheat seeds by electronic nose

Identification of different wheat seeds by electronic nose

Rapid Methods as Analytical Tools for Food and Feed Contaminant Evaluation: Methodological Implications for Mycotoxin Analysis in Cereals

Electronic nose with polymer-composite sensors for monitoring fungal deterioration of stored rapeseed

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