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Electronic Nose Chemical Sensor Feasibility Study for the Differentiation of Apple Cultivars

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Electronic Nose Chemical Sensor Feasibility Study for the Differentiation of Apple Cultivars ELECTRONIC NOSE CHEMICAL SENSOR FEASIBILITY STUDY FOR THE DIFFERENTIATION OF APPLE CULTIVARS W. N. Marrazzo, P. H. Heinemann, R. E. Crassweller, E. LeBlanc ABSTRACT. The ability to analytically differentiate and match intact apple (Malus domestica, Borkh) fruit and fruit juice extracts from different apple cultivars is of interest to the food industry. This study tested the feasibility of detecting the difference among volatile gases evolved from intact ‘McIntosh (Buhr),’ ‘Delicious,’ and ‘Gala’ apples and their extracted juice using a prototype 32−array polymeric detector chemical sensor. All data were first processed to obtain principal components. PCA analysis clearly separated whole ‘McIntosh,’ ‘Gala,’ and ‘Delicious’ samples from juiced on day 1. PCA analysis of day 2 samples showed clustering of whole vs. juiced for all three cultivars, although there was some overlap between the clusters. A soft independent modeling of class analogy (SIMCA) class discrimination of the sensor principal component data sets was then performed to determine the degree of difference. SIMCA analysis of the same samples showed a pronounced difference (SIMCA value >3.00) for only the ‘McIntosh’ samples. SIMCA values between 2.00 and 3.00 were found for the other two cultivars on day 1. For day 2 samples, no SIMCA values greater than 2.00 were found for any cultivar whole vs. juiced. PCA analysis showed clear separation between cultivars for day 1 whole samples. SIMCA analysis showed that there was a difference between ‘Delicious’ and ‘McIntosh’ and between ‘Delicious’ and ‘Gala.’ Neither PCA nor SIMCA showed good separation between day 2 whole cultivars, nor between juiced cultivars on either day. As a reference, the same sample headspace volatile gases were analyzed with a mass spectrometer. A hierarchical cluster analysis (HCA) of the principal components from the mass spectrometer data sets revealed five clusters that discriminated differences among intact apple and apple juice samples but did not discriminate between samples from different apple cultivars. Keywords. Apple volatiles, Electronic nose, Nanotechnology, Sensory evaluation. ualitative and quantitative differences have been Delwiche, 1998). The primary disadvantages of solid−state found in the volatiles emitted from intact apples sensors, however, are sensor poisoning, alcohol and water in- (Malus domestica, Borkh) of different cultivars terference, lack of volatile structural information, short and and from juice extracts of the same apples (Di- long term drift, and time−consuming calibrations (InfoMe- Qmick and Hoskin, 1983; MacGregor et al., 1964; trix, 1999). Morton and MacLeod, 1990). Refinement of analytic detec- Several studies have investigated the use of “electronic tion methods for rapid detection of these differences contin- nose” type sensors for apple quality evaluation. Royal Gala ues. The quest remains to replace the human nose as the apple aroma was characterized through the use of an sensory analysis tool most widely used for quantification of electronic nose in a study by Young et al. (1999). The goal food−associated volatile gases. Volatile gases emitted from was to determine the utility of the nose as a maturity foods are often measured using chromatography and/or spec- indicator. Apples harvested at four different maturity levels troscopy with either temporal or spectral separation. Recent were assessed and compared to gas chromatography and a studies have compared the advantages and disadvantages of sensory panel. The electronic nose and the GC techniques gas chromatography−mass spectroscopy (GC−MS; Heiden et were able to classify the apples by harvest date. al., 2002) to separate, identify, and quantify volatile gases. Brezmes et al. (2001) assessed ripeness of Pinklady apples More recently, there has been increased reliance on the use using an electronic nose and PCA, fuzzy logic, and neural of chemometric techniques. These detectors vary from rapid network classification. The fuzzy logic and neural network analysis mass spectrometers to solid−state sensors (Sarig and approaches were successful in classifying the apples based on shelf life. The PCA was unsuccessful in determining clusters based on ripeness. Article was submitted for review in November 2004; approved for Rye and Mercer (2003) used an electronic nose to publication by the Information & Electrical Technologies Division of determine differences in the headspace of processed vs. ASABE in September 2005. non−processed apple cider, as well as differences based on The authors are William N. Marrazzo, Former Graduate Fellow, and different thermal processing temperatures. The electronic Paul H. Heinemann, ASABE Member Engineer, Professor, Department of Agricultural and Biological Engineering, The Pennsylvania State nose was able to show significant differences between apple University, University Park, Pennsylvania; Robert E. Crassweller, cider processed at 90°C and unprocessed apple cider. Professor, Department of Horticulture, The Pennsylvania State University, However, there were no significant differences between University Park, Pennsylvania; and Eric LeBlanc, Statistician, USDA− unprocessed cider and cider processed at 60°C, 70°C, and ARS−BARC Statistics Group, Beltsville, Maryland. Corresponding 80°C. author: Paul Heinemann, 224 Agricultural Engineering Bldg., University Park, PA 16802; phone: 814−865−2633; fax: 814−863−1031; e−mail: An electronic nose and a mass spectrometer based [email protected]. electronic nose (MSE−nose) were used by Lammertyn et al. Transactions of the ASAE Vol. 48(5): 1995−2002 2005 American Society of Agricultural Engineers ISSN 0001−2351 1995 (2003) to investigate changes in volatile emissions from MULTIPLE ARRAY CHEMICAL SENSOR − DATA LOGGER apples after a storage time of eight months. The apples were PROTOTYPE stored under three different conditions, and then the head- The multiple array chemical sensor − data logger used in this spaces were measured for 15 days after removing the apples study was provided by Cyrano Sciences, Inc., Pasadena, from storage. Canonical variate (CV) analysis was able to California (prototype data logger serial number distinguish differences in storage and changes over the DL−0027−012999, sensor set number CN−7100A−608). It has 15−day shelf−life period. However, the electronic nose could a portable polymeric resistance−change sensor unit that con- only detect differences over the shelf−life period and could nects to a laptop computer. The instrument is also referred to as not show differences between storage conditions. a data logger, multiple array chemical sensor, chemical sensor, To alleviate the disadvantages previously described by “e−nose,” or “electronic nose.” The chemical sensors (32 total) InfoMetrix (1999), a prototype chemical sensor was devel- are carbon elements impregnated with distinct non−conducting oped by Cyrano Sciences (Doleman et al., 1998). This sensor polymers whose resistance changes when exposed to different is made up of an array of carbon black organic polymer volatile gases. Since each sensor is unique, each will respond to composites that swell differentially and reversibly upon different chemical compounds after exposure to a headspace exposure to various volatile gases or classes of volatile sample. The sensors are enclosed in an electronically heated chemical compounds. The chemical sensor array’s quick chamber with inlet and outlet ports. Two intake lines (sample response time, instrument portability, and ease of use would and purge, with an electronic valve to switch between them) facilitate the industrial and laboratory need for a practical feed the sampling pump connected to the inlet of the sensor tool to identify and characterize agricultural commodities chamber (fig. 1). When the sample gas stream passes over the and other foods through analyses of volatile gases. The sensors, they swell depending on each sensor’s susceptibility to objective of this study was to evaluate the feasibility of the compounds in the sample. This swelling causes a change in detecting differences between volatile gases evolved from sensor resistance, which is measured by the device and given as intact apples and apple juice extracts from different cultivars output (fig. 2). Hence, each sample provides up to 32 different using this prototype array chemical sensor. resistance responses, which can be used to characterize the sample. Only 31 of the 32 sensors were used in this study since the MATERIALS AND METHODS manufacturer indicated that the output from one of the sensors was unreliable and should not be used. The prototype SAMPLES chemical sensors used in the data logger were not expected ‘McIntosh,’ ‘Delicious,’ and ‘Gala’ apples were pur- to be as stable, accurate, or precise as those manufactured chased from a retail market in June 1999. For each variety, using refined mass−production techniques. In this regard, the apples less than 8.5 cm diameter were randomly selected, results obtained in this study with the prototype sensors were weighed, and transferred to a two−gallon glass jar, which was considered a worst−case scenario. sealed and fitted with ports for flow−through gas sampling. Each sample jar contained five fruit with a total weight CHEMICAL SENSOR PROCEDURE between 850 and 900 g. Samples were prepared and The steady−state headspace atmosphere of samples headspace volatile gases measured on two consecutive days. The ambient temperature during measurements was 23.3°C prepared as described above was measured
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