2006
DOI: 10.1002/elan.200603523
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The Recognition of Growth Conditions and Metabolic Type of Plants by a Potentiometric Electronic Tongue

Abstract: The application of a potentiometric electronic tongue for the recognition and classification of plant samples is presented. Homogenates from the leaves of various plants subtypes (maize and guinea grass) were measured with the use of sensor array based on ion-selective and partially selective electrodes. It was found that this device is capable of recognizing with high correctness, the type of plant metabolism (distinguishing between two types of cereals) and the factors affecting nutritional values of plants … Show more

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Cited by 27 publications
(22 citation statements)
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References 27 publications
(25 reference statements)
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“…In the last decade, potentiometric sensor arrays have been widely used in food analysis namely, for milk recognition and classification [2,[4][5][6], wine recognition and quantitative analysis and its correlation with human sensory perception [7], beer recognition [2,8], plant samples recognition and classification [9], beverage analysis [2,[10][11][12], soy sauce taste analysis [13] and honey classification according to the pollen type [14]. In these works, several types of sensors have been tested in the potentiometric devices, namely lipid membranes [2,13], chalcogenide sensors [15], cation and anion-sensitive PVC based membranes [5,11], cation and anion-sensitive and partially selective electrodes [4,6,8,12,16], and polymeric membranes formed on solid conducting silver supports [14].…”
Section: Introductionmentioning
confidence: 99%
“…In the last decade, potentiometric sensor arrays have been widely used in food analysis namely, for milk recognition and classification [2,[4][5][6], wine recognition and quantitative analysis and its correlation with human sensory perception [7], beer recognition [2,8], plant samples recognition and classification [9], beverage analysis [2,[10][11][12], soy sauce taste analysis [13] and honey classification according to the pollen type [14]. In these works, several types of sensors have been tested in the potentiometric devices, namely lipid membranes [2,13], chalcogenide sensors [15], cation and anion-sensitive PVC based membranes [5,11], cation and anion-sensitive and partially selective electrodes [4,6,8,12,16], and polymeric membranes formed on solid conducting silver supports [14].…”
Section: Introductionmentioning
confidence: 99%
“…The composition of the sensor array was selected on the basis of previous experience [14,18,21]. The sensors' selectivity patterns were examined to verify their performance.…”
Section: Resultsmentioning
confidence: 99%
“…Such devices have been mainly used in the field of food analysis: for classification of wine [9], beer [10], tea and herbal products [11], tomato samples [12], coffee [13], and milk [14]. An electronic tongue was also applied in the analysis of industrial samples (fermentation samples [15]) and in environment monitoring (water quality analysis [16], identification on toxic substances like heavy metals [17] and plant samples [18]). The aim of this study was to evaluate the taste (or, actually, different chemical image formed with the use of sensor array) of two APIs, namely Ibuprofen and Roxithromycin, before and after microencapsulation.…”
Section: Introductionmentioning
confidence: 99%
“…A recent contribution used a four sensor array and an expert system based on case-based reasoning to detect deviations in the composition of equivalent fertigation solutions [107]. A curious work by Ciosek and co-workers optimized an electronic tongue for the recognition and classification of plant samples [108]. Leaf material from the plants was extracted in aqueous solution and measured with an array formed by 8 PVC membrane ISEs, allowing to differentiate between plant (maize and guinea grass) and to deduct cultivation conditions of the plant, such as light conditions and cultivation time, features hard to investigate by classical analytical techniques.…”
Section: Illustrative Applicationsmentioning
confidence: 99%