Detection of 3-Carene in mango using a quartz crystal microbalance sensor

Ali, Sk Babar; Ghatak, Barnali; Gupta, Sudipto Dutta; Debabhuti, Nilava; Chakraborty, Parthojit; Sharma, Prolay; Ghosh, Arunangshu; Tudu, Bipan; Mitra, S.; Sarkar, Mousumi Poddar; Bhattacharyya, Nabarun; Bandyopadhyay, Rajib

doi:10.1016/j.snb.2016.03.005

Cited by 27 publications

(7 citation statements)

References 20 publications

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“…As the most crucial part, the sensor array has been made up of different kinds of gas sensors. Various studies have applied conductive polymer (CP) sensors [17,18], surface acoustic wave (SAW) sensors [19,20] and quartz crystal microbalance (QCM) sensors [21,22] in the E-nose system to detect the ripeness of fruit. Compared with these sensors, metal oxide semiconductor (MOS) sensors, which have the advantages of rapid response, high sensitivity and most importantly low cost, have also been widely used in E-nose applications [23].…”

Section: Introductionmentioning

confidence: 99%

Ripeness Prediction of Postharvest Kiwifruit Using a MOS E-Nose Combined with Chemometrics

Wang

et al. 2019

Sensors

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Postharvest kiwifruit continues to ripen for a period until it reaches the optimal “eating ripe” stage. Without damaging the fruit, it is very difficult to identify the ripeness of postharvest kiwifruit by conventional means. In this study, an electronic nose (E-nose) with 10 metal oxide semiconductor (MOS) gas sensors was used to predict the ripeness of postharvest kiwifruit. Three different feature extraction methods (the max/min values, the difference values and the 70th s values) were employed to discriminate kiwifruit at different ripening times by linear discriminant analysis (LDA), and results showed that the 70th s values method had the best performance in discriminating kiwifruit at different ripening stages, obtaining a 100% original accuracy rate and a 99.4% cross-validation accuracy rate. Partial least squares regression (PLSR), support vector machine (SVM) and random forest (RF) were employed to build prediction models for overall ripeness, soluble solids content (SSC) and firmness. The regression results showed that the RF algorithm had the best performance in predicting the ripeness indexes of postharvest kiwifruit compared with PLSR and SVM, which illustrated that the E-nose data had high correlations with overall ripeness (training: R2 = 0.9928; testing: R2 = 0.9928), SSC (training: R2 = 0.9749; testing: R2 = 0.9143) and firmness (training: R2 = 0.9814; testing: R2 = 0.9290). This study demonstrated that E-nose could be a comprehensive approach to predict the ripeness of postharvest kiwifruit through aroma volatiles.

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Section: Introductionmentioning

confidence: 99%

Ripeness Prediction of Postharvest Kiwifruit Using a MOS E-Nose Combined with Chemometrics

Wang

et al. 2019

Sensors

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“…The incorporation of molecularly imprinted polymers on QCM also showed high affinity and sensitivity toward target molecules [ 89 ]. Polymers through their porous structures are another commonly applied method for better selectivity [ 9 , 90 , 91 ]. Nanostructured modified QCM was also used for successful detection of plasticizer vapors, hydrogen sulfide and ammonia [ 92 , 93 , 94 ].…”

Section: Gas Sensing Methodsmentioning

confidence: 99%

“…For example, breath volatile organic compounds (VOCs) have found immense value in noninvasive disease diagnosis and metabolism monitoring [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 ]. Food industry uses gas sensing technologies for quality control of fruit ripeness and detection of meat spoilage [ 9 , 10 , 11 , 12 , 13 ]. Analysis of indoor air quality domestically and industrially has been implemented for monitoring hazardous and asphyxiant gases [ 14 , 15 , 16 ].…”

Section: Introductionmentioning

confidence: 99%

Affinity Ionic Liquids for Chemoselective Gas Sensing

Chang

Chang³

et al. 2018

Molecules

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Selective gas sensing is of great importance for applications in health, safety, military, industry and environment. Many man-made and naturally occurring volatile organic compounds (VOCs) can harmfully affect human health or cause impairment to the environment. Gas analysis based on different principles has been developed to convert gaseous analytes into readable output signals. However, gas sensors such as metal-oxide semiconductors suffer from high operating temperatures that are impractical and therefore have limited its applications. The cost-effective quartz crystal microbalance (QCM) device represents an excellent platform if sensitive, selective and versatile sensing materials were available. Recent advances in affinity ionic liquids (AILs) have led them to incorporation with QCM to be highly sensitive for real-time detection of target gases at ambient temperature. The tailorable functional groups in AIL structures allow for chemoselective reaction with target analytes for single digit parts-per-billion detection on mass-sensitive QCM. This structural diversity makes AILs promising for the creation of a library of chemical sensor arrays that could be designed to efficiently detect gas mixtures simultaneously as a potential electronic in future. This review first provides brief introduction to some conventional gas sensing technologies and then delivers the latest results on our development of chemoselective AIL-on-QCM methods.

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“…The fermentation of black tea has been monitored through a similar approach [505]. TSMRs coated with poly(dimethyl siloxane) were employed to evaluate the ripening degree of mango fruits after the released amount of Reproduced with the kind permission of Elsevier B.V. from reference [158] 3-carene [506]. The assessment of virgin oil quality through gravimetric arrays was reported by Escuderos et al [338].…”

Section: Targeted Applicationsmentioning

confidence: 99%