Research Article
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Year 2022, Volume 10, Issue 1, 42 - 47, 01.01.2022
https://doi.org/10.21541/apjess.1060757

Abstract

References

  • A. D’Amico vd., “An investigation on electronic nose diagnosis of lung cancer”, Lung Cancer, c. 68, sy 2, ss. 170-176, May. 2010, doi: 10.1016/j.lungcan.2009.11.003.
  • R. F. Machado vd., “Detection of Lung Cancer by Sensor Array Analyses of Exhaled Breath”, Am J Respir Crit Care Med, c. 171, sy 11, ss. 1286-1291, Haz. 2005, doi: 10.1164/rccm.200409-1184OC.
  • B. H. Tozlu, C. Şimşek, O. Aydemir, ve Y. Karavelioglu, “A High performance electronic nose system for the recognition of myocardial infarction and coronary artery diseases”, Biomedical Signal Processing and Control, c. 64, s. 102247, Şub. 2021, doi: 10.1016/j.bspc.2020.102247.
  • S. Scarlata, G. Pennazza, M. Santonico, C. Pedone, ve R. A. Incalzi, “Exhaled breath analysis by electronic nose in respiratory diseases”, Expert Review of Molecular Diagnostics, c. 15, sy 7, ss. 933-956, Tem. 2015, doi: 10.1586/14737159.2015.1043895.
  • N. Fens vd., “Exhaled breath profiling enables discrimination of chronic obstructive pulmonary disease and asthma”, Am. J. Respir. Crit. Care Med., c. 180, sy 11, ss. 1076-1082, Ara. 2009, doi: 10.1164/rccm.200906-0939OC.
  • J.-P. Bach vd., “Measuring Compounds in Exhaled Air to Detect Alzheimer’s Disease and Parkinson’s Disease”, PLOS ONE, c. 10, sy 7, s. e0132227, Tem. 2015, doi: 10.1371/journal.pone.0132227.
  • U. Tisch vd., “Detection of Alzheimer’s and Parkinson’s disease from exhaled breath using nanomaterial-based sensors”, Nanomedicine, c. 8, sy 1, ss. 43-56, Eki. 2012, doi: 10.2217/nnm.12.105.
  • S. Esfahani, A. Wicaksono, E. Mozdiak, R. P. Arasaradnam, ve J. A. Covington, “Non-Invasive Diagnosis of Diabetes by Volatile Organic Compounds in Urine Using FAIMS and Fox4000 Electronic Nose”, Biosensors (Basel), c. 8, sy 4, Ara. 2018, doi: 10.3390/bios8040121.
  • A. Bermak ve M. Hassan, “Noninvasive Diabetes Monitoring with Electronic Nose”, Mar. 2016, c. 2016, s. HBPP2776. doi: 10.5339/qfarc.2016.HBPP2776.
  • J. Gebicki, B. Szulczynski, ve M. Kaminski, “Determination of authenticity of brand perfume using electronic nose prototypes”, Meas. Sci. Technol., c. 26, sy 12, s. 125103, Eki. 2015, doi: 10.1088/0957-0233/26/12/125103.
  • A. Carrasco, C. Saby, ve P. Bernadet, “Discrimination of Yves Saint Laurent perfumes by an electronic nose”, Flavour and Fragrance Journal, c. 13, sy 5, ss. 335-348, Eyl. 1998.
  • X. Huang, S. Pan, Z. Sun, Y. Wei‐tao, ve J. H. Aheto, “Evaluating quality of tomato during storage using fusion information of computer vision and electronic nose”, Ağu. 2018, [Çevrimiçi]. Erişim adresi: https://doi.org/10.1111/jfpe.12832
  • “Evaluation of peach quality indices using an electronic nose by MLR, QPST and BP network”, Sensors and Actuators B: Chemical, c. 134, sy 1, ss. 332-338, Ağu. 2008, doi: 10.1016/j.snb.2008.05.008.
  • “Qualification and quantisation of processed strawberry juice based on electronic nose and tongue”, LWT - Food Science and Technology, c. 60, sy 1, ss. 115-123, Oca. 2015, doi: 10.1016/j.lwt.2014.08.041.
  • M. Aleixandre, J. M. Cabellos, T. Arroyo, ve M. C. Horrillo, “Quantification of Wine Mixtures with an Electronic Nose and a Human Panel”, Front. Bioeng. Biotechnol., c. 6, 2018, doi: 10.3389/fbioe.2018.00014.
  • B. Tozlu, H. I. Okumus, ve C. Simsek, “Onlıne Qualıty Classıfyıng Wıth Electronıc Nose For Black Tea Productıon.”, International Journal of Academic Research, c. 6, sy 4, 2014.
  • S. Labreche, S. Bazzo, S. Cade, ve E. Chanie, “Shelf life determination by electronic nose: application to milk”, Sensors and Actuators B: Chemical, c. 106, sy 1, ss. 199-206, Nis. 2005, doi: 10.1016/j.snb.2004.06.027.
  • S. Güney ve A. Atasoy, “Freshness Classification of Horse Mackerels with E-Nose System Using Hybrid Binary Decision Tree Structure”, Int. J. Patt. Recogn. Artif. Intell., c. 34, sy 03, s. 2050003, May. 2019, doi: 10.1142/S0218001420500032.
  • “Study of peach freshness predictive method based on electronic nose”, Food Control, c. 28, sy 1, ss. 25-32, Kas. 2012, doi: 10.1016/j.foodcont.2012.04.025.
  • R. Dutta, E. L. Hines, J. W. Gardner, D. D. Udrea, ve P. Boilot, “Non-destructive egg freshness determination: an electronic nose based approach”, Meas. Sci. Technol., c. 14, sy 2, ss. 190-198, Oca. 2003, doi: 10.1088/0957-0233/14/2/306.
  • E. Ergün ve Ö. Aydemir, “Decoding of Binary Mental Arithmetic Based Near-Infrared Spectroscopy Signals”, içinde 2018 3rd International Conference on Computer Science and Engineering (UBMK), Eyl. 2018, ss. 201-204. doi: 10.1109/UBMK.2018.8566462.
  • A. Ceccarelli vd., “Nectarine volatilome response to fresh-cutting and storage”, Postharvest Biology and Technology, c. 159, s. 111020, Oca. 2020, doi: 10.1016/j.postharvbio.2019.111020.

Determination of Chopped Fruits Freshness with High Accuracy by Using Electronic Nose

Year 2022, Volume 10, Issue 1, 42 - 47, 01.01.2022
https://doi.org/10.21541/apjess.1060757

Abstract

In this study, the effect of evaporator pinch point temperature difference (∆TPP,e) value in Organic Rankine Cycle (ORC) on system performance was determined. Under different applications of ORC, optimum ∆TPP,e value has been determined in ORC systems designed with different heat source temperatures. By changing the ∆TPP,e value, the heat input provided to the system, the mass flow of organic fluid, the evaporation pressure and the enthalpy drop in the turbine are affected. In thermodynamic optimization, the objective function is determined as turbine power maximization. Genetic algorithm optimization technique is used. Within the scope of low and high temperature ORC applications, the optimum ∆TPP,e value of different organic fluids under 10 different heat source temperatures (Low, 90-130 °C; High, 250-290 °C) has been determined. Low temperature organic fluids have been selected from dry, isentropic, wet and new-generation categories. High temperature organic fluids have been selected from the alkane, aromatic hydrocarbon, and siloxane categories. The effect of ∆TPP,e on fluids of different categories was determined for low and high temperature ORCs. It has been determined that taking the ∆TPP,e value constant regardless of the heat source temperature and organic fluid causes performance loss in ORC.

References

  • A. D’Amico vd., “An investigation on electronic nose diagnosis of lung cancer”, Lung Cancer, c. 68, sy 2, ss. 170-176, May. 2010, doi: 10.1016/j.lungcan.2009.11.003.
  • R. F. Machado vd., “Detection of Lung Cancer by Sensor Array Analyses of Exhaled Breath”, Am J Respir Crit Care Med, c. 171, sy 11, ss. 1286-1291, Haz. 2005, doi: 10.1164/rccm.200409-1184OC.
  • B. H. Tozlu, C. Şimşek, O. Aydemir, ve Y. Karavelioglu, “A High performance electronic nose system for the recognition of myocardial infarction and coronary artery diseases”, Biomedical Signal Processing and Control, c. 64, s. 102247, Şub. 2021, doi: 10.1016/j.bspc.2020.102247.
  • S. Scarlata, G. Pennazza, M. Santonico, C. Pedone, ve R. A. Incalzi, “Exhaled breath analysis by electronic nose in respiratory diseases”, Expert Review of Molecular Diagnostics, c. 15, sy 7, ss. 933-956, Tem. 2015, doi: 10.1586/14737159.2015.1043895.
  • N. Fens vd., “Exhaled breath profiling enables discrimination of chronic obstructive pulmonary disease and asthma”, Am. J. Respir. Crit. Care Med., c. 180, sy 11, ss. 1076-1082, Ara. 2009, doi: 10.1164/rccm.200906-0939OC.
  • J.-P. Bach vd., “Measuring Compounds in Exhaled Air to Detect Alzheimer’s Disease and Parkinson’s Disease”, PLOS ONE, c. 10, sy 7, s. e0132227, Tem. 2015, doi: 10.1371/journal.pone.0132227.
  • U. Tisch vd., “Detection of Alzheimer’s and Parkinson’s disease from exhaled breath using nanomaterial-based sensors”, Nanomedicine, c. 8, sy 1, ss. 43-56, Eki. 2012, doi: 10.2217/nnm.12.105.
  • S. Esfahani, A. Wicaksono, E. Mozdiak, R. P. Arasaradnam, ve J. A. Covington, “Non-Invasive Diagnosis of Diabetes by Volatile Organic Compounds in Urine Using FAIMS and Fox4000 Electronic Nose”, Biosensors (Basel), c. 8, sy 4, Ara. 2018, doi: 10.3390/bios8040121.
  • A. Bermak ve M. Hassan, “Noninvasive Diabetes Monitoring with Electronic Nose”, Mar. 2016, c. 2016, s. HBPP2776. doi: 10.5339/qfarc.2016.HBPP2776.
  • J. Gebicki, B. Szulczynski, ve M. Kaminski, “Determination of authenticity of brand perfume using electronic nose prototypes”, Meas. Sci. Technol., c. 26, sy 12, s. 125103, Eki. 2015, doi: 10.1088/0957-0233/26/12/125103.
  • A. Carrasco, C. Saby, ve P. Bernadet, “Discrimination of Yves Saint Laurent perfumes by an electronic nose”, Flavour and Fragrance Journal, c. 13, sy 5, ss. 335-348, Eyl. 1998.
  • X. Huang, S. Pan, Z. Sun, Y. Wei‐tao, ve J. H. Aheto, “Evaluating quality of tomato during storage using fusion information of computer vision and electronic nose”, Ağu. 2018, [Çevrimiçi]. Erişim adresi: https://doi.org/10.1111/jfpe.12832
  • “Evaluation of peach quality indices using an electronic nose by MLR, QPST and BP network”, Sensors and Actuators B: Chemical, c. 134, sy 1, ss. 332-338, Ağu. 2008, doi: 10.1016/j.snb.2008.05.008.
  • “Qualification and quantisation of processed strawberry juice based on electronic nose and tongue”, LWT - Food Science and Technology, c. 60, sy 1, ss. 115-123, Oca. 2015, doi: 10.1016/j.lwt.2014.08.041.
  • M. Aleixandre, J. M. Cabellos, T. Arroyo, ve M. C. Horrillo, “Quantification of Wine Mixtures with an Electronic Nose and a Human Panel”, Front. Bioeng. Biotechnol., c. 6, 2018, doi: 10.3389/fbioe.2018.00014.
  • B. Tozlu, H. I. Okumus, ve C. Simsek, “Onlıne Qualıty Classıfyıng Wıth Electronıc Nose For Black Tea Productıon.”, International Journal of Academic Research, c. 6, sy 4, 2014.
  • S. Labreche, S. Bazzo, S. Cade, ve E. Chanie, “Shelf life determination by electronic nose: application to milk”, Sensors and Actuators B: Chemical, c. 106, sy 1, ss. 199-206, Nis. 2005, doi: 10.1016/j.snb.2004.06.027.
  • S. Güney ve A. Atasoy, “Freshness Classification of Horse Mackerels with E-Nose System Using Hybrid Binary Decision Tree Structure”, Int. J. Patt. Recogn. Artif. Intell., c. 34, sy 03, s. 2050003, May. 2019, doi: 10.1142/S0218001420500032.
  • “Study of peach freshness predictive method based on electronic nose”, Food Control, c. 28, sy 1, ss. 25-32, Kas. 2012, doi: 10.1016/j.foodcont.2012.04.025.
  • R. Dutta, E. L. Hines, J. W. Gardner, D. D. Udrea, ve P. Boilot, “Non-destructive egg freshness determination: an electronic nose based approach”, Meas. Sci. Technol., c. 14, sy 2, ss. 190-198, Oca. 2003, doi: 10.1088/0957-0233/14/2/306.
  • E. Ergün ve Ö. Aydemir, “Decoding of Binary Mental Arithmetic Based Near-Infrared Spectroscopy Signals”, içinde 2018 3rd International Conference on Computer Science and Engineering (UBMK), Eyl. 2018, ss. 201-204. doi: 10.1109/UBMK.2018.8566462.
  • A. Ceccarelli vd., “Nectarine volatilome response to fresh-cutting and storage”, Postharvest Biology and Technology, c. 159, s. 111020, Oca. 2020, doi: 10.1016/j.postharvbio.2019.111020.

Details

Primary Language English
Subjects Computer Science, Artifical Intelligence
Published Date January 2022
Journal Section Research Articles
Authors

Bilge Han TOZLU (Primary Author)
Department of Electrical Electronics Engineering, Hitit University, Çorum
0000-0001-6896-7451
Türkiye

Early Pub Date January 20, 2022
Publication Date January 1, 2022
Application Date June 15, 2021
Acceptance Date October 31, 2021
Published in Issue Year 2022, Volume 10, Issue 1

Cite

IEEE B. H. Tozlu , "Determination of Chopped Fruits Freshness with High Accuracy by Using Electronic Nose", Academic Platform Journal of Engineering and Smart Systems, vol. 10, no. 1, pp. 42-47, Jan. 2022, doi:10.21541/apjess.1060757

Academic Platform Journal of Engineering and Smart Systems