PENGEMBANGAN ALAT UJI KEMATANGAN JERUK PAMELO DENGAN METODE IMPEDANSI

Citrus Pamela / Citrus Maxima adalah jeruk dengan ukuran besar dan kulit tebal. Pamelo setengah matang atau matang berwarna hijau atau hijau kekuningan sehingga agak sulit untuk dibedakan. Dalam penelitian ini, dikembangkan perangkat untuk menentukan kematangan pamelo menggunakan metode impedansi. Sifat listrik pamelo dibandingkan untuk menentukan kematangan buah. Pengukuran impedansi dan fase dilakukan dengan menyuntikkan arus bolak-balik menggunakan probe dua-elektroda yang terhubung ke buah. Frekuensi bolak-balik dipilih antara 1 kHz hingga 100 kHz. Kami juga mengukur keasaman dan kadar gula pamelo dengan menggunakan pH meter dan Refractometer Brix. Hasil penelitian menunjukkan AD5933 dapat digunakan untuk mengukur rangkaian ekuivalen model cole dan juga mengukur impedansi jeruk pamelo. Pengukuran kadar gula (obrix) pada sampel jeruk menunjukkan nilai antara 10.5 % hingga 14.00 % dan pH dari 4.00 hingga 5.85.Kata kunci : kematangan buah, citrus pamelo, sifat kelistrikan buah, bio-impedans

ELECTRICAL IMPEDANCE SPECTROSCOPY AND TOMOGRAPHY: APPLICATIONS ON PLANT CHARACTERIZATION

World population will grow to 9.6 billion by 2050 and global food production needs to be increased by 70% to feed the increased population. Hence, better insight into plant physiology can impart better quality in fruits, vegetables, and crops, and eventually contribute to food security and sustainability. In this direction, this thesis utilizes electrical sensing technology, electrical impedance spectroscopy (EIS) and tomography (EIT), for better understanding and characterization of a number of physiological and structural aspects of the plant. It investigates the dehydration process in onion and ripening process in avocado by EIS, and perform 3D structural imaging of root by EIT. The thesis tracks and analyzes the dynamics of natural dehydration in onion and also assesses its moisture content using EIS. The work develops an equivalent electrical circuit that simulates the response of the onion undergoing natural drying for a duration of three weeks. The developed electrical model shows better congruence with the experimental data when compared to other conventional models for plant tissue with a mean absolute error of 0.42% and root mean squared error of 0.55%. Moreover, the study attempts to find a correlation between the measured impedance data and the actual moisture content of the onions under test (measured by weighing) and develops a simple mathematical model. This model provides an alternative tool for assessing the moisture content of onion nondestructively. The model shows excellent correlation with the ground truth data with a deterministic coefficient of 0.977, root mean square error of 0.030 and sum of squared error of 0.013. Next, the thesis presents an approach that will integrate EIS and machine learning technique that allows us to monitor ripening degree of avocado. It is evident from this study that the impedance absolute magnitude of avocado gradually decreases as the ripening stages (firm, breaking, ripe and overripe) proceed at a particular frequency. In addition, Principal component analysis shows that impedance magnitude (two principal components combined explain 99.95% variation) has better discrimination capabilities for ripening degrees compared to impedance phase angle, impedance real part, and impedance imaginary part. The developed classifier utilizes two principal component features over 100 EIS responses and demonstrate classification over firm, breaking, ripe and overripe stages with an accuracy of 90%, precision of 93%, recall of 90%, f1-score of 90% and an area under ROC curve (AUC) of 88%. Later on, this thesis presents the design, development, and implementation of a low-cost EIT system and analyzes root imaging as well. The designed prototype consists of an electrode array system, an Impedance analyzer board, 2 multiplexer units, and an Arduino. The Eval-Ad5933-EBZ is used for measuring the bio-impedance of the root, and two CD74HC4067 Multiplexers are used as electrode switching unit. Measuring and data collecting are controlled by the Arduino, and data storage is performed in a PC. By performing Finite Element Analysis and solving forward and inverse problem, the tomographic image of the root is reconstructed. The system is able to localize and build 2D and 3D tomographic image of root in a liquid medium. This proposed low-cost and easy-to-access system enables the users to capture the repetitive, noninvasive and non-destructive image of a plant root. Furthermore, the study proposes a simple mathematical model, based on ridge regression, which can predict root biomass from EIT data nondestructively with an accuracy of more than 93%. Thus, this study offers plant scientists and crop consultants the ability to better understand plant physiology nondestructively and noninvasively

ELECTRICAL IMPEDANCE SPECTROSCOPY AND TOMOGRAPHY: APPLICATIONS ON PLANT CHARACTERIZATION

World population will grow to 9.6 billion by 2050 and global food production needs to be increased by 70% to feed the increased population. Hence, better insight into plant physiology can impart better quality in fruits, vegetables, and crops, and eventually contribute to food security and sustainability. In this direction, this thesis utilizes electrical sensing technology, electrical impedance spectroscopy (EIS) and tomography (EIT), for better understanding and characterization of a number of physiological and structural aspects of the plant. It investigates the dehydration process in onion and ripening process in avocado by EIS, and perform 3D structural imaging of root by EIT. The thesis tracks and analyzes the dynamics of natural dehydration in onion and also assesses its moisture content using EIS. The work develops an equivalent electrical circuit that simulates the response of the onion undergoing natural drying for a duration of three weeks. The developed electrical model shows better congruence with the experimental data when compared to other conventional models for plant tissue with a mean absolute error of 0.42% and root mean squared error of 0.55%. Moreover, the study attempts to find a correlation between the measured impedance data and the actual moisture content of the onions under test (measured by weighing) and develops a simple mathematical model. This model provides an alternative tool for assessing the moisture content of onion nondestructively. The model shows excellent correlation with the ground truth data with a deterministic coefficient of 0.977, root mean square error of 0.030 and sum of squared error of 0.013. Next, the thesis presents an approach that will integrate EIS and machine learning technique that allows us to monitor ripening degree of avocado. It is evident from this study that the impedance absolute magnitude of avocado gradually decreases as the ripening stages (firm, breaking, ripe and overripe) proceed at a particular frequency. In addition, Principal component analysis shows that impedance magnitude (two principal components combined explain 99.95% variation) has better discrimination capabilities for ripening degrees compared to impedance phase angle, impedance real part, and impedance imaginary part. The developed classifier utilizes two principal component features over 100 EIS responses and demonstrate classification over firm, breaking, ripe and overripe stages with an accuracy of 90%, precision of 93%, recall of 90%, f1-score of 90% and an area under ROC curve (AUC) of 88%. Later on, this thesis presents the design, development, and implementation of a low-cost EIT system and analyzes root imaging as well. The designed prototype consists of an electrode array system, an Impedance analyzer board, 2 multiplexer units, and an Arduino. The Eval-Ad5933-EBZ is used for measuring the bio-impedance of the root, and two CD74HC4067 Multiplexers are used as electrode switching unit. Measuring and data collecting are controlled by the Arduino, and data storage is performed in a PC. By performing Finite Element Analysis and solving forward and inverse problem, the tomographic image of the root is reconstructed. The system is able to localize and build 2D and 3D tomographic image of root in a liquid medium. This proposed low-cost and easy-to-access system enables the users to capture the repetitive, noninvasive and non-destructive image of a plant root. Furthermore, the study proposes a simple mathematical model, based on ridge regression, which can predict root biomass from EIT data nondestructively with an accuracy of more than 93%. Thus, this study offers plant scientists and crop consultants the ability to better understand plant physiology nondestructively and noninvasively

Espectroscopia de impedancia eléctrica aplicada al control de la calidad en la industria alimentaria

Electrical impedance spectroscopy (EIE) is a technique used to analyze the electrical properties of the materials (including biological) inducing and measuring alternating electrical signals at different frequencies. Impedance measurements are employed to determine ripeness in fruits, identify adulterations in meat and dairy products, determine physical-chemical properties in all types of food matrices and even to quantify microorganisms present in food and on work surfaces. This technique is safe, non-invasive, fast, portable, inexpensive and easy to use; which makes it a method with great potential to be used in the food industry to monitor and control quality processes. This systematic review compiles scientific information published between 2012 and 2018 that describes the use of EIE applied to food quality control. Search was made in the ScienceDirect, Springer databases and the search engine Scholar Google, through the strategy: Spectroscopy electrical impedance AND Foods. After using a series of filters and a manual search, 53 articles and a thesis related to the topic were found. As a result of the systematic review, it was found that most of the studies focus on the quality assessment of meat and fishery products, as well as on the characterization of the changes generated during the thermal processes and ripening of fruits.La espectroscopia de impedancia eléctrica (EIE) es una técnica que permite analizar las propiedades eléctricas de materiales, incluso biológicos, al inducir señales eléctricas alternas a diferentes frecuencias y medir las señales de respuesta. Se ha utilizado para determinar la madurez en frutos, identificar adulteraciones en productos cárnicos y lácteos, determinar propiedades físico-químicas en todo tipo de matrices alimentarias e incluso para cuantificar microorganismos presentes en alimentos y en superficies de trabajo. Esta técnica es segura, no invasiva, rápida, portátil, de bajo costo y fácil de usar; lo que la convierte en un método con un gran potencial ser usado en la industria de alimentos para monitorear y controlar los procesos de calidad. La presente revisión sistemática recopila información científica publicada entre el año 2012 y 2018 que describe el uso EIE aplicada al control de calidad de alimentos. Se realizó una búsqueda en las bases de datos ScienceDirect, Springer y también en el buscador Google académico mediante la estrategia: Spectroscopy electrical impedance AND Foods. Aplicando una serie de filtros y una búsqueda manual se encontraron 53 artículos y una tesis relacionados con la temática. Se encontró que la mayoría de los estudios se centran en la evaluación de calidad de productos cárnicos y pesqueros, así como en la caracterización de los cambios generados durante los procesos térmicos y maduración de frutas

Diseño de un sistema innovador de laboratorio para la detección temprana de congelación de la naranja

[ES] Se trata del diseño de un innovador sistema de laboratorio para la detección temprana del daño por congelación en naranjas de una manera económica, limpia, rápida, segura y fiable[EN] It is the design of an innovative laboratory system for the early detection of freezing damage in oranges in an economical, clean, fast, safe and reliable way.Muñoz Albero, M. (2020). Diseño de un sistema innovador de laboratorio para la detección temprana de congelación de la naranja. Universitat Politècnica de València. http://hdl.handle.net/10251/151754TFG

Freeze-Damage Detection in Lemons Using Electrochemical Impedance Spectroscopy

[EN] Lemon is the most sensitive citrus fruit to cold. Therefore, it is of capital importance to detect and avoid temperatures that could damage the fruit both when it is still in the tree and in its subsequent commercialization. In order to rapidly identify frost damage in this fruit, a system based on the electrochemical impedance spectroscopy technique (EIS) was used. This system consists of a signal generator device associated with a personal computer (PC) to control the system and a double-needle stainless steel electrode. Tests with a set of fruits both natural and subsequently frozen-thawed allowed us to differentiate the behavior of the impedance value depending on whether the sample had been previously frozen or not by means of a single principal components analysis (PCA) and a partial least squares discriminant analysis (PLS-DA). Artificial neural networks (ANNs) were used to generate a prediction model able to identify the damaged fruits just 24 hours after the cold phenomenon occurred, with sufficient robustness and reliability (CCR = 100%).This research was funded by the the Spanish Government/FEDER funds (RTI2018-100910-B-C43) (MINECO/FEDER) and the Conselleria d'Educacio, Investigacio, Cultura i Esport de la Generalitat Valenciana (GV/2018/090).Ochandio Fernández, A.; Olguín Pinatti, CA.; Masot Peris, R.; Laguarda-Miro, N. (2019). Freeze-Damage Detection in Lemons Using Electrochemical Impedance Spectroscopy. Sensors. 19(18):1-12. https://doi.org/10.3390/s19184051S1121918Zabihi, H., Vogeler, I., Amin, Z. M., & Gourabi, B. R. (2016). Mapping the sensitivity of citrus crops to freeze stress using a geographical information system in Ramsar, Iran. Weather and Climate Extremes, 14, 17-23. doi:10.1016/j.wace.2016.10.002Tan, E. S., Slaughter, D. C., & Thompson, J. F. (2005). 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K., Xanthakis, E., Chevallier, S., Jury, V., & Le-Bail, A. (2019). Assessment of freeze damage in fruits and vegetables. Food Research International, 121, 479-496. doi:10.1016/j.foodres.2018.12.002Sala, J. M., & Lafuente, M. T. (1999). Catalase in the Heat-Induced Chilling Tolerance of Cold-Stored Hybrid Fortune Mandarin Fruits. Journal of Agricultural and Food Chemistry, 47(6), 2410-2414. doi:10.1021/jf980805eMoomkesh, S., Mireei, S. A., Sadeghi, M., & Nazeri, M. (2017). Early detection of freezing damage in sweet lemons using Vis/SWNIR spectroscopy. Biosystems Engineering, 164, 157-170. doi:10.1016/j.biosystemseng.2017.10.009Obenland, D. M., Aung, L. H., Bridges, D. L., & Mackey, B. E. (2003). Volatile Emissions of Navel Oranges as Predictors of Freeze Damage. Journal of Agricultural and Food Chemistry, 51(11), 3367-3371. doi:10.1021/jf021109oGambhir, P. N., Choi, Y. J., Slaughter, D. C., Thompson, J. F., & McCarthy, M. J. (2005). Proton spin-spin relaxation time of peel and flesh of navel orange varieties exposed to freezing temperature. Journal of the Science of Food and Agriculture, 85(14), 2482-2486. doi:10.1002/jsfa.2266Fuentes, A., Masot, R., Fernández-Segovia, I., Ruiz-Rico, M., Alcañiz, M., & Barat, J. M. (2013). Differentiation between fresh and frozen-thawed sea bream (Sparus aurata) using impedance spectroscopy techniques. Innovative Food Science & Emerging Technologies, 19, 210-217. doi:10.1016/j.ifset.2013.05.001Conesa, C., García-Breijo, E., Loeff, E., Seguí, L., Fito, P., & Laguarda-Miró, N. (2015). An Electrochemical Impedance Spectroscopy-Based Technique to Identify and Quantify Fermentable Sugars in Pineapple Waste Valorization for Bioethanol Production. Sensors, 15(9), 22941-22955. doi:10.3390/s150922941Wu, L., Ogawa, Y., & Tagawa, A. (2008). Electrical impedance spectroscopy analysis of eggplant pulp and effects of drying and freezing–thawing treatments on its impedance characteristics. Journal of Food Engineering, 87(2), 274-280. doi:10.1016/j.jfoodeng.2007.12.003Serrano-Pallicer, E., Muñoz-Albero, M., Pérez-Fuster, C., Masot Peris, R., & Laguarda-Miró, N. (2018). Early Detection of Freeze Damage in Navelate Oranges with Electrochemical Impedance Spectroscopy. Sensors, 18(12), 4503. doi:10.3390/s18124503Grossi, M., & Riccò, B. (2017). Electrical impedance spectroscopy (EIS) for biological analysis and food characterization: a review. Journal of Sensors and Sensor Systems, 6(2), 303-325. doi:10.5194/jsss-6-303-2017Chowdhury, A., Kanti Bera, T., Ghoshal, D., & Chakraborty, B. (2016). Electrical Impedance Variations in Banana Ripening: An Analytical Study with Electrical Impedance Spectroscopy. Journal of Food Process Engineering, 40(2), e12387. doi:10.1111/jfpe.12387Bauchot, A. D., Harker, F. R., & Arnold, W. M. (2000). The use of electrical impedance spectroscopy to assess the physiological condition of kiwifruit. Postharvest Biology and Technology, 18(1), 9-18. doi:10.1016/s0925-5214(99)00056-3Figueiredo Neto, A., Cárdenas Olivier, N., Rabelo Cordeiro, E., & Pequeno de Oliveira, H. (2017). Determination of mango ripening degree by electrical impedance spectroscopy. Computers and Electronics in Agriculture, 143, 222-226. doi:10.1016/j.compag.2017.10.018Benavente, J., Ramos-Barrado, J. ., & Heredia, A. (1998). A study of the electrical behaviour of isolated tomato cuticular membranes and cutin by impedance spectroscopy measurements. Colloids and Surfaces A: Physicochemical and Engineering Aspects, 140(1-3), 333-338. doi:10.1016/s0927-7757(97)00290-2Ando, Y., Maeda, Y., Mizutani, K., Wakatsuki, N., Hagiwara, S., & Nabetani, H. (2016). Impact of blanching and freeze-thaw pretreatment on drying rate of carrot roots in relation to changes in cell membrane function and cell wall structure. LWT - Food Science and Technology, 71, 40-46. doi:10.1016/j.lwt.2016.03.019Ando, Y., Maeda, Y., Mizutani, K., Wakatsuki, N., Hagiwara, S., & Nabetani, H. (2016). Effect of air-dehydration pretreatment before freezing on the electrical impedance characteristics and texture of carrots. Journal of Food Engineering, 169, 114-121. doi:10.1016/j.jfoodeng.2015.08.026Fuentes, A., Vázquez-Gutiérrez, J. L., Pérez-Gago, M. B., Vonasek, E., Nitin, N., & Barrett, D. M. (2014). Application of nondestructive impedance spectroscopy to determination of the effect of temperature on potato microstructure and texture. Journal of Food Engineering, 133, 16-22. doi:10.1016/j.jfoodeng.2014.02.016M’hiri, N., Veys-Renaux, D., Rocca, E., Ioannou, I., Boudhrioua, N. M., & Ghoul, M. (2016). Corrosion inhibition of carbon steel in acidic medium by orange peel extract and its main antioxidant compounds. Corrosion Science, 102, 55-62. doi:10.1016/j.corsci.2015.09.017Conesa, C., Ibáñez Civera, J., Seguí, L., Fito, P., & Laguarda-Miró, N. (2016). An Electrochemical Impedance Spectroscopy System for Monitoring Pineapple Waste Saccharification. Sensors, 16(2), 188. doi:10.3390/s16020188Conesa, C., Sánchez, L. G., Seguí, L., Fito, P., & Laguarda-Miró, N. (2017). Ethanol quantification in pineapple waste by an electrochemical impedance spectroscopy-based system and artificial neural networks. Chemometrics and Intelligent Laboratory Systems, 161, 1-7. doi:10.1016/j.chemolab.2016.12.005Ulrich, C., Petersson, H., Sundgren, H., Björefors, F., & Krantz-Rülcker, C. (2007). Simultaneous estimation of soot and diesel contamination in engine oil using electrochemical impedance spectroscopy. Sensors and Actuators B: Chemical, 127(2), 613-618. doi:10.1016/j.snb.2007.05.014Olivati, C. A., Riul, A., Balogh, D. T., Oliveira, O. N., & Ferreira, M. (2008). Detection of phenolic compounds using impedance spectroscopy measurements. Bioprocess and Biosystems Engineering, 32(1), 41-46. doi:10.1007/s00449-008-0218-4Martínez Gil, P., Laguarda-Miro, N., Camino, J. S., & Peris, R. M. (2013). Glyphosate detection with ammonium nitrate and humic acids as potential interfering substances by pulsed voltammetry technique. Talanta, 115, 702-705. doi:10.1016/j.talanta.2013.06.030Górski, Ł., Sordoń, W., Ciepiela, F., Kubiak, W. W., & Jakubowska, M. (2016). Voltammetric classification of ciders with PLS-DA. Talanta, 146, 231-236. doi:10.1016/j.talanta.2015.08.027Kumar, G., & Buchheit, R. G. (2008). Use of Artificial Neural Network Models to Predict Coated Component Life from Short-Term Electrochemical Impedance Spectroscopy Measurements. CORROSION, 64(3), 241-254. doi:10.5006/1.3278469Eddahech, A., Briat, O., Bertrand, N., Delétage, J.-Y., & Vinassa, J.-M. (2012). Behavior and state-of-health monitoring of Li-ion batteries using impedance spectroscopy and recurrent neural networks. International Journal of Electrical Power & Energy Systems, 42(1), 487-494. doi:10.1016/j.ijepes.2012.04.050Conesa, C., Seguí, L., Laguarda-Miró, N., & Fito, P. (2016). Microwaves as a pretreatment for enhancing enzymatic hydrolysis of pineapple industrial waste for bioethanol production. Food and Bioproducts Processing, 100, 203-213. doi:10.1016/j.fbp.2016.07.001Masot, R., Alcañiz, M., Fuentes, A., Schmidt, F. C., Barat, J. M., Gil, L., … Soto, J. (2010). Design of a low-cost non-destructive system for punctual measurements of salt levels in food products using impedance spectroscopy. Sensors and Actuators A: Physical, 158(2), 217-223. doi:10.1016/j.sna.2010.01.010Wold, S., Sjöström, M., & Eriksson, L. (2001). PLS-regression: a basic tool of chemometrics. Chemometrics and Intelligent Laboratory Systems, 58(2), 109-130. doi:10.1016/s0169-7439(01)00155-1Legin, Zadorozhnaya, Khaydukova, Kirsanov, Rybakin, Zagrebin, … Legin. (2019). Rapid Evaluation of Integral Quality and Safety of Surface and Waste Waters by a Multisensor System (Electronic Tongue). Sensors, 19(9), 2019. doi:10.3390/s19092019Garcia-Breijo, E., Atkinson, J., Gil-Sanchez, L., Masot, R., Ibañez, J., Garrigues, J., … Olguin, C. (2011). A comparison study of pattern recognition algorithms implemented on a microcontroller for use in an electronic tongue for monitoring drinking waters. Sensors and Actuators A: Physical, 172(2), 570-582. doi:10.1016/j.sna.2011.09.039Garcia-Breijo, E., Garrigues, J., Sanchez, L., & Laguarda-Miro, N. (2013). An Embedded Simplified Fuzzy ARTMAP Implemented on a Microcontroller for Food Classification. Sensors, 13(8), 10418-10429. doi:10.3390/s130810418Brezmes, J., Cabre, P., Rojo, S., Llobet, E., Vilanova, X., & Correig, X. (2005). Discrimination between different samples of olive oil using variable selection techniques and modified fuzzy artmap neural networks. IEEE Sensors Journal, 5(3), 463-470. doi:10.1109/jsen.2005.846186Ibáñez Civera, J., Garcia Breijo, E., Laguarda Miró, N., Gil Sánchez, L., Garrigues Baixauli, J., Romero Gil, I., … Alcañiz Fillol, M. (2011). Artificial neural network onto eight bit microcontroller for Secchi depth calculation. Sensors and Actuators B: Chemical, 156(1), 132-139. doi:10.1016/j.snb.2011.04.001Fricke, H., & Morse, S. (1925). THE ELECTRIC RESISTANCE AND CAPACITY OF BLOOD FOR FREQUENCIES BETWEEN 800 AND 4½ MILLION CYCLES. Journal of General Physiology, 9(2), 153-167. doi:10.1085/jgp.9.2.153Damez, J.-L., Clerjon, S., Abouelkaram, S., & Lepetit, J. (2007). Dielectric behavior of beef meat in the 1–1500kHz range: Simulation with the Fricke/Cole–Cole model. Meat Science, 77(4), 512-519. doi:10.1016/j.meatsci.2007.04.028Zhang, L., Shen, H., & Luo, Y. (2010). Study on the electric conduction properties of fresh and frozen-thawed grass carp (Ctenopharyngodon idellus) and tilapia(Oreochromis niloticus). International Journal of Food Science & Technology, 45(12), 2560-2564. doi:10.1111/j.1365-2621.2010.02428.