Nothing Special   »   [go: up one dir, main page]

skip to main content
survey

Digital Food Sensing and Ingredient Analysis Techniques to Facilitate Human-Food Interface Designs

Published: 07 October 2024 Publication History

Abstract

Interactive technologies that shape the traditional human-food experiences are being explored under the emerging field of Human-Food Interaction (HFI). A key challenge in developing HFI technologies is the digital sensing of food, beverages, and their ingredients, commonly known as digital food sensing. Digital food sensing involves recognizing different food and beverages and their internal attributes, such as volume and ingredients (e.g., salt and sugar content). Contemporary research on interactive food applications, such as dietary assessment, primarily employs Computer Vision (CV) techniques to identify food; however, they are ineffective when (1) identifying food’s internal attributes, (2) discriminating visually similar food and beverages, and (3) seamlessly integrating with people’s natural interactions while consuming food. Thus, this article reviews potential food and beverage sensing technologies that can facilitate novel Human-Food Interfaces, primarily focusing on non-disruptive sensing techniques to analyze food and beverages during consumption. First, we review ten different digital food sensing techniques and their applications in four categories. Then, we discuss three main aspects to consider when adopting these food-sensing techniques for human-food interface designs. Finally, we suggest the future research requirements in digital food sensing methodologies, followed by potential applications of digital food sensing in future developments of Human-Food Interfaces.

References

[1]
Andreia M. Afonso, Maria D. Antunes, Sandra Cruz, Ana M. Cavaco, and Rui Guerra. 2022. Non-destructive follow-up of ‘Jintao’ kiwifruit ripening through VIS-NIR spectroscopy – individual vs. average calibration model’s predictions. Postharvest Biology and Technology 188 (2022), 111895. DOI:
[2]
Leili Afsah-Hejri, Parvaneh Hajeb, Parsa Ara, and Reza J. Ehsani. 2019. A comprehensive review on food applications of terahertz spectroscopy and imaging. Comprehensive Reviews in Food Science and Food Safety 18, 5 (2019), 1563–1621.
[3]
Muhammad Haseeb Ahmad, Zainab Shahbaz, Muhammad Imran, Muhammad Kamran Khan, Niaz Muhammad, Sanaullah Iqbal, Waqas Ahmed, and Tanvir Ahmad. 2021. Monitoring of frying process in canola oil blend using fourier transform infrared and chemometrics techniques. Food Science and Nutrition 9, 11 (2021), 6089–6098.
[4]
Khawla Alhasan, Eleonora Ceccaldi, Alexandra Covaci, Maurizio Mancini, Ferran Altarriba Bertran, Gijs Huisman, Mailin Lemke, and Chee Siang Ang. 2022. The playful potential of digital commensality: Learning from spontaneous playful remote dining practices. Proc. ACM Hum.-Comput. Interact. 6, CHI PLAY (2022), 24 pages. DOI:
[5]
Ferran Altarriba, Stefano Eugenio Lanzani, Ana Torralba, and Mathias Funk. 2017. The grumpy bin: Reducing food waste through playful social interactions. In Proceedings of the 2017 ACM Conference Companion Publication on Designing Interactive Systems (Edinburgh, United Kingdom). Association for Computing Machinery, New York, NY, USA, 90–94. DOI:
[6]
Ferran Altarriba Bertran, Samvid Jhaveri, Rosa Lutz, Katherine Isbister, and Danielle Wilde. 2019. Making sense of human-food interaction. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (Glasgow, Scotland Uk). Association for Computing Machinery, New York, NY, USA, 1–13. DOI:
[7]
Ferran Altarriba Bertran, Danielle Wilde, Ernő Berezvay, and Katherine Isbister. 2019. Playful human-food interaction research: State of the art and future directions. In Proceedings of the Annual Symposium on Computer-Human Interaction in Play (Barcelona, Spain). Association for Computing Machinery, New York, NY, USA, 225–237. DOI:
[8]
Chamath Amarasinghe and Nimesha Ranasinghe. 2022. SipBit: A sensing platform to recognize beverage type, volume, and sugar content using electrical impedance spectroscopy and deep learning. In Proceedings of the Extended Abstracts of the 2022 CHI Conference on Human Factors in Computing Systems (New Orleans, LA, USA) . Association for Computing Machinery, New York, NY, USA, Article 371, 8 pages. DOI:
[9]
Petter Vejle Andersen, Nils Kristian Afseth, Kjersti Aaby, Mari Øvrum Gaarder, Siv Fagertun Remberg, and Jens Petter Wold. 2023. Prediction of chemical and sensory properties in strawberries using raman spectroscopy. Postharvest Biology and Technology 201 (2023), 112370. DOI:
[10]
Petter Vejle Andersen, Nils Kristian Afseth, Eli Gjerlaug-Enger, and Jens Petter Wold. 2021. Prediction of water holding capacity and pH in porcine longissimus lumborum using raman spectroscopy. Meat Science 172 (2021), 108357.
[11]
Petter Vejle Andersen, Jens Petter Wold, Eli Gjerlaug-Enger, and Eva Veiseth-Kent. 2018. Predicting post-mortem meat quality in porcine longissimus lumborum using raman, near infrared and fluorescence spectroscopy. Meat Science 145 (2018), 94–100.
[12]
Yoshikazu Ando, Takumi Ege, Jaehyeong Cho, and Keiji Yanai. 2019. DepthCalorieCam: A mobile application for volume-based foodcalorie estimation using depth cameras. In Proceedings of the 5th International Workshop on Multimedia Assisted Dietary Management (Nice, France). Association for Computing Machinery, New York, NY, USA, 76–81. DOI:
[13]
Yasumasa Ando, Yuka Maeda, Koichi Mizutani, Naoto Wakatsuki, Shoji Hagiwara, and Hiroshi Nabetani. 2016. Effect of air-dehydration pretreatment before freezing on the electrical impedance characteristics and texture of carrots. Journal of Food Engineering 169 (2016), 114–121.
[14]
Yasumasa Ando, Yuka Maeda, Koichi Mizutani, Naoto Wakatsuki, Shoji Hagiwara, and Hiroshi Nabetani. 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 (2016), 40–46.
[15]
Mohammed Yusuf Ansari and Marwa Qaraqe. 2023. MEFood: A large-scale representative benchmark of quotidian foods for the middle east. IEEE Access 11 (2023), 4589–4601. DOI:
[16]
Pablo Albelda Aparisi, Elena Fortes Sánchez, Laura Contat Rodrigo, Rafael Masot Peris, and Nicolás Laguarda-Miró. 2021. A rapid electrochemical impedance spectroscopy and sensor-based method for monitoring freeze-damage in tangerines. IEEE Sensors Journal 21, 10 (2021), 12009–12018.
[17]
Peter Arnold, Rohit Ashok Khot, and Florian ’Floyd’ Mueller. 2018. “You better eat to survive”: Exploring cooperative eating in virtual reality games. In Proceedings of the 12th International Conference on Tangible, Embedded, and Embodied Interaction (Stockholm, Sweden). Association for Computing Machinery, New York, NY, USA, 398–408. DOI:
[18]
Ioannis S. Arvanitoyannis, Konstantinos V. Kotsanopoulos, and Amalia G. Savva. 2017. Use of ultrasounds in the food industry–methods and effects on quality, safety, and organoleptic characteristics of foods: A review. Critical Reviews in Food Science and Nutrition 57, 1 (2017), 109–128.
[19]
Malika Auvray and Charles Spence. 2008. The multisensory perception of flavor. Consciousness and cognition 17, 3 (2008), 1016–1031.
[20]
T.S. Awad, H.A. Moharram, O.E. Shaltout, D. Asker, and M.M. Youssef. 2012. Applications of ultrasound in analysis, processing and quality control of food: A review. Food Research International 48, 2 (2012), 410–427. DOI:
[21]
Tawseef Ayoub Shaikh, Tabasum Rasool, and Faisal Rasheed Lone. 2022. Towards leveraging the role of machine learning and artificial intelligence in precision agriculture and smart farming. Computers and Electronics in Agriculture 198 (2022), 107119. DOI:
[22]
Jing Bai, Mingwu Zang, Hao Zou, Jiajia Wu, Yuxuan Shi, Hui Wang, Shouwei Wang, and Xiaoling Qiao. 2022. Prediction of the lipid degradation and storage time of chilled beef flank by using raman spectroscopy and chemometrics. Food Analytical Methods 15, 8 (2022), 2213–2223.
[23]
Shima Behkami, Sharifuddin M Zain, Mehrdad Gholami, and Mohd Fared Abdul Khir. 2019. Classification of cow milk using artificial neural network developed from the spectral data of single-and three-detector spectrophotometers. Food Chemistry 294 (2019), 309–315.
[24]
Gopinath Bej, Tamal Dey, Abhra Pal, Sabyasachi Majumdar, Rishin Banerjee, Devdulal Ghosh, Vamshi Krishna Palakurthi, Amitava Akuli, and Nabarun Bhattacharyya. 2021. Classification of bruised apple using ultrasound technology and SVM classifier. In Proceedings of the Smart Computing Techniques and Applications. Springer, New York, NY, USA, 573–582.
[25]
Alessandro Benelli, Chiara Cevoli, Angelo Fabbri, and Luigi Ragni. 2022. Ripeness evaluation of kiwifruit by hyperspectral imaging. Biosystems Engineering 223 (2022), 42–52. DOI: New advances in measurement and data processing techniques for Agriculture, Food and Environment..
[26]
Simone Bianco, Marco Buzzelli, Gaetano Chiriaco, Paolo Napoletano, and Flavio Piccoli. 2023. Food recognition with visual transformers. In Proceedings of the 2023 IEEE 13th International Conference on Consumer Electronics - Berlin. 82–87. DOI:
[27]
Antonio Biscotti, R. Lazzarini, G. Virgilli, F. Ngatcha, A. Valisi, and M. Rossi. 2018. Optimizing a portable biosensor system for bacterial detection in milk based mix for ice cream. Sensing and Bio-sensing Research 18 (2018), 1–6.
[28]
Karla Rodrigues Borba, Poliana Cristina Spricigo, Didem Peren Aykas, Milene Corso Mitsuyuki, Luiz Alberto Colnago, and Marcos David Ferreira. 2021. Non-invasive quantification of vitamin C, citric acid, and sugar in ‘Valência’oranges using infrared spectroscopies. Journal of Food Science and Technology 58, 2 (2021), 731–738.
[29]
Flavia T. Borghi, Priscilla C. Santos, Francine D. Santos, Márcia H. C. Nascimento, Thayná Corrêa, Mirelly Cesconetto, André A. Pires, Araceli V. F. N. Ribeiro, Valdemar Lacerda, Wanderson Romão, and Paulo R. Filgueiras. 2020. Quantification and classification of vegetable oils in extra virgin olive oil samples using a portable near-infrared spectrometer associated with chemometrics. Microchemical Journal 159 (2020), 105544.
[30]
Lukas Bossard, Matthieu Guillaumin, and Luc Van Gool. 2014. Food-101 – mining discriminative components with random forests. In Computer Vision – ECCV 2014. David Fleet, Tomas Pajdla, Bernt Schiele, and Tinne Tuytelaars (Eds.), Springer, New York, NY, USA, 446–461. DOI:
[31]
Yuxi Cao, Zufang Wu, and Peifang Weng. 2020. Comparison of bayberry fermented wine aroma from different cultivars by GC-MS combined with electronic nose analysis. Food Science and Nutrition 8, 2 (2020), 830–840.
[32]
Jingjing Chen and Chong-wah Ngo. 2016. Deep-based ingredient recognition for cooking recipe retrieval. In Proceedings of the 24th ACM International Conference on Multimedia (Amsterdam, The Netherlands). Association for Computing Machinery, New York, NY, USA, 32–41. DOI:
[33]
Wei Chen, Yao-Ze Feng, Gui-Feng Jia, and Hai-Tao Zhao. 2018. Application of artificial fish swarm algorithm for synchronous selection of wavelengths and spectral pretreatment methods in spectrometric analysis of beef adulteration. Food Analytical Methods 11, 8 (2018), 2229–2236.
[34]
Jiehong Cheng, Jun Sun, Kunshan Yao, Min Xu, and Chunxia Dai. 2023. Multi-task convolutional neural network for simultaneous monitoring of lipid and protein oxidative damage in frozen-thawed pork using hyperspectral imaging. Meat Science 201 (2023), 109196. DOI:
[35]
Eun Kyoung Choe, Saeed Abdullah, Mashfiqui Rabbi, Edison Thomaz, Daniel A. Epstein, Felicia Cordeiro, Matthew Kay, Gregory D. Abowd, Tanzeem Choudhury, James Fogarty, Bongshin Lee, Mark Matthews, and Julie A. Kientz. 2017. Semi-automated tracking: A balanced approach for self-monitoring applications. IEEE Pervasive Computing 16, 1 (2017), 74–84. DOI:
[36]
Atanu Chowdhury, Tushar Kanti Bera, Dibyendu Ghoshal, and Badal Chakraborty. 2017. Electrical impedance variations in banana ripening: An analytical study with electrical impedance spectroscopy. Journal of Food Process Engineering 40, 2 (2017), e12387.
[37]
Patrycja Ciosek and Wojciech Wróblewski. 2007. Sensor arrays for liquid sensing–electronic tongue systems. Analyst 132, 10 (2007), 963–978.
[38]
Joana J. Costa, Felismina T.C. Moreira, Susana Soares, Elsa Brandão, Nuno Mateus, Victor De Freitas, and M. Goreti F. Sales. 2022. Wine astringent compounds monitored by an electrochemical biosensor. Food Chemistry 395 (2022), 133587. DOI:
[39]
R. Cunnell, T. Luce, J. H. P. Collins, R. Rungsawang, J. R. Freeman, H. E. Beere, D. A. Ritchie, L. F. Gladden, M. L. Johns, and J. A. Zeitler. 2009. Quantification of emulsified water content in oil using a terahertz quantum cascade laser. In Proceedings of the 2009 34th International Conference on Infrared, Millimeter, and Terahertz Waves. IEEE, New York, NY, USA, 1–2. DOI:
[40]
Tomislav Ćurić, Nives Marušić Radovčić, Tibor Janči, Igor Lacković, and Sanja Vidaček. 2017. Salt and moisture content determination of fish by bioelectrical impedance and a needle-type multi-electrode array. International Journal of Food Properties 20, 11 (2017), 2477–2486.
[41]
Ana Carolina da Costa Fulgêncio, Glaucimar Alex Passos Resende, Marden Claret Fontoura Teixeira, Bruno Gonçalves Botelho, and Marcelo Martins Sena. 2022. Determination of alcohol content in beers of different styles based on portable near-infrared spectroscopy and multivariate calibration. Food Analytical Methods 15, 2 (2022), 307--316.
[42]
Chirantan Das, Subhadip Chakraborty, Anupam Karmakar, and Sanatan Chattopadhyay. 2018. On-chip detection and quantification of soap as an adulterant in milk employing electrical impedance spectroscopy. In Proceedings of the 2018 International Symposium on Devices, Circuits and Systems. IEEE, New York, NY, USA, 1–4. DOI:
[43]
Alexandre Gomes Marques de Freitas, Lucas Almir Cavalcante Minho, Bárbara Elizabeth Alves de Magalhães, Walter Nei Lopes Dos Santos, Leandro Soares Santos, and Sérgio Augusto de Albuquerque Fernandes. 2021. Infrared spectroscopy combined with random forest to determine tylosin residues in powdered milk. Food Chemistry 365 (2021), 130477.
[44]
Tais Carpintero Barroso de Morais, Dayvison Ribeiro Rodrigues, Urijatan Teixeira de Carvalho Polari Souto, and Sherlan G. Lemos. 2019. A simple voltammetric electronic tongue for the analysis of coffee adulterations. Food Chemistry 273 (2019), 31–38.
[45]
Thiago de Oliveira Mendes, Bruno Vinícius Manzolli Rodrigues, Brenda Lee Simas Porto, Roney Alves da Rocha, Marcone Augusto Leal de Oliveira, Filomena Karla de Castro, Virgilio de Carvalho dos Anjos, and Maria José Valenzuela Bell. 2020. Raman spectroscopy as a fast tool for whey quantification in raw milk. Vibrational Spectroscopy 111 (2020), 103150.
[46]
M. De Prados, E. Fulladosa, P. Gou, I. Muñoz, José Vicente Garcia-Perez, and J. Benedito. 2015. Non-destructive determination of fat content in green hams using ultrasound and X-rays. Meat Science 104 (2015), 37–43.
[47]
Aslihan Demirdöven and Taner Baysal. 2008. The use of ultrasound and combined technologies in food preservation. Food Reviews International 25, 1 (2008), 1–11.
[48]
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei. 2009. ImageNet: A large-scale hierarchical image database. In Proceedings of the 2009 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, New York, NY, USA, 248–255. DOI:
[49]
Sergio Diaz-Almanza, Iván Adrian García-Galicia, Ana Luisa Rentería-Monterrubio, and Raúl Alberto Reyes-Villagrana. 2021. Analysis of the simultaneous measurement of acoustic phase velocity and stress-strain relationship in beef: An approach to Young’s modulus. Applied Acoustics 182 (2021), 108237.
[50]
Nadia El Alami El Hassani, Khalid Tahri, Eduard Llobet, Benachir Bouchikhi, Abdelhamid Errachid, Nadia Zine, and Nezha El Bari. 2018. Emerging approach for analytical characterization and geographical classification of Moroccan and French honeys by means of a voltammetric electronic tongue. Food Chemistry 243 (2018), 36–42.
[51]
Ole-Christian Galbo Engstrøm, Erik Schou Dreier, Birthe Møller Jespersen, and Kim Steenstrup Pedersen. 2023. Improving deep learning on hyperspectral images of grain by incorporating domain knowledge from chemometrics. In Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops. 485–494.
[52]
Ole-Christian Galbo Engstrøm, Erik Schou Dreier, and Kim Steenstrup Pedersen. 2021. Predicting protein content in grain using hyperspectral deep learning. In Proceedings of the IEEE/CVF International Conference on Computer Vision Workshops. 1372–1380.
[53]
Cong Fang, Hua-Yao Li, Long Li, Hu-Yin Su, Jiang Tang, Xiang Bai, and Huan Liu. 2022. Smart electronic nose enabled by an all-feature olfactory algorithm. Advanced Intelligent Systems 4, 7 (2022), 2200074.
[54]
Lola Fariñas, Marina Contreras, Virginia Sanchez-Jimenez, Jose Benedito, and Jose V. Garcia-Perez. 2021. Use of air-coupled ultrasound for the non-invasive characterization of the textural properties of pork burger patties. Journal of Food Engineering 297 (2021), 110481.
[55]
Lola Fariñas, Eduardo A. Sanchez-Torres, Virginia Sanchez-Jimenez, Ricardo Diaz, Jose Benedito, and Jose V. Garcia-Perez. 2021. Assessment of avocado textural changes during ripening by using contactless air-coupled ultrasound. Journal of Food Engineering 289 (2021), 110266.
[56]
Jessica Farrugia, Sholeem Griffin, Vasilis P. Valdramidis, Kenneth Camilleri, and Owen Falzon. 2021. Principal component analysis of hyperspectral data for early detection of mould in cheeselets. Current Research in Food Science 4 (2021), 18–27.
[57]
Lei Feng, Min Zhang, Bhesh Bhandari, and Zhimei Guo. 2018. A novel method using MOS electronic nose and ELM for predicting postharvest quality of cherry tomato fruit treated with high pressure argon. Computers and Electronics in Agriculture 154 (2018), 411–419.
[58]
Xin Feng, Huihua Zhang, and Peiqiang Yu. 2021. X-ray fluorescence application in food, feed, and agricultural science: A critical review. Critical Reviews in Food Science and Nutrition 61, 14 (2021), 2340–2350.
[59]
Patrizia Firmani, Giuseppe La Piscopia, Remo Bucci, Federico Marini, and Alessandra Biancolillo. 2020. Authentication of PGI gragnano pasta by near infrared (NIR) spectroscopy and chemometrics. Microchemical Journal 152 (2020), 104339.
[60]
Mahmoud Soltani Firouz, Ali Farahmandi, and Soleiman Hosseinpour. 2021. Early detection of freeze damage in navel orange fruit using nondestructive low intensity ultrasound coupled with machine learning. Food Analytical Methods 14, 6 (2021), 1140–1149. DOI:
[61]
Marco Franzoi, Matteo Ghetti, Lorenzo Di Monte, and Massimo De Marchi. 2021. Investigation of weight loss in mozzarella cheese using NIR predicted chemical composition and multivariate analysis. Journal of Food Composition and Analysis 102 (2021), 104002. DOI:
[62]
Marco Furini, Silvia Mirri, Manuela Montangero, and Catia Prandi. 2020. Privacy perception when using smartphone applications. Mob. Networks Appl. 25, 3 (2020), 1055–1061.
[63]
Gianmarco Gabrieli, Michal Muszynski, Edouard Thomas, David Labbe, and Patrick W. Ruch. 2022. Accelerated estimation of coffee sensory profiles using an AI-assisted electronic tongue. Innovative Food Science and Emerging Technologies 82 (2022), 103205. DOI:
[64]
Juan C. Rodriguez Gamboa, Eva Susana Albarracin E., Adenilton J. da Silva, Luciana L. de Andrade Lima, and Tiago A. E. Ferreira. 2019. Wine quality rapid detection using a compact electronic nose system: Application focused on spoilage thresholds by acetic acid. Lwt 108 (2019), 377–384.
[65]
Eva Ganglbauer, Geraldine Fitzpatrick, and Florian Güldenpfennig. 2015. Why and what did we throw out? Probing on reflection through the food waste diary. In Proceedings of the 33rd Annual ACM Conference on Human Factors in Computing Systems (Seoul, Republic of Korea). Association for Computing Machinery, New York, NY, USA, 1105–1114. DOI:
[66]
S. Ghosh, Bipan Tudu, Nabarun Bhattacharyya, and Rajib Bandyopadhyay. 2019. A recurrent elman network in conjunction with an electronic nose for fast prediction of optimum fermentation time of black tea. Neural Computing and Applications 31, 2 (2019), 1165–1171.
[67]
Valentina Giovenzana, Raffaele Civelli, Roberto Beghi, Roberto Oberti, and Riccardo Guidetti. 2015. Testing of a simplified LED based vis/NIR system for rapid ripeness evaluation of white grape (vitis vinifera L.) for franciacorta wine. Talanta 144 (2015), 584–591.
[68]
Adriano A. Gomes, Liudmyla Khvalbota, Andrea Machyňáková, Katarína Furdíková, Claudia A. Zini, and Ivan Špánik. 2021. Slovak tokaj wines classification with respect to geographical origin by means of one class approaches. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 257 (2021), 119770.
[69]
Thays Raphaela Gonçalves, Larissa Naida Rosa, Rhayanna Priscila Gonçalves, Alex Sanches Torquato, Paulo Henrique Março, Sandra T Marques Gomes, Makoto Matsushita, and Patrícia Valderrama. 2018. Monitoring the oxidative stability of monovarietal extra virgin olive oils by UV–Vis spectroscopy and MCR–ALS. Food Analytical Methods 11, 7 (2018), 1936–1943.
[70]
José Raymundo González-Araiza, María Coral Ortiz-Sánchez, Francisco Miguel Vargas-Luna, and José Manuel Cabrera-Sixto. 2017. Application of electrical bio-impedance for the evaluation of strawberry ripeness. International Journal of Food Properties 20, 5 (2017), 1044–1050.
[71]
M. Inmaculada González-Martín, Ana M. Vivar-Quintana, Isabel Revilla, and Javier Salvador-Esteban. 2020. The determination of fatty acids in cheeses of variable composition (cow, ewe’s, and goat) by means of near infrared spectroscopy. Microchemical Journal 156 (2020), 104854.
[72]
Alberto González-Mohino, Antonio Jiménez, Montaña Rufo, Jesús M. Paniagua, Teresa Antequera, and Trinidad Perez-Palacios. 2022. Ultrasound parameters used to characterize Iberian fresh pork loins of different feeding systems. Journal of Food Engineering 314 (2022), 110795.
[73]
A.A. Gowen, C. O’Sullivan, and C.P. O’Donnell. 2012. Terahertz time domain spectroscopy and imaging: Emerging techniques for food process monitoring and quality control. Trends in Food Science and Technology 25, 1 (2012), 40–46.
[74]
Aoife A Gowen, Colm P O’Donnell, Patrick J Cullen, Gérard Downey, and Jesus M Frias. 2007. Hyperspectral imaging–an emerging process analytical tool for food quality and safety control. Trends in Food Science and Technology 18, 12 (2007), 590–598.
[75]
Marco Grossi and Bruno Riccò. 2017. Electrical impedance spectroscopy (EIS) for biological analysis and food characterization: A review. Journal of Sensors and Sensor Systems 6, 2 (2017), 303–325.
[76]
Zhiming Guo, Mingming Wang, Alberta Osei Barimah, Quansheng Chen, Huanhuan Li, Jiyong Shi, Hesham R El-Seedi, and Xiaobo Zou. 2021. Label-free surface enhanced Raman scattering spectroscopy for discrimination and detection of dominant apple spoilage fungus. International Journal of Food Microbiology 338 (2021), 108990.
[77]
Ussama Harzalli, Nuno Rodrigues, Ana CA Veloso, Luís G. Dias, José A. Pereira, Souheib Oueslati, and António M. Peres. 2018. A taste sensor device for unmasking admixing of rancid or winey-vinegary olive oil to extra virgin olive oil. Computers and Electronics in Agriculture 144 (2018), 222–231.
[78]
Hamid Hassannejad, Guido Matrella, Paolo Ciampolini, Ilaria De Munari, Monica Mordonini, and Stefano Cagnoni. 2016. Food image recognition using very deep convolutional networks. In Proceedings of the 2nd International Workshop on Multimedia Assisted Dietary Management (Amsterdam, The Netherlands). Association for Computing Machinery, New York, NY, USA, 41–49. DOI:
[79]
Ariana Raluca Hategan, Maria David, Camelia Berghian-Grosan, and Dana Alina Magdas. 2023. Geographical and varietal origin differentiation of alcoholic beverages through the association between FT-Raman spectroscopy and advanced data processing strategies. Food Chemistry: X 20 (2023), 100902. DOI:
[80]
Hongsheng He, Fanyu Kong, and Jindong Tan. 2015. DietCam: Multiview food recognition using a multikernel SVM. IEEE Journal of Biomedical and Health Informatics 20, 3 (2015), 848–855.
[81]
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. 2016. Deep residual learning for image recognition. In Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition. IEEE, New York, NY, USA, 770–778. DOI:
[82]
Elahesadat Hosseini, Jahan B Ghasemi, Bahram Daraei, Gholamhassan Asadi, and Nooshin Adib. 2021. Near-infrared spectroscopy and machine learning-based classification and calibration methods in detection and measurement of anionic surfactant in milk. Journal of Food Composition and Analysis 104 (2021), 104170.
[83]
Jun Hu, Zhen Xu, Maopeng Li, Yong He, and Yande Liu. 2021. Discriminant analysis and quantitative study of antibiotics in infant milk powder based on hyperspectral detection. Vibrational Spectroscopy 114 (2021), 103244.
[84]
Jun Hu, Zhen Xu, Maopeng Li, Yong He, Xudong Sun, and Yande Liu. 2021. Detection of foreign-body in milk powder processing based on terahertz imaging and spectrum. Journal of Infrared, Millimeter, and Terahertz Waves 42, 8 (2021), 878–892.
[85]
Xiao-Zhen Hu, Si-Qi Liu, Xiao-Hong Li, Chuan-Xian Wang, Xin-Lu Ni, Xia Liu, Yang Wang, Yuan Liu, and Chang-Hua Xu. 2019. Geographical origin traceability of cabernet sauvignon wines based on infrared fingerprint technology combined with chemometrics. Scientific Reports 9, 1 (2019), 1–9.
[86]
Godwin Idoje, Tasos Dagiuklas, and Muddesar Iqbal. 2021. Survey for smart farming technologies: Challenges and issues. Computers and Electrical Engineering 92 (2021), 107104. DOI:
[87]
Kerem Ilaslan, Ismail Hakki Boyaci, and Ali Topcu. 2015. Rapid analysis of glucose, fructose and sucrose contents of commercial soft drinks using raman spectroscopy. Food Control 48 (2015), 56–61.
[88]
Teppei Imaizumi, Fumihiko Tanaka, Daisuke Hamanaka, Yuma Sato, and Toshitaka Uchino. 2015. Effects of hot water treatment on electrical properties, cell membrane structure and texture of potato tubers. Journal of Food Engineering 162 (2015), 56–62.
[89]
Sawsan Jaafreh, Rene Breuch, Klaus Günther, Judith Kreyenschmidt, and Peter Kaul. 2018. Rapid poultry spoilage evaluation using portable fiber-optic raman spectrometer. Food Analytical Methods 11, 8 (2018), 2320–2328.
[90]
Meetha Nesam James, Nimesha Ranasinghe, Anthony Tang, and Lora Oehlberg. 2022. Flavor-videos: Enhancing the flavor perception of food while eating with videos. In Proceedings of the 2022 ACM International Conference on Interactive Media Experiences (Aveiro, JB, Portugal). Association for Computing Machinery, New York, NY, USA, 33–46. DOI:
[91]
Amit, Rahul Jamwal, Shivani Kumari, Amit S. Dhaulaniya, Biji Balan, and Dileep Kumar Singh. 2020. Application of ATR-FTIR spectroscopy along with regression modelling for the detection of adulteration of virgin coconut oil with paraffin oil. Lwt 118 (2020), 108754.
[92]
Peter Uhd Jepsen, Uffe Møller, and Hannes Merbold. 2007. Investigation of aqueous alcohol and sugar solutions with reflection terahertz time-domain spectroscopy. Optics Express 15, 22 (2007), 14717–14737.
[93]
Hongyao Jiang, Min Zhang, Bhesh Bhandari, and Benu Adhikari. 2018. Application of electronic tongue for fresh foods quality evaluation: A review. Food Reviews International 34, 8 (2018), 746–769.
[94]
Antonio Jiménez, Alberto González-Mohino, Montaña Rufo, Jesús M Paniagua, Teresa Antequera, and Trinidad Perez-Palacios. 2022. Dry-cured loin characterization by ultrasound physicochemical and sensory parameters. European Food Research and Technology 248, 10 (2022), 2603–2613.
[95]
Haoquan Jin, Hao Li, Zhikang Yin, Yingying Zhu, Aimin Lu, Di Zhao, and Chunbao Li. 2021. Application of raman spectroscopy in the rapid detection of waste cooking oil. Food Chemistry 362 (2021), 130191.
[96]
Huaizhou Jin, Qipeng Lu, Xingdan Chen, Haiquan Ding, Hongzhi Gao, and Shangzhong Jin. 2016. The use of raman spectroscopy in food processes: A review. Applied Spectroscopy Reviews 51, 1 (2016), 12–22.
[97]
Olusola Samuel Jolayemi, Figen Tokatli, and Banu Ozen. 2021. UV–Vis spectroscopy for the estimation of variety and chemical parameters of olive oils. Journal of Food Measurement and Characterization 15, 5 (2021), 4138--4149.
[98]
Dhanus Raj Kanaga Raj, Marcus Vinicius da Silva Ferreira, Maria Luisa Braunger, Antonio Riul, Jibu Thomas, and Douglas Fernandes Barbin. 2023. Exploration of an impedimetric electronic tongue and chemometrics for characterization of black tea from different origins. Journal of Food Composition and Analysis 123 (2023), 105535. DOI:
[99]
Nazife Nur Yazgan Karacaglar, Tugba Bulat, Ismail Hakki Boyaci, and Ali Topcu. 2019. Raman spectroscopy coupled with chemometric methods for the discrimination of foreign fats and oils in cream and yogurt. Journal of Food and Drug Analysis 27, 1 (2019), 101–110.
[100]
Bhuwan Kashyap, Charles K. Sestok, Anand G. Dabak, Srinath Ramaswamy, and Ratnesh Kumar. 2019. Ultra-precision liquid level sensing using impedance spectroscopy and data analytics. IEEE Sensors Journal 19, 20 (2019), 9468–9478.
[101]
Yoshiyuki Kawano and Keiji Yanai. 2014. Automatic expansion of a food image dataset leveraging existing categories with domain adaptation. In Proceedings of the European Conference on Computer Vision. Springer, Springer, New York, NY, USA, 3–17. DOI:
[102]
Yoshiyuki Kawano and Keiji Yanai. 2015. Foodcam: A real-time food recognition system on a smartphone. Multimedia Tools and Applications 74, 14 (2015), 5263–5287.
[103]
H.M. Hussain Khan, Ultan McCarthy, Karen Esmonde-White, Imelda Casey, and Norah O’Shea. 2023. Potential of raman spectroscopy for in-line measurement of raw milk composition. Food Control 152 (2023), 109862. DOI:
[104]
Rasool Khodabakhshian and Mohammad Hossein Abbaspour-Fard. 2020. Pattern recognition-based Raman spectroscopy for non-destructive detection of pomegranates during maturity. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 231 (2020), 118127.
[105]
Rohit Ashok Khot and Florian Mueller. 2019. Human-food interaction. Foundations and Trends® in Human–Computer Interaction 12, 4 (2019), 238–415.
[106]
Kombo Othman Kombo, Shidiq Nur Hidayat, Kuwat Triyana, Trisna Julian, and Ahmad Kusmaatmaja. 2019. Electronic nose coupled with support vector machines for rapid discrimination of black tea according to the quality levels. In Proceedings of the 2019 International Conference on Electrical Engineering and Informatics. IEEE, IEEE, New York, NY, USA, 306–309. DOI:
[107]
Fanyu Kong and Jindong Tan. 2012. DietCam: Automatic dietary assessment with mobile camera phones. Pervasive and Mobile Computing 8, 1 (2012), 147–163.
[108]
Fotios S. Konstantakopoulos, Eleni I. Georga, and Dimitrios I. Fotiadis. 2023. An automated image-based dietary assessment system for mediterranean foods. IEEE Open Journal of Engineering in Medicine and Biology 4 (2023), 45–54. DOI:
[109]
Paul Krebs and Dustin T. Duncan. 2015. Health app use among US mobile phone owners: A national survey. JMIR mHealth uHealth 3, 4 (2015), e101. DOI:
[110]
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E. Hinton. 2017. ImageNet classification with deep convolutional neural networks. Communications of the ACM 60, 6 (2017), 84–90.
[111]
Christopher T. Kucha, Li Liu, Michael Ngadi, and Claude Gariépy. 2022. Prediction and visualization of fat content in polythene-packed meat using near-infrared hyperspectral imaging and chemometrics. Journal of Food Composition and Analysis 111 (2022), 104633. DOI:
[112]
Christopher T. Kucha, Li Liu, Michael Ngadi, and Claude Gariépy. 2023. Hyperspectral imaging and chemometrics assessment of intramuscular fat in pork longissimus thoracic et lumborum primal cut. Food Control 145 (2023), 109379. DOI:
[113]
Palash K. Kundu and Madhusree Kundu. 2016. Classification of tea samples using SVM as machine learning component of E-tongue. In Proceedings of the 2016 International Conference on Intelligent Control Power and Instrumentation. IEEE, IEEE, New York, NY, USA, 56–60. DOI:
[114]
Chao-Yang Lee, Abida Khanum, and Pinninti Praneeth Kumar. 2023. Multi-food detection using a modified swin-transfomer with recursive feature pyramid network. Multimedia Tools and Applications 83, 19 (2023), 57731--57757.
[115]
Younju Lee and Takashi Watanabe. 2022. Bio-electrochemical impedance spectroscopy and X-ray computed tomography analysis of prefreezing-induced cell-structure changes in sweet potatoes and their impacts on the physical properties after baking. Food Structure 31 (2022), 100255. DOI:
[116]
Jersson X Leon-Medina, Diana Acosta-Opayome, Carlos Alberto Fuenmayor, Carlos Mario Zuluaga-Domínguez, Maribel Anaya, and Diego A Tibaduiza. 2023. Intelligent electronic tongue system for the classification of genuine and false honeys. International Journal of Food Properties 26, 1 (2023), 327–343.
[117]
Pei Li, Jie Geng, Hongcheng Li, and Zhiyou Niu. 2020. Fish meal freshness detection by GBDT based on a portable electronic nose system and HS-SPME–GC–MS. European Food Research and Technology 246, 6 (2020), 1129–1140.
[118]
Yuanpeng Li, Tao Fang, Siqi Zhu, Furong Huang, Zhenqiang Chen, and Yong Wang. 2018. Detection of olive oil adulteration with waste cooking oil via raman spectroscopy combined with iPLS and SiPLS. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 189 (2018), 37–43.
[119]
Buwen Liang, Changhui Wei, Xinxing Li, Ziyi Zhang, and Xiaoyan Huang. 2023. Incorporating bioimpedance technique with ensemble learning algorithm for mutton tenderness detection. Food and Bioprocess Technology 16, 12 (2023), 2761–2771.
[120]
Veranika Lim, Mathias Funk, Matthias Rauterberg, Lucio Marcenaro, and Carlo Regazzoni. 2015. E-COmate: What’s your non-consumption?. In Advances in Computational Intelligence: 13th International Work-Conference on Artificial Neural Networks, IWANN 2015, Palma de Mallorca, Spain, June 10–12, 2015. Proceedings, Part I 13. Springer, 486–499.
[121]
Mengxi Liu, Sizhen Bian, Bo Zhou, Agnes Gruenerbl, and Paul Lukowicz. 2023. Smart cup: An impedance sensing based fluid intake monitoring system for beverages classification and freshness detection. In Adjunct Proceedings of the 2022 ACM International Joint Conference on Pervasive and Ubiquitous Computing and the 2022 ACM International Symposium on Wearable Computers (Cambridge, United Kingdom). Association for Computing Machinery, New York, NY, USA, 78–80. DOI:
[122]
Qiang Liu, Nan Zhao, Dandan Zhou, Ye Sun, Ke Sun, Leiqing Pan, and Kang Tu. 2018. Discrimination and growth tracking of fungi contamination in peaches using electronic nose. Food Chemistry 262 (2018), 226–234.
[123]
Sanqing Liu, Shuxiang Fan, Lin Lin, and Wenqian Huang. 2022. An improved method for predicting soluble solids content in apples by heterogeneous transfer learning and near-infrared spectroscopy. Computers and Electronics in Agriculture 203 (2022), 107455. DOI:
[124]
Wei Liu, Changhong Liu, Junjie Yu, Yan Zhang, Jian Li, Ying Chen, and Lei Zheng. 2018. Discrimination of geographical origin of extra virgin olive oils using terahertz spectroscopy combined with chemometrics. Food Chemistry 251 (2018), 86–92.
[125]
Wei Liu, Pengguang Zhao, Yule Shi, Changhong Liu, and Lei Zheng. 2021. Rapid determination of peroxide value of peanut oils during storage based on terahertz spectroscopy. Food Analytical Methods 14, 6 (2021), 1269–1277.
[126]
Wei Liu, Pengguang Zhao, Chaosheng Wu, Changhong Liu, Jianbo Yang, and Lei Zheng. 2019. Rapid determination of aflatoxin B1 concentration in soybean oil using terahertz spectroscopy with chemometric methods. Food Chemistry 293 (2019), 213–219.
[127]
Bingxu Lu, Feng Tian, Cheng Chen, Wei Wu, Xuecong Tian, Chen Chen, and Xiaoyi Lv. 2023. Identification of chinese red wine origins based on raman spectroscopy and deep learning. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 291 (2023), 122355. DOI:
[128]
Xi Lu, Edison Thomaz, and Daniel A. Epstein. 2022. Understanding people’s perceptions of approaches to semi-automated dietary monitoring. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 6, 3 (2022), 27 pages. DOI:
[129]
Gamal M. ElMasry and Shigeki Nakauchi. 2016. Image analysis operations applied to hyperspectral images for non-invasive sensing of food quality – A comprehensive review. Biosystems Engineering 142 (2016), 53–82. DOI:
[130]
Dana Alina Magdas, Bogdan Ionut Cozar, Ioana Feher, Francois Guyon, Adriana Dehelean, and Simona Cinta Pinzaru. 2019. Testing the limits of FT-Raman spectroscopy for wine authentication: Cultivar, geographical origin, vintage and terroir effect influence. Scientific Reports 9, 1 (2019), 1–8.
[131]
Alberto Mannu, Matteo Poddighe, Sebastiano Garroni, and Luca Malfatti. 2022. Application of IR and UV–VIS spectroscopies and multivariate analysis for the classification of waste vegetable oils. Resources, Conservation and Recycling 178 (2022), 106088. DOI:
[132]
Niki Martinel, Gian Luca Foresti, and Christian Micheloni. 2018. Wide-slice residual networks for food recognition. In Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision. IEEE, New York, NY, USA, 567–576. DOI:
[133]
Angélica Rocha Martins, Márcio Talhavini, Maurício Leite Vieira, Jorge Jardim Zacca, and Jez Willian Batista Braga. 2017. Discrimination of whisky brands and counterfeit identification by UV–Vis spectroscopy and multivariate data analysis. Food Chemistry 229 (2017), 142–151.
[134]
Yuji Matsuda, Hajime Hoashi, and Keiji Yanai. 2012. Recognition of multiple-food images by detecting candidate regions. In Proceedings of the 2012 IEEE International Conference on Multimedia and Expo. IEEE, New York, NY, USA, 25–30. DOI:
[135]
Derek McColl and Goldie Nejat. 2013. Meal-time with a socially assistive robot and older adults at a long-term care facility. J. Hum.-Robot Interact. 2, 1 (2013), 152–171. DOI:
[136]
Al-Selwi Metwalli, Wei Shen, and Chase Q Wu. 2020. Food image recognition based on densely connected convolutional neural networks. In Proceedings of the 2020 International Conference on Artificial Intelligence in Information and Communication. IEEE, New York, NY, USA, 027–032. DOI:
[137]
Karla Danielle Tavares Melo Milanez, Thiago César Araújo Nóbrega, Danielle Silva Nascimento, Matías Insausti, Beatriz Susana Fernández Band, and Márcio José Coelho Pontes. 2017. Multivariate modeling for detecting adulteration of extra virgin olive oil with soybean oil using fluorescence and UV–Vis spectroscopies: A preliminary approach. LWT-Food Science and Technology 85 (2017), 9–15.
[138]
Jelena Milinovic, Raquel Garcia, Ana Elisa Rato, and Maria Joao Cabrita. 2019. Rapid assessment of monovarietal portuguese extra virgin olive oil’s (EVOO’s) fatty acids by fourier-transform near-infrared spectroscopy (FT-NIRS). European Journal of Lipid Science and Technology 121, 3 (2019), 1800392.
[139]
Weiqing Min, Linhu Liu, Zhiling Wang, Zhengdong Luo, Xiaoming Wei, Xiaolin Wei, and Shuqiang Jiang. 2020. ISIA food-500: A dataset for large-scale food recognition via stacked global-local attention network. In Proceedings of the 28th ACM International Conference on Multimedia (Seattle, WA, USA). Association for Computing Machinery, New York, NY, USA, 393–401. DOI:
[140]
Weiqing Min, Zhiling Wang, Yuxin Liu, Mengjiang Luo, Liping Kang, Xiaoming Wei, Xiaolin Wei, and Shuqiang Jiang. 2023. Large scale visual food recognition. IEEE Transactions on Pattern Analysis and Machine Intelligence 45, 8 (2023), 9932–9949. DOI:
[141]
Taiz Alana Minetto, Beatriz Denardi França, Gabriel da Silva Dariz, Emiliano Amarante Veiga, Alessandro Cazonatto Galvão, and Weber da Silva Robazza. 2022. Identifying adulteration of raw bovine milk with urea through electrochemical impedance spectroscopy coupled with chemometric techniques. Food Chemistry 385 (2022), 132678. DOI:
[142]
Toktam Mohammadi Moghaddam, Seyed Razavi, and Masoud Taghizadeh. 2013. Applications of hyperspectral imaging in grains and nuts quality and safety assessment: A review. Journal of Food Measurement and Characterization 7, 3 (2013), 129–140.
[143]
Olga Monago-Maraña, Nils Kristian Afseth, Svein Halvor Knutsen, Sileshi Gizachew Wubshet, and Jens Petter Wold. 2021. Quantification of soluble solids and individual sugars in apples by raman spectroscopy: A feasibility study. Postharvest Biology and Technology 180 (2021), 111620.
[144]
DS Morrison and UR Abeyratne. 2014. Ultrasonic technique for non-destructive quality evaluation of oranges. Journal of Food Engineering 141 (2014), 107–112.
[145]
Florian ‘Floyd’ Mueller, Marianna Obrist, Ferran Altarriba Bertran, Neharika Makam, Soh Kim, Christopher Dawes, Patrizia Marti, Maurizio Mancini, Eleonora Ceccaldi, Nandini Pasumarthy, Sahej Claire, Kyung seo Jung, Jialin Deng, Jürgen Steimle, Nadejda Krasteva, Matti Schwalk, Harald Reiterer, Hongyue Wang, and Yan Wang. 2024. Grand challenges in human-food interaction. International Journal of Human-Computer Studies 183 (2024), 103197. DOI:
[146]
Sona Mundody and Ram Mohana Reddy Guddeti. 2024. A framework for low cost, ubiquitous and interactive smart refrigerator. Multimedia Tools and Applications 83, 5 (2024), 13337–13368.
[147]
Austin Myers, Nick Johnston, Vivek Rathod, Anoop Korattikara, Alex Gorban, Nathan Silberman, Sergio Guadarrama, George Papandreou, Jonathan Huang, and Kevin Murphy. 2015. Im2Calories: Towards an automated mobile vision food diary. In Proceedings of the 2015 IEEE International Conference on Computer Vision. IEEE, New York, NY, USA, 1233–1241. DOI:
[148]
Judith Müller-Maatsch, Martin Alewijn, Michiel Wijtten, and Yannick Weesepoel. 2021. Detecting fraudulent additions in skimmed milk powder using a portable, hyphenated, optical multi-sensor approach in combination with one-class classification. Food Control 121 (2021), 107744. DOI:
[149]
Takuji Narumi. 2016. Multi-sensorial virtual reality and augmented human food interaction. In Proceedings of the 1st Workshop on Multi-Sensorial Approaches to Human-Food Interaction (Tokyo, Japan). Association for Computing Machinery, New York, NY, USA, Article 1, 6 pages. DOI:
[150]
Fran Nekvapil, Ioana Brezestean, Daniel Barchewitz, Branko Glamuzina, Vasile Chiş, and Simona Cintă Pinzaru. 2018. Citrus fruits freshness assessment using raman spectroscopy. Food Chemistry 242 (2018), 560–567.
[151]
Karen M. Nunes, Marcus Vinicius O. Andrade, Mariana R. Almeida, Cristiano Fantini, and Marcelo M. Sena. 2019. Raman spectroscopy and discriminant analysis applied to the detection of frauds in bovine meat by the addition of salts and carrageenan. Microchemical Journal 147 (2019), 582–589.
[152]
Homin Park, Homanga Bharadhwaj, and Brian Y. Lim. 2019. Hierarchical multi-task learning for healthy drink classification. In Proceedings of the 2019 International Joint Conference on Neural Networks. IEEE, New York, NY, USA, 1–8. DOI:
[153]
Ricardo NMJ Páscoa, Patrícia ALS Porto, António L. Cerdeira, and João A. Lopes. 2020. The application of near infrared spectroscopy to wine analysis: An innovative approach using lyophilization to remove water bands interference. Talanta 214 (2020), 120852.
[154]
Celio Pasquini. 2018. Near infrared spectroscopy: A mature analytical technique with new perspectives–A review. Analytica Chimica Acta 1026 (2018), 8–36.
[155]
Himanshu K. Patel and Mona J. Kunpara. 2011. Electronic nose sensor response and qualitative review of e-nose sensors. In Proceedings of the 2011 Nirma University International Conference on Engineering. IEEE, New York, NY, USA, 1–6. DOI:
[156]
Marta Podrażka, Ewa Bączyńska, Magdalena Kundys, Paulina S Jeleń, and Emilia Witkowska Nery. 2018. Electronic tongue—A tool for all tastes? Biosensors 8, 1 (2018), 3.
[157]
Parisa Pouladzadeh, Pallavi Kuhad, Sri Vijay Bharat Peddi, Abdulsalam Yassine, and Shervin Shirmohammadi. 2016. Food calorie measurement using deep learning neural network. In Proceedings of the 2016 IEEE International Instrumentation and Measurement Technology Conference Proceedings. IEEE, New York, NY, USA, 1–6. DOI:
[158]
Parisa Pouladzadeh, Shervin Shirmohammadi, and Rana Al-Maghrabi. 2014. Measuring calorie and nutrition from food image. IEEE Transactions on Instrumentation and Measurement 63, 8 (2014), 1947–1956. DOI:
[159]
Aoife C. Power, John Jones, Caoimhe NiNeil, Sive Geoghegan, Susan Warren, Sinead Currivan, and Daniel Cozzolino. 2021. Whats in this drink? Classification and adulterant detection in irish whiskey samples using near infrared spectroscopy combined with chemometrics. Journal of the Science of Food and Agriculture 101, 12 (2021), 5256–5263.
[160]
John Prescott. 2015. Multisensory processes in flavour perception and their influence on food choice. Current Opinion in Food Science 3 (2015), 47–52. DOI: Sensory Sciences and Consumer Perception \(\bullet\) Food Physics and Material Science.
[161]
Hasitha Priyashantha, Annika Höjer, Karin Hallin Saedén, Åse Lundh, Monika Johansson, Gun Bernes, Paul Geladi, and Mårten Hetta. 2021. Determining the end-date of long-ripening cheese maturation using NIR hyperspectral image modelling: A feasibility study. Food Control 130 (2021), 108316. DOI:
[162]
Nimesha Ranasinghe, Adrian Cheok, Ryohei Nakatsu, and Ellen Yi-Luen Do. 2013. Simulating the sensation of taste for immersive experiences. In Proceedings of the 2013 ACM International Workshop on Immersive Media Experiences (Barcelona, Spain). Association for Computing Machinery, New York, NY, USA, 29–34. DOI:
[163]
Nimesha Ranasinghe, Pravar Jain, Shienny Karwita, and Ellen Yi-Luen Do. 2017. Virtual lemonade: Let’s teleport your lemonade!. In Proceedings of the 11th International Conference on Tangible, Embedded, and Embodied Interaction (Yokohama, Japan). Association for Computing Machinery, New York, NY, USA, 183–190. DOI:
[164]
Nimesha Ranasinghe, Thi Ngoc Tram Nguyen, Yan Liangkun, Lien-Ya Lin, David Tolley, and Ellen Yi-Luen Do. 2017. Vocktail: A virtual cocktail for pairing digital taste, smell, and color sensations. In Proceedings of the 25th ACM International Conference on Multimedia (Mountain View, California, USA). Association for Computing Machinery, New York, NY, USA, 1139–1147. DOI:
[165]
S. Khushbu, M. Yashini, Ashish Rawson, and Sunil C. K. 2021. Recent advances in terahertz time-domain spectroscopy and imaging techniques for automation in agriculture and food sector. Food Analytical Methods 15, 2 (2021), 498–526.
[166]
Guangxin Ren, Tiehan Li, Yuming Wei, Jingming Ning, and Zhengzhu Zhang. 2021. Estimation of congou black tea quality by an electronic tongue technology combined with multivariate analysis. Microchemical Journal 163 (2021), 105899.
[167]
Rocío Ríos-Reina, Silvina Mariela Azcarate, J. Camiña, and Raquel M. Callejón. 2020. Assessment of UV–visible spectroscopy as a useful tool for determining grape-must caramel in high-quality wine and balsamic vinegars. Food Chemistry 323 (2020), 126792.
[168]
Rocío Ríos-Reina, Silvana Mariela Azcarate, J. Camiña, Raquel M. Callejón, and José Manuel Amigo. 2019. Application of hierarchical classification models and reliability estimation by bootstrapping, for authentication and discrimination of wine vinegars by UV–vis spectroscopy. Chemometrics and Intelligent Laboratory Systems 191 (2019), 42–53.
[169]
Chima Robert, Sara J. Fraser-Miller, William T. Jessep, Wendy E. Bain, Talia M. Hicks, James F. Ward, Cameron R. Craigie, Mark Loeffen, and Keith C. Gordon. 2021. Rapid discrimination of intact beef, venison and lamb meat using raman spectroscopy. Food Chemistry 343 (2021), 128441.
[170]
Edmund T. Rolls. 2015. Taste, olfactory, and food reward value processing in the brain. Progress in Neurobiology 127–128 (2015), 64–90. DOI:
[171]
Patrick W. Ruch, Rui Hu, Luca Capua, Yuksel Temiz, Stephan Paredes, Antonio Lopez, Jorge Barroso, Aaron Cox, Eiji Nakamura, and Keiji Matsumoto. 2019. A portable potentiometric electronic tongue leveraging smartphone and cloud platforms. In Proceedings of the 2019 IEEE International Symposium on Olfaction and Electronic Nose. IEEE, New York, NY, USA, 1–3. DOI:
[172]
Jana Sádecká and Michaela Jakubíková. 2022. Classification of tokaj wines by ultraviolet–visible spectroscopy. Food Analytical Methods 15, 1 (2022), 56–66.
[173]
Michael Siegrist, Chin-Yih Ung, Markus Zank, Max Marinello, Andreas Kunz, Christina Hartmann, and Marino Menozzi. 2019. Consumers’ food selection behaviors in three-dimensional (3D) virtual reality. Food Research International 117 (2019), 50–59. DOI: Special issue on “Virtual reality and food: Applications in sensory and consumer science”.
[174]
Karen Simonyan and Andrew Zisserman. 2015. Very deep convolutional networks for large-scale image recognition. In 3rd International Conference on Learning Representations (ICLR'15), San Diego, CA, USA, May 7-9, 2015, Conference Track Proceedings. http://arxiv.org/abs/1409.1556
[175]
Dorian Sinclear, Linda Birch Flensborg, Ask Lindblad Fogsgaard, and Markus Lochtefeld. 2022. Face-the-waste - learning about food waste through a serious game. In Proceedings of the 20th International Conference on Mobile and Ubiquitous Multimedia (Leuven, Belgium). Association for Computing Machinery, New York, NY, USA, 67–72. DOI:
[176]
Ryan M. Smith and Mark A. Arnold. 2011. Terahertz time-domain spectroscopy of solid samples: Principles, applications, and challenges. Applied Spectroscopy Reviews 46, 8 (2011), 636–679.
[177]
Juliana Coatrini Soares, Andrey Coatrini Soares, Mario Popolin-Neto, Fernando Vieira Paulovich, Osvaldo N. Oliveira, and Luiz Henrique Caparelli Mattoso. 2022. Detection of staphylococcus aureus in milk samples using impedance spectroscopy and data processing with information visualization techniques and multidimensional calibration space. Sensors and Actuators Reports 4 (2022), 100083. DOI:
[178]
Charles Spence, Carmel A. Levitan, Maya U. Shankar, and Massimiliano Zampini. 2010. Does food color influence taste and flavor perception in humans? Chemosensory Perception 3 (2010), 68–84.
[179]
Charles Spence, Maurizio Mancini, and Gijs Huisman. 2019. Digital commensality: Eating and drinking in the company of technology. Frontiers in Psychology 10 (2019), 2252.
[180]
Jan Steinbrener, Konstantin Posch, and Raimund Leitner. 2019. Hyperspectral fruit and vegetable classification using convolutional neural networks. Computers and Electronics in Agriculture 162 (2019), 364–372.
[181]
Sergio Luiz Stevan, Hugo Valadares Siqueira, Bruno Adriano Menegotto, Lucas Caillot Schroeder, Isabela Leticia Pessenti, and Ricardo Antonio Ayub. 2023. Discrimination analysis of wines made from four species of blueberry through their olfactory signatures using an e-nose. LWT 187 (2023), 115320. DOI:
[182]
Katarzyna Sujka and Piotr Koczoń. 2018. The application of FT-IR spectroscopy in discrimination of differently originated and aged whisky. European Food Research and Technology 244, 11 (2018), 2019–2025.
[183]
Jian Sun, Rongbiao Zhang, Yecheng Zhang, Guoxiao Li, and Qiufang Liang. 2017. Estimating freshness of carp based on EIS morphological characteristic. Journal of Food Engineering 193 (2017), 58–67.
[184]
Jian Sun, Rongbiao Zhang, Yecheng Zhang, Qiufang Liang, Fei Zhang, Peifeng Xu, and Guoxiao Li. 2020. Evaluation of fish freshness using impedance spectroscopy based on the characteristic parameter of orthogonal direction difference. Journal of the Science of Food and Agriculture 100, 11 (2020), 4124–4131.
[185]
Xudong Sun, Dongdong Cui, Yun Shen, Wenping Li, and Jiahua Wang. 2022. Non-destructive detection for foreign bodies of tea stalks in finished tea products using terahertz spectroscopy and imaging. Infrared Physics and Technology 121 (2022), 104018. DOI:
[186]
Xudong Sun, Chao Xu, Jiajun Li, Dongfu Xie, Zhiyuan Gong, Wei Fu, and Xinpeng Wang. 2023. Nondestructive detection of insect foreign bodies in finished tea products using THz-TDS combination of baseline correction and variable selection algorithms. Journal of Food Process Engineering 46, 2 (2023), e14224.
[187]
D. Suzuki, S. Oda, and Y. Kawano. 2016. A flexible and wearable terahertz scanner. Nature Photonics 10, 12 (2016), 809–813.
[188]
Mon Myat Swe, Tanthip Eamsa-Ard, Toemsak Srikhirin, and Teerakiat Kerdcharoen. 2019. Monitoring the freshness level of beef using nanocomposite gas sensors in electronic nose. In Proceedings of the 2019 IEEE International Conference on Consumer Electronics - Asia.IEEE, New York, NY, USA, 100–103. DOI:
[189]
Yusuke Tahara and Kiyoshi Toko. 2013. Electronic tongues–a review. IEEE Sensors Journal 13, 8 (2013), 3001–3011.
[190]
Juzhong Tan and Jie Xu. 2020. Applications of electronic nose (e-nose) and electronic tongue (e-tongue) in food quality-related properties determination: A review. Artificial Intelligence in Agriculture 4 (2020), 104–115. DOI:
[191]
Imam Tazi, Kuwat Triyana, Dwi Siswanta, Ana CA Veloso, António M. Peres, and Luís G. Dias. 2018. Dairy products discrimination according to the milk type using an electrochemical multisensor device coupled with chemometric tools. Journal of Food Measurement and Characterization 12, 4 (2018), 2385–2393.
[192]
Quin Thames, Arjun Karpur, Wade Norris, Fangting Xia, Liviu Panait, Tobias Weyand, and Jack Sim. 2021. Nutrition5k: Towards automatic nutritional understanding of generic food. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 8903–8911.
[193]
Yijun Tian, Chuxu Zhang, Ronald Metoyer, and Nitesh V. Chawla. 2021. Recipe representation learning with networks. In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (Virtual Event, Queensland, Australia). Association for Computing Machinery, New York, NY, USA, 1824–1833. DOI:
[194]
Mojtaba Tohidi, Mahdi Ghasemi-Varnamkhasti, Vahid Ghafarinia, Seyed Saeid Mohtasebi, and Mojtaba Bonyadian. 2018. Identification of trace amounts of detergent powder in raw milk using a customized low-cost artificial olfactory system: A novel method. Measurement 124 (2018), 120–129.
[195]
Tamas Toth, Paul J. Mwau, George Bazar, Gabriella Andrassy-Baka, Hajnalka Hingyi, Eva Csavajda, and Laszlo Varga. 2019. Effect of feed supplementation based on extruded linseed meal and fish oil on composition and sensory properties of raw milk and ultra-high temperature treated milk. International Dairy Journal 99 (2019), 104552.
[196]
José Varela-Aldás, Esteban M. Fuentes, Jorge Buele, Raúl Grau Meló, José Manuel Barat, and Miguel Alcañiz. 2020. Support vector machine as tool for classifying coffee beverages. In Proceedings of the International Conference on Information Technology and Systems. Springer, New York, NY, USA, 275–284. DOI:
[197]
Haydar Vasighi-Shojae, Mohammad Gholami-Parashkouhi, Davood Mohammadzamani, and Ahmad Soheili. 2018. Ultrasonic based determination of apple quality as a nondestructive technology. Sensing and Bio-sensing Research 21 (2018), 22–26.
[198]
Henike Guilherme Jordan Voss, Sergio Luiz Stevan, and Ricardo Antonio Ayub. 2019. Peach growth cycle monitoring using an electronic nose. Computers and Electronics in Agriculture 163 (2019), 104858. DOI:
[199]
Chen Wang, Jianyuan Qin, Wendao Xu, Min Chen, Lijuan Xie, and Yibin Ying. 2018. Terahertz imaging applications in agriculture and food engineering: A review. Transactions of the ASABE 61, 2 (2018), 411–424.
[200]
Chen Wang, Ruiyun Zhou, Yuxin Huang, Lijuan Xie, and Yibin Ying. 2019. Terahertz spectroscopic imaging with discriminant analysis for detecting foreign materials among sausages. Food Control 97 (2019), 100–104.
[201]
Jun Wang, Luyi Zhu, Weilin Zhang, and Zhenbo Wei. 2019. Application of the voltammetric electronic tongue based on nanocomposite modified electrodes for identifying rice wines of different geographical origins. Analytica Chimica Acta 1050 (2019), 60–70.
[202]
Lu Wang, Da-Wen Sun, Hongbin Pu, and Jun-Hu Cheng. 2017. Quality analysis, classification, and authentication of liquid foods by near-infrared spectroscopy: A review of recent research developments. Critical Reviews in Food Science and Nutrition 57, 7 (2017), 1524–1538.
[203]
Qi Wang, Saima Hameed, Lijuan Xie, and Yibin Ying. 2020. Non-destructive quality control detection of endogenous contaminations in walnuts using terahertz spectroscopic imaging. Journal of Food Measurement and Characterization 14, 5 (2020), 2453–2460.
[204]
Qian Wang, Lu Li, Wu Ding, Dequan Zhang, Jiayi Wang, Kevin Reed, and Boce Zhang. 2019. Adulterant identification in mutton by electronic nose and gas chromatography-mass spectrometer. Food Control 98 (2019), 431–438.
[205]
Wei Wang, Weiqing Min, Tianhao Li, Xiaoxiao Dong, Haisheng Li, and Shuqiang Jiang. 2022. A review on vision-based analysis for automatic dietary assessment. Trends in Food Science and Technology 122 (2022), 223–237. DOI:
[206]
Yan Wang, Zhuying Li, Robert S. Jarvis, Angelina Russo, Rohit Ashok Khot, and Florian ’Floyd’ Mueller. 2019. Towards understanding the design of playful gustosonic experiences with ice cream. In Proceedings of the Annual Symposium on Computer-Human Interaction in Play (, Barcelona, Spain,). Association for Computing Machinery, New York, NY, USA, 239–251. DOI:
[207]
Zhiling Wang, Weiqing Min, Zhuo Li, Liping Kang, Xiaoming Wei, Xiaolin Wei, and Shuqiang Jiang. 2022. Ingredient-guided region discovery and relationship modeling for food category-ingredient prediction. IEEE Transactions on Image Processing 31 (2022), 5214–5226. DOI:
[208]
Tomasz Wasilewski, Dorian Migoń, Jacek Gębicki, and Wojciech Kamysz. 2019. Critical review of electronic nose and tongue instruments prospects in pharmaceutical analysis. Analytica Chimica Acta 1077 (2019), 14–29.
[209]
Jun Wei, Xuan Wang, Roshan Lalintha Peiris, Yongsoon Choi, Xavier Roman Martinez, Remi Tache, Jeffrey Tzu Kwan Valino Koh, Veronica Halupka, and Adrian David Cheok. 2011. CoDine: An interactive multi-sensory system for remote dining. In Proceedings of the 13th International Conference on Ubiquitous Computing (Beijing, China). Association for Computing Machinery, New York, NY, USA, 21–30. DOI:
[210]
Zhenbo Wei, Jun Wang, and Weifeng Jin. 2013. Evaluation of varieties of set yogurts and their physical properties using a voltammetric electronic tongue based on various potential waveforms. Sensors and Actuators B: Chemical 177 (2013), 684–694.
[211]
Juhong Wen, Yongli Zhao, Qian Rong, Zhimeng Yang, Jianxin Yin, and Zhi Peng. 2022. Rapid odor recognition based on reliefF algorithm using electronic nose and its application in fruit identification and classification. Journal of Food Measurement and Characterization 16, 3 (2022), 2422–2433.
[212]
Xiaojie Xia, Wei Liu, Liuan Wang, and Jun Sun. 2023. HSIFoodIngr-64: A dataset for hyperspectral food-related studies and a benchmark method on food ingredient retrieval. IEEE Access 11 (2023), 13152–13162.
[213]
Yiming Xia, Wei Liu, Yule Shi, Shoaib Younas, Changhong Liu, and Lei Zheng. 2022. Rapid determination of capsaicin concentration in soybean oil by terahertz spectroscopy. Journal of Food Science 87, 2 (2022), 567–575. arXiv:
[214]
Shijie Xiao, Qiaohua Wang, Chunfang Li, Wenju Liu, Jingjing Zhang, Yikai Fan, Jundong Su, Haitong Wang, Xuelu Luo, and Shujun Zhang. 2022. Rapid identification of A1 and A2 milk based on the combination of mid-infrared spectroscopy and chemometrics. Food Control 134 (2022), 108659. DOI:
[215]
Anguo Xie, Jing Sun, Tingmin Wang, and Yunhong Liu. 2022. Visualized detection of quality change of cooked beef with condiments by hyperspectral imaging technique. Food Science and Biotechnology 31, 10 (2022), 1257–1266.
[216]
Yi Xu, Peng Zhong, Aimin Jiang, Xing Shen, Xiangmei Li, Zhenlin Xu, Yudong Shen, Yuanming Sun, and Hongtao Lei. 2020. Raman spectroscopy coupled with chemometrics for food authentication: A review. TrAC Trends in Analytical Chemistry 131 (2020), 116017. DOI:
[217]
Jing Yan, Louka van Stuijvenberg, and Saskia M. van Ruth. 2019. Handheld near-infrared spectroscopy for distinction of extra virgin olive oil from other olive oil grades substantiated by compositional data. European Journal of Lipid Science and Technology 121, 12 (2019), 1900031.
[218]
Tingyu Yan, Jiexin Lin, Jianxin Zhu, Naixing Ye, Jianfeng Huang, Pengjie Wang, Shan Jin, Deyong Zheng, and Jiangfan Yang. 2022. Aroma analysis of fuyun 6 and jinguanyin black tea in the fu’an area based on e-nose and GC–MS. European Food Research and Technology 248, 4 (2022), 947–961.
[219]
Biao Yang, Wenchuan Guo, Wenting Liang, Yihang Zhou, and Xinhua Zhu. 2022. Design and evaluation of a miniature milk quality detection system based on UV/Vis spectroscopy. Journal of Food Composition and Analysis 106 (2022), 104341. DOI:
[220]
Hongbo Yang, David L. Hopkins, Yimin Zhang, Lixian Zhu, Pengcheng Dong, Xinyi Wang, Yanwei Mao, Xin Luo, and Stephanie M Fowler. 2020. Preliminary investigation of the use of raman spectroscopy to predict beef spoilage in different types of packaging. Meat Science 165 (2020), 108136.
[221]
Huihui Yang, Yutang Wang, Jinyong Zhao, Ping Li, Long Li, and Fengzhong Wang. 2023. A machine learning method for juice human sensory hedonic prediction using electronic sensory features. Current Research in Food Science 7 (2023), 100576. DOI:
[222]
Si Yang, Chenxi Li, Yang Mei, Wen Liu, Rong Liu, Wenliang Chen, Donghai Han, and Kexin Xu. 2021. Determination of the geographical origin of coffee beans using terahertz spectroscopy combined with machine learning methods. Frontiers in Nutrition 8 (2021), 313.
[223]
Yan Yang, Huixiang Liu, and Yu Gu. 2020. A model transfer learning framework with back-propagation neural network for wine and chinese liquor detection by electronic nose. IEEE Access 8 (2020), 105278–105285.
[224]
Xinli Yao, Fuhong Cai, Peiyi Zhu, Haixuan Fang, Jingwei Li, and Sailing He. 2019. Non-invasive and rapid pH monitoring for meat quality assessment using a low-cost portable hyperspectral scanner. Meat Science 152 (2019), 73–80.
[225]
Nazife N. Yazgan, Huseyin E. Genis, Tugba Bulat, Ali Topcu, Sahin Durna, Atila Yetisemiyen, and Ismail H Boyaci. 2020. Discrimination of milk species using raman spectroscopy coupled with partial least squares discriminant analysis in raw and pasteurized milk. Journal of the Science of Food and Agriculture 100, 13 (2020), 4756–4765.
[226]
Xujun Ye, Shyota Ishioka, and Shuhuai Zhang. 2017. Estimation of the degree of red coloration in flesh of a red-fleshed apple cultivar ‘Kurenai no Yume’with a UV–vis-NIR interactance device. Postharvest Biology and Technology 124 (2017), 128–136.
[227]
Zhenyi Ye, Yaonian Li, Ruth Jin, and Qiliang Li. 2024. Toward accurate odor identification and effective feature learning with an AI-empowered electronic nose. IEEE Internet of Things Journal 11, 3 (2024), 4735–4746. DOI:
[228]
Gulgun Yildiz Tiryaki and Huseyin Ayvaz. 2017. Quantification of soybean oil adulteration in extra virgin olive oil using portable raman spectroscopy. Journal of Food Measurement and Characterization 11, 2 (2017), 523–529.
[229]
Yaping Yu, Hui Zhao, Renjie Yang, Guimei Dong, Liuan Li, Jingjing Yang, Tianming Jin, Weiyu Zhang, and Yuan Liu. 2015. Pure milk brands classification by means of a voltammetric electronic tongue and multivariate analysis. Int. J. Electrochem. Sci 10 (2015), 4381–4392.
[230]
Mohammad Reza Zarezadeh, Mohammad Aboonajmi, and Mahdi Ghasemi Varnamkhasti. 2021. Fraud detection and quality assessment of olive oil using ultrasound. Food Science and Nutrition 9, 1 (2021), 180–189.
[231]
Mohammad Reza Zarezadeh, Mohammad Aboonajmi, Mahdi Ghasemi Varnamkhasti, and Fatemeh Azarikia. 2021. Olive oil classification and fraud detection using e-nose and ultrasonic system. Food Analytical Methods 14 (2021), 2199–2210. DOI:
[232]
Jiahong Zhang, Yu Lei, Lin He, Xinjun Hu, Jianping Tian, Manjiao Chen, Dan Huang, and Huibo Luo. 2023. The rapid detection of the tannin content of grains based on hyperspectral imaging technology and chemometrics. Journal of Food Composition and Analysis 123 (2023), 105604. DOI:
[233]
Mengsheng Zhang, Bo Zhang, Hao Li, Maosheng Shen, Shijie Tian, Haihui Zhang, Xiaolin Ren, Libo Xing, and Juan Zhao. 2020. Determination of bagged ‘Fuji’apple maturity by visible and near-infrared spectroscopy combined with a machine learning algorithm. Infrared Physics and Technology 111 (2020), 103529.
[234]
Nan Zhang, Sheng Jie Lim, Jia Min Toh, Yue Fan Wei, Rusli, and Lin Ke. 2022. Investigation of spoilage in salmon by electrochemical impedance spectroscopy and time-domain terahertz spectroscopy. ChemPhysMater 1, 2 (2022), 148–154. DOI:
[235]
Peipei Zhang, Huaiwen Wang, Hongwei Ji, Yankun Li, Xiaochuan Zhang, and Yanan Wang. 2023. Hyperspectral imaging-based early damage degree representation of apple: a method of correlation coefficient. Postharvest Biology and Technology 199 (2023), 112309. DOI:
[236]
Wen Zhang, Zhenzhen Lv, and Shuangli Xiong. 2018. Nondestructive quality evaluation of agro-products using acoustic vibration methods—A review. Critical Reviews in Food Science and Nutrition 58, 14 (2018), 2386–2397.
[237]
Yaoxin Zhang, Minchong Zheng, Rongguang Zhu, and Rong Ma. 2022. Adulteration discrimination and analysis of fresh and frozen-thawed minced adulterated mutton using hyperspectral images combined with recurrence plot and convolutional neural network. Meat Science 192 (2022), 108900. DOI:
[238]
Xin Zhao, Chunhua Li, Zhilei Zhao, Guangchen Wu, Liya Xia, Hongzhe Jiang, Tingxin Wang, Xuan Chu, and Jia Liu. 2021. Generic models for rapid detection of vanillin and melamine adulterated in infant formulas from diverse brands based on near-infrared hyperspectral imaging. Infrared Physics and Technology 116 (2021), 103745.
[239]
Wenbo Zheng, Yan Shi, Xiuxin Xia, Yuxiang Ying, and Hong Men. 2022. A data processing method for electronic tongue based on computational model of taste pathways and convolutional neural network. Measurement 205 (2022), 112150. DOI:
[240]
Lei Zhou, Chu Zhang, Zhengjun Qiu, and Yong He. 2020. Information fusion of emerging non-destructive analytical techniques for food quality authentication: A survey. TrAC Trends in Analytical Chemistry 127 (2020), 115901. DOI:
[241]
Yongxin Zhou, Jiale Chen, Xiong Zhang, Wenxiong Kang, and Zeng Ming. 2022. Semantic center guided windows attention fusion framework for food recognition. In Proceedings of the Chinese Conference on Pattern Recognition and Computer Vision.Springer, 626–638.
[242]
Zongwei Zhou, Jae Shin, Lei Zhang, Suryakanth Gurudu, Michael Gotway, and Jianming Liang. 2017. Fine-tuning convolutional neural networks for biomedical image analysis: Actively and incrementally. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.
[243]
Yiwen Zhu, Xirui Zhou, Yan Ping Chen, Ziyuan Liu, Shui Jiang, Gaole Chen, and Yuan Liu. 2022. Exploring the relationships between perceived umami intensity, umami components and electronic tongue responses in food matrices. Food Chemistry 368 (2022), 130849. DOI:
[244]
Jiewen Zuo, Yankun Peng, Yongyu Li, Wenlong Zou, Yahui Chen, Daoyu Huo, and Kuanglin Chao. 2023. Nondestructive detection of nutritional parameters of pork based on NIR hyperspectral imaging technique. Meat Science 202 (2023), 109204. DOI:
[245]
Necati Çetin, Kevser Karaman, Erhan Kavuncuoğlu, Bekir Yıldırım, and Ahmad Jahanbakhshi. 2022. Using hyperspectral imaging technology and machine learning algorithms for assessing internal quality parameters of apple fruits. Chemometrics and Intelligent Laboratory Systems 230 (2022), 104650. DOI:
[246]
Ítala M. G. Marx, Nuno Rodrigues, Luís G. Dias, Ana C. A. Veloso, José A. Pereira, Deisy A. Drunkler, and António M. Peres. 2017. Quantification of table olives’ acid, bitter and salty tastes using potentiometric electronic tongue fingerprints. LWT - Food Science and Technology 79 (2017), 394–401. DOI:

Recommendations

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image ACM Computing Surveys
ACM Computing Surveys  Volume 57, Issue 1
January 2025
984 pages
EISSN:1557-7341
DOI:10.1145/3696794
  • Editors:
  • David Atienza,
  • Michela Milano
Issue’s Table of Contents

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 07 October 2024
Online AM: 30 July 2024
Accepted: 15 July 2024
Revised: 01 June 2024
Received: 08 May 2023
Published in CSUR Volume 57, Issue 1

Check for updates

Author Tags

  1. Human-food interaction
  2. food recognition
  3. food sensing
  4. ingredient sensing

Qualifiers

  • Survey

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 492
    Total Downloads
  • Downloads (Last 12 months)492
  • Downloads (Last 6 weeks)132
Reflects downloads up to 18 Nov 2024

Other Metrics

Citations

View Options

Login options

Full Access

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Full Text

View this article in Full Text.

Full Text

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media