{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T10:56:05Z","timestamp":1782989765394,"version":"3.54.5"},"reference-count":28,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2019,3,29]],"date-time":"2019-03-29T00:00:00Z","timestamp":1553817600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Beijing Agricultural Forestry Academy Youth Fund","award":["QNJJ201630"],"award-info":[{"award-number":["QNJJ201630"]}]},{"name":"Special Projects of Construction of Science and Technology Innovation Ability of Beijing Academy of Agriculture and Forestry Sciences","award":["KJCX20170420"],"award-info":[{"award-number":["KJCX20170420"]}]},{"DOI":"10.13039\/501100004826","name":"Beijing Natural Science Foundation","doi-asserted-by":"publisher","award":["L182031"],"award-info":[{"award-number":["L182031"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["21806013"],"award-info":[{"award-number":["21806013"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31801634"],"award-info":[{"award-number":["31801634"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["21806014"],"award-info":[{"award-number":["21806014"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"International Cooperation Fund of Beijing Agricultural Forestry Academy","award":["GJHZ2018-05"],"award-info":[{"award-number":["GJHZ2018-05"]}]},{"name":"Project of Beijing Science and Technology","award":["Z171100001517017"],"award-info":[{"award-number":["Z171100001517017"]}]},{"name":"Project of Beijing Excellent Talents","award":["2017000020060G127"],"award-info":[{"award-number":["2017000020060G127"]}]},{"name":"Open Project of Risk Assessment Laboratory for Agro-products of the Ministry of Agriculture","award":["KFKT201707"],"award-info":[{"award-number":["KFKT201707"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>In this study, the PEN3 electronic nose was used to detect and recognize fresh and moldy apples inoculated with Penicillium expansum and Aspergillus niger, taking Golden Delicious apples as the model subject. Firstly, the apples were divided into two groups: individual apple inoculated only with\/without different molds (Group A) and mixed apples of inoculated apples with fresh apples (Group B). Then, the characteristic gas sensors of the PEN3 electronic nose that were most closely correlated with the flavor information of the moldy apples were optimized and determined to simplify the analysis process and improve the accuracy of the results. Four pattern recognition methods, including linear discriminant analysis (LDA), backpropagation neural network (BPNN), support vector machines (SVM), and radial basis function neural network (RBFNN), were applied to analyze the data obtained from the characteristic sensors, aiming at establishing the prediction model of the flavor information and fresh\/moldy apples. The results showed that only the gas sensors of W1S, W2S, W5S, W1W, and W2W in the PEN3 electronic nose exhibited a strong signal response to the flavor information, indicating most were closely correlated with the characteristic flavor of apples and thus the data obtained from these characteristic sensors were used for modeling. The results of the four pattern recognition methods showed that BPNN had the best prediction performance for the training and testing sets for both Groups A and B, with prediction accuracies of 96.3% and 90.0% (Group A), 77.7% and 72.0% (Group B), respectively. Therefore, we demonstrate that the PEN3 electronic nose not only effectively detects and recognizes fresh and moldy apples, but also can distinguish apples inoculated with different molds.<\/jats:p>","DOI":"10.3390\/s19071526","type":"journal-article","created":{"date-parts":[[2019,3,29]],"date-time":"2019-03-29T03:50:21Z","timestamp":1553831421000},"page":"1526","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":76,"title":["Electronic Nose-Based Technique for Rapid Detection and Recognition of Moldy Apples"],"prefix":"10.3390","volume":"19","author":[{"given":"Wenshen","family":"Jia","sequence":"first","affiliation":[{"name":"Beijing Research Center for Agricultural Standards and Testing, Beijing Academy of Agriculture and Forestry Science, Beijing 100097, China"},{"name":"Risk Assessment Lab for Agro-products (Beijing), Ministry of Agriculture, Beijing 100097, China"},{"name":"Beijing Municipal Key Laboratory of Agriculture Environment Monitoring, Beijing 100197, China"},{"name":"Key Laboratory of Urban Agriculture (North China), Ministry of Agriculture and Rural Affairs, Beijing 100097, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gang","family":"Liang","sequence":"additional","affiliation":[{"name":"Beijing Research Center for Agricultural Standards and Testing, Beijing Academy of Agriculture and Forestry Science, Beijing 100097, China"},{"name":"Risk Assessment Lab for Agro-products (Beijing), Ministry of Agriculture, Beijing 100097, China"},{"name":"Beijing Municipal Key Laboratory of Agriculture Environment Monitoring, Beijing 100197, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Tian","sequence":"additional","affiliation":[{"name":"Beijing Research Center for Agricultural Standards and Testing, Beijing Academy of Agriculture and Forestry Science, Beijing 100097, China"},{"name":"Risk Assessment Lab for Agro-products (Beijing), Ministry of Agriculture, Beijing 100097, China"},{"name":"Beijing Municipal Key Laboratory of Agriculture Environment Monitoring, Beijing 100197, China"},{"name":"Key Laboratory of Urban Agriculture (North China), Ministry of Agriculture and Rural Affairs, Beijing 100097, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Sun","sequence":"additional","affiliation":[{"name":"Chinese Academy of Agricultural Engineering, Beijing 100121, China"},{"name":"Key Laboratory of Agro-Products Postharvest Handling, Ministry of Agriculture, Beijing 100121, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cihui","family":"Wan","sequence":"additional","affiliation":[{"name":"Beijing Research Center for Agricultural Standards and Testing, Beijing Academy of Agriculture and Forestry Science, Beijing 100097, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,3,29]]},"reference":[{"key":"ref_1","first-page":"175","article-title":"Survey on the occurrence and distribution of apple diseases in China","volume":"42","author":"Hu","year":"2016","journal-title":"Plant Prot."},{"key":"ref_2","first-page":"47","article-title":"Classification and identification of apple diseases","volume":"6","author":"Yu","year":"1998","journal-title":"North. Hortic."},{"key":"ref_3","first-page":"49","article-title":"Determination of cyhalothrin pesticide residue in apple by capillary GC method","volume":"26","author":"Liang","year":"2008","journal-title":"Agric. Res. Arid Areas"},{"key":"ref_4","first-page":"164","article-title":"Aroma quality of Gala apple during storage evaluated by electronic nose and gas chromatography-mass spectrometry","volume":"35","author":"Fan","year":"2014","journal-title":"Food Sci."},{"key":"ref_5","first-page":"32","article-title":"Application of near infrared spectroscopy in nondestructive testing of apple quality","volume":"6","author":"Qu","year":"2014","journal-title":"Agric. Sci. Technol. Equip."},{"key":"ref_6","first-page":"6","article-title":"Electronic nose and its latest research progress in various fields","volume":"16","author":"Jin","year":"2010","journal-title":"Sens. World"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Xu, S., Sun, X., Lu, H., Yang, H., Ruan, Q., Huang, H., and Chen, M. (2018). Detecting and monitoring the flavor of tomato (Solanum lycopersicum) under the impact of postharvest handlings by physicochemical parameters and electronic nose. Sensors, 18.","DOI":"10.3390\/s18061847"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2916","DOI":"10.1007\/s12161-018-1283-1","article-title":"Electronic noses as a powerful tool for assessing meat quality: A mini review","volume":"11","author":"Jia","year":"2018","journal-title":"Food Anal. Methods"},{"key":"ref_9","first-page":"211","article-title":"A Brief History of Electronic Nose","volume":"18\u201319","author":"Gardner","year":"1994","journal-title":"Sens. Actuators B Chem."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1038\/299352a0","article-title":"Analysis of discrimination mechanisms in the mammalian olfactory system using a model nose","volume":"299","author":"Persaud","year":"1982","journal-title":"Nature"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"142","DOI":"10.3390\/s8010142","article-title":"Electronic Nose Based on Metal Oxide Semiconductor Sensors as an Alternative Technique for the Spoilage Classification of Red Meat","volume":"8","author":"Noureddine","year":"2008","journal-title":"Sensors"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"6271","DOI":"10.1039\/C4AY00014E","article-title":"Non-destructive evaluation of pork freshness using a portable electronic nose (E-nose) based on a colorimetric sensor array","volume":"6","author":"Li","year":"2014","journal-title":"Anal. Methods"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"62","DOI":"10.1016\/j.jfoodeng.2017.04.024","article-title":"Fusion of electronic nose, electronic tongue and computer vision for animal source food authentication and quality assessment\u2014A review","volume":"210","author":"Leone","year":"2017","journal-title":"J. Food Eng."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1423","DOI":"10.1021\/jf403215y","article-title":"Food analysis using artificial senses","volume":"62","author":"Dymerski","year":"2014","journal-title":"J. Agric. Food Chem."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/j.foodchem.2013.10.105","article-title":"E-Nose and e-Tongue combination for improved recognition of fruit juice samples","volume":"150","author":"Haddi","year":"2014","journal-title":"Food Chem."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.aca.2015.04.042","article-title":"Data fusion methodologies for food and beverage authentication and quality assessment\u2014A review","volume":"891","author":"Mestres","year":"2015","journal-title":"Anal. Chim. Acta"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"896","DOI":"10.1016\/j.foodchem.2013.03.052","article-title":"Nondestructive flavor evaluation of red onion (Allium cepa L.) Ecotypes: An electronic-nose-based approach","volume":"141","author":"Russo","year":"2013","journal-title":"Food Chem."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1016\/j.jfoodeng.2015.03.025","article-title":"Detecting sour skin infected onions using a customized gas sensor array","volume":"160","author":"Konduru","year":"2015","journal-title":"J. Food Eng."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"422","DOI":"10.1016\/j.talanta.2014.04.057","article-title":"Detection of potato brown rot and ring rot by electronic nose: From laboratory to real scale","volume":"129","author":"Spinelli","year":"2014","journal-title":"Talanta"},{"key":"ref_20","first-page":"68","article-title":"Research on distinguishing tomato seeding infected with early blight disease by electronic nose","volume":"29","author":"Cheng","year":"2013","journal-title":"Bull. Sci. Technol."},{"key":"ref_21","first-page":"254","article-title":"Identification method for different moldy degrees of maize using electronic nose coupled with multi-features fusion","volume":"32","author":"Yin","year":"2016","journal-title":"Trans. CSAE"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1016\/j.foodcont.2013.09.048","article-title":"Screening of deoxynivalenol contamination in durum wheat by MOS-based electronic nose and identification of the relevant pattern of volatile compounds","volume":"37","author":"Lippolis","year":"2014","journal-title":"Food Control"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"71","DOI":"10.17660\/ActaHortic.2016.1120.10","article-title":"Monitoring shelf life of fresh-cut apples packed in different atmospheres by electronic nose","volume":"1120","author":"Cortellino","year":"2016","journal-title":"Acta Hortic."},{"key":"ref_24","first-page":"266","article-title":"Early detection of fungal disease infection in strawberry fruits by e-nose during postharvest storage","volume":"29","author":"Zhu","year":"2013","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_25","first-page":"146","article-title":"Distinguishing different cultivar apples by electronic nose on support vector machine","volume":"23","author":"Zou","year":"2007","journal-title":"Trans. CSAE"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"82","DOI":"10.1007\/s12161-012-9414-6","article-title":"Fuji apple storage time predictive method using electronic nose","volume":"6","author":"Hui","year":"2013","journal-title":"Food Anal. Methods"},{"key":"ref_27","first-page":"183","article-title":"Prediction of low-temperature storage time and quality of apples based on electronic nose","volume":"5","author":"Li","year":"2015","journal-title":"J. Northwest Univ."},{"key":"ref_28","first-page":"119","article-title":"The electronic nose 1-MCP at room temperature different time apple discriminant analysis","volume":"12","author":"Zhang","year":"2015","journal-title":"North. Hortic."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/7\/1526\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:41:22Z","timestamp":1760186482000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/19\/7\/1526"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,3,29]]},"references-count":28,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2019,4]]}},"alternative-id":["s19071526"],"URL":"https:\/\/doi.org\/10.3390\/s19071526","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,3,29]]}}}