{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T09:13:36Z","timestamp":1760346816575,"version":"build-2065373602"},"reference-count":55,"publisher":"MDPI AG","issue":"19","license":[{"start":{"date-parts":[[2019,9,20]],"date-time":"2019-09-20T00:00:00Z","timestamp":1568937600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100010661","name":"Horizon 2020 Framework Programme","doi-asserted-by":"publisher","award":["732541"],"award-info":[{"award-number":["732541"]}],"id":[{"id":"10.13039\/100010661","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The performance of an Unsupervised Online feature Selection (UOS) algorithm was investigated for the selection of training features of multispectral images acquired from a dairy product (vanilla cream) stored under isothermal conditions. The selected features were further used as input in a support vector machine (SVM) model with linear kernel for the determination of the microbiological quality of vanilla cream. Model training (n = 65) was based on two batches of cream samples provided directly by the manufacturer and stored at different isothermal conditions (4, 8, 12, and 15 \u00b0C), whereas model testing (n = 132) and validation (n = 48) were based on real life conditions by analyzing samples from different retail outlets as well as expired samples from the market. Qualitative analysis was performed for the discrimination of cream samples in two microbiological quality classes based on the values of total viable counts [TVC \u2264 2.0 log CFU\/g (fresh samples) and TVC \u2265 6.0 log CFU\/g (spoiled samples)]. Results exhibited good performance with an overall accuracy of classification for the two classes of 91.7% for model validation. Further on, the model was extended to include the samples in the TVC range 2\u20136 log CFU\/g, using 1 log step to define the microbiological quality of classes in order to assess the potential of the model to estimate increasing microbial populations. Results demonstrated that high rates of correct classification could be obtained in the range of 2\u20135 log CFU\/g, whereas the percentage of erroneous classification increased in the TVC class (5,6) that was close to the spoilage level of the product. Overall, the results of this study demonstrated that the UOS algorithm in tandem with spectral data acquired from multispectral imaging could be a promising method for real-time assessment of the microbiological quality of vanilla cream samples.<\/jats:p>","DOI":"10.3390\/s19194071","type":"journal-article","created":{"date-parts":[[2019,9,20]],"date-time":"2019-09-20T10:48:14Z","timestamp":1568976494000},"page":"4071","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Online Feature Selection for Robust Classification of the Microbiological Quality of Traditional Vanilla Cream by Means of Multispectral Imaging"],"prefix":"10.3390","volume":"19","author":[{"given":"Alexandra","family":"Lianou","sequence":"first","affiliation":[{"name":"Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science and Human Nutrition, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3753-0457","authenticated-orcid":false,"given":"Arianna","family":"Mencattini","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, University of Rome for Vergata, via del Politecnico 1, 00133 Roma, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6050-2908","authenticated-orcid":false,"given":"Alexandro","family":"Catini","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, University of Rome for Vergata, via del Politecnico 1, 00133 Roma, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0543-4348","authenticated-orcid":false,"given":"Corrado","family":"Di Natale","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, University of Rome for Vergata, via del Politecnico 1, 00133 Roma, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2673-6425","authenticated-orcid":false,"given":"George-John E.","family":"Nychas","sequence":"additional","affiliation":[{"name":"Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science and Human Nutrition, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6673-2066","authenticated-orcid":false,"given":"Eugenio","family":"Martinelli","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, University of Rome for Vergata, via del Politecnico 1, 00133 Roma, Italy"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0317-1177","authenticated-orcid":false,"given":"Efstathios Z.","family":"Panagou","sequence":"additional","affiliation":[{"name":"Laboratory of Microbiology and Biotechnology of Foods, Department of Food Science and Human Nutrition, Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.cofs.2016.06.005","article-title":"Novel approaches for food safety management and communication","volume":"12","author":"Nychas","year":"2016","journal-title":"Curr. 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