{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:16:42Z","timestamp":1760217402079,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2015,8,21]],"date-time":"2015-08-21T00:00:00Z","timestamp":1440115200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>The aim of this study is a further characterization of the electrical conductivity (EC) signal of goat milk, acquired on-line by EC sensors, to identify new indexes representative of the EC variations that can be observed during milking, when considering not healthy (NH) glands. Two foremilk gland samples from 42 Saanen goats, were collected for three consecutive weeks and for three different lactation stages (LS: 0\u201360 Days In Milking (DIM); 61\u2013120 DIM; 121\u2013180 DIM), for a total amount of 1512 samples. Bacteriological analyses and somatic cells counts (SCC) were used to define the health status of the glands. With negative bacteriological analyses and SCC &lt; 1,000,000 cells\/mL, glands were classified as healthy. When bacteriological analyses were positive or showed a SCC &gt; 1,000,000 cells\/mL, glands were classified as NH. For each milk EC signal, acquired on-line and for each gland considered, the Fourier frequency spectrum of the signal was calculated and three representative frequency peaks were identified. To evaluate data acquired a MIXED procedure was used considering the HS, LS and LS \u00d7 HS as explanatory variables in the statistical model.Results showed that the studied frequency peaks had a significant relationship with the gland\u2019s health status. Results also explained how the milk EC signals\u2019 pattern change in case of NH glands. In fact, it is characterized by slower fluctuations (due to the lower frequencies of the peaks) and by an irregular trend (due to the higher amplitudes of all the main frequency peaks). Therefore, these frequency peaks could be used as new indexes to improve the performances of algorithms based on multivariate models which evaluate the health status of dairy goats through the use of gland milk  EC sensors.<\/jats:p>","DOI":"10.3390\/s150820698","type":"journal-article","created":{"date-parts":[[2015,8,21]],"date-time":"2015-08-21T10:38:09Z","timestamp":1440153489000},"page":"20698-20716","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Evaluation of the Fourier Frequency Spectrum Peaks of Milk Electrical Conductivity Signals as Indexes to Monitor the Dairy Goats\u2019 Health Status by On-Line Sensors"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8800-1777","authenticated-orcid":false,"given":"Mauro","family":"Zaninelli","sequence":"first","affiliation":[{"name":"Faculty of Agriculture, Universit\u00e0 Telematica San Raffaele Roma, Via di Val Cannuta 247,  00166 Rome, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alessandro","family":"Agazzi","sequence":"additional","affiliation":[{"name":"Department of Health, Animal Science and Food Safety (VESPA), Universit\u00e0 degli Studi di Milano, Via Celoria 10, 20133 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1038-6886","authenticated-orcid":false,"given":"Annamaria","family":"Costa","sequence":"additional","affiliation":[{"name":"Department of Health, Animal Science and Food Safety (VESPA), Universit\u00e0 degli Studi di Milano, Via Celoria 10, 20133 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Francesco","family":"Tangorra","sequence":"additional","affiliation":[{"name":"Department of Health, Animal Science and Food Safety (VESPA), Universit\u00e0 degli Studi di Milano, Via Celoria 10, 20133 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1178-4683","authenticated-orcid":false,"given":"Luciana","family":"Rossi","sequence":"additional","affiliation":[{"name":"Department of Health, Animal Science and Food Safety (VESPA), Universit\u00e0 degli Studi di Milano, Via Celoria 10, 20133 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Giovanni","family":"Savoini","sequence":"additional","affiliation":[{"name":"Department of Health, Animal Science and Food Safety (VESPA), Universit\u00e0 degli Studi di Milano, Via Celoria 10, 20133 Milan, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2015,8,21]]},"reference":[{"key":"ref_1","first-page":"267","article-title":"Intramammary infections in dairy goats: Recent knowledge and indicators for detection of subclinical mastitis","volume":"60","author":"Stuhr","year":"2010","journal-title":"Landbauforschung"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1016\/j.livsci.2007.05.012","article-title":"Mastitis detection in dairy cows by application of neural networks","volume":"114","author":"Cavero","year":"2008","journal-title":"Livest. 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