Signal spectral analysis to characterize gland milk electrical conductivity in dairy goats
Intramammary infection affects quality and quantity of milk. Having as final target the improving of animal health’ monitoring, this research studied the gland milk electrical conductivity (EC) signal in order to identify a possible parameter more representative of the EC variations that can be obse...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Taylor & Francis Group
2015-07-01
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| Series: | Italian Journal of Animal Science |
| Subjects: | |
| Online Access: | http://www.aspajournal.it/index.php/ijas/article/view/3518 |
| _version_ | 1828877274464649216 |
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| author | Mauro Zaninelli Luciana Rossi Annamaria Costa Francesco M. Tangorra Alessandro Agazzi Giovanni Savoini |
| author_facet | Mauro Zaninelli Luciana Rossi Annamaria Costa Francesco M. Tangorra Alessandro Agazzi Giovanni Savoini |
| author_sort | Mauro Zaninelli |
| collection | DOAJ |
| description | Intramammary infection affects quality and quantity of milk. Having as final target the improving of animal health’ monitoring, this research studied the gland milk electrical conductivity (EC) signal in order to identify a possible parameter more representative of the EC variations that can be observed, during a milking, when not healthy (NH) glands are considered. Two foremilk gland samples, from 40 Saanen goats, were acquired for three weeks and lactation stages (LS: 0-60 Days In Milking; 61-120 DIM; =>120 DIM), for a total amount of 1440 samples. Bacteriological analyses and somatic cells counts (SCC) were used to define glands health status. In case of negative bacteriological analyses and SCC <1,000,000 cells/mL, glands were classified as healthy; alternatively, when bacteriological analyses were positive or SCC higher than 1,000,000 cells/mL, for two or more consecutive days, glands were classified as NH. A spectral analysis, to calculate the frequency spectrum and the bandwidth length of the milk EC signal, was performed. To validate data acquired, A MIXED procedure was used considering the HS, LS and the LS x HS as explanatory variables of the statistical model. Results showed that spectral analysis allows characterizing the milk EC variations thorough the bandwidth length parameter. This parameter has a significant relationship with the gland health status and it provides more accurate information than other traits, like the statistical variance of the signal. Therefore, it could be useful to improve the performances of multivariate models/algorithms that detect dairy goat health status. |
| first_indexed | 2024-12-13T08:37:36Z |
| format | Article |
| id | doaj.art-cb4783838cbb410baf701d35690bba8f |
| institution | Directory Open Access Journal |
| issn | 1594-4077 1828-051X |
| language | English |
| last_indexed | 2024-12-13T08:37:36Z |
| publishDate | 2015-07-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Italian Journal of Animal Science |
| spelling | doaj.art-cb4783838cbb410baf701d35690bba8f2022-12-21T23:53:36ZengTaylor & Francis GroupItalian Journal of Animal Science1594-40771828-051X2015-07-0114310.4081/ijas.2015.35182371Signal spectral analysis to characterize gland milk electrical conductivity in dairy goatsMauro Zaninelli0Luciana Rossi1Annamaria Costa2Francesco M. Tangorra3Alessandro Agazzi4Giovanni Savoini5San Raffaele Telematic University, RomeDipartimento di Scienze Veterinarie per la Salute, la Produzione Animale e la Sicurezza Alimentare, University of MilanDipartimento di Scienze Veterinarie per la Salute, la Produzione Animale e la Sicurezza Alimentare, University of MilanDipartimento di Scienze Veterinarie per la Salute, la Produzione Animale e la Sicurezza Alimentare, University of MilanDipartimento di Scienze Veterinarie per la Salute, la Produzione Animale e la Sicurezza Alimentare, University of MilanDipartimento di Scienze Veterinarie per la Salute, la Produzione Animale e la Sicurezza Alimentare, University of MilanIntramammary infection affects quality and quantity of milk. Having as final target the improving of animal health’ monitoring, this research studied the gland milk electrical conductivity (EC) signal in order to identify a possible parameter more representative of the EC variations that can be observed, during a milking, when not healthy (NH) glands are considered. Two foremilk gland samples, from 40 Saanen goats, were acquired for three weeks and lactation stages (LS: 0-60 Days In Milking; 61-120 DIM; =>120 DIM), for a total amount of 1440 samples. Bacteriological analyses and somatic cells counts (SCC) were used to define glands health status. In case of negative bacteriological analyses and SCC <1,000,000 cells/mL, glands were classified as healthy; alternatively, when bacteriological analyses were positive or SCC higher than 1,000,000 cells/mL, for two or more consecutive days, glands were classified as NH. A spectral analysis, to calculate the frequency spectrum and the bandwidth length of the milk EC signal, was performed. To validate data acquired, A MIXED procedure was used considering the HS, LS and the LS x HS as explanatory variables of the statistical model. Results showed that spectral analysis allows characterizing the milk EC variations thorough the bandwidth length parameter. This parameter has a significant relationship with the gland health status and it provides more accurate information than other traits, like the statistical variance of the signal. Therefore, it could be useful to improve the performances of multivariate models/algorithms that detect dairy goat health status.http://www.aspajournal.it/index.php/ijas/article/view/3518Electrical conductivitySpectral analysisFast Fourier transformMastitisDairy goats |
| spellingShingle | Mauro Zaninelli Luciana Rossi Annamaria Costa Francesco M. Tangorra Alessandro Agazzi Giovanni Savoini Signal spectral analysis to characterize gland milk electrical conductivity in dairy goats Italian Journal of Animal Science Electrical conductivity Spectral analysis Fast Fourier transform Mastitis Dairy goats |
| title | Signal spectral analysis to characterize gland milk electrical conductivity in dairy goats |
| title_full | Signal spectral analysis to characterize gland milk electrical conductivity in dairy goats |
| title_fullStr | Signal spectral analysis to characterize gland milk electrical conductivity in dairy goats |
| title_full_unstemmed | Signal spectral analysis to characterize gland milk electrical conductivity in dairy goats |
| title_short | Signal spectral analysis to characterize gland milk electrical conductivity in dairy goats |
| title_sort | signal spectral analysis to characterize gland milk electrical conductivity in dairy goats |
| topic | Electrical conductivity Spectral analysis Fast Fourier transform Mastitis Dairy goats |
| url | http://www.aspajournal.it/index.php/ijas/article/view/3518 |
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