title: Evaluation of the Fourier Frequency Spectrum Peaks of Milk Electrical Conductivity Signals as Indexes to Monitor the Dairy Goats' Health Status by On-Line Sensors.
abstract: 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: 0-60 Days In Milking (DIM); 61-120 DIM; 121-180 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 < 1,000,000 cells/mL, glands were classified as healthy. When bacteriological analyses were positive or showed a SCC > 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 × HS as explanatory variables in the statistical model.Results showed that the studied frequency peaks had a significant relationship with the gland's health status. Results also explained how the milk EC signals' 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.
authors: Faculty of Agriculture, Università Telematica San Raffaele Roma, Via di Val Cannuta 247, 00166 Rome, Italy. mauro.zaninelli@unisanraffaele.gov.it.
authors: Mauro
authors: M
authors: Zaninelli
authors: Department of Health, Animal Science and Food Safety (VESPA), Università degli Studi di Milano, Via Celoria 10, 20133 Milan, Italy. alessandro.agazzi@unimi.it.
authors: Alessandro
authors: A
authors: Agazzi
authors: Department of Health, Animal Science and Food Safety (VESPA), Università degli Studi di Milano, Via Celoria 10, 20133 Milan, Italy. annamaria.costa@unimi.it.
authors: Annamaria
authors: A
authors: Costa
authors: Department of Health, Animal Science and Food Safety (VESPA), Università degli Studi di Milano, Via Celoria 10, 20133 Milan, Italy. francesco.tangorra@unimi.it.
authors: Francesco Maria
authors: FM
authors: Tangorra
authors: Department of Health, Animal Science and Food Safety (VESPA), Università degli Studi di Milano, Via Celoria 10, 20133 Milan, Italy. luciana.rossi@unimi.it.
authors: Luciana
authors: L
authors: Rossi
authors: Department of Health, Animal Science and Food Safety (VESPA), Università degli Studi di Milano, Via Celoria 10, 20133 Milan, Italy. giovanni.savoini@unimi.it.
authors: Giovanni
authors: G
authors: Savoini
mesh_terms: D000818:Animals; D003612:Dairying; D004553:Electric Conductivity; D005260:Female; D005583:Fourier Analysis; D006041:Goats; D006304:Health Status; D007774:Lactation; D016014:Linear Models; D008321:Mammary Glands, Animal / Q000382:microbiology; D008892:Milk / Q000737:chemistry*; D009862:Online Systems / Q000295:instrumentation*; D012815:Signal Processing, Computer-Assisted
keywords: Fast Fourier Transform; dairy goats; electrical conductivity; frequency peaks; mastitis; spectrum