Because a human observer is typically not present during milking process when automatic milking systems (AMS) are used, human observation is replaced by mastitis detection systems consisting of sensors and algorithms that create alerts. Several authors suggest that sensing systems to detect clinical mastitis (CM) are in need of improvement. The aim of this retrospective study was to observe trends over time of potential indicators of CM, thus identifying promising CM indicators and analysis methods. Data from a Northeastern USA commercial dairy farm with 1280 Holstein Friesian cows using 20 AMS units were used for the analysis. Over a oneyear time period, there were 117 confirmed cases of CM in this herd. Thirty milking sessions prior to CM confirmation were used for this analysis (n ¼ 3134). Of the 117 confirmed CM cases, 12% were in primiparous cows (L1), 24% in second lactation cows (L2) and 64% in third or greater lactation cows (L3þ). Differences between group average CM-confirmed and non-CM quarters were observed prior to CM confirmation for quarter-level electrical conductivity (ECq), milk production rate (MPRq), average milk flow rate (AMFq) and peak milk flow rate (PMFq). Positive indications of CM were apparent well before confirmation of visual signs of CM for ECq and MPRq; however, positive indications for AMFq occurred only one day before CM confirmation. The combination of ECq, MPRq and AMFq is potentially useful for differentiating between an early (before visual signs of CM are manifested) detection and a false positive detection.
Changes in electrical conductivity, milk production rate and milk flow rate prior to clinical mastitis confirmation / V. Inzaghi, M. Zucali, P.D. Thompson, J.F. Penry, D.J. Reinemann. - In: ITALIAN JOURNAL OF ANIMAL SCIENCE. - ISSN 1594-4077. - 20:1(2021), pp. 1552-1559. [10.1080/1828051X.2021.1984852]
Changes in electrical conductivity, milk production rate and milk flow rate prior to clinical mastitis confirmation
M. Zucali
Secondo
Writing – Original Draft Preparation
;
2021
Abstract
Because a human observer is typically not present during milking process when automatic milking systems (AMS) are used, human observation is replaced by mastitis detection systems consisting of sensors and algorithms that create alerts. Several authors suggest that sensing systems to detect clinical mastitis (CM) are in need of improvement. The aim of this retrospective study was to observe trends over time of potential indicators of CM, thus identifying promising CM indicators and analysis methods. Data from a Northeastern USA commercial dairy farm with 1280 Holstein Friesian cows using 20 AMS units were used for the analysis. Over a oneyear time period, there were 117 confirmed cases of CM in this herd. Thirty milking sessions prior to CM confirmation were used for this analysis (n ¼ 3134). Of the 117 confirmed CM cases, 12% were in primiparous cows (L1), 24% in second lactation cows (L2) and 64% in third or greater lactation cows (L3þ). Differences between group average CM-confirmed and non-CM quarters were observed prior to CM confirmation for quarter-level electrical conductivity (ECq), milk production rate (MPRq), average milk flow rate (AMFq) and peak milk flow rate (PMFq). Positive indications of CM were apparent well before confirmation of visual signs of CM for ECq and MPRq; however, positive indications for AMFq occurred only one day before CM confirmation. The combination of ECq, MPRq and AMFq is potentially useful for differentiating between an early (before visual signs of CM are manifested) detection and a false positive detection.File | Dimensione | Formato | |
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