Evaluation of measurements of the conductivity of quarter milk samples for the early diagnosis of mastitis

Somatic cell count (SCC), bacteriological findings and electrical conductivity (EC) were measured in milk from 216 quarters of 54 Murrah crossbred buffaloes for characterization of buffalo milk. Mean SCC in normal, subclinical and clinical mastitic milk was 171, 799 and 6039 ¥ 10 3 /mL, respectively. Coagulase negative Staphylococci (CNS) were the major organisms associated with subclinical mastitis, whereas CNS and coliforms were the predominant organisms in clinical mastitis. EC values were found to be significantly higher in buffalo milk with mammary infection. The best trade-off between sensitivity and specificity for diagnosing mastitis in buffaloes by EC score was found at the cut-off value of 3.7 mS/cm. The direct measures such as SCC, EC, bacteriological findings, and appearance of milk were found to be useful for the evaluation of udder health of buffaloes and categorization of milk.

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“…An EC is a useful parameter for evaluating milk quality and has been introduced as an indicator of udder health (Biggadike et al . 2002).…”

Section: Discussionmentioning

confidence: 99%

“…Mastitis causes changes in the conductivity of milk, by damaging mammary epithelia and thereby altering the balance of sodium, potassium and chloride ions (Kitchen 1981). A rise in sodium and chloride contents results in increased electrical conductivity (EC) in the milk (Biggadike et al . 2002).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of direct and indirect measures of quarter milk from crossbred buffaloes

Dhakal

Neupane

Nagahata

2008

Animal Science Journal

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“…Eckersall and others (2001) were the first to demonstrate significant increases in their concentrations in the milk of cows with clinical mastitis. Their results suggested that serum amyloid A was produced locally in the mammary gland, potentially making it an early, specific marker of mastitis, which might prove more sensitive than a bacteriological examination and less influenced by the physiological stage of the cow than the somatic cell count or the electrical conductivity of the milk (Sheldrake and others 1983, Biggadike and others 2002). However, it is still not known whether inflammatory processes occurring outside the mammary gland influence its concentration in milk.…”

Section: Methodsmentioning

confidence: 99%

Acute phase protein concentrations in serum and milk from healthy cows, cows with clinical mastitis and cows with extramammary inflammatory conditions

Nielsen¹,

Jacobsen²,

Andersen³

et al. 2004

Veterinary Record

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The concentrations of the two acute phase proteins, serum amyloid A and haptoglobin, in serum and milk were compared in 10 cows with clinical mastitis, 11 cows with extramammary inflammatory conditions and 10 clinically healthy control cows. The concentrations of both acute phase proteins were higher in the serum and milk of the cows with mastitis than in the cows in the other two groups. Four of the cows with extramammary inflammatory conditions had serum amyloid A concentrations in serum above 100 pg/ml, but negligible concentrations in milk, indicating that a pathogen must be present in the mammary gland for serum amyloid A to accumulate in milk. The acute phase protein concentrations in milk increased significantly with increasing somatic cell count, suggesting that they may be indicators of the severity of an infection.

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“…Most studied methods for cow mastitis detection using EC are based on processing data from EC sensors located at short milk tube or claw (also at gland level) and applying algorithms that consider the comparison of gland EC with the moving average of previous milkings (Lansberger et al 1994;Mele et al 2001;Biggadike et al 2002;Zecconi et al 2004;Cavero et al 2007; Kamphuis et al 2008a) and the comparison of EC of collateral glands (Maatje et al 1992(Maatje et al , 1997Lien et al 2005). In all these studies, specificity (SPEC) was around 90%, but sensitivity (SENS) was lower (different results were obtained depending on the study and type of mastitis: clinical, subclinical or somatic cell count (SCC) increases, from 25 to 89%).…”

Section: Introductionmentioning

confidence: 99%

Goat mastitis detection using daily records of milk conductivity: comparative results of different algorithms

Romero¹,

Reinemann²,

Alejandro³

et al. 2014

CZECH J ANIM SCI

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Milk electrical conductivity is employed for mastitis detection in cows due to its automation, low cost, and infection detectability at early stage. Nevertheless, the number of publications about its use in dairy goats is scarce. The aim of this study was to check and compare the detectability of goat mastitis (sensitivity and specificity) using different algorithms, constructed with individual daily conductivity data from glands, in order to improve the know how about the potential of this variable for goat mastitis detection. A total of 18 goats (8 primiparous and 10 multiparous) free of mastitis were used, and gland milk conductivity was daily monitored. After 16 days of monitoring, some unfavourable situations for gland health were simulated in order to increase the cases of infection. Once infection was established (9 goats and 12 glands got infected), the experiment continued for further 16 days. A total of 19 different algorithms that employed conductivity data from gland were designed; they were tested using gland milk conductivity (EC) and ratio of EC of collateral glands in the same goat (RAT EC ). The algorithms were tested in all the animals and intramammary infection detection ability characteristics (sensitivity (SENS), specificity (SPEC), positive predictive value (PPV), and negative predictive value (NPV)) were recorded. All clinical cases were detected (n = 2, 100% SENS) with all the algorithms. Best global SENS (clinical and subclinical, 33.3-58.3%) and SPEC (77.8-100%) were similar to results reported in previous studies in cows, and obtained with algorithms ARIMA and Rule 1 (3 standard deviations of data). The best algorithms to use in mastitis detection depend on the prevalence and type of mastitis. EC ARIMA and Rule 1 algorithms detected the most severe cases on-line and quickly, with a low proportion of false positives.

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Evaluation of measurements of the conductivity of quarter milk samples for the early diagnosis of mastitis

Cited by 16 publications

References 4 publications

Evaluation of direct and indirect measures of quarter milk from crossbred buffaloes

Evaluation of direct and indirect measures of quarter milk from crossbred buffaloes

Acute phase protein concentrations in serum and milk from healthy cows, cows with clinical mastitis and cows with extramammary inflammatory conditions

Goat mastitis detection using daily records of milk conductivity: comparative results of different algorithms

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