Milking Procedures and Facilities

Marnet, Pierre‐Guy

doi:10.1002/9781118534168.ch3

Cited by 7 publications

(3 citation statements)

References 55 publications

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“…The higher SCC found in goats varies within a day [17] and may not always be related to intramammary bacterial infections. In addition, high SCC levels in goats could be due, at least to some extent, to co-infection with lentivirus and non-infectious inflammatory factors such as parity, stage of lactation, season, oestrus, milking rhythm, and response to machine milking [18][19][20][21][22][23][24][25]. It is assumed that these factors mask the connection between SCC and bacterial infection of the udder.…”

Section: Introductionmentioning

confidence: 99%

Infrared Thermography of Teat in French Dairy Alpine Goats: A Promising Tool to Study Animal–Machine Interaction during Milking but Not to Detect Mastitis

Marnet,

Velasquez,

Dzidic

2024

Animals

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There is a need to develop tools for mastitis management in goats and to measure the effects of milking machines on teats. Infrared thermography (IRT), as shown in cows, was a good candidate for early mastitis detection and focusing on milking equipment and settings implicated in potential problems. The aim of this study was to test IRT to detect udder inflammation and the effects of mechanical milking on teats in relation to inflammation status, udder balance, and teat shape in Alpine goats. IRT spectra were compared before and after milking in 551 goats from three commercial herds compared to their individual SCC (somatic cell count). We found no regression or trend between logSCC and IRT measurement or response to milking, even in highly inflamed goat udders. The effect of milking was significant (p < 0.05) with global temperature reduction after milking, but differences were seen between teat parts and unbalanced half udders. The highest reduction in skin temperature was observed at the teat orifice (−1.06 ± 0.05) and the lowest at the teat barrel (−0.37 ± 0.05). The teats with long barrels showed more IRT reactions, which clearly indicates poor adaptation to the liners used. In conclusion, the IRT was not able to detect mastitis, but it is a good tool to diagnose the effects of the milking machine in order to adapt milking equipment and settings to the goats and improve their welfare.

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Section: Introductionmentioning

confidence: 99%

Infrared Thermography of Teat in French Dairy Alpine Goats: A Promising Tool to Study Animal–Machine Interaction during Milking but Not to Detect Mastitis

Marnet,

Velasquez,

Dzidic

2024

Animals

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“…For many decades, mechanical milking is spread everywhere, in a different type of dairy farms (cows, sheep, goats, buffaloes and others). It is nowadays common also in traditional small-scale dairy farms of the Mediterranean areas [27][28][29], where different (and sometimes outdated) milking systems are present (bucket, trolley, tethered, small parlors). As in large herd sizes, though also in smaller herds, the number of cows, the financial resource, the skilled workforce and the availability of time are parameters influencing the selection of the milking system.…”

Section: Introductionmentioning

confidence: 99%

Sizing Milking Groups in Small Cow Dairies of Mediterranean Countries

Calvo

Airoldi

2020

Animals

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A dairy farmer chooses the number of milking groups in function of the herd size, stall type and milking system also in small cow dairies (number of animals lower than 100–120). In these dairies, there are different milking systems (bucket, trolley, pipeline, little autotandem, herringbone or parallel parlors) and each of them has a different work routine. The knowledge of the routine is the starting point for assessing the milking installation, because it determines the number of milked cows per hour. Different milking systems have common tasks (as pre-dipping, inspecting foremilk, udder preparation, attaching teat cups, post-dipping), but in the meantime there are different operations that characterize each specific routine (e.g., animal entry and exit if there is a parlor, bucket, trolley or milking group positioning if tie-stall). For this reason, we surveyed twenty small dairy farms located in the Piedmont Region (Italy) with different milking systems to correctly acquire the specific milking routines. Different models were therefore studied using the observed routines in in the examined farms. These models were then used to calculate the number of milked cows per hour and the number of milking groups. The main findings were simple equations, specific for each milking system, easily accessible by the farmer to correctly size his milking system.

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“…However, other factors that also affect SCC in goat milk include parity, stage of lactation, oestrus cycle and breed (Paape et al, 2007;Persson et al, 2014). Udder and teat morphologies, milking frequency, grazing management, milking machine equipment and settings (Marnet et al, 2018) and viral co-infection with CAEV (Sanchez et al, 2001) can all influence SCC, making high SCC difficult to interpret in goats, compared with cows and ewes (Persson and Olofsson, 2011). Further, subclinical mastitis is a problem in goats where prevalence rates are important (reported as 35% to 70%: Leitner et al 2004a;Hall and Rycroft, 2007).…”

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confidence: 99%

Pathogens in milk of goats and their relationship with somatic cell count

Tvarožková,

Tančin,

Uhrinčať

et al. 2023

Journal of Dairy Research

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We evaluated the presence of bacterial pathogens in the milk of goats and their relationship with somatic cell count (SCC) and milk composition. The study was performed on a dairy farm in northern Slovakia. Half udder milk samples were collected from goats in June and July. The samples were divided on the basis of SCC into 4 bands (SCC1 lowest to SCC4 highest). Bacterial pathogens were only detected in 13% of samples. SCC3 and SCC4 had 15 and 25% positive samples respectively compared with SCC1 (2%) and SCC2 (14%). Coagulase-negative staphylococci (CNS) were the most common isolates (73%), of which Staphylococcus caprae was the most frequently isolated (65%). In samples with ≥ 1000 × 103 cells ml− 1 (SCC3, SCC4) there was higher somatic cell score (SCS) in the presence of a pathogen (7.48 ± 0.11) than without a pathogen (7.16 ± 0.05, P < 0.01). Statistically significant but weak negative correlations were observed between SCS and lactose, dry matter and non-fat dry matter. In conclusion, a higher percentage of bacteriologically positive milk samples was observed in both SCC3 and SCC4 groups but this does not explain the aetiology of high SCC in the milk of goats that are apparently free of bacteria. As a diagnostic tool, SCC is probably less useful in goats than in cows.

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Milking Procedures and Facilities

Cited by 7 publications

References 55 publications

Infrared Thermography of Teat in French Dairy Alpine Goats: A Promising Tool to Study Animal–Machine Interaction during Milking but Not to Detect Mastitis

Infrared Thermography of Teat in French Dairy Alpine Goats: A Promising Tool to Study Animal–Machine Interaction during Milking but Not to Detect Mastitis

Sizing Milking Groups in Small Cow Dairies of Mediterranean Countries

Pathogens in milk of goats and their relationship with somatic cell count

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