Area of hock hair loss in dairy cows : risk factors and correlation to a categorical scale

Data from 3691 dairy cows from 76 farms were used to investigate the risk factors associated with area of hair loss over the lateral aspect of the hock, and the correlation between the area of hair loss as calculated using a hock map and hock lesion scores determined using a pre-existing categorical scale. Six factors were associated with a greater area of hair loss, including cows with locomotion score 3, a cleanliness score (10-18/28), high daily milk yield (25.1 - 58.1 kg), poor body condition score (1-1.5), duration of winter housing (≥41 days) and some combinations of cubicle base and bedding materials. Compared with cows housed in cubicles with a concrete base and whole straw or rape straw bedding, cows housed in cubicles with concrete bases with sand or chopped straw bedding had smaller areas of hair loss and cows housed on a mattress base with whole straw or rape straw bedding had a larger area of hair loss. Area of hair loss, as measured on hock maps, was not significantly different between cows with score 1 (median=23.6 cm2) and score 2 (median=20.3 cm2) on the categorical scale for hock lesions. This suggests that the categorical scale was not reflecting the extent of hair loss and that hock maps are a good alternative for studying the dynamics of hock lesions over time. Further work is required to explore the aetiology of hock lesions and find better ways to control this common condition. Keywords: Hock lesions; Hair loss; Dairy cow; Welfare; Hock map

Variation in enteric methane emissions among cows on commercial dairy farms

Methane (CH4) emissions by dairy cows vary with feed intake and diet composition. Even when fed on the same diet at the same intake, however, variation between cows in CH4 emissions can be substantial. The extent of variation in CH4 emissions among dairy cows on commercial farms is unknown, but developments in methodology now permit quantification of CH4 emissions by individual cows under commercial conditions. The aim of this research was to assess variation among cows in emissions of eructed CH4 during milking on commercial dairy farms. Enteric CH4 emissions from 1,964 individual cows across 21 farms were measured for at least 7 days per cow using CH4 analysers at robotic milking stations. Cows were predominantly of Holstein Friesian breed and remained on the same feeding systems during sampling. Effects of explanatory variables on average CH4 emissions per individual cow were assessed by fitting a linear mixed model. Significant effects were found for week of lactation, daily milk yield and farm. The effect of milk yield on CH4 emissions varied among farms. Considerable variation in CH4 emissions was observed among cows after adjusting for fixed and random effects, with the coefficient of variation ranging from 22 to 67% within farms. This study confirms that enteric CH4 emissions vary among cows on commercial farms, suggesting that there is considerable scope for selecting individual cows and management systems with reduced emissions

A heritable subset of the core rumen microbiome dictates dairy cow productivity and emissions

A 1000-cow study across four European countries was undertaken to understand to what extent ruminant microbiomes can be controlled by the host animal and to identify characteristics of the host rumen microbiome axis that determine productivity and methane emissions. A core rumen microbiome, phylogenetically linked and with a preserved hierarchical structure, was identified. A 39-member subset of the core formed hubs in co-occurrence networks linking microbiome structure to host genetics and phenotype (methane emissions, rumen and blood metabolites, and milk production efficiency). These phenotypes can be predicted from the core microbiome using machine learning algorithms. The heritable core microbes, therefore, present primary targets for rumen manipulation toward sustainable and environmentally friendly agriculture.R. John Wallace, Goor Sasson, Philip C. Garnsworthy, Ilma Tapio, Emma Gregson ... John L. Williams ... et al