Sentence examples for cattle level from inspiring English sources

The reduced production volumes reflect the inward shift in fed cattle supply, derived inward shifts in wholesale and retail beef supplies, and derived demand reductions experienced at the feeder cattle level following the increased production costs for feedlots.

At the univariate analysis in this production system, there was no significant association between agro-geographical zone impacts and CBPP sero-geospatial burden at both the cattle level (X 2 = 2.52; p = 0.29) and herd level (X 2 = 2.04; p = 0.36).

There were 19,633 samples (level 1), from 10,039 cattle (level 2) in 102 herds (level 3) with no missing values.

There were three hierarchical levels in the models: routine visits (level 1), clustered by cattle (level 2), and herd (level 3) to control for clustering at the cow and herd levels.

aPart of the Randomised Badger Culling Trial (RBCT) in the south west region with three treatments – reactive proactive or no culling of badgers (survey only) b Standard Error There were 13,595 samples (level 1), from 6,952 cattle (level 2) in 57 herds (level 3) included in the model of herds with seroprevalence < 10%.

βX0 is the intercept, βX is a series of vectors of fixed effects varying at herd (k), cattle (jk) and visit (ijk), ν k + u jk are the variances at the herd and cattle levels respectively, and e ijk is the residual variance.

The models took the form: (1) Y ijk = βX 0 + βX k + βX jk + βX ijk + ν k + u jk + e ijk where Y ijk is the PP value or seropositivity value at visit i from cow j in herd k. βX0 is the intercept, βX is a series of vectors of fixed effect varying at the herd (k), cattle (jk) and visit (ijk), ν k + u jk are the variances at the herd and cattle levels, and e ijk is the residual variance.

The overall cattle-level CBPP sero-positive burdens in nomadic and sedentary pastoral herds were 16.2 % and 9.6 %, respectively.

Statistical significant relationship of the two pastoral cattle populations was also determined by comparing the confidence intervals of their cattle-level sero-positivity.

The overall cattle-level sero-positivity confidence intervals of the two populations were compared and found not to overlap (Tables 1 and 2) and therefore significantly different populations.

At the multivariate regressions, Agro-geographical zone A was more likely (OR 3.42; 95 % CI 1.90, 6.15) to have significant impacts on cattle-level sero-geospatial burden than Agro-zone B. Also, Agro-geographical zone C was more likely (OR 5.14; 95 % CI 2.91, 9.08) to have significant impacts on cattle-level sero-geospatial burden than Agro-zone B (Table 3).