Epidemiology of bovine colostrum production in New York Holstein herds: Prepartum nutrition and metabolic indicators

Effect of oxytocin use during colostrum harvest and association of cow characteristics with colostrum yield and IgG concentration in Holstein dairy cows

Our objectives were to determine the effect of oxytocin use during colostrum harvest on colostrum yield (CY) and IgG concentration in Holstein dairy cows on a commercial dairy in New York and to describe associations of cow characteristics with these outcomes. Animals were enrolled between July and October 2023 using a randomized block design, with day of enrollment as the unit of randomization. A median (range) of 10 (3 to 19) cows were enrolled/d. Treatments were 1) 40 IU Oxytocin (OXY40), 2) 20 IU Oxytocin (OXY20), and 3) an untreated control group (CNTR). Oxytocin was administered intramuscularly (IM) approximately 45 s before unit attachment in a rotary parlor. Colostrum weight was measured using the colostrum bucket-embedded scale or a platform scale when the yield was less than the smallest bucket scale. The concentration of IgG ([IgG]) in colostrum was determined using radial immunodiffusion (RID) and used to calculate total IgG, and dry matter (%) was determined by oven drying. Individual cow characteristics such as parity, calf sex, weight, dystocia score, stillbirth, milk production in wk 4 of lactation, and for multiparous cows, dry period length, previous lactation dry off linear score (LS) were collected. Data were analyzed separately for primiparous and multiparous cows using backward stepwise elimination to produce final mixed effects ANOVA models Primiparous cows (n = 201) were randomized to 35.8% (n = 72) OXY40, 32.8% (n = 66) OXY20, and 31.3% (n = 63) CNTR. Multiparous groups (n = 435) were randomized to 34.7% (n = 151) OXY40, 29.7% (n = 129) OXY20, and 35.6% (n = 155) CNTR. The median (range) CY was 6.0 (0 to 20.6) kg and [IgG] was 98.5 (0.1 to 293.6) g/L in the study population. In primiparous cows, OXY40 had a higher colostrum yield (LSM [95% CI]) of 5.4 (4.9 to 5.9) kg compared with both OXY20 (4.1 [3.5 to 4.7] kg) and CNTR (3.8 [3.3 to 4.3] kg) (P < 0.001). In multiparous cows, OXY40, OXY20, and CTNR did not differ in CY (5.9 [5.3 to 6.5], 5.7 [6.3 to 5.1], and 5.4 [6.0 to 4.8] kg, respectively, P = 0.43), but colostrum yield was greater in parity 2 compared with all other parities, cows giving birth to male calves, cows with the highest milk production at wk 4 of lactation, and with a dry period of >65 d. Oxytocin use did not affect [IgG] in either primiparous or multiparous cows (P > 0.56), but [IgG] was highest in cows in parity ≥4 and lowest in cows dry >65 d. In summary, oxytocin use at 40 IU IM in primiparous was associated with a higher CY but not [IgG]. Oxytocin use likely addressed disturbed milk ejection and therefore increased CY in heifers milked for the first time in a rotary parlor. This study confirms cow characteristics associated with colostrum production within a single herd.

Creating models for the prediction of colostrum quantity, quality, and Immunoglobulin G yield in multiparous Jersey Cows from performance in the previous lactation and environmental changes

With multiparous Jersey cows, colostrum production seems to be variable. Due to this, we aimed to identify specific variables involved in colostrum production and quality. From 2021 to 2023, data from 28 US farms (415 multiparous Jersey cows) were used to investigate if colostrum yield, immunoglobulin G concentration (IgG, g/L), and IgG yield (g) could be predicted by farm variables and transmitting abilities. With the data collected, multiple regression equations were developed to aid in predicting colostrum yield, IgG concentration, and IgG yield. Colostrum was weighed and sampled for IgG analysis. Dairy Herd Information (DHI), calving, diet, and management information data were compiled. Days below 5°C (D <), d above 23°C (D >), and d between 5 and 23°C (D) were recorded. Transmitting abilities for milk, fat, protein, and dollars; previous lactation milk yield, fat percent, fat yield, protein percent, protein yield, previous lactation somatic cell score, previous lactation d open, previous lactation d dry, previous lactation d in milk, and previous parity; current lactation parity, d dry, and calving information, birth ordinal d, and latitude were evaluated. Colostrum yield, IgG yield, and concentration had 1 added to correct for values = 0. After addition, values >0 were transformed to ln or log10. Non-transformed variables were also used to develop the model. Variance inflation factor analysis was conducted, followed by backward elimination. The log10 colostrum yield model (r2 = 0.55; β in parentheses) included herd size (-0.0001), ordinal d (-0.001), Ln ordinal d (0.07), latitude (-0.02), dry period length (0.004), D < (-0.005), D (-0.003), time to harvest (0.05), Ln time to harvest (-0.35), IgG (-0.004), log10 IgG (0.46), feedings/d (0.06), Ln pasture access (-0.13), and Ln previous lactation d open (0.14). The model showed that previous lactation d open contributed the most toward increasing and latitude contributed the most toward decreasing colostrum yield. The IgG model (r2 = 0.21) included herd size (0.02), D > (0.38), Ln time to harvest (-19.42), colostrum yield (-4.29), Ln diet type (18.00), Ln previous lactation fat percent (74.43), and previous parity (5.72). The model showed that previous lactation milkfat percent contributed the most toward increasing and time from parturition to colostrum harvest contributed the most toward decreasing colostrum IgG concentration. The log10 IgG yield model (r2 = 0.79) included Ln ordinal d (0.03), time to harvest (-0.01), colostrum yield (-0.11), Ln colostrum yield (1.20), Ln pasture access (-0.09), Ln previous lactation fat percent (0.53), and previous parity (0.02). The model showed that colostrum yield contributed the most toward increasing IgG yield, followed by previous lactation milkfat percent. Pasture access contributed the most toward decreasing IgG yield, though the contribution is very small. These models were validated using 39 samples from 22 farms. Actual minus predicted colostrum yield and IgG concentration and yield were 0.89 kg, -21.10 g/L, and -65.15 g respectively. These models indicate that dry period management and cow information can predict colostrum yield, and IgG concentration and yield.

INVITED REVIEW: Nutritional and management factors that influence colostrum production and composition in dairy cows

Colostrum is a rich source of nutritional and non-nutritional components and is recognized as essential to transfer passive immunity to newborn calves. Because of the individual and seasonal variability in colostrum yield and composition, maintaining an adequate supply of high-quality colostrum year-round remains a challenge for commercial dairy producers. In this narrative review, we described the individual, seasonal, and herd-level variability of colostrum production and summarized the association between individual animal factors such as parity, sex of the calf, calf birth weight, as well as indicators of the cow's metabolic status and the yield and composition of colostrum. Further, we reviewed the current knowledge on the influence of prepartum nutrition and management strategies on colostrum production. Research on the metabolizable energy and protein supplied in the prepartum diet as well as into the inclusion and source of vitamins, minerals, and feed additives suggests prepartum nutrition influences the yield, quality, and composition of colostrum. Furthermore, the prepartum environment and dry period length remain influential factors in the production of colostrum. However, additional research is needed to understand the mechanisms by which prepartum nutrition and management affects colostrum production. Lastly, time to colostrum harvest and oxytocin administration as well as the current knowledge on the effect of heat-treatment and colostrum storage strategies on colostral components were discussed. To conclude, we identify critical gaps in knowledge for future focus of investigation in colostrum research.