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.
