Project description:BackgroundEnhancing the post-ruminal supply of arginine (Arg), a semi-essential amino acid (AA), elicits positive effects on milk production. Our objective was to determine the effects of Arg infusion on milk production parameters and aspects of nitrogen (N) absorption and utilization in lactating dairy cows. Six lactating Chinese Holstein cows of similar body weight (508 ± 14 kg), body condition score (3.0 ± 0), parity (4.0 ± 0), milk yield (30.6 ± 1.8 kg) and days in milk (20 ± 2 d) were randomly assigned to 3 treatments in a replicated 3 × 3 Latin square design with 21 d for each period (1 week for infusion and 2 weeks for washout). Treatments were 1) Control: saline; 2) Arg group: saline + 9.42 g/L L-Arg; 3) Alanine (Ala) group: saline + 19.31 g/L L-Ala (iso-nitrogenous to the Arg group). Milk production and composition, dry matter intake, apparent absorption of N, profiles of amino acids (AA) in blood, urea N in urine, milk, and blood, and gene expression of AA transporters were determined.ResultsCompared with the Control or Ala group, the infusion of Arg led to greater expression of AA transporters (SLC7A2 and SLC7A8) and apparent uptake of free AA in the mammary gland, and was accompanied by greater milk yield, milk protein yield and milk efficiency (calculated by dividing milk yield over feed intake), together with lower concentration of urea N [regarded as an indicator of N utilization efficiency (NUE)] in blood and milk. Furthermore, in the cows infused with Arg, the NUE was higher and the concentration of urea N in urine was lower than those in the Ala group, although no differences were detected in NUE and urea N in urine between the Control and Arg group. The infusion of Ala had no effect on those indices compared with the Control.ConclusionsOverall, enhancing the post-ruminal supply of Arg via the jugular vein had a positive effect on the synthesis of milk protein at least in part by increasing gene expression of some AA transporters and uptake of free AA by mammary gland.

Project description:Increased energy demands to support lactation, coupled with lowered feed intake capacity results in negative energy balance (NEB) and is typically characterized by extensive mobilization of body energy reserves in the early postpartum dairy cow. The catabolism of stored lipid leads to an increase in the systemic concentrations of nonesterified fatty acids (NEFA) and -hydroxy butyrate (BHB). Oxidation of NEFA in the liver result in the increased production of reactive oxygen species and the onset of oxidative stress and can lead to disruption of normal metabolism and physiology. The immune system is depressed in the peripartum period and early lactation and dairy cows are therefore more vulnerable to bacterial infections causing mastitis and or endometritis at this time. A bovine Affymetrix oligonucleotide array was used to determine global gene expression in the spleen of dairy cows in the early postpartum period. Spleen tissue was removed post mortem from five severe NEB (SNEB) and five medium NEB (MNEB) cows 15 days postpartum.SNEB increased systemic concentrations of NEFA and BHB, and white blood cell and lymphocyte numbers were decreased in SNEB animals. A total of 545 genes were altered by SNEB. Network analysis using Ingenuity Pathway Analysis revealed that SNEB was associated with NRF2-mediated oxidative stress, mitochondrial dysfunction, endoplasmic reticulum stress, natural killer cell signaling, p53 signaling, downregulation of IL-15, BCL-2, and IFN- ; upregulation of BAX and CHOP and increased apoptosis with a potential negative impact on innate and adaptive immunity. Multiparous Holstein-Friesian cows (n=24) were blocked 2 weeks prior to expected calving date according to parity, body condition score, and previous lactation yield (average lactation 6477M-BM-1354kg) and randomly allocated to mild (MNEB; n=12) or severe (SNEB; n=12) NEB groups. MNEB cows were fed ad lib grass silage and 8 kg day-1 concentrates and milked once daily; SNEB cows were fed 25 kg day-1 silage and 4kg day-1 concentrate and milked three times daily. Measurements of body condition score and EB were used to select cows which showed extremes in EB from each group (MNEB, n=5; SNEB, n=5). Cows were slaughtered on days 6-7 of the first follicular wave after calving (mean number of days post-partum: MNEB mean 13.6 M-BM-1 0.75, range 11M-bM-^@M-^S15; SNEB mean 14.3 M-BM-1 0.56, range 13M-bM-^@M-^S16), based on daily transrectal ultrasonography.At slaughter the entire spleen was removed and weighed, and samples weighing 1 g were dissected, rinsed in RNase-free phosphate buffer, snap frozen in liquid nitrogen, stored for 4 h in dry ice, and subsequently stored at 80M-BM-0C.

Project description:BackgroundNitrate leaching to groundwater and surface water and ammonia volatilization from dairy farms have negative impacts on the environment. Meanwhile, the increasing demand for dairy products will result in more pollution if N losses are not controlled. Therefore, a more efficient, and environmentally friendly production system is needed, in which nitrogen use efficiency (NUE) of dairy cows plays a key role. To genetically improve NUE, extensively recorded and cost-effective proxies are essential, which can be obtained by including mid-infrared (MIR) spectra of milk in prediction models for NUE. This study aimed to develop and validate the best prediction model of NUE, nitrogen loss (NL) and dry matter intake (DMI) for individual dairy cows in China.ResultsA total of 86 lactating Chinese Holstein cows were used in this study. After data editing, 704 records were obtained for calibration and validation. Six prediction models with three different machine learning algorithms and three kinds of pre-processed MIR spectra were developed for each trait. Results showed that the coefficient of determination (R2) of the best model in within-herd validation was 0.66 for NUE, 0.58 for NL and 0.63 for DMI. For external validation, reasonable prediction results were only observed for NUE, with R2 ranging from 0.58 to 0.63, while the R2 of the other two traits was below 0.50. The infrared waves from 973.54 to 988.46 cm-1 and daily milk yield were the most important variables for prediction.ConclusionThe results showed that individual NUE can be predicted with a moderate accuracy in both within-herd and external validations. The model of NUE could be used for the datasets that are similar to the calibration dataset. The prediction models for NL and 3-day moving average of DMI (DMI_a) generated lower accuracies in within-herd validation. Results also indicated that information of MIR spectra variables increased the predictive ability of models. Additionally, pre-processed MIR spectra do not result in higher accuracy than original MIR spectra in the external validation. These models will be applied to large-scale data to further investigate the genetic architecture of N efficiency and further reduce the adverse impacts on the environment after more data is collected.

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Nitrogen efficiency in dairy cows

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