RESUMEN
Heifers are a fundamental resource on farms, and their importance is reflected in both farm management and economy. Therefore, the selection of heifers to be reared on a farm should be carefully performed to select only the best animals. Genomic selection is available nowadays to evaluate animals in a fast and economic way. However, it is mainly used on the sire line and on performance traits. Ten farms were selected based on their 5-year records of average somatic cell count and evenly classified into high (>300,000 cells/mL) and low somatic cell count (<150,000 cells/mL). Genomic indexes (regarding both wellness and productive traits) were evaluated in 157 Italian Holstein heifers reared in the selected ten farms (90 from high-cells farms and 67 from low-cells ones). Linear mixed models were fitted to analyze the effects of the abovementioned genomic indexes on related phenotypes. Results have shown that farms classified into low somatic cell count had an overall better animal genomic pool compared to high somatic cell count ones. Additionally, the results shown in this study highlighted a difference in wellness genomic indexes in animals from farms with either a high or a low average somatic cell count. Applying genomic tools directly to heifer selection could improve economic aspects related to herd turnover.
RESUMEN
This study was aimed at collecting data on presence, dissemination and persistence of Pseudomonas in small-scale dairy farms. Six farms (located in Piedmont) were visited three times over 2014: 116 waters (wells and different faucets/pipes) and 117 environmental samples (milking equipments and drains) were collected. Enumeration of Pseudomonadaceae was performed, 3-5 colonies/samples were selected for identification via 16SrDNA/oprI polymerase chain reaction (PCR), and typed by enterobacterial-repetitive-intergenic-consensus (ERIC)-PCR. Pseudomonadaceae were detected in 77% of samples. No statistical differences were found among proportions of positives across farms, sample typologies and seasons. Most isolates were Pseudomonas fluorescens (45%), and ERIC-PCR showed 32 persistent types diffused across farms. All in all, Pseudomonas spp. represents a challenge, considering its presence over time in water as well as in teat cups, indicating a continuous source of contamination. Moreover, persistency of strains may indicate biofilm-formation and/or sanitisers resistance, therefore emphasising the role of primary production for preventing milk contamination by Pseudomonas spp.
RESUMEN
Near (NIR) and medium (MIR) infrared reflectance spectroscopy (IR) predictions of fatty acid (FA) composition, expressed as g/kg of milk or g/100g of FA, on fresh and thawed milk were compared. Two-hundred-and-fifty bulk cow milks, collected from 70 farms in northwest Italy, were scanned by MIR in liquid form and by NIR in liquid and oven-dried forms. MIR and NIR FA (g/100g FA) predictions on oven-dried milk were similar for the sum of even chain-saturated FA (ECSFA), odd chain-FA (OCFA), unsaturated FA (UFA), conjugated linoleic acid (CLA), n-3 FA, and C18:1cis9 to C16 ratio. The monounsaturated FA (MUFA), n-6 to n-3 ratio, polyunsaturated FA (PUFA), and n-6 FA were predicted better by NIR on oven-dried milk. The NIR showed worse predictions than MIR for almost all FA, when expressed as g/kg of milk. The NIR predictions on fresh liquid and oven-dried milk were similar, but the reliability decreased for thawed liquid milk. The high performance shown by NIR and MIR allows their use for routine milk FA composition recording.
