LARGE-SCALE PHENOTYPING OF BOVINE COLOSTRUM: IMPLICATIONS FOR QUALITY MONITORING AND GENETIC IMPROVEMENT

Bovine colostrum (BC) is a vital matrix for neonatal calves, providing nutrients and bioactive compounds that support growth, early development, metabolism, and immune function. BC is rich in serum proteins, immunoglobulins (Ig)—particularly the isotype G (IgG) which is the main determinant of passive transfer of immunity (PTI). In addition, key components such as lipids, amino acids, and minerals contribute to its nutritional quality. The effectiveness of PTI from the dam to the calf relies on timely ingestion of sufficient volumes of high-quality colostrum, whereas delay, inadequate intake and low IgG content can compromise calf health, increasing disease susceptibility and mortality. However, reference methods for assessing BC quality are laborious, costly, and unsuitable for large-scale or on-farm application, limiting the real-time decision-making and informed management choices, e.g., banking. This motivates the exploration of rapid, non-destructive spectroscopic and analytical approaches to enable accurate and practical evaluation of BC composition, particularly in terms of immunological quality. The overall objectives of the present thesis were: i) to assess BC quality by evaluating both specific quality traits, such as IgG concentration, and broad compositional traits, including gross (protein, fat, lactose) and fine compositional characteristics (essential amino acids and mineral elements); ii) to develop and validate spectroscopic approaches for rapid, non-destructive, cost-effective, and large-scale phenotyping of BC, ranging from laboratory-based mid- and near-infrared devices to portable on-farm tools, and energy-dispersive X-ray fluorescence (ED-XRF); iii) to investigate the effects of non-genetic factors (e.g., parity, calving season, photoperiod at calving, and BC productivity classes) on BC composition, colostrum yield (CY), and quality; iv) to estimate the genetic parameters of CY and quality traits, and evaluate their potential integration into selective breeding programs aimed at improving calves’ health and welfare. Chapter I focuses on evaluating the potential of mid-infrared spectroscopy using a benchtop instrument for predicting IgG, minor Ig isotypes (IgA and IgM), and total Ig concentrations, as well as fat, protein, and lactose content in BC from Italian Holstein cows. In Chapter II, the application of mid- and near-infrared spectroscopy with benchtop instruments is explored to predict the concentrations of essential amino acids and mineral elements. The phenotypic variability of reference data is analysed to evaluate how the main non-genetic factors, such as parity and calving season, affect these traits. Moreover, correlations between reference data for essential amino acids and mineral elements and Ig fractions are calculated. Chapter III addresses the validation of a portable, on-farm near-infrared spectrometer for real-time BC analysis, covering both IgG concentration and gross and fine composition. Chapter IV investigates the potential of ED-XRF as a novel technique for element quantification, expanding the analytical possibilities beyond infrared methods. Finally, in Chapter V, heritability and genetic correlations are estimated for CY and quality traits, specifically IgG, total Ig, protein, and fat concentrations, in the Holstein population. The same chapter also includes a phenotypic analysis of CY to estimate the influence of parity and photoperiod at calving, and of BC composition traits considering the effects of these factors and BC productivity classes. Using this range of approaches, the study demonstrated practical and cost-effective strategies for evaluating BC quality, providing useful tools for calves’ precision feeding, herd management, and potential industrial applications. Moreover, by examining the influence of genetic variability on BC traits, the present thesis offers new insights that could drive genetic selection toward calves' health in Italian Holsteins.