Disease-related milk losses directly impact dairy herds' profitability and the production efficiency of the dairy industry. Therefore, this study aimed to quantify phenotypic variability in milk fluctuation periods related to diseases and to explore milk fluctuation traits as indicators of disease resilience. By combining high-frequency daily milk yield data with disease records of cows that were treated and recovered from the disease, we estimated milk variability trends within a fixed period around the treatment day of each record for 5 diseases: udder health, reproductive disorders, metabolic disorders, digestive disorders, and hoof health. The average milk yield decreased rapidly from 6 to 8 d before the treatment day for all diseases, with the largest milk reduction observed on the treatment day. Additionally, we assessed the significance of milk fluctuation periods highly related to diseases by defining milk fluctuations as a period of at least 10 consecutive days in which milk yield fell below 90% of the expected milk production values at least once. We defined the development and recovery phases of milk fluctuations using 3,847 milk fluctuation periods related to disease incidences, and estimated genetic parameters of milk fluctuation traits, including milk losses, duration of the fluctuation, variation rate in daily milk yield, and standard deviation of milk deviations for each phase and their genetic correlation with several important traits. In general, the disease-related milk fluctuation periods lasted 21.19 ± 10.36 d with a milk loss of 115.54 ± 92.49 kg per lactation. Compared with the development phase, the recovery phase lasted an average of 3.3 d longer, in which cows produced 11.04 kg less milk and exhibited a slower variation rate in daily milk yield of 0.35 kg/d. There were significant differences in milk fluctuation traits depending on the disease, and greater milk losses were observed when multiple diseases occurred simultaneously. All milk fluctuation traits evaluated were heritable with heritability estimates ranging from 0.01 to 0.10, and moderate to high genetic correlations with milk yield (0.34 to 0.64), milk loss throughout the lactation (0.22 to 0.97), and resilience indicator (0.39 to 0.95). These results indicate that cows with lower milk losses and higher resilience tend to have more stable milk fluctuations, which supports the potential for breeding for more disease-resilient cows based on milk fluctuation traits. Overall, this study confirms the high impact of diseases on milk yield variability and provides insightful information about their relationship with relevant traits in Holstein cattle. Furthermore, this study shows the potential of using high frequency automatic monitoring of milk yield to assist on breeding practices and health management in dairy cows.

Hematological parameters refer to the assessment of changes in the number and distribution of blood cells, including leukocytes (LES), erythrocytes (ERS), and platelets (PLS), which are essential for the early diagnosis of hematological system disorders and other systemic diseases in livestock. In this context, the primary objectives of this study were to investigate the genomic background of 19 hematological parameters in Holstein cattle, focusing on LES, ERS, and PLS blood components. Genetic and phenotypic (co)variances of hematological parameters were calculated based on the average information restricted maximum likelihood method and 1,610 genotyped individuals and 5,499 hematological parameter records from 4,543 cows. Furthermore, we assessed the genetic relationship between these hematological parameters and other economically important traits in dairy cattle breeding programs. We also carried out genome-wide association studies and candidate gene analyses. Blood samples from 21 primiparous cows were used to identify candidate genes further through RNA sequencing (RNA-seq) analyses. Hematological parameters generally exhibited low-to-moderate heritabilities ranging from 0.01 to 0.29, with genetic correlations between them ranging from -0.88 ± 0.09 (between mononuclear cell ratio and lymphocyte cell ratio) to 0.99 ± 0.01 (between white blood cell count and granulocyte cell count). Furthermore, low-to-moderate approximate genetic correlations between hematological parameters with one longevity, 4 fertility, and 5 health traits were observed. One hundred ninety-nine significant SNP located primarily on the Bos taurus autosomes (BTA) BTA4, BTA6, and BTA8 were associated with 16 hematological parameters. Based on the RNA-seq analyses, 6,687 genes were significantly downregulated and 4,119 genes were upregulated when comparing 2 groups of cows with high and low phenotypic values. By integrating genome-wide association studies (GWAS), RNA-seq, and previously published results, the main candidate genes associated with hematological parameters in Holstein cattle were ACRBP, ADAMTS3, CANT1, CCM2L, CNN3, CPLANE1, GPAT3, GRIP2, PLAGL2, RTL6, SOX4, WDFY3, and ZNF614. Hematological parameters are heritable and moderately to highly genetically correlated among themselves. The large number of candidate genes identified based on GWAS and RNA-seq indicate the polygenic nature and complex genetic determinism of hematological parameters in Holstein cattle.

Milk production rate (MPR) refers to the rate of milk secretion per hour (kg/h), calculated from the harvested milk yield and milking interval, and it is considered an appropriate measure to evaluate the production potential of cows. The objective of this study was to estimate the phenotypic and genetic parameters of milk production rate traits. In this study, the milking records of 4760 Holstein cows were collected, and four milk yield traits and six milk production rate traits were defined. The MIXED procedure was used to detect the impacts of non-genetic effects on milk yield and milk production rate traits, including parity, measured season and lactation stage. Variance and covariance components for milk yield and milk production rate traits were estimated using a univariate linear repeatability model. Parity, measurement season and lactation stage had significant effects (p < 0.01) on milk yield, milk production rate and its stability. Milk yield and milk production traits had high heritability, and ranged from 0.25 to 0.39. The stability of milk production rate had low heritability (0.04~0.05). Milk production rate is beneficial for the devolving novel trait in dairy breeding and provides new insights for herd management and genetic selection of production performance of dairy cattle.

Disease represents a key constraint to farm sustainability by greatly compromising productivity and animal welfare in the dairy industry. Previous research has focused on short-term milk losses during the disease periods. However, in the longer term, cows often fail to fully recover milk yield even after clinical cure. Therefore, the main objective of this study was to quantify the short-term (during the disease period) and long-term (after clinical cure) milk losses and elucidate the causal relationships between diseases and lactation features using large-scale on-farm records and causal inference approaches, thereby enhancing the understanding of disease challenges and helping to reduce their burden. We collected high-throughput session milk yields and disease records (udder health; reproductive, metabolic, and digestive disorders; and hoof health) of 37,246 Holstein cattle from 2020 to 2024. Two causal inference approaches were applied to assess causal effects on milk yield and the variability of session milk yields, including propensity score matching and overlap weighting. Overall, cows of later parities, lower overall resilience, difficult calving, greater number of artificial inseminations, and stillbirth faced higher disease risks, with hazard ratios ranging from 1.05 to 2.40. Genetic analyses revealed that higher milk yield and greater variability in session milk yields were positively genetically correlated with increased disease prevalence. Causal inference revealed that clinical diseases significantly reduced 305-d milk yield by 680.81 ± 0.01 kg per lactation. This causal impact intensified with disease frequency within a lactation, escalating from 646.18 ± 0.01 kg for a single disease onset to 920.83 ± 0.04 kg for multiple onsets, suggesting a nonlinear cumulative burden. For each type of disease, the estimated causal effects on 305-d milk yield ranged from 345.76 ± 0.81 kg for metabolic disorders to 511.72 ± 0.04 kg for reproductive disorders. On average, 7.20% of milk yield was completely unrecoverable after disease cure, ranging from 4.06% for metabolic disorders to 8.42% for digestive disorders. Notably, phenotypic trends, causal estimates, and genetic correlations consistently identified increased variability in session milk yields as a concomitant feature of disease onset. The coefficient of variation increased sharply approximately 5 d before the appearance of clinical signs, rising by 30% for metabolic disorders and up to 58% for digestive disorders, highlighting its potential as an early indicator of diseases in dairy cattle. In summary, this study provides new insights into the causal relationships between diseases and lactation features. Furthermore, it demonstrates the potential of causal inference approaches to advance precision livestock farming.