Milk protein content represents a key economic trait in dairy production, yet the genetic architecture underlying this trait remains unexplored in Romanian dual-purpose cattle breeds. This study conducted a genome-wide association analysis for milk protein content in 313 Romanian Simmental (n = 271) and Romanian Brown (n = 42) cows belonging to the Research and Development Station for Bovine Arad, Romania. Following quality control, 33,531 SNPs were tested for association with protein percentage adjusted for other effects (breed, days in milk, season, year, parity) using linear regression with the first five principal components as covariates to control population stratification. Although no SNP reached genome-wide significance (p < 5 × 10⁻⁸), one SNP achieved significance (p < 2.98 × 10⁻⁵) and seven additional SNPs exceeded the nominal threshold (p < 1 × 10⁻⁴) across six chromosomes. The strongest association (p = 9.56 × 10⁻⁶) mapped to chromosome 25 near C7orf61. Biologically relevant candidate genes included KLF6 on chromosome 13, previously associated with milk traits in Chinese Holstein, and AHCYL1 on chromosome 3, involved in calcium homeostasis. These findings provide initial insights into genomic regions influencing milk protein content in Romanian dual-purpose cattle, though validation in larger cohorts needs to be carried out.

Heat stress (HS) is a critical challenge in dairy farming, affecting metabolism, milk production, and overall cow health. This review explores the impact of HS on fatty acid metabolism, milk fatty acid composition, and lipid metabolism shifts under elevated temperatures. While HS typically induces a negative energy balance (NEBAL), studies reveal paradoxical findings regarding non-esterified fatty acids (NEFAs) dynamics, with some reporting increased fat mobilization and others showing blunted NEFA responses. Additionally, short- and medium-chain fatty acids (SCFAs and MCFAs) decline under heat stress, whereas certain long-chain fatty acids (LCFAs), particularly unsaturated fatty acids (UFAs) like C18:1 cis-9, increase, suggesting their role as biomarkers for HS adaptation. The primary tools in this review are the academic databases (PubMed and Google Scholar). These databases were used for literature retrieval based on defined search terms and Boolean operators. The review also highlights genetic variations in fatty acid responses to HS and the potential of specific fatty acids in monitoring heat stress effects. Understanding these metabolic alterations is crucial for developing strategies to mitigate the adverse effects of heat stress in dairy cattle.

Heat stress, indexed by the Temperature–Humidity Index (THI), can alter milk composition; we aimed to quantify the association between daily THI and milk fat (%) and lactose (%) in Romanian Simmental and Romanian Brown cows using routine test-day records. We conducted a retrospective, repeated-measures study of 20,564 test-day observations from 1,123 cows (2014 to 2024), linking each control to same-day THI (observed range ≈28.5–78.7). Linear mixed-effects models with a random intercept for cow included a THI×month interaction and adjustments for breed, parity, and a smooth term for days-in-milk; effects are reported per +10 THI. Results showed season-dependent responses. For fat, higher THI was associated with decreases in mid-summer and late winter (e.g., January −0.12, February −1.09, July −0.21, August −0.75 per +10 THI), but with increases across much of spring and autumn (e.g., March +0.21, April +0.19, May +0.47, September +0.78, October +0.08, November +1.14, December +0.12). For lactose, associations were predominantly negative year-round, with small exceptions (e.g., March +0.03; April ~0): decreases were observed in January −0.047, February −0.171, May −0.111, June −0.135, July −0.064, August −0.097, September −0.121, October −0.050, November −0.048, and December −0.095 per +10 THI. A pooled comparison confirmed concurrent reductions in both fat and lactose during warm months (June–August), whereas outside summer, fat generally increased with THI while lactose remained mildly negative. In conclusion, rising THI is linked to a summer depression of milk fat and modest, broadly negative shifts in lactose; month-specific interactions highlight the importance of modeling seasonal context when evaluating milk-quality resilience in these breeds.

Background: Endurance performance depends on progressive conditioning, controlled metabolic adaptation, and close veterinary supervision. This study documents the physiological and metabolic changes in two Arabian geldings during a 12-week structured conditioning program designed on Long Slow Distance (LSD) principles. Both horses underwent a four-phase training protocol including walking, trotting, cantering, and tapering, with continuous heart-rate and lactate monitoring. Data were recorded weekly for resting heart rate (HRrest), post-exercise heart rate (HR10), lactate concentration, and recovery time. Feeding emphasized slow-release energy substrates (fibre and oil) and electrolyte supplementation. Both horses demonstrated significant cardiovascular and metabolic adaptation. In Horse A, HRrest decreased from 44 to 36 bpm, HR10 from 108 to 68 bpm, and blood lactate from 7.1 to 2.9 mmol/L. Horse B showed a decline from 48 to 38 bpm (HRrest) and from 115 to 72 bpm (HR10), with lactate falling from 7.8 to 3.2 mmol/L. Recovery time improved from >20 min to 8 min. Progressive conditioning improved aerobic fitness, reduced lactic acidosis, and enhanced recovery efficiency. The veterinary role remains essential in designing individualized programs and ensuring physiological adaptation without metabolic or orthopedic compromise

The integration of Artificial Intelligence (AI) into dairy production medicine offers transformative opportunities for herd health management, early disease detection, and nutritional optimization. This study focuses on the use of the milk fat-to-protein ratio as a key indicator of the nutritional status of dairy cows. By analyzing individual milk composition data, AI models can identify deviations from optimal values, revealing dietary imbalances such as over - or under - consumption of concentrates, insufficient structural fiber, or excessive fiber intake. In our study, 235 dairy cows were monitored across two testing periods, generating a total of 470 observations. During the first control, the distribution was dominated by Optimal animals (n=157), with fewer in the Below 1.1 category (n=83) and very few Above 1.5 (n=6). In the second control, the Below 1.1 group increased (n=105), while Optimal declined (n=134); the Above 1.5 group remained small and stable (n=7). Based on these insights, the AI system can provide automated recommendations for adjusting feed rations or regrouping animals according to their milk production performance. AI technologies enable dairy farmers and researchers to process large datasets with unprecedented precision, enhancing decision-making in feeding strategies, disease management, and genetic selection. The adoption of AI not only improves productivity and operational efficiency but also supports sustainable farming practices by optimizing resource use and reducing environmental impact. hese applications highlight AI’s capacity to power integrated e-extension solutions that improve animal health, boost production efficiency, and promote the long-term sustainability of dairy farming systems.

The detection of cell-free fetal DNA (cfDNA) in maternal plasma provides a non-invasive approach for early prenatal diagnosis and fetal sex determination in cattle. The present pilot study aimed to evaluate the feasibility of this method under routine laboratory conditions using plasma samples from pregnant cows. Eight plasma samples were collected from clinically confirmed pregnant cows during mid-gestation. cfDNA was isolated from 300 µL of plasma using a modified protocol based on the QIAamp DNA Mini Kit. Conventional PCR (Polymerase Chain Reaction) assays were applied to amplify Y-chromosome-specific SRY and AMEL gene sequences, while a known male bovine DNA sample served as a positive control. The amplification of a 162 bp fragment of the SRY gene or a double band pattern for the AMEL gene (241 bp for X and 178 bp for Y) was interpreted as indicative of a male fetus. Among the analyzed samples, one cow showed positive amplification for both SRY and AMEL-Y sequences, confirming the presence of a male fetus, whereas the remaining seven samples were negative for Y-specific amplicons, consistent with female pregnancies. These findings confirm the applicability of circulating cfDNA from maternal plasma for non-invasive detection of bovine fetal sex, even when a limited sample number is used. Although this preliminary experiment demonstrates the feasibility of the method, further optimization and validation using a larger population and quantitative PCR analysis are required to determine diagnostic accuracy and to establish cfDNA-based fetal sexing as a reliable routine procedure in cattle breeding programs.