Juan Carlos Angeles-Hernandez

The online version contains supplementary material available at 10.1007/s12011-026-05078-6.

This study evaluated the impact of incorporating citrus pulp (CiP) into the rations of high-producing dairy cows under tropical conditions. Eighteen lactating dairy cows were assigned to two dietary treatments: corn meal (CM) or CiP as the main energy source. Dairy cows were allocated to a crossover design comprising two 21-day periods. The rations were formulated to be isocaloric and isonitrogenous. Replacing CM with CiP reduced the intakes of dry matter (19.9 vs. 19.5 kg/d), organic matter (17.9 vs. 17.4 kg/d), digestible organic matter (12.3 vs. 11.7 kg/d), and crude protein (3.43 vs. 3.35 kg/d), while increasing neutral detergent fibre intake (7.39 vs. 7.63 kg/d). Apparent total tract digestibility decreased for all nutrients, including DM, OM, CP, NDF, and ADF, when CiP replaced CM. Milk production was lower in cows fed CiP than in those fed CM (23.7 vs. 22.7 kg/d), although milk feed efficiency (milk/DMI) was not different. An economic analysis showed that cows fed CM had higher milk gross income and income over feed cost. These results suggest that the partial replacement (60%) of CM with CiP may negatively affect feed intake, nutrient digestibility, milk production, and profitability in dairy cows in tropical regions.

La miel es una sustancia natural dulce que se ha utilizado con fines medicinales y se ha consumido como parte de la dieta desde tiempos prehistóricos. Está compuesta principalmente por monosacáridos (glucosa y fructosa), agua, vitaminas, minerales, enzimas, aminoácidos, ácidos orgánicos y compuestos bioactivos como los fenoles y flavonoides. Diversas investigaciones han relacionado a los compuestos bioactivos con los efectos terapéuticos de la miel de abejas sin guijón, como su capacidad antioxidante, antiinflamatoria, antibacterial, antifúngica y anticancerígena. Sin embargo los estudios sobre los parámetros fisicoquímicos y propiedades biológicas de la miel de abejas sin aguijón son muy pocos, por lo que es necesario realizar más estudios e investigaciones acerca de la miel de abejas sin aguijón.

Energy-demanding processes in animal production rise in tandem with increased nutritional intake. This meta-analysis aimed to quantify the metabolizable energy (ME) requirements for maintenance (kMEm) and metabolizable energy to support metabolism (HiEv), considering genotype and gender, in beef cattle under tropical conditions. A total of 273 individual records of comparative slaughter from seven studies (theses and dissertations) grouped by animal gender (intact males and castrated males), and genotype (Nellore or crossbreed) were used in the current study. We estimated kMEm and HiEv based on the independent variables’ ME intake and full body weight (FBW). The meta-analysis showed no effect of genotype on kMEm (p = 0.66). However, intact males exhibited a 34.41 % lower kMEm compared to castrated males (p = 0.01). Crossbred steers had a 61.33 % higher HiEv than Nellore steers (p < 0.001). Similarly, intact males had a 41.07 % higher energy support demand (p = 0.05) than castrated males. In addition, we observed positive correlations (medium to high) between body protein (r = 0.67; p > 0.001), body fat (r = 0.59; p > 0.001), and retained energy (r = 0.71; p > 0.001) and HiEv. Thus, the greater the deposition of protein (mainly), fat, and body energy, the greater the HiEv. In conclusion, the genotype of the animals did not affect the kMEm. Intact males had lower HiEv than castrated males. Both Nellore steers and intact males utilized HiEv more.

This research paper aimed to develop a supervised machine learning (ML) approach that learns and predicts data-based culling from farm information that reflects the criteria of the decisions taken to cull a cow by a farm manager. Data containing the features of milk yield, days in milk, lactation number, pregnancy status, days open and days pregnant were obtained from January to December 2020 from dairy cows on a large dairy farm in northern Mexico. The cows were labelled as those that were data-based culled ( Cull ) and those that were not culled ( Stay ). Six supervised ML algorithms were evaluated in a binary classification including logistic regression (LR), Gaussian naïve Bayes (GNB), k-nearest neighbors (k-NN), support vector machine (SVM), random forest (RF) and multilayer perceptron (MLP). Each model was subjected to hyperparameter optimization using a grid search approach combined with tenfold stratified cross-validation. This ensured that the class imbalance ( Cull vs. Stay ) was accounted during model evaluation. The best-performing model for each algorithm was selected on cross-validated accuracy. To evaluate the prediction performance of the ML algorithms on both labels from learned data, the metrics accuracy, precision, recall, F ₁ -score and the Matthews correlation coefficient (MCC) were employed. Accuracy among all classifiers was >0.90. The poorest prediction performance was observed in GNB (MCC = 0.50) and LR (MCC = 0.72). Conversely, the rest of the classifiers achieved superior prediction performance in learning the specific culling criteria, reaching an MCC score >0.91. Overall, culling criteria can be learned and predicted by ML algorithms and their performance varies among classifiers. This study identified RF as the best performing algorithm, but k-NN, SVM and MLP are possible candidates to be used in on-farm conditions. To increase their reliability, these approaches need to be tested in several farms, under different scenarios and varieties of features.

For centuries, Scaptotrigona mexicana honey has been treasured in Mexico, where pre-Columbian cultures harvested it not only for its sweet flavor but also for its medicinal and ceremonial purposes. Today, it remains a high-value product in local markets, prized above Apis mellifera honey for its unique sensory qualities and traditional health benefits. Yet its scientific characterization and functional potential remain underexplored. In this study, twenty-four samples from diverse regions were analyzed to quantify bioactive compounds and determine physicochemical composition, α-amylase inhibition, and antioxidant activity. Non-parametric statistical tests revealed distinct compositional clusters, with samples from Cruz Blanca showing exceptional phenolic content and stronger α-amylase inhibition (5.6–49.2%). Antioxidant capacity correlated positively with phenols and flavonoids, showing moderate effect sizes for ABTS (η² = 0.49) and DPPH (η² = 0.37). Compared with Apis mellifera honey, Scaptotrigona mexicana contained more moisture, free acidity, phenols, and antioxidants, but less diastase, hydroxymethylfurfural, and reducing sugars. Importantly, natural α-amylase inhibitors can help modulate postprandial glucose, offering dietary support for type 2 diabetes management. Kinetic analyses (EC50, Vmax, and Km) suggested mixed inhibition. These findings highlight Scaptotrigona mexicana as both a heritage product and a promising functional ingredient for developing foods that merge tradition with metabolic health innovation.

In dairy sheep, optimum nutrition is required to maintain a positive energy and nitrogen balance, and therefore, achieve adequate performance levels. In this sense, supplemental rumen-protected methionine (RPMet) has been a nutritional strategy used to improve the availability of amino acids in sheep for milk production. The aim of the current study is to assess the effect of RPMet supplementation on the milk yield and milk composition of crossbred dairy sheep. Twenty F1 sheep (50% Pelibuey × 50% East Friesian) were randomly assigned to one of the following three treatments: C (control: 0 g/d), 3 g (3.0 g/d), or 6 g (6 g/d) of RPMet added to the basal diet from day 2 to 120 after lambing. Milk yield was significantly higher in sheep supplemented with 6 g of RPMet (p = 0.04) with a linear effect (p < 0.001). In relation to protein yield, the 6 g treatment showed the highest values (55.5 g/day) in comparison with the control (35.2 g/day) and 3 g (42.3 g/day) treatments. Also, lactose (p = 0.02) and non-fat solid yield (p = 0.03) were positively affected by the methionine supplementation. Our results suggest that methionine supplementation is an option to increase milk production, likely associated with the better availability of nutrients of dairy sheep farms using crossbred sheep in regions with an incipient dairy sheep industry.

Background: Antimicrobial resistance (AMR) represents an alarming global public health concern exacerbated by livestock antibiotic misuse, affecting humans and the environment. However, the precise magnitude of antimicrobial residue concentrations in animal‐derived products remains not well understood. This study aimed to quantify antimicrobial residues in animal products through an analytical literature review.Methods: This review covered the scientific articles from 1977 to 2020. The antimicrobials were classified according to the European Medicines Agency (EMA) guidelines into four categories. The final database comprised seven qualitative variables (antibiotic, antibiotic class, region, country, decade, EMA category, animal product and animal species) and one quantitative variable (residue concentration recorded as µg/kg). Due to the number of variables involved in the study, a multivariate analysis approach was used using a Factor Analysis of Mixed Data (FAMD) carried out in R.Results: The highest concentrations of antimicrobial residues were detected in fish samples, followed by egg. Notably, concentrations of ruminant‐derived products were lower than to monogastric. β‐Lactam was the most prevalent residue followed by aminoglycosides, sulphonamides and quinolones, respectively. Moreover, South America had the highest residues levels, followed by Asia and Europe.Conclusions: The multivariate analysis reveals a possible association between the EMA category, animal species, antimicrobial class and animal product. In conclusion, the concentration of antimicrobial residues in products of animal origin depends mainly on their origin (product, species and geographic region), showing the highest concentrations in products derived from fish and poultry.