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Mastitis, an important disease in dairy cows, causes significant losses in herd profitability. Accurate diagnosis is crucial for adequate control. Studies using artificial intelligence (AI) models to classify, identify, predict, and diagnose mastitis show promise in improving mastitis control. This bibliometric review aimed to evaluate AI and bovine mastitis terms in the most relevant Scopus-indexed papers from 2011 to 2021. Sixty-two documents were analyzed, revealing key terms, prominent researchers, relevant publications, main themes, and keyword clusters. "Mastitis" and "machine learning" were the most cited terms, with an increasing trend from 2018 to 2021. Other terms, such as "sensors" and "mastitis detection", also emerged. The United States was the most cited country and presented the largest collaboration network. Publications on mastitis and AI models notably increased from 2016 to 2021, indicating growing interest. However, few studies utilized AI for bovine mastitis detection, primarily employing artificial neural network models. This suggests a clear potential for further research in this area.

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The impact of heat stress on dairy cattle leads to significant economic losses and a negative impact on the welfare of the animals. The objective of this research was to evaluate the effect of the nutritional additive (Thermoplus®) in dairy cows under postpartum heat stress conditions, and its effects on the metabolic profile, production and quality of milk. Eighteen lactating Holstein cows (8 multiparous and ten primiparous), in a free-stall system, with a mean body condition score (BCS) of 3.14 ± 0.05, live weight of 624.55 ± 18, 61 kg, with initial mean days in milk (DIM) of 90 ± 10.11, were selected. The animals were grouped into a control (CG, n = 9) and a treatment (TG, n = 9). Both groups underwent 14 days of diet adaptation, the TG received the basal diet supplemented with 50 g of the additive, once a day, individually, while the control group received only the total diet. Data collection of metabolic and productive parameters were evaluated on days -14 (before adaptation), 1 (after the diet adaptation period), 16, 30, and 44. Milk, blood, and body condition score (BCS) were collected once a day, and heart rate, respiratory rate, and rectal temperature were collected twice a day. Serum concentrations of albumin, calcium, magnesium, glucose, gamma-glutamyl transferase (GGT), beta-hydroxybutyrate (BHBA), non-esterified fatty acids (NEFAs), and paraoxonase-1 (PON-1) were evaluated. In the milk, the percentage of fat, protein, lactose, and total solids were determined in each sampling. Milk yield was measured daily. Humidity and ambient temperature values were collected on the days of the collection every 30 min, from 5:30 am to 5:00 pm, to calculate the temperature-humidity index (THI). Statistical analyzes were performed using the SAS software (version 9.3, SAS Institute Inc., Cary, NC, USA). The THI ranged from 62.22 to 79.47. Our findings showed that when the THI was greater than 72, the animals in the TG were able to maintain milk yield (Odds ratio (OD) = -0.0577,), and the animals in the CG had a greater chance of reducing it (OD = -0.2301). Multiparous cows in the TG had higher milk yield than CG (32.57 ± 0.34 vs 30.50 ± 0.36 kg per day; P = 0.0078) and lower SCC (34.110 ± 6,940 vs 665.50 ± 214.41 cells per ml; P = 0.03), with the same percentages of total solids (P > 0.05). In multiparous metabolic markers, TG when compared CG had higher albumin concentrations (2.50 ± 0.07 vs 2.12 ± 0.07 g/dl; < 0.001), equal PON-1 (P > 0.05), and higher BHBA levels (0.49 ± 0.03 vs 0.39 ± 0.04 mmol/l). Primiparous from the CG had higher concentrations of NEFA (0.18 ± 0.02 mmol/l) than multiparous from the same group (0.09 ± 0.02 mmol/l) P = 0.0265. The use of the plant polyphenol extract in postpartum Holstein cows challenged by heat stress had beneficial effects on the production and health of the mammary gland in multiparous cows without decreasing milk solids. The non-reduction of the activities of the acute phase proteins indicates an immunomodulatory and inflammatory-reducing effect of the product used.

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This study aimed to determine the influence of heat stress during the dry period on milk yield and reproductive performance of Holstein cows in a hot environment. Breeding and milk production records of cows, as well as meteorological data between 2017 and 2020 from a commercial dairy herd (n = 12,102 lactations), were used to determine the relationship between climatic conditions during the dry period (average of the temperature-humidity index (THI) at the beginning, middle, and end of the dry period) and reproductive efficiency and milk yield traits. THI was divided into < 70 (no heat stress), 70-80 (moderate heat stress), and > 80 (severe heat stress). First-service pregnancy rate of cows decreased (P < 0.01) with increasing hyperthermia during the dry period (9.5, 7.3, and 3.4% for THI < 70, 70-80, and > 80, respectively). All-service pregnancy rate was highest (P < 0.01) for cows not undergoing heat stress during the dry period (60.2%) and lowest (42.6%) for cows with severe heat stress during the dry period. Cows not experiencing heat stress during the dry period required a mean ± SD of 5.6 ± 3.8 services per pregnancy compared with 6.5 ± 3.6 (P < 0.01) for cows subjected to THI > 80 during the dry period. Cows not suffering heat stress during the dry period produced more (P < 0.01) 305-day milk (10,926 ± 1206 kg) than cows subjected to moderate (10,799 ± 1254 kg) or severe (10,691 ± 1297 kg) heat stress during the dry period. Total milk yield did not differ (P > 0.10) between cows not undergoing heat stress (13,337 ± 3346 kg) and cows subjected to severe heat stress during the dry period (13,911 ± 4018 kg). It was concluded that environmental management of dry cows during hot months is warranted to maximize reproductive performance and milk yield in the following lactation.

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The objective of this observational study was to evaluate estrous expression at the first estrus occurring between 7 to 30 d in milk (DIM), as detected by an automated activity monitor (AAM), and its association with genomic daughter pregnancy rate (GDPR) and genomic expected milk production (GEM) in lactating dairy cows. A total of 4,119 lactations from 2,602 Holstein cows were included. Cows were enrolled as first lactation (n = 1,168), second lactation (n = 1,525) and third and greater lactation (n = 1,426). Hair samples were collected from the tail switch, and cows were genotyped using an SNP platform (Clarifide, Zoetis, São Paulo, SP, Brazil). Postpartum cows were examined daily by the farm personnel from calving until 10 DIM. Calving was classified as assisted (forced calf extraction) and unassisted (normal calving). Retained fetal membranes (RFM), hyperketonemia (KET), and left displaced abomasum (LDA) were also recorded. Mean GDPR (± SD) was -0.29 ± 1.4, and the intensity and duration of the first estrus event was 15.9 ± 13.1 x-factor (intensity unit measurement) and 11.1 ± 3.8 h, respectively. Cows that had greater GDPR had greater intensity and longer duration of estrus at the alert, independent of parity. Overall resumption of estrous expression, between 7 to 30 DIM, was 41.2% (1,695/4,119), where 58.8% (2,424/4,119) did not have an estrus event, 31.0% (1,274/4,119) of cows had one event of estrus, and 10.2% (421/4,119) of cows had 2 or more events of estrus early postpartum. Mean DIM (± SD) at first estrus event, detected by the AAM, was 19.4 ± 4.4 d. Days in milk at first event for cows with one event was 20.7 ± 1.6 d and 15.9 ± 3.1 d for cows with 2 or more events of estrus. First lactation cows were more likely to have an estrus event early postpartum when compared with second and third and greater lactation cows (45.2 ± 1.4% [530/1168] vs. 41.6 ± 1.3% [636/1525] vs. 37.2 ± 1.3% [529/1426], respectively). There was an interaction of parity and GDPR on the proportion of cows demonstrating an early postpartum estrus. There was no difference in the proportion of cows with an early postpartum estrus between those with assisted or unassisted calving, RFM, or LDA. However, cows that had KET were less likely to have an alert early postpartum when compared with cows that did not have KET. Mean genomic expected milk production (± SD) was 256.8 ± 600.1 kg. There was no interaction between GEM and parity on estrous expression (i.e., intensity and duration). There was no interaction between GEM and GDPR on the proportion of estrus early postpartum.

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This study evaluated the effect of different fiber sources supplied with cactus cladodes in diets on the intake and digestibility of nutrients, ingestive behavior, milk yield, and composition of dairy goats. The fiber sources were corn silage, sorghum silage, Digitaria pentzii Stent. hay, and sugarcane bagasse. Twelve Saanen goats with an average weight of 48.9 ± 7.3 kg and average production of 2.8 ± 0.7 kg of milk/day were assigned in three simultaneous 4 × 4 Latin squares (four animals, four treatments, and four experimental periods). There was no difference between the fiber sources for intake (P > 0.05) of dry matter (2.58 kg/day), organic matter (2.30 kg/day), crude protein (0.385 kg/day), neutral detergent fiber (0.895 kg/day), non-fibrous carbohydrates (0.858 kg/day), and metabolizable energy (5.66 Mcal/day). Also, the fiber sources did not influence dry matter and nutrient digestibility (P > 0.05). The association of cactus cladodes with silages, hay, and sugarcane bagasse did not change milk production, milk production corrected for 3.5% of fat and corrected for energy (2.78; 2.53 and 2,55 kg/day, respectively), in addition to milk composition (P > 0.05). No differences were observed in ingestive behavior (P > 0.05). Any fiber sources evaluated are recommended.

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In recent years, machine learning (ML) algorithms have emerged as powerful tools for predicting and modeling complex data. Therefore, the aim of this study was to evaluate the prediction ability of different ML algorithms and a traditional empirical model to estimate the parameters of lactation curves. A total of 1186 monthly records from 156 sheep lactations were used. The model development process involved training and testing models using ML algorithms. In addition to these algorithms, lactation curves were also fitted using the Wood model. The goodness of fit was assessed using correlation coefficient (r), mean absolute error (MAE), root mean square error (RMSE), relative absolute error (RAE), and relative root mean square error (RRSE). SMOreg was the algorithm with the best estimates of the characteristics of the sheep lactation curve, with higher values of r compared to the Wood model (0.96 vs. 0.68) for the total milk yield. The results of the current study showed that ML algorithms are able to adequately predict the characteristics of the lactation curve, using a relatively small number of input data. Some ML algorithms provide an interpretable architecture, which is useful for decision-making at the farm level to maximize the use of available information.

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In Mexico, pasture degradation is associated with extensive pastures; additionally, under these conditions, livestock activities contribute considerably to greenhouse gas (GHG) emissions. Among the options to improve grazing systems and reduce GHG emissions, silvopastoral systems (SPS) have been recommended. The objectives of this work were to quantify the N outflow in a soil-plant-animal interface, as well as the CH4 emissions and milk production in an SPS with woody legumes (Leucaena leucocephala) that is associated with stargrass (Cynodon nlemfuensis). This was then compared with stargrass in a monoculture system (MS) in the seasons (dry and rainy period) over a two-year period. Dung was collected from the animals of each of the grazing systems and applied fresh to the land plots. Fresh dung and urine were collected from the cows of each grazing system and were applied to the experimental plots. In addition, the soil CH4 and N2O contents were measured to quantify the emissions. Average milk yield by seasons was similar: MS (7.1 kg per animal unit (AU)/day-1) and SPS (6.31 kg per AU/day-1). Cows in the MS had a mean N intake of 171.9 g/UA day-1 without seasonal variation, while the SPS animals' mean N intake was 215.7 g/UA day-1 for both seasons. For the urine applied to soil, the N2O outflow was higher in the MS (peak value = 1623.9 µg N-N2O m-2 h-1). The peak value for the SPS was 755.9 µg of N-N2O m-2 h-1. The N2O emissions were higher in the rainy season (which promotes denitrification). The values for the feces treatment were 0.05% (MS) and 0.01% (SPS). The urine treatment values were 0.52% (MS) and 0.17% (SPS). The emissions of CH4 showed that the feces of the SPS systems resulted in a higher accumulation of gas in the rainy season (29.8 g C ha-1), followed by the feces of the MS system in the dry season (26.0 g C ha-1). Legumes in the SPS helped to maintain milk production, and the N2O emissions were lower than those produced by the MS (where the pastures were fertilized with N).

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The traditional point of view regarding dairy cattle selection has been challenged by recent genomic studies indicating that livestock productivity prediction can be redefined based on the evaluation of genomic and phenotypic data. Several studies that included different genomic-derived traits only indicated that interactions among them or even with conventional phenotypic evaluation criteria require further elucidation. Unfortunately, certain genomic and phenotypic-derived traits have been shown to be secondary factors influencing dairy production. Thus, these factors, as well as evaluation criteria, need to be defined. Owing to the variety of genomic and phenotypic udder-derived traits which may affect the modern dairy cow functionality and conformation, a definition of currently important traits in the broad sense is indicated. This is essential for cattle productivity and dairy sustainability. The main objective of the present review is to elucidate the possible relationships among genomic and phenotypic udder evaluation characteristics to define the most relevant traits related to selection for function and conformation in dairy cattle. This review aims to examine the potential impact of various udder-related evaluation criteria on dairy cattle productivity and explore how to mitigate the adverse effects of compromised udder conformation and functionality. Specifically, we will consider the implications for udder health, welfare, longevity, and production-derived traits. Subsequently, we will address several concerns covering the application of genomic and phenotypic evaluation criteria with emphasis on udder-related traits in dairy cattle selection as well as its evolution from origins to the present and future prospects.

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The possible effect of heat stress (HS), measured with the temperature-humidity index (THI) across seasons of the year (SY) upon milk production (MP), feed-to-milk efficiency (FME), and cow comfort (CC) was assessed in Holstein-Friesian cows in northern-arid Mexico. Data from 2467 cows (2146 milking and 321 dry) were recorded across SY [spring (SP), summer (SM), autumn (AT), and winter (WN)] between 2016 and 2019 in an intensive dairy farm located in the Comarca Lagunera (25° NL) with large fluctuations regarding ambient temperature and solar radiation. The THI was stratified into four classes: non-HS, <68; light HS, 68-71; moderate HS, 72-76; and intense HS, ≥77. The considered response variables were Milk production: both on a farm basis (totMP) and on a cow basis (cowMP); Nutritional efficiency: dry matter intake (DMI, kg); Feed conversion efficiency (FCE, kg) and energy-corrected milk (ECM, kg); Percentage of milking cows: (MC%); and Cow comfort: lying time (LT, h). Analyses of variance for unbalanced data were performed through "R". Both totMP and cowMP differed (p < 0.05) as HS increased; the largest values (i.e., 77,886 L and 35.9 L) occurred at lower THIs (i.e., <68 and 68-71) while the milk production fell (i.e., 66,584 L and 31.7 L) with the highest THIs (i.e., ≥77). Not only feed-to-milk efficiency (i.e., DMI, FCE, and ECM) but also the MC% exhibited a similar trend; a visible drop (p < 0.05) occurred from a THI of 68-71 onwards. Furthermore, the LT declined as the THI augmented, from 10.6 h at <68 to 8.5 h at ≥77. Moreover, differences (p < 0.05) also arose across seasons; TotMP, cowMP, DMI, FCE, and ECM revealed their largest (p < 0.05) values in WN and SP, halfway ones in AT, with the lowermost figures in SM. In the same way, cow comfort differed (p < 0.05) among seasons, with diverse lying times (h); WT, 10.5; AT, 10.20; SP, 9.3 h; and 8.8 in SM. Finally, the potential economic burden that HS caused at the producer (USD 233.2 million) and industry-market levels (USD 311.1 M), as well as its impact upon nutrient and alimentary security at the society level (i.e., 311 M milk liters and 195,415.82 Gcal), were also quantified.

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Supplementation of rumen-protected amino acids may improve dairy cow performance but few studies have evaluated the implications of supplementing low-forage diets. Our objective was to evaluate the effects of supplementing rumen-protected methionine (Met) and lysine (Lys) on milk production and composition as well as on mammary gland health of mid-lactating Holstein cows from a commercial dairy farm feeding a high by-product low-forage diet. A total of 314 multiparous cows were randomly assigned to control (CON; 107 g of dry distillers' grains) or rumen-protected Met and Lys (RPML; 107 g dry distillers' grains + 107 g of RPML). All study cows were grouped in a single dry-lot pen and fed the same total mixed ration diet twice a day for a total of 7 weeks. Treatments were top-dressed on the total mix ration immediately after morning delivery with 107 g of dry distillers' grains for 1 week (adaptation period) and then with CON and RPML treatments for 6 weeks. Blood samples were taken from a subset of 22 cows per treatment to determine plasma AA (d 0 and 14) and plasma urea nitrogen and minerals (d 0, 14, and 42). Milk yield and clinical mastitis cases were recorded daily, and milk components were determined bi-weekly. Body condition score change was evaluated from d 0 to 42 of the study. Milk yield and components were analyzed by multiple linear regression. Treatment effects were evaluated at the cow level considering parity and milk yield and composition taken at baseline as a covariate in the models. Clinical mastitis risk was assessed by Poisson regression. Plasma Met increased (26.9 vs 36.0 µmol/L), Lys tended to increase (102.5 vs 121.1 µmol/L), and Ca increased (2.39 vs 2.46 mmol/L) with RPML supplementation. Cows supplemented with RPML had higher milk yield (45.4 vs 46.0 kg/d) and a lower risk of clinical mastitis (risk ratio = 0.39; 95% CI = 0.17-0.90) compared to CON cows. Milk components yield and concentrations, somatic cell count, body condition score change, plasma urea nitrogen, and plasma minerals other than Ca were not affected by RPML supplementation. Results suggest that RPML supplementation increases milk yield and decreases the risk of clinical mastitis in mid-lactation cows fed a high by-product low-forage diet. Further studies are needed to clarify the biological mechanisms for mammary gland responses to RPML supplementation.

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