Intensive Dairy Research Articles

Isolation and antimicrobial sensitivity test of Salmonella isolates from selected intensive dairy farms in Bishoftu town, Central Ethiopia

Salmonella is one of persisting foodborne pathogenic infection particularly food of animal origin including dairy cattle products. Accoringly a cross-sectional study was conducted from July to September 2021 to determine the prevalence and antibiotics resistant of Salmonella in Bishoftu town. To conduct the study 61 samples were collected randomly from the individual lactating cows. The Salmonella was recovered from the samples; conventional culture characterization of Salmonella was conducted by pre-enrichment on the buffered peptone water broth and enrichment in Rappaport- Vassiliadis (RV) broth, subsequently isolation was done on selective XLD and biochemical confirmation of Salmonella isolates. Finally, antibiotic sensitivity tests against the identified isolate were done by using eight drugs. Salmonella was isolated from 13/61 (21.3%, 95% CI: 11.3-31.3) of the total samples. Out of the 13 Salmonella isolates, 11/49 (22.4% 95% CI: 11.4-33.4) and 2/121 (16.7% 95% CI: 4.77-38.17) were isolated from milk cows and milk container respectively with no significance (P-value = 0.362). The isolates were susceptible to Ciprofloxacin, Penicillin and Vancomycin) were susceptible to the isolates, while, Streptomycin, Ampicillin, Tetracycline Rifampicillin and Cloxacillin) were resistant to the isolates. The effectiveness of such drugs like ciprofloxacin may be because they are not widely used in countries like Ethiopia and other African countries for animal’s treatment. 100% rate of resistant was recorded to Ampicillin, Chloramphenicol, Cloxacillin, Streptomycin and Amoxicillin. The study indicated the prevalence of Salmonella with high proportion of multiple antimicrobial resistance to the commercial used in the study area. Therefore, the government, farmers and other stakeholders should give concern for dairy farm hygiene and antibiotics uses in dairy farms.

Probabilistic simulation of phosphorus loss using the Vermont P-index: a bottom-up field to watershed approach

Abstract Anthropogenic nutrient loading from land use, especially agriculture, is a major threat to waterbodies worldwide. Efforts to govern nutrient pollution are increasingly based on simulation modeling for research, evaluation, and regulation. This study develops a novel approach to simulate nutrient losses from agriculture applied to the Lake Champlain basin in the US state of Vermont. The Vermont Phosphorus-Index—a farm-based empirical model regularly used for site evaluation—is scaled up to the basin level with high-resolution geographic data and probabilistic estimation of unknown parameters and management practices. Results are comparable with analyses using more data and computationally intensive tools. Important insights into basin-wide management include: (1) nutrient-management planning can significantly reduce P losses in a livestock-agriculture-dominated watershed by re-distributing manure applications from areas of high loss to low loss; (2) hotspot identification from geographic data alone may be deeply complicated by high underlying heterogeneity of soil phosphorus; and (3) probabilistic modeling using simple, field-scale models is a potentially useful complement to complex watershed process models. Findings suggest that currently available best-management practices will likely be insufficient to reach reduction targets in the most impaired sub-watersheds. Reductions of agricultural land use and herd size, particularly in intensive dairy operations, may be necessary.

The effects of spring feeding strategy on pasture productivity, sward quality, and animal performance within intensive pasture-based dairy systems

The objective of this research was to evaluate how different feeding strategies based on various pasture availability (PA) treatments within intensive seasonal production systems affected pasture production and utilization, sward quality, and the milk production, body weight (BW), and body condition score (BCS) of dairy cows. The performance data were obtained from a 3-yr experiment conducted previously (2018-2020, inclusive). In total, records from 208 spring-calving dairy cows were available for analysis. The animals were randomly allocated to 1 of 3 PA grazing treatments in spring that varied in average pasture cover (measured as herbage mass available above 3.5 cm) that was established via different pasture management strategies in the previous autumn. Thus, the opening average pasture cover across all paddocks on February 1 was 1,100 kg of dry matter (DM)/ha for high pasture availability (HPA), 880 for medium pasture availability (MPA), and 650 for low pasture availability (LPA), respectively. The measurements were taken over an 8-wk period during the first grazing rotation in spring, commencing on February 16 (±2 d) and finishing when all paddocks were grazed once on April 12 (±5 d). Paddocks that were part of the HPA treatment showed the highest pregrazing herbage masses and pregrazing sward heights (1,645 kg of DM/ha and 8.2 cm, respectively) compared with MPA (1,412 kg of DM/ha and 7.5 cm, respectively) and LPA (1,170 kg of DM/ha and 6.9 cm, respectively). Owing to the differences in PA, daily herbage allowance was greatest for HPA (11.7 kg of DM/cow), intermediate for MPA (10.2 kg of DM/cow), and lowest for LPA (8.8 kg of DM/cow), with the remaining feed deficit composed of additional daily grass silage supplementation (0.8, 1.5, and 2.8 kg of DM/cow for HPA, MPA, and LPA, respectively), while the daily concentrate and daily total feed allowance were equal between treatments during spring (2.7 and 15.0 kg of DM/cow). Despite salient differences in fresh pasture used, complementing pasture intake with grass silage did not affect daily or cumulative milk, solids-corrected milk, fat, or protein yield or milk constituents. Similarly, BW and BCS were also unaffected by PA treatment. The results highlight the importance of high spring pasture utilization and grazing efficiency achievable with higher pregrazing herbage masses, which also allow larger animal intakes from grazed pasture as the cheapest feed source during spring. Moreover, targeting an adequate pasture supply at the commencement of calving increases the grazing days per hectare and lowers the requirement for supplementary feed on farm, particularly when facing increasing variability in climatic conditions.

Gastrointestinal parasitic infections in intensive dairy cattle breeding: Update on the epidemiology and associated risk factors in northern Italy.

Parasitic infections such as Strongylida and Eimeria still represent a major health problem of dairy cattle impacting their health, welfare, and productivity. In view of the scarcity of data on risk factors contributing to the spread of parasitic infections in cattle breeding, an epidemiological study in intensive dairy farms in northern Italy was planned. 495 animals (lactating and dry cows, heifers, and calves) from 19 farms were enrolled in the study. Individual fecal samples were analyzed by a quantitative copromicroscopic analysis to detect the number of Strongylida eggs or Eimeria oocysts per gram of faeces (EPG/OPG). Data concerning management, sanitary and biosecurity measures were collected using a questionnaire; a management measures score (MMS) was also calculated. The possible influence of risk factors on Strongylida and Eimeria was thus assessed by statistical analysis using generalized linear mixed models (GLMMs). Eimeria spp. was the most frequently detected parasitic taxon (herd and individual prevalence: 89.5% and 46.2%, respectively), followed by Strongylida (herd and individual prevalence: 63.1% and 16.6%, respectively). The presence of Strongylida resulted associated to the productive category (p-value=0.028), with heifers and dry cows at higher risk of infection than lactating cows and calves, and to the MMS (p-value=0.007). Higher prevalence values were recorded in farms with intermediate or low MMS compared to those with optimal MMS. As regard Eimeria infection, a greater effect of MMS on OPG was recorded in calves when compared to those recorded in heifers (OR=0.228, p-value=0.003) and dry cows (OR=0.241, p-value=0.009). Gastrointestinal parasitic infections still remain an underestimated problem in intensive dairy cattle breeding. MMS may help in the choice of strategies aimed at minimizing the impact of parasites on animal health, thus improving the productivity of the entire herd.

Differences in the microRNAs Levels of Raw Milk from Dairy Cattle Raised under Extensive or Intensive Production Systems.

Studying microRNA (miRNAs) in certain agri-food products is attractive because (1) they have potential as biomarkers that may allow traceability and authentication of such products; and (2) they may reveal insights into the products' functional potential. The present study evaluated differences in miRNAs levels in fat and cellular fractions of tank milk collected from commercial farms which employ extensive or intensive dairy production systems. We first sequenced miRNAs in three milk samples from each production system, and then validated miRNAs whose levels in the cellular and fat fraction differed significantly between the two production systems. To accomplish this, we used quantitative PCR with both fractions of tank milk samples from another 20 commercial farms. Differences in miRNAs were identified in fat fractions: overall levels of miRNAs, and, specifically, the levels of bta-mir-215, were higher in intensive systems than in extensive systems. Bovine mRNA targets for bta-miR-215 and their pathway analysis were performed. While the causes of these miRNAs differences remain to be elucidated, our results suggest that the type of production system could affect miRNAs levels and potential functionality of agri-food products of animal origin.

Towards healthier and more sustainable diets in the Australian context: comparison of current diets with the Australian Dietary Guidelines and the EAT-Lancet Planetary Health Diet

BackgroundThere is increasing focus on moving populations towards healthier and more environmentally sustainable dietary patterns. The Australian Dietary Guidelines provide dietary patterns that promote health and wellbeing. It is unclear how these guidelines align with the more recently published global recommendations of the EAT-Lancet Planetary Health Reference Diet, and how Australian diets compare to both sets of recommendations.MethodsData from one 24-h recall collected for the 2011–13 National Nutrition and Physical Activity Survey were analysed for 5,920 adults aged 19–50 years. Subgroups of this population were identified by diet quality and lower or higher consumption of foods often considered to be environmentally intensive (higher animal meat and dairy foods) or associated with healthiness (higher vegetables and lower discretionary choices). Food group and nutrient composition of Australian diets were compared to diets modelled on the Australian Dietary Guidelines and Planetary Health Reference Diet. The environmental impacts of diets were estimated using an index of combined metrics.ResultsCompared with the Planetary Health Reference Diet, the Australian Dietary Guidelines contained more servings of the vegetable, dairy and alternatives, fruit, and discretionary choices. The amount of meat and alternatives was higher in the Planetary Health Reference Diet than Australian Dietary Guidelines due to the inclusion of more plant-based meat alternatives. The average Australian diet contained two to almost four times the Australian Dietary Guidelines and Planetary Health Reference Diet maximum recommended intake of discretionary choices, and provided inadequate amounts of the vegetables, cereals, unsaturated fats and meats and alternatives food groups, primarily due to lower intakes of plant-based alternatives. The average Australian diet also contained less dairy and alternatives than the Australian Dietary Guidelines. In the average Australian diet, red meat and poultry contributed 73% to the total servings of meat and alternatives compared to 33% and 10% for the Australian Dietary Guidelines and Planetary Health Reference Diet respectively. The modelled Australian Dietary Guidelines diet met the relevant nutrient reference value for all 22 nutrients examined, whereas the Planetary Health Reference Diet contained an inadequate amount of calcium. The environmental impact scores of the Planetary Health Reference Diet and Australian Dietary Guidelines were 31% and 46% lower than the average Australian diet.ConclusionsSignificant changes are required for Australians’ dietary intake to align more closely with national and global dietary recommendations for health and environmental sustainability.

Entrepreneurship in Dairy Cattle Sector: Key Features of Successful Administration and Management

In this study, data envelopment analysis is applied to 47 dairy cattle farms to estimate their level of efficiency in the utilization of the available resources and to identify the most efficient ones. The analysis is based on technical and economic data collected through a farm management survey. The main structural and financial characteristics of the most efficient farms are presented, revealing the features that make them better than their peers. A comparative financial analysis is applied between the efficient and inefficient farms, highlighting the appropriate farm structure and determining the major cost drivers in modern dairy cattle farming. The results show that there is still room for improvement in intensive dairy farming. Dairy cattle farms must operate with increased variable cost and utilize their infrastructure at full capacity to decrease their fixed cost per cow. Farms should increase their economic resilience and be less risk averse in an environment where margins to lower production costs in highly intensive farms have been narrowed down. The findings of this study verify that dairy cattle farms of entrepreneurial mindset have the potential to rise to the future economic, environmental and social challenges that will affect the survival of the sector.

Nutrient use efficiency of intensive dairy farms in China – Current situation and analyses of options for improvement

CONTEXTGlobal dairy production contributes a relatively large share of the total emissions of nitrogen (N) and phosphorus (P) to air and water bodies, which are a concern. However, there are large differences among dairy farming systems in performance, and these differences are not well understood. This relates especially to emerging market economies such as China, where dairy production is increasing, and where new dairy farms are relatively large, intensive, and on small areas of farmland. OBJECTIVESThis study estimated the N and P flows and use efficiencies (NUE and PUE) of 141 dairy farms at the farm, herd, and manure management levels. Emission mitigation technologies were also explored to identify the effects of improving farm nutrient use efficiencies on each farm via scenario analyses. METHODSWe collected data from farm surveys and feed sample analyses. Based on the empirical management data, a nutrient flow model was developed and used for the quantification of nutrient flows. RESULTS AND CONCLUSIONSWe found substantial variation among the farms in NUE (53 ± 20%) and PUE (84 ± 22%) at the farm level, but not at the herd level. Our estimates of NUE and PUE were much higher, and N and P losses were much lower, than previous estimates. The effects of management technologies varied greatly among farms; increases in farm-level NUE ranged from 0 to 53% and in PUE from 0 to 79%. Improving manure storage and treatment technologies and increasing manure export had relatively large effects on farm-level NUE and PUE and nutrient losses, while the effects of low-protein feeding were limited. SIGNIFICANCEOur findings highlight the need for farm-specific technologies targeted to specific aspects of the whole manure management chain to improve the NUE and PUE of the industrial dairy production sector in China. Furthermore, manure application limits are needed to prevent excessive manure applications and nutrient losses from croplands.

Is Dairy Effluent an Alternative for Maize Crop Fertigation in Semiarid Regions? An Approach to Agronomic and Environmental Effects.

Simple SummaryDairy effluent can be an environmental problem if it is not properly managed. Several application technologies exist for its reuse as a source of nutrients in agricultural crops. Our study provides new information on GHG emissions after the application of dairy effluent through a subsurface drip irrigation system on a semiarid soil of the southern Pampean Region (Argentina). In addition, some edaphic properties are compared with conventional chemical fertilization on the yield of a corn crop, contributing as a proposal for an improvement in agricultural sustainability.The reuse of effluents from intensive dairy farms combined with localized irrigation techniques (fertigation) has become a promising alternative to increase crop productivity while reducing the environmental impact of waste accumulation and industrial fertilizers production. Currently, the reuse of dairy effluents through fertigation by subsurface drip irrigation (SDI) systems is of vital importance for arid regions but it has been poorly studied. The present study aimed to assess the greenhouse gas (GHG) emissions, soil properties, and crop yield of a maize crop fertigated with either treated dairy effluent or dissolved granulated urea applied through an SDI system at a normalized N application rate of 200 kg N ha−1. Fertilizer application was divided into six fertigation events. GHG fluxes were measured during fertigation (62-day) using static chambers. Soil properties were measured previous to fertilizer applications and at the harvest coinciding with crop yield estimation. A slight increase in soil organic matter was observed in both treatments for the 20–60 cm soil depth. Both treatments also showed similar maize yields, but the dairy effluent increased net GHG emissions more than urea during the fertigation period. Nevertheless, the net GHG emissions from the dairy effluent were lower than the theoretical CO2eq emission that would have been emitted during urea manufacturing or the longer storage of the effluent if it had not been used, showing the need for life-cycle assessments. Local-specific emission factors for N2O were determined (0.07%), which were substantially lower than the default value (0.5%) of IPCC 2019. Thus, the subsurface drip irrigation systems can lead to low GHG emissions, although further studies are needed.

Concentrations of Essential Trace and Toxic Elements Associated with Production and Manufacturing Processes in Galician Cheese.

The objective of this study was to determine the trace element composition and the toxic metal residues in Galician cow’s milk cheese produced in different systems (artisan, industrial, and organic). Fourteen elements (As, Cd, Co, Cr, Cu, Fe, Hg, I, Mn, Mo, Ni, Pb, Se, and Zn) were determined in 58 representative samples of Galician cheeses by inductively coupled plasma mass spectrometry. The toxic elements were present at low concentrations, similar to those reported for other unpolluted geographical areas. The essential elements were also within the normal range in cheeses. There were no statistically significant differences between smoked and unsmoked cheeses for any of the elements. Chemometric analyses (principal component analysis and cluster analysis) revealed that the industrial cheeses produced in Galicia using the milk from intensive dairy farms were different, in terms of elemental content, from artisan and organic cheeses, in which the elemental contents were similar.

DAIRY CATTLE REPRODUCTIVE PERFORMANCE UNDER DIFFERENT PRODUCTION SYSTEM IN ETHIOPIA: NIGERIA’S BILATERAL TRADE RELATIONS WITH CHINA: AN ASSESSMENT, 2010 – 2019

Reproductive performance of dairy cattle in terms of age at first service (AFS), age at first calving (AFC), calving interval (CI), day open (DO), and a number of service preconceptions (NSPC) in the different production system in Ethiopia is reviewed. The reproductive performance parameter of dairy cattle like age at first serves (AFS), age at first calving (AFC), calving interval (CI), Day opens (DO), and the number of service preconceptions (NSPC) under different production system is quite different. Age at first calving (AFC) in pastoral and agro-pastoral and intensive dairy production systems were 43.5±1.5months and 33.2 months, respectively. Days open (DO) in pastoral and agro-pastoral, smallholder dairy production, and urban and dairy products for local cows were 141±7 days, 185±51.2days, and 199.8±11.60 days, respectively. 85 to 115days considered as optimum for a dairy herd, 116 to 130 days indicate slight problems, 131 to 145 days moderate problems. This, indicated that days open in the different production system is not within the normal range. Similarly, for cross dairy cows in an intensive dairy production system was157.8 days. The calving interval (CI) in pastoral and agro-pastoral, smallholder dairy production systems, urban and pre-urban for local cows were 14.63±10 months, 14.36± 1.03 months, and 22.17±0.79 months, respectively. Whereas urban and pre-urban and intensive dairy production for cross dairy cows were12.42±5.9 months, 15.820±.41months, and 14.56 months, respectively. NSPC for Horro x Jersey (1.8) and Horror (2.1) are not within the normal range, But for Borana (1.6), Fogera (1.28), Friesian x Zebu (1.56) were within the normal range. This difference might be due to poor management in terms of nutrition, health care, housing, heat detection, timely insemination, and breeding as well as environmental factors. It could be concluded that proper management in terms of nutrition, health care, housing, heat detection, and timely insemination would improve reproductive performance under different production systems. Besides this, to boost dairy cattle reproductive performance, intensification of dairy cattle production should be promoted in Ethiopia to meet the increasing demand for dairy products and to reduce imports of dairy commodities. Thus, all coordinated works of all concerned bodies should be in place to boost production and productivity and thereby enhance the livelihood of the dairy farmers.

Dairy Manure Co-composting with Wood Biochar Plays a Critical Role in Meeting Global Methane Goals.

Livestock are the largest source of anthropogenic methane (CH4) emissions, and in intensive dairy systems, manure management can contribute half of livestock CH4. Recent policies such as California’s short-lived climate pollutant reduction law (SB 1383) and the Global Methane Pledge call for cuts to livestock CH4 by 2030. However, investments in CH4 reduction strategies are primarily aimed at liquid dairy manure, whereas stockpiled solids remain a large source of CH4. Here, we measure the CH4 and net greenhouse gas reduction potential of dairy manure biochar-composting, a novel manure management strategy, through a composting experiment and life-cycle analysis. We found that biochar-composting reduces CH4 by 79%, compared to composting without biochar. In addition to reducing CH4 during composting, we show that the added climate benefit from biochar production and application contributes to a substantially reduced life-cycle global warming potential for biochar-composting: −535 kg CO2e Mg–1 manure compared to −194 kg CO2e Mg–1 for composting and 102 kg CO2e Mg–1 for stockpiling. If biochar-composting replaces manure stockpiling and complements anaerobic digestion, California could meet SB 1383 with 132 less digesters. When scaled up globally, biochar-composting could mitigate 1.59 Tg CH4 yr–1 while doubling the climate change mitigation potential from dairy manure management.

Effects of routine treatment with nonsteroidal anti-inflammatory drugs at calving and when lame on the future probability of lameness and culling in dairy cows: A randomized controlled trial

Claw horn lesions (CHL) are reported as the most common cause of lameness in intensive dairy systems. Despite their prevalence, the underlying pathological mechanisms and preventive strategies for CHL remain poorly understood. Recent advances have pointed to the role of inflammation in disease aetiopathogenesis. Moderating inflammation from first calving may lead to long-term benefits and a viable intervention for treating and preventing disease. We conducted a 34-mo randomized controlled trial to investigate the effects of routine treatment with the nonsteroidal anti-inflammatory drug ketoprofen at calving and during treatment for lameness, on the future probability of lameness and culling, caused by exposure to normal farm conditions. A cohort of dairy heifers were recruited from a single, commercial dairy herd between January 8, 2018, and June 22, 2020, and randomly allocated to one of 4 treatment groups before first calving. The lactating herd was lameness scored every 2 wk on a 0 to 3 scale, to identify animals that became lame (single score ≥2a) and hence required treatment. Animals in group 1 received a therapeutic trim and a hoof block on the sound claw (if deemed necessary) every time they were treated for lameness. Animals in group 2 received the same treatment as group 1 with the addition of a 3-d course of ketoprofen (single dose daily) every time they were treated for lameness. Animals in group 3 received the same treatment as group 2 with the addition of a 3-d course of ketoprofen (single dose daily) starting 24 to 36 h after each calving. Animals in group 4 received a 3-d course of ketoprofen (single dose daily) every time they were identified with lameness. No therapeutic trim was administered to this group, unless they were identified as severely lame (a single score ≥3a). Animals were followed for the duration of the study (ending October 23, 2020). Probability of lameness was assessed by a lameness outcome score collected every 14 d. Data on culling was extracted from farm records. One hundred thirty-two animals were recruited to each group, with data from 438 animals included in the final analysis (111 in group 1, 117 in group 2, 100 in group 3, and 110 in group 4). Mixed effect logistic regression models were used to evaluate the effect of treatment group on the ongoing probability of lameness. Compared with the control group (group 1), animals in group 3 were less likely to become lame (odds ratio: 0.66) and severely lame (odds ratio: 0.28). A Cox proportional hazards survival model was used to investigate the effect of treatment group on time to culling. Compared with group 1, animals in groups 2 and 3 were at reduced risk of culling (hazard ratios: 0.55 and 0.56, respectively). The lameness effect size we identified was large and indicated that treating a cohort of animals with the group 3 protocol, would lead to an absolute reduction in population lameness prevalence of approximately 10% and severe lameness prevalence of 3%, compared with animals treated in accordance with conventional best practice (group 1).

The Early Prediction of Common Disorders in Dairy Cows Monitored by Automatic Systems with Machine Learning Algorithms.

Simple SummaryIdentifying cows with a higher risk of health disorders such as clinical mastitis, subclinical ketosis, lameness, and metritis could be advantageous for farms to prevent and ameliorate the negative effects of these disorders in a timely manner. In this study, we adopt eight machine learning algorithms using an R software for analyzing a dataset of 14-dimensions of dairy cows with health disorders across the whole lactation period in intensive Chinese dairy farms, applying automatic monitoring systems and milking systems. The variables analyzed by the machine learning algorithms include milk yield, physical activity, changes in rumination time, and the electrical conductivity of milk. Six parameters were presented to evaluate the performance metrics of the models, with the Rpart algorithm outperforming others and indicating a strong generalization ability of this algorithm. A total of 10 variables of greater importance in three models of Rpart, eXtreme Gradient, and Adaboost demonstrated the consistency of those variables as predictors for disorders of dairy cows monitored by automatic systems. The results obtained in this study highlighted the importance of using big data on the farm to develop predictive and prescriptive decision support tools to boost the development of precision livestock farming.We use multidimensional data from automated monitoring systems and milking systems to predict disorders of dairy cows by employing eight machine learning algorithms. The data included the season, days in milking, parity, age at the time of disorders, milk yield (kg/day), activity (unitless), six variables related to rumination time, and two variables related to the electrical conductivity of milk. We analyze 131 sick cows and 149 healthy cows with identical lactation days and parity; all data are collected on the same day, which corresponds to the diagnosis day for disordered cows. For disordered cows, each variable, except the ratio of rumination time from daytime to nighttime, displays a decreasing/increasing trend from d-7 or d-3 to d0 and/or d-1, with the d0, d-1, or d-2 values reaching the minimum or maximum. The test data sensitivity for three algorithms exceeded 80%, and the accuracies of the eight algorithms ranged from 65.08% to 84.21%. The area under the curve (AUC) of the three algorithms was >80%. Overall, Rpart best predicts the disorders with an accuracy, precision, and AUC of 81.58%, 92.86%, and 0.908, respectively. The machine learning algorithms may be an appropriate and powerful decision support and monitoring tool to detect herds with common health disorders.

Occurrence of Polyphenols, Isoflavonoids, and Their Metabolites in Milk Samples from Different Cow Feeding Regimens

In this work, milk samples collected in a cohort of intensive dairy farms of the Po Valley (Italy) were screened for their (poly)-phenolic profile to check the occurrence of phenolic metabolites of biological interest. The selected dairy farms were previously classified on the basis of their cow feeding system, considering the utilization of corn silage as the main ingredient of the rations. Overall, ultra-high-pressure liquid chromatography coupled with mass spectrometry using an Orbitrap analyzer, followed by unsupervised and supervised statistics, allowed identifying clear different phenolic distributions in the milk samples. Accordingly, a great variability in the phenolic profiles of the different milk samples was observed, with two main phenolic clusters outlined by the unsupervised hierarchical clustering approach and not fully correlated to the nutritional strategy considered. The variables’ importance in the projection approach allowed selecting the most important metabolites, resulting in samples’ discrimination. Among the most discriminative compounds, we found phenolic metabolites (such as hippuric acid and 4-hydroxyhippuric acid), followed by lignans (such as enterolactone) and isoflavonoids (such as equol and O-desmethylangolensin). Taken together, our findings suggested that both the feeding systems and the ability of dairy cows to process parent phenolic compounds were the main factors providing the final (poly)-phenolic profile of the milk samples. Future targeted and ad hoc studies appear of great interest to evaluate the potential biological effects of these compounds on cow health.

Ambient mass spectrometry for rapid authentication of milk from Alpine or lowland forage.

Metabolomics approaches, such as direct analysis in real time-high resolution mass spectrometry (DART-HRMS), allow characterising many polar and non-polar compounds useful as authentication biomarkers of dairy chains. By using both a partial least squares discriminant analysis (PLS-DA) and a linear discriminant analysis (LDA), this study aimed to assess the capability of DART-HRMS, coupled with a low-level data fusion, discriminate among milk samples from lowland (silages vs. hay) and Alpine (grazing; APS) systems and identify the most informative biomarkers associated with the main dietary forage. As confirmed also by the LDA performed against the test set, DART-HRMS analysis provided an accurate discrimination of Alpine samples; meanwhile, there was a limited capacity to correctly recognise silage- vs. hay-milks. Supervised multivariate statistics followed by metabolomics hierarchical cluster analysis allowed extrapolating the most significant metabolites. Lowland milk was characterised by a pool of energetic compounds, ketoacid derivates, amines and organic acids. Seven informative DART-HRMS molecular features, mainly monoacylglycerols, could strongly explain the metabolomic variation of Alpine grazing milk and contributed to its classification. The misclassification between the two lowland groups confirmed that the intensive dairy systems would be characterised by a small variation in milk composition.

Evaluation of environmental and physiological indicators in lactating dairy cows exposed to heat stress.

This study aimed to better understand environmental heat stress and physiological heat strain indicators in lactating dairy cows. Sixteen heat stress indicators were derived using microenvironmental parameters that were measured at the surrounding of cows and at usual fixed locations in the barn by using handheld and fixed subarea sensors, respectively. Twenty high-producing Holstein-Friesian dairy cows (> 30.0kg/day) from an intensive dairy farm were chosen to measure respiration rate (RR), vaginal temperature (VT), and body surface temperature of forehead (FT), eye (ET), and muzzle (MT). Our results show that microenvironments measured by the handheld sensor were slightly warmer and drier than those measured by the fixed subarea sensor; however, their derived heat stress indicators correlated equally well with physiological indicators. Interestingly, ambient temperature (Ta) had the highest correlations with physiological indicators and the best classification performance in recognizing actual heat strain state. Using segmented mixed models, the determined Ta thresholds for maximum FT, mean FT, RR, maximum ET, mean ET, VT, mean MT, and maximum MT were 24.1°C, 24.2°C, 24.4°C, 24.6°C, 24.6°C, 25.3°C, 25.4°C, and 25.4°C, respectively. Thus, we concluded that the fixed subarea sensor is a reliable tool for measuring cows' microenvironments; Ta is an appropriate heat stress indicator; FT, RR, and ET are good early heat strain indicators. The results of this study could be helpful for dairy practitioners in a similar intensive setting to detect and respond to heat strain with more appropriate indicators.

Influence of precision livestock farming on the environmental performance of intensive dairy goat farms

The implementation of Precision Livestock Farming (PLF) concepts has been pointed out as an indirect strategy that could potentially help mitigating the environmental impacts of livestock production systems. To date, few studies have focused on analyzing specifically the relationship among PLF adoption and environmental performance, so sustainability benefits have not yet been quantified for many technologies. Moreover, studies evaluating the environmental impact of dairy production have traditionally focused on cattle, and when exploring sheep or goats, they have often involved extensive, low-productive systems, providing an incomplete picture of the sector. In this study we apply life cycle assessment (LCA) to analyze the environmental impact associated to intensive dairy goat production, and to explore the influence of adopting a smart-farming PLF platform on the environmental performance of a group of dairy goat farms in Spain. The PLF-platform relies on systematic on-farm monitoring of individual animal data, coupled with big data processing and interpretation, which supports farmers to take adequate -and timely-farm management decisions. In order to capture its influence, two different periods were analyzed in five selected farms: a baseline year just before innovation was implemented (2014) and four years after (2018), when most of the effect of improved management was reflected. Results after the PLF-platform implementation showed significant reductions (−11%) in greenhouse gas emissions and similar trends in other impact categories (9–16% reductions). The PLF platform provided a precise monitoring of the productivity, genetic merit and physiological state of each animal, allowing adequate criteria for a number of decision-making processes, such as selecting animals for breeding, replacement or culling. This optimization led to an increase in the genetic selection progress, ultimately reflected on milk productivity. Moreover, a reduction of unproductive periods such as first partum age or dry period length was often achieved. As a result of this general improvement, the efficiency of resource usage in relation to milk (and meat) production was increased, with positive effect on the environmental performance. Production of 1 kg of fat and protein corrected milk (FPCM) resulted in 1.53–1.71 kg CO2 eq. Results in other impacts categories were also in a similar range than previously reported values for highly productive dairy systems, including dairy cattle, which stresses the important role that small ruminant farming can play on environmentally sustainable livestock production, particularly in the Mediterranean context.

Fertilizer potential of slurry from intensive dairy cattle farms in Intensive production forestry systems

Intensive dairy cattle breeding has a relevant social and economic impact in Portugal, particularly in the northern region. This activity generates a high flow of livestock effluents (slurry), rich in important nutrients for plant growth, which can be introduced into intensive production forestry systems. These effluents can provide a good alternative to mineral fertilizers, not only from an economic perspective but, particularly, from the point of view of environmental protection. In the present study, the effect of increasing doses of slurry on tree growth, either with or without mycorrhizal arbuscular fungi (AMF) and plant growth-promoting bacteria (PGPB) inoculation, was evaluated in clones of Paulownia CoT2 and Populus i214, as they are genotypes that have a high efficiency in the mobilization of soil nutrients (namely N) and in the capture of CO2 from the atmosphere, as well as high biomass calorific value. For this purpose, a demonstration field trial was installed, occupying an area of 14,607 m2, where the trees were planted with the compasses of: 2.5 x 1.5 m and 2.5 x 0.75 m, respectively for Paulownia and for Poplar. Prior to transplantation to the field, some plants were inoculated with AMF and PGPB. In the field, the following treatments were performed: T0 - no fertilization, either mineral or organic; T1 - amount of slurry equivalent to 85 kg of N ha-1; T2 - amount of slurry equivalent to 170 kg of N ha-1; T3 - amount of slurry equivalent to 340 kg of N ha-1, both with and without inoculation. Results revealed a significant and positive effect of the slurry application, both in the diameter at breast height (DBH) and total stand height (TH), showing its high fertilizing potential, and, on the other hand, there was no increased contamination by nitrates and by pathogenic microorganism in the leachates for the experimental doses of slurry. Therefore, we can conclude that, under the experimental conditions, the slurry resulting from the intensive exploitation of cattle constitutes an alternative to exclusively mineral fertilization in intensive production forestry systems, either by increasing the production of biomass or by the absence of contamination of aquifers by nitrates and pathogens.

Utility of the Intradermal Skin Test in a Test-and-Cull Approach to Control Bovine Tuberculosis: A Pilot Study in Ethiopia.

Bovine tuberculosis (bTB) is one of the top three, high-priority, livestock diseases in Ethiopia and hence, the need for evaluation of potential control strategies is critical. Here, we applied the test-and-segregate followed by cull strategy for the control of bTB in the intensive Alage dairy farm in Ethiopia. All cattle reared on this farm were repeatedly skin tested using the Comparative Cervical Tuberculin (CCT) test for a total of five times between 2015 and 2021. During the first (October 2015) and second (March 2017) rounds of testing, all reactor animals (>4 mm) were culled, while those that were deemed as inconclusive (1–4 mm) were segregated and retested. At retest, animals with CCT >2 mm were removed from the herd. In the third (December 2017) and fourth (June 2018) rounds of tuberculin testing, a more stringent approach was taken wherein all reactors per the severe mode of CCT test interpretation (>2 mm) were culled. A final herd status check was performed in May 2021. In summary, the number of CCT positives (>4 mm) in the farm dropped from 23.1% (31/134) in October 2015 to 0% in December 2017 and remained 0% until May 2021. In contrast, the number of Single Cervical Tuberculin (SCT) test positives (≥4 mm) increased from 1.8 to 9.5% (from 2017 to 2021), indicating that CCT test might not be sufficient to effectively clear the herd of bTB. However, a more stringent approach would result in a drastic increase in the number of false positives. The total cost of the bTB control effort in this farm holding 134–200 cattle at any given time was conservatively estimated to be ~US$48,000. This, together with the need for culling an unacceptably high number of animals based on skin test status, makes the test-and-cull strategy impractical for nationwide implementation in Ethiopia and other low- and middle-income countries (LMICs) where the infection is endemic. Hence, there is an increased emphasis on the need to explore alternate, affordable measures such as vaccination alongside accurate diagnostics to help control bTB in endemic settings.