Dairy Systems Research Articles

Ability of three dairy feed evaluation systems to predict postruminal outflows of amino acids in dairy cows: A meta-analysis

Adequate prediction of postruminal outflows of essential AA (EAA) is the starting point of balancing rations for EAA in dairy cows. The objective of this meta-analysis was to compare the performance of 3 dairy feed evaluation systems (National Research Council [NRC], Cornell Net Protein and Carbohydrate System version 6.5.5 [CNCPS], and National Academies of Sciences, Engineering and Medicine [NASEM]) to predict EAA outflows (Trp was not tested). The data set included a total of 354 treatment means from 70 duodenal and 24 omasal studies. To avoid Type I error, mean and linear biases were considered of concern if statistically significant and representing >5.0% of the observed mean. Analyses were conducted on raw observed values and on observations adjusted for the random effect of study. The analysis on raw data indicates the ability of the feed evaluation system to predict absolute values whereas the analysis on adjusted values indicates its ability to predict responses of EAA outflows to dietary changes. For the prediction of absolute values (based on raw data), NRC underpredicted outflows of all EAA, from 5.3% to 8.6% of the observed mean (%obs.mean) except for Leu, Lys, and Val; NASEM overpredicted Lys (10.8%obs.mean); and CNCPS overpredicted Arg, His, Lys, Met, and Val (5.2 to 26.0%obs.mean). No EAA had a linear bias of concern with NASEM, followed by NRC for His (6.8%obs.mean), and CNCPS for all EAA (5.6 to 12.2%obs.mean) except Leu, Phe, and Thr. In contrast, for the prediction of responses to dietary changes (based on adjusted data), NRC had 2 EAA presenting a linear bias of concern, followed by NASEM and CNCPS with 4 and 6 EAA, respectively. Predictions of His showed a linear bias of concern (5.3 to 9.6%obs.mean) with the 3 feed evaluation systems. Measured chemistry of crude protein and EAA were reported for 1 or more feed ingredients of the ration in 36% of the studies, and resulted in decreased linear biases in the 3 feed evaluation systems. The difference in mean biases of Met outflows was systematically positive when comparing omasal versus duodenal studies. Predictions of Met outflows with NRC had a higher concordance correlation coefficient in duodenal (used to develop NRC equations) versus omasal studies, whereas the opposite was observed with CNCPS, the latter showing the lowest mean bias for Met in omasal sampling studies. The 30% difference in Met mean biases between sampling sites appeared related to a similar difference found for observed Met versus nonammonia nitrogen outflows between duodenal and omasal studies, which is independent of predictions. In conclusion, NRC and NASEM yielded accurate predictions of EAA outflows, with a small superiority of NASEM to predict absolute values, and slight superiority of NRC to predict the responses to dietary changes. In comparison, CNCPS may present mean and linear biases of concern for many EAA. Moreover, it remains to determine which sampling site is more representative of the true supply of EAA to the cows.

Modelling the effect of context-specific greenhouse gas and nitrogen emission mitigation options in key European dairy farming systems

Understanding the environmental consequences associated with dairy cattle production systems is crucial for the implementation of targeted strategies for emission reduction. However, few studies have modelled the effect of tailored emission mitigation options across key European dairy production systems. Here, we assess the single and combined effect of six emission mitigation practises on selected case studies across Europe through the Sustainable and Integrated Management System for Dairy Production model. This semi-mechanistic model accounts for the interacting flows from a whole-farm perspective simulating the environmental losses in response to different management strategies and site-specific conditions. The results show how reducing the crude protein content of the purchased fraction of the diet was an adequate strategy to reduce the greenhouse gas and nitrogen emission intensity in all systems. Furthermore, implementing an anaerobic digestion plant reduced the greenhouse gas emissions in all tested case studies while increasing the nitrogen emissions intensity, particularly when slurry was applied using broadcast. Regarding the productivity increase, contrasting effects were observed amongst the case studies modelled. Moreover, shallow slurry injection effectively mitigated the intensity of nitrogen losses from the fields due to strong reductions in ammonia volatilisation. When substituting urea with ammonium nitrate as mineral fertiliser, site-specific conditions affected the mitigation potential observed, discouraging its application on sandy-loam soils. Rigid slurry covers effectively reduced the storage-related nitrogen emissions intensity while showing a minor effect on total greenhouse gas emission intensity. In addition, our results provide novel evidence regarding the advantages of cumulative implementation of adapted mitigation options to offset the negative trade-offs of single-option applications (i.e. slurry covers or anaerobic digestion and slurry injection). Through this study, we contribute to a better understanding of the effect of emission mitigation options across dairy production systems in Europe, thus facilitating the adoption of tailored and context-specific emission reduction strategies.

Enhancing the Quality of Dairy Products by Reducing the Pilferage and Increase the Efficiency of Logistics Performance by Using Automated Dairy System.

Background: Dairy farming is a vital sector in developing countries, where small farmers contribute approximately 80% of the dairy milk supply. These farmers often rely on traditional practices and are disconnected from technological advancements. This gap highlights the necessity for technology integration to meet the increasing global demand for dairy products. Objective: This research paper aims to prevent water adulteration in milk and enhance the monitoring of the milk trade through an Automated Dairy System, ensuring the provision of pure milk to the public. Methods: Our Automated Dairy System incorporates several components and interfaces, including a Sensor Interface (I/O), Internet Connection Interface, Bluetooth Interface, and Audio Interface. The system enables dairy farmers to check milk quality for impurities before dispatching to vendors and upon arrival. Additionally, it tracks the transportation of milk containers from farms using GPS technology. Results: Initial tests on the prototype demonstrate the system's effectiveness in detecting changes in milk volume, indicating potential adulteration. The GPS tracking feature successfully monitors the transport process, ensuring the milk's purity during transit. Conclusion: The implementation of this Automated Dairy System in dairy farming, especially in Pakistan, represents a significant stride towards improving milk quality and quantity. This innovation not only meets the current technological gap in traditional farming practices but also aligns with the growing global demand for high-quality dairy products. Our system is expected to have a substantial impact on the dairy industry by ensuring the delivery of pure milk to consumers and enhancing the overall efficiency of milk production and trade.

Typification and differentiation of smallholder dairy production systems in smallholder mixed farming in the highlands of southern Ethiopia.

The present study aimed to classify smallholder dairy production systems by analyzing land allocation for various crop types and characterizing them based on integration with specific crops which is gap in earlier studies. A total of 360 smallholder farmers were interviewed to generate firsthand information in addition to using secondary data sources. The classification utilized K-means clustering, while discriminant analysis was applied to accentuate the distinct characteristics of dairy production systems (DPSs). Subsequently, for a particular crop to be considered dominant, the minimum farmland allocation had to exceed 30%. Based on this, the 360 respondent farmers in the study areas were categorized into four distinct DPSs: diversified crop-based (DCB) at 31%, enset-based (EB) at 28%, cereal-based (CB) at 24% and cash crop-based (CCB) with coffee, khat, vegetables, fruits, and sugarcane accounting for 17%. Within the CCB dairy production system, where cash crops were cultivated most dominantly, averaging 56% of the farmland, farmers reported the highest annual income and, consequently, acquired more improved dairy cows, facilitating their entry into intensive dairy production. Ownership of improved dairy cattle breeds, use of agro-industrial byproducts as feed, practicing stall feeding and better housing are observed practices in this DPS that relate to the intensification of dairy production. This positive relationship was observed between the commercialization of crops and the intensification of dairy production in the CCB dairy production system. In the EB dairy system, enset dominates with a 33% area share, leading to increased residues for cattle feed. They keep large herds of local cattle, limited crossbreeding experience, and prefer conventional feeding. The CB system allocates 47% of land to cereals, justifying cereal residues as primary dairy feed. Cultivating grasses like Pennisetum pedicellatum and Phalaris arundinacea is also highly valued in the system. The DCB system, with diverse crops (none exceeding 30%), implies varied residues for dairy feed. These findings reveal unique characteristics across dairy systems, indicating a positive correlation between crop commercialization and dairy intensification. Hence, understanding each type of DPS and its characteristics will help development experts or those in charge of designing agricultural policy to establish the best strategic plans for enhancing the productivity of dairy cattle under smallholder conditions.

Nutrient cycling in dairy systems under different levels of intensification

Nutrient cycling in dairy systems under different levels of intensification

Cattle Welfare in Dairy and Beef Systems: A New Approach to Global Issues - Edited by Marie Haskell (2023). Animal Welfare Series, Volume 23. Published by Springer, Cham, Switzerland, 431 pages. ISBN (hardback): 978-3-031-21019-8. Price: £127.50 (eBook), £159.99 (hardback).

Cattle Welfare in Dairy and Beef Systems: A New Approach to Global Issues - Edited by Marie Haskell (2023). Animal Welfare Series, Volume 23. Published by Springer, Cham, Switzerland, 431 pages. ISBN (hardback): 978-3-031-21019-8. Price: £127.50 (eBook), £159.99 (hardback).

Dairy sheep and goats sort for particle size and protein in mixed rations

Sorting for specific parts or nutrients in feed is a natural behavior of ruminants, but for intensive dairy systems it is disadvantageous if it leads to nutritional imbalances for the individual or the herd. To prevent feed sorting in cattle, mixed rations (MR) are fed and forage components are cut as short as possible. In small ruminants, feed sorting is well documented but not well studied in relation to MR. The aim of this study was to investigate the ability of dairy sheep and goats to feed sort in MR. Experiments were conducted with each of 12 pairs of female adult dairy sheep and goats. In the first experiment, three MR composed of different forages (hay, grass silage, maize silage) were tested consecutively, each in a long and short cutting length variant. In the second experiment, two short cut variants of a grass silage-hay MR were investigated that differed in nutritional value. For all experiments, animals received each variant of MR for five consecutive days. The composition of feed rests at 11:00, 15:00 and the next day were compared to the ration fed at 09:00. Both species sorted all of the offered MR for large particles, and sheep but not goats sorted for protein. In the short cut MR variants, particle size sorting was reduced in the first two hours after feed delivery (09:00–11:00), but cutting length had no relevant effect thereafter, or on protein sorting. The nutritional value of the MR had no detectable influence on feed sorting. Both species sorted for larger particles in both variants, and goats sorted against protein in the first two hours after feed delivery, whereas sheep sorted for protein thereafter. These results show that sheep and goats are able to change the composition of MR within two hours after feed delivery. A short cutting length delayed feed sorting to a limited extent. Maintaining the feed quality of a mixed ration throughout the day is important for the health and welfare of dairy sheep and goats but seems to be a major challenge for feeding management.

Antibiotic quality and use practices amongst dairy farmers and drug retailers in central Kenyan highlands

Understanding antibiotic use in dairy systems is critical to guide antimicrobial stewardship programs. We investigated antibiotic use practices in small-holder dairy farms, antibiotic quality, and antimicrobial resistance (AMR) awareness among veterinary drug retailers in a mixed farming community in the central Kenyan highlands. Data were collected from 248 dairy farms and 72 veterinary drug stores between February 2020 and October 2021. A scale was developed to measure knowledge about AMR and antibiotic use using item response theory, and regression models were used to evaluate factors associated with antibiotic use and AMR knowledge. The active pharmaceutical ingredient (API) content of 27 antibiotic samples was determined using high-performance liquid chromatography (HPLC). The presence and levels of 11 antibiotic residues in 108 milk samples collected from the study farms were also investigated using liquid chromatography tandem mass spectrometry (LC–MS/MS). Almost all farms (98.8%, n = 244) reported using antibiotics at least once in the last year, mostly for therapeutic reasons (35.5%). The most used antibiotics were tetracycline (30.6%), penicillin (16.7%), and sulfonamide (9.4%), either individually or in combination, and predominantly in the injectable form. Larger farm size (OR = 1.02, p < 0.001) and history of vaccination use (OR = 1.17, p < 0.001) were significantly associated with a higher frequency of antibiotic use. Drug retailers who advised on animal treatments had a significantly higher mean knowledge scores than those who only sold drugs. We found that 44.4% (12/27) of the tested antibiotics did not meet the United States Pharmacopeial test specifications (percentage of label claim). We detected nine antibiotics in milk, including oxytetracycline, sulfamethoxazole, and trimethoprim. However, only three samples exceeded the maximum residue limits set by the Codex Alimentarius Commission. Our findings indicate that antibiotics of poor quality are accessible and used in small-holder dairy systems, which can be found in milk. These results will aid future investigations on how to promote sustainable antibiotic use practices in dairy systems.

Genome-wide association study of age at puberty and its (co)variances with fertility and stature in growing and lactating Holstein-Friesian dairy cattle

Reproductive performance is a key determinant of cow longevity in a pasture-based, seasonal dairy system. Unfortunately, direct fertility phenotypes such as inter-calving interval or pregnancy rate tend to have low heritabilities and occur relatively late in an animal's life. In contrast, age at puberty (AGEP) is a moderately heritable, early-in-life trait, that may be estimated using an animal's age at first measured elevation in blood plasma progesterone (AGEP4) concentrations. Understanding the genetic architecture of AGEP4 in addition to genetic relationships between AGEP4 and fertility traits in lactating cows is important, as is its relationship with body size in the growing animal. Thus, the objectives of this research were 3-fold. First, to estimate the genetic and phenotypic (co)variances between AGEP4 and subsequent fertility during first and second lactations. Second, to quantify the associations between AGEP4 and height, length, and body weight (BW) measured when animals were around 11 mo old (SD = 0.5). Third, to identify genomic regions that are likely to be associated with variation in AGEP4. We measured AGEP4, height, length, and BW in around 5,000 Holstein-Friesian or Holstein-Friesian x Jersey crossbred yearling heifers, across 54 pasture-based herds managed in seasonal calving farm systems. We also obtained calving rate (CR42: success or failure to calve within the first 42 d of the seasonal calving period), breeding rate (PB21: success or failure to be presented for breeding within the first 21 d of the seasonal breeding period) and pregnancy rate (PR42: success or failure to become pregnant within the first 42 d of the seasonal breeding period) phenotypes from their first and second lactations. The animals were genotyped using the Weatherby's Versa 50K SNP array (Illumina, USA). The estimated heritabilities of AGEP4, height, length, and BW were 0.34 (0.30, 0.37), 0.28 (0.25, 0.31), 0.21 (0.18, 0.23), and 0.33 (0.30, 0.36), respectively. In contrast, the heritabilities of CR42, PB21 and PR42 were all < 0.05 in both first and second lactations. The genetic correlations between AGEP4 and these fertility traits were generally moderate ranging from 0.11 to 0.60, whereas genetic correlations between AGEP4 and yearling body conformation traits ranged from 0.02 to 0.28. Our genome wide association study (GWAS) highlighted a genomic window on chromosome 5 that was strongly associated with variation in AGEP4. We also identified 4 regions, located on chromosomes 14, 6, 1 and 11 (in order of decreasing importance), that exhibited suggestive associations with AGEP4. Our results show that AGEP4 is a reasonable predictor of estimated breeding values (EBVs) for fertility traits in lactating cows. While the GWAS provided insights into genetic mechanisms underpinning AGEP4, further work is required to test genomic predictions of fertility that use this information.

Carbon footprints, mitigation effects and economic performance of dairy farm systems in Inner Mongolia

CONTEXTReducing the GHG emissions intensity of milk production has become a key sustainability challenge for the dairy sector. Addressing this challenge requires thorough understanding of the current GHG emission levels of individual farms, the practices influencing GHG emissions, and the economic trade-offs associated with reducing those emissions. OBJECTIVEQuantify the carbon footprint (CF) and economic performance of milk production in Inner Mongolia (the main dairy farming region in China), and understand the main contributing factors to them. The effects of potential mitigation options at dairy farm system level were evaluated. METHODS: Life cycle assessment methodology was used to analyze the CF of 15 dairy farms (with year-round cow housing and crop feeding) selected for different milk production levels, herd structures and diet composition. RESULTS AND CONCLUSIONSThe average CF per kg of fat and protein corrected milk (FPCM; after allocation to milk) was 2.3 kg carbon dioxide equivalents (CO2-eq) (1.5–3.4 kg CO2-eq). Emissions related to feed production, manure management and enteric fermentation were the top three GHG emission sources and contributed an average of 27% (5%–46%), 28% (19%–38%) and 18% (14%–25%), respectively, to total emissions. The average cost of the farm system per ton FPCM was USD 540 per year. Feed costs dominated at 70% of the total costs. The CF of milk was negatively correlated with profit per kg FPCM. Mitigation potential of the CF of dairy production for single mitigation strategies ranged from 2.3% to 20.0% compared with business as usual, and combined mitigation measures could reduce emissions by 48.3%. The most effective mitigation measures should focus on decreasing N-fertilizer use per ha for feed crop production and increasing feed crop yield, adjusting herd structure for milk productivity and using localized feed inputs. All mitigation measures had a positive impact on farm profit, except for the improved manure management (changing the farms using manure composting to a static compost system and changing natural storage to direct land application). Therefore, the combination of crop and dairy production and manure management offer the greatest potential to reduce the GHG emissions from Inner Mongolia dairy farm systems. Economic subsidies and extension of findings to farmers might encourage more rapid adoption of these technologies. SIGNIFICANCEThe insights from our study can provide guidance for defining and prioritizing mitigation strategies for dairy production to reduce GHGs emission in other rapidly developing countries and regions with crop-based housed-cow dairy production.

On-Farm Methane Mitigation and Animal Health Assessment of a Commercially Available Tannin Supplement in Organic Dairy Heifers.

The objective of this experiment was to demonstrate the effectiveness of a commercially available tannin product (Silvafeed® ByPro, 70% tannic acid) as an enteric methane (CH4) mitigation and preventative animal health strategy in Holstein heifers (BW = 219 ± 17 kg; 9 mo), reared under organic production system requirements. Twenty heifers were randomly assigned to one of four commercial tannin supplementation treatments as follows: 0% (0 g/hd/d; CON), 0.075% (~5 g/hd/d; LOW), 0.15% (~10 g/hd/d; MED), and 0.30% (~21 g/hd/d; HIG) of dry matter intake (DMI). Heifers received their treatment in individual animal feeding stanchions and were fed a basal total mixed ration (TMR) through four SmartFeed Pro intake measurement bunk systems (C-Lock Inc., Rapid City, SD, USA) for 45 d. An automatic head chamber system (AHCS; i.e., GreenFeed, C-Lock Inc., Rapid City, SD, USA) was used to continuously evaluate enteric CH4 production. No effect was observed among the treatments for CH4 emissions (p ≥ 0.55), animal performance (p ≥ 0.38), or oxidative stress biomarker concentration (p ≥ 0.55). Superoxide dismutase (SOD) and reduced glutathione (GSH) concentrations exhibited a linear response to increasing tannin dose (p = 0.003), indicating a potential tannin effect on the antioxidant status of dairy heifers. This observation may encourage future tannin research relating to animal health, which may be of particular interest to organic dairy systems. The results of this study suggest that tannin supplementation at 0%, 0.075%, 0.15%, and 0.30% of DMI, did not alter CH4 emissions, animal performance, or oxidative stress biomarker concentration in organic Holstein heifers when assessed under an on-farm research approach. Further, the results of this study affirm the challenges associated with on-farm research and the development of climate-smart strategies that are capable of mitigating climate impacts in less controlled environments under standard working conditions.

CowScreeningDB: A public benchmark database for lameness detection in dairy cows

Lameness is one of the costliest pathological problems affecting dairy animals. It is usually assessed by trained veterinary clinicians who observe features such as gait symmetry or gait parameters as step counts in real time. With the development of artificial intelligence, various modular systems have been proposed to minimize subjectivity in lameness assessment. However, the major limitation in their development is the unavailability of a public database, as most existing ones are either commercial or privately held. To tackle this limitation, we have introduced CowScreeningDB, a multi-sensor database which was built with data from 43 dairy cows. Cows were monitored using smart watches during their normal daily routine. The uniqueness of the database lies in its data collection environment, sampling methodology, detailed sensor information, and the applications used for data conversion and storage, which ensure transparency and replicability. This data transparency makes CowScreeningDB a valuable and objectively comparable resource for further development of techniques for lameness detection for dairy cows. In addition to publicly sharing the database, we present a machine learning technique which classifies cows as healthy or lame by using raw sensory data. To facilitate fair comparisons with state-of-the-art methods, we introduce a novel benchmark. Combining the database, the machine learning technique and the benchmark validate our major objective, which is to establish the relationship between sensor data and lameness. The developed technique reports an average accuracy of 77 % for the best case scenario and presents perspectives for further development. By introducing this framework which encompasses the database, the classification algorithm and the benchmark, we significantly reduce subjectively in lameness assessment. This contribution to lameness detection fosters innovation in the field and promotes transparent, reproducible research in the pursuit of more effective management of dairy cow lameness. ImplicationsLameness detection is one of the main tasks in dairy systems, given its importance in the production ambit. However, the data used during detection is generally either held privately or sold commercially. In this study, we create a multi-sensor database (CowScreeningDB), which can be used for lameness. Because we have made the database public11(CowScreeningDB can be downloaded from https://github.com/Shahid-Ismail/CowScreeningDB-A-public-database-for-lameness-detection or https://gpds.ulpgc.es/) and free of charge for research purposes, it should act as a benchmark allowing to objectively compare techniques put forth to deal with lameness. We also provide details of the sampling system used, comprised of hardware and a baseline classification algorithm.

Biocontrol capacity of bacteria isolated from sawdust of the dairy cattle production environment

This research paper aimed to find endemic bacteria from the cattle production system to control the growth of mastitis pathogens. Bacteria were isolated from compost barn sawdust of two dairy cattle systems and later tested to verify their ability to control the growth of Staphylococcus aureus isolates obtained from cattle with mastitis. Bacterial isolates from these systems were tested to verify biocontrol capacity using the double-layer method. A total of 189 isolates were obtained from all samples by considering the morphology of the different bacterial colonies, with 30 isolates showing positive results for the growth control of at least one S. aureus strain and 19 isolates showing the ability to control more than one pathogen strain. The ability to control more than one pathogen and present a significant halo of inhibition in our isolates represents positive traits in the search for cattle mastitis biocontrol microorganisms. Thus, the results obtained represent the range of bacteria capable of controlling the pathogens without the use of antibiotics.

Enteric methane emission factors of smallholder dairy farming systems across intensification gradients in the central highlands of Ethiopia

BackgroundFollowing global pledges to reduce greenhouse gas (GHG) emissions by 30% by 2030 compared to the baseline level of 2020, improved quantification of GHG emissions from developing countries has become crucial. However, national GHG inventories in most Sub-Saharan African countries use default (Tier I) emission factors (EFS) generated by the Intergovernmental Panel on Climate Change (IPCC) to estimate enteric CH4 emissions from animal agriculture. The present study provides an improved enteric CH4 emission estimate (Tier II) based on animal energy requirements derived from animal characteristics and performance data collected from about 2500 cattle in 480 households from three smallholder farming systems to represent the common dairy farming in the central highlands of Ethiopia. Using average seasonal feed digestibility data, we estimated daily methane production by class of animal and farming system and subsequently generated improved EF.ResultsOur findings revealed that the estimated average EF and emission intensities (EI) vary significantly across farming systems. The estimated value of EF for adult dairy cows was 73, 69, and 34 kg CH4/cow/year for urban, peri-urban, and rural farming systems, respectively. Rural dairy farming had significantly higher emission intensity (EI) estimated at 1.78 CO2-eq per kg of fat protein-corrected milk (FPCM) than peri-urban and urban 0.71 and 0.64 CO2-eq kg−1 FPCM dairy farming systems, respectively. The EF estimates in this study are lower than the IPCC's (2019) default value for both stall-fed high-productive and dual-purpose low-productive cows.ConclusionsThe current findings can be used as a baseline for the national emission inventory, which can be used to quantify the effects of future interventions, potentially improving the country's commitment to reducing GHG emissions. Similarly, this study suggests that increased animal productivity through improved feed has a considerable mitigation potential for reducing enteric methane emissions in smallholder dairy farming systems in the study area.

Eco‐efficiency of leys—The trigger for sustainable integrated crop‐dairy farming systems

AbstractThe specialisation of agricultural systems in Western Europe and the intensification of livestock and cropping production are intrinsically linked to substantial resource inputs. This intensified approach frequently leads to nutrient surpluses and biodiversity loss, resulting in detrimental environmental impacts. A transformative agricultural shift is imperative in light of climate and environmental protection objectives. Addressing this need, the Lindhof eco‐efficient pasture‐based milk production initiative, initiated in 2016, is a tangible manifestation of a productive and profitable dairy system integrated within a ley‐based Integrated Crop‐Livestock System (ICLS). Operational at the organically managed Lindhof farm, this approach involves a rotational stocking system of spring‐calving Jersey cows stocked on grass‐clover‐herb leys embedded within a cash crop rotation. The dairy cows benefit from these highly productive swards, rich in nutritive value comparable to concentrate feeding. At the same time, the cultivated crops derive advantages from the legacy effect of leys due to nutrient exchange facilitated by grazing excreta and residual crop matter. Compared to specialised systems, the ley‐based ICLS emerges as an alternative dairy production paradigm that supports many ecosystem services – including minimised nutrient losses, a lower carbon footprint and positive contributions to agro‐biodiversity. These outcomes are realised without compromising overall land‐use efficiency while reducing environmental and social costs of 20–30 Eurocent per kg of milk produced compared to specialised systems. Thus, the ley‐based ICLS conforms to the principles of ecological intensification, enhancing functional diversity within the agricultural landscape. Essentially, the Lindhof initiative represents a holistic and environmentally responsible approach to farming that could contribute to realising the EU Farm to Fork Strategy.

Youth engagement in livestock production and marketing in East Africa

There is limited empirical evidence about how youth engage in livestock production in East Africa. The primary objective of this article is to better understand youth engagement in the livestock sector, namely commercialization and marketing. We compare youth to non-youth in four areas: livestock asset ownership, access to and use of services and improved practices and lastly, market participation. Our framework draws upon agricultural transformation concepts to suggest a tentative pathway through which livestock can support youth in transitions. We draw upon quantitative data and analyze and compare youth to nonyouth in intensive and extensive livestock systems in Kenya, Uganda, Ethiopia, and Tanzania and investigate four livestock systems, dairy, extensive ruminants, pig, and chicken systems. The results showed that there were no systematic youth-specific trends across the asset ownership, levels of commercialization or market participation. Also, low asset ownership did not generate observable youth specific differences in market participation. Rather, education and improved practices correlate with higher levels of market participation. Exploring how livestock are acquired and implications upon asset-based approaches is recommended to better understand the potential of livestock as a source of income during youth transitions in different livestock systems. More evidence is needed to inform and tailor policy approaches to support equitable opportunities in the livestock sector better. Research into understanding how social factors, including gender, shape youth opportunities and constraints, is needed.

Serovars, Virulence and Antimicrobial Resistance Genes of Non-Typhoidal Salmonella Strains from Dairy Systems in Mexico.

Salmonella isolated from dairy farms has a significant effect on animal health and productivity. Different serogroups of Salmonella affect both human and bovine cattle causing illness in both reservoirs. Dairy cows and calves can be silent Salmonella shedders, increasing the possibility of dispensing Salmonella within the farm. The aim of this study was to determine the genomic characteristics of Salmonella isolates from dairy farms and to detect the presence of virulence and antimicrobial resistance genes. A total of 377 samples were collected in a cross-sectional study from calves, periparturient cow feces, and maternity beds in 55 dairy farms from the states of Aguascalientes, Baja California, Chihuahua, Coahuila, Durango, Mexico, Guanajuato, Hidalgo, Jalisco, Queretaro, San Luis Potosi, Tlaxcala, and Zacatecas. Twenty Salmonella isolates were selected as representative strains for whole genome sequencing. The serological classification of the strains was able to assign groups to only 12 isolates, but with only 5 of those being consistent with the genomic serotyping. The most prevalent serovar was Salmonella Montevideo followed by Salmonella Meleagridis. All isolates presented the chromosomal aac(6')-Iaa gene that confers resistance to aminoglycosides. The antibiotic resistance genes qnrB19, qnrA1, sul2, aph(6)-Id, aph(3)-ld, dfrA1, tetA, tetC, flor2, sul1_15, mph(A), aadA2, blaCARB, and qacE were identified. Ten pathogenicity islands were identified, and the most prevalent plasmid was Col(pHAD28). The main source of Salmonella enterica is the maternity areas, where periparturient shedders are contaminants and perpetuate the pathogen within the dairy in manure, sand, and concrete surfaces. This study demonstrated the necessity of implementing One Health control actions to diminish the prevalence of antimicrobial resistant and virulent pathogens including Salmonella.

Milk Protein Hydrolysis by Actinidin-Kinetic and Thermodynamic Characterisation and Comparison to Bromelain and Papain.

Plant proteases, including actinidin, papain and bromelain, have been widely used in the food industry but with limited application in dairy systems. This research aimed to establish and compare operational parameters (kinetics, temperature, enzyme type, time and thermodynamics) relevant to the applications of these enzymes in the hydrolysis of whey protein isolates (WPI), whey protein concentrates (WPC) or milk protein concentrates (MPC). The degree of hydrolysis (DH) increased with the rise in temperature, and the maximum DH was achieved at 60 °C for all three dairy systems. The addition of papain resulted in a greater %DH of whey proteins in comparison to bromelain. The cleavage of proteins was clearly time-dependent (p < 0.05), while the pH did not change significantly (p > 0.05) during this time. PAGE analysis revealed that all three enzymes mainly acted on α-lactalbumin and αs-casein in WPI and MPC, respectively. Kinetic parameters from the Lineweaver-Burk plot at 60 °C using WPC and MPC as a substrate varied widely, establishing that WPC hydrolysis was characterised by a lower KM, higher kcat, kcat/KM and Vmax compared to MPC in the case of all three enzymes. The difference in kcat/KM values amongst all enzymes (actinidin > papain > bromelain) indicated the difference in the strength of substrate binding sites. The thermodynamic parameters of these enzymes with MPC and WPC were also determined at a temperature range of 15-60 °C, and the results indicate the potential application of papain and actinidin in the dairy industry.

Farm management and husbandry practices associated with spontaneous humeral fractures in New Zealand dairy heifers

ABSTRACT Aims To use a farm-based survey to identify characteristics of the New Zealand dairy system associated with the risk of spontaneous humeral fracture in dairy heifers. Methods A questionnaire was designed and made available in print and online to collect information from dairy farmers and/or veterinarians, across New Zealand, about the management and nutrition of cows from birth to first lactation. Data were collected from July 2019 to March 2020 from farms that either had recorded (case farms) or not recorded (control farms) cases of humeral fractures in dairy heifers. Results A total of 68 completed questionnaires were returned, with 35 responses from case farms and 33 responses from control farms. Twenty-six responses (38%) were from the South Island (13 case farms and 13 control farms) and 38 responses (56%) were from the North Island (20 case farms and 18 control farms). For four questionnaires (6%) farm location was not given. Adjusting for the effect of age when calves accessed pasture, case farms had increased odds of having Holstein-Friesian Jersey crossbreed cows as the predominant breed (OR = 9.7; 95% CI = 3.1–36.0; p < 0.001). Adjusting for the effect of breed, allowing calves access to pasture a week later decreased the odds of being a case farm (OR = 0.68; 95% CI = 0.47–0.90; p = 0.006). Conclusions Cows being Holstein-Friesian Jersey crossbreed was identified as a possible risk factor associated with spontaneous humeral fracture in dairy heifers in New Zealand. Given the small sample size, the likely multifactorial aetiology for humeral fractures, and the non-randomised survey, this risk factor, and the possible association between age at turn out and herd production with humeral fractures, all require further investigation.

Seasonal dynamics of bulk milk somatic cell count in grazing Norwegian dairy goats

Somatic cell count (SCC) is a widely used indicator of milk quality in the dairy industry. It is a relatively good indicator of udder health in dairy cows, but strongly confounded by non-infection factors, including season, in dairy goats. This study's objectives were to estimate the variation in SCC explained by season and stage of lactation. We also investigated associations between SCC and other milk quality parameters routinely measured, including total bacterial count, fat, protein, and lactose content, in different seasons and stages of lactation. In this observational study, we included results from the routine analyses of bulk milk samples (n = 5,180) collected every third day in 88 Norwegian goat herds through one year. Herd information was collected via a questionnaire and from the dairy herd recording system. The herds had a notable increase in bulk SCC associated with the pasture season. The median bulk SCC was 470,000 cells/mL in deliveries from the indoor spring period and 1,100,000 cells/mL in the pasture season. During the indoor fall season, when most goat herds are in late lactation, the median SCC was 940,000 cells/mL. The combined effect of the season and herd stage of lactation explained 53.5% of the variation in bulk milk SCC. Fat and protein contents varied significantly with season and stage of lactation, and the association with SCC was non-significant for fat content and explained less than 3% of the variation in protein content. Lactose content was associated with SCC, stage of lactation, and season. Total bacterial count was associated with SCC and the indoor seasons. Determination of normal seasonal variation of goat bulk milk SCC is necessary to establish thresholds for defining milk as abnormal and unacceptable for further processing and improving the usefulness of SCC as a tool for milk quality improvement in dairy goats. The results suggest that SCC thresholds for taking action to improve the milk quality should be adjusted for season and stage of lactation.