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The growth of the world population is leading to an increased demand for food production. Consequently, there is a need to update agricultural processes to enhance production. Smart farming has evolved as a farm management concept that leverages real-time, dependable, and site-specific agricultural information to ensure consistent and sustainable yields. This study focuses on soil nutrient analysis, specifically nitrogen (N), phosphorus (P), and potassium (K) for enhancing crop production. Maintaining an appropriate balance of NPK is crucial for the well-rounded nutrition of crops. Various environmental factors such as temperature, rainfall, humidity, and soil pH affect the NPK composition of agricultural land. The optimal usage of NPK levels can help to improve plant growth, increase crop yields, and enhance overall farm productivity. Hence, we have proposed a stack regressor learning algorithm comprising of two layers for accurate, reliable, and context-sensitive predictions of NPK levels. The proposed approach considers the combined impact of these environmental factors and predicts the optimal NPK requirements tailored to specific crops and agricultural land. The analysis of graphs demonstrates that the predictive accuracy of the proposed stacked regressor model far surpasses that of preexisting built-in machine learning models. This study helps farmers make informed decisions, leading to productivity and sustainability. [ABSTRACT FROM AUTHOR]

As part of sustainable agricultural innovations and the alternative food movement, agroecology provides important tools to achieve the sustainable development goals (SDGs). Yet very few existing studies have explicitly addressed their linkages. Synergies among the SDGs are often examined at the national level, overlooking nuanced opportunities revealed by small agroecology initiatives at the local scale. Based on literature review, field visits and semi-structured interviews with farms and relevant organizations in China, this research investigates how locally embedded agroecology practices lead to advancement of multiple SDG targets and facilitate the synergies among the SDGs. It also highlights their motivations, achievements, and challenges. We argue that the technocentric metrics of SDGs underappreciate the application of traditional knowledge and small-scale low-tech innovations. By bringing visibility to low-tech and small agroecology initiatives, this paper advocates for stronger inclusion of grassroots agroecology initiatives in SDG discussions among researchers and policy makers. [ABSTRACT FROM AUTHOR]

• Understanding the dynamics of N 2 O and CH 4 fluxes avoids emissions during storage. • Manure discharge release significant N 2 O and CH 4 emissions due to feed inefficiency. • Shortening manure storage is the most viable management at smallholder dairy farms. • Trade-offs between reducing CH 4 or N 2 O fluxes often appears in manure management. Storing manure emits greenhouse gas (GHG) emissions, including nitrous oxide (N 2 O) and methane (CH 4). However, the emissions from types of manure stored at smallholder dairy farms remains unknown. Hence, the study aims to analyse the dynamics of N 2 O and CH 4 from different types of dairy manure as affected by storage periods. We collected samples from fresh manure (FM-DF1), manure from communal ponds in an urban dairy farm (IP-DF1, FP-DF1, MS-DF1), fresh manure from an urban dairy farm (FM-DF2), and fresh (FM-DF3), separated (FS-DF3), and fermented manure (FR-DF3) from a peri -urban dairy farm, and stored them for eight weeks and analyse them using the closed chamber method. The changes of manure composition including total solids (TS), nitrogen (N), ammonia–nitrogen (N-NH 3), and carbon (C) were analysed. Results indicated an increase TS in all treatments except for MS-DF1, while N, N-NH 3 , and C content decreased in all treatments. The N 2 O emissions formed at the start, peaked in the middle, and declined towards the end storage period. The CH 4 emissions peaked at the start and decreased until the end storage period. Treatment FM-DF2 yield highest cumulative of N 2 O (0.82 g/m2) and CH 4 (41.63 g/m2) compared to other fresh manure treatment. A mixed model analysis detected a significant interaction (p < 0.05) between manure types and storage periods. In conclusion, manure types and storage periods affect the emissions. Changes in manure concentration during storage and animal diets are two important factors influencing emissions. Strategies to reduce emissions include reducing moisture content in manure, shortening storage periods, and improving feed quality. [ABSTRACT FROM AUTHOR]

The recalcitrant, fibrous protein keratin is found in the outermost layer of vertebrate skin, feathers, hair, horn, and hooves. Approximately, 10 million tons of keratin wastes are produced annually worldwide, of which around 8.5 million tons are from feather wastes. The biodegradation of keratin has been a challenge due to the lack of understanding of biological parameters that modulate the process. Few soil-borne microbes are capable of producing keratinase enzyme which has the potential to degrade the hard keratin. However, various pesticides are abundantly used for the management of poultry farms and reports suggest the presence of the pesticide residues in feather. Hence, it was hypothesized that pesticides would interact with the substrate-binding or allosteric sites of the keratinase enzyme and interferes with the keratin-degradation process. In the present study, molecular interactions of 20 selected pesticides with the keratinase enzyme were analyzed by performing molecular docking. In blind docking, 14 out of 20 pesticides showed higher inhibitory potential than the known inhibitor phenylmethylsulfonyl flouride, all of which exhibited higher inhibitory potential in site-specific docking. The stability and strength of the protein complexes formed by the top best potential pesticides namely fluralaner, teflubenzuron, cyhalothrin, and cyfluthrin has been further validated by molecular dynamic simulation studies. The present study is the first report for the preliminary investigation of the keratinase-inhibitory potential of pesticides and highlights the plausible role of these pesticides in hindering the biological process of keratin degradation and thereby their contribution in environmental pollution. Illustration depicting the hypothesis, experimental procedure, and the resultant keratinase-inhibitory potential of selected pesticides. [ABSTRACT FROM AUTHOR]

The present study aims to characterise dairy cattle farms in two Algerian agro-ecological regions; the semi-arid region (SAR) and the arid region (AR). The survey was carried out on 213 farms. Accordingly, more than 40% of farms are characterised by small herds with ≤15 heads/farm and ≤5 dairy cows/herd. SAR farms benefit from both agricultural land types of 1–300 ha (Used Agricultural Area UAA and pastoral area), while the Saharan ones rely on small UAA. Fertility levels were higher in SAR farms where is recorded a fertility index ≤2 in 92.6% and open period ≤90 days postpartum in 68.6% with a mean lactation length exceeding 305 days in 44.6% farms. The average daily milk yield is 15 litres/cow in both regions. It is recommended to implement strategic and reliable farm management to improve herd management, minimise constraints, and maximise production, particularly in the AR. [ABSTRACT FROM AUTHOR]

This document discusses the use of intelligent approaches in animal husbandry to accelerate genetic progress, ensure animal welfare, and protect the environment. It highlights various innovative methods such as using sexed semen, implementing estrus synchronization protocols, and applying artificial insemination to produce animals with desirable traits and reduce herd sizes. The document also emphasizes the importance of automated sensor systems and diagnostic methods for monitoring animal health and behavior, as well as the digitization of the technological process for efficient management decisions. The special issue covers a range of topics related to intelligent animal husbandry, including dairy animals, pigs, silkworms, rabbits, and chickens. It also addresses challenges in rearing specific sexes of animals and the need for intelligent solutions in waste management, animal behavior recognition, and diagnostic tools. The document acknowledges that there are still unresolved issues and limitations in implementing artificial intelligence in animal husbandry, but it encourages further research and the development of advanced digital tools. Overall, the special issue aims to stimulate discussions and provide valuable insights for farmers interested in incorporating intelligent approaches in their practices. [Extracted from the article]

Simple Summary: This study involved 138 Holstein dairy calves from one UK farm, who were either reared individually or as pairs until 2–4 weeks of age, when they were subsequently batched together. Although there were no differences in growth rate, disease treatments or mortality, the paired calves demonstrated improved behavioural indicators of calf welfare. In addition, the heaviest calf in the pair grew more quickly and displayed less fear and more exploratory behaviour than the lightest calf in the pair. Although recent advice to farmers has been to rear calves in pairs, this study suggests that this may be potentially detrimental to the smaller calf. Previous research has indicated that preweaned dairy calves reared in pairs compared with individually have improved performance and indicators of animal welfare. One hundred and thirty Holstein female calves completed the trial, with eighty-five being allocated to paired housing and forty-five calves being allocated to individual housing. Daily live weight gain (DLWG), treatments and mortality were recorded throughout the preweaning period. Salivary cortisol, latency to feed and latency to approach a novel object were assessed at batching. There were no significant differences in DLWG, mortality and disease treatments between the average of the pair and the individually housed calves, although the pair-reared calves were quicker to approach the milk feed after batching and interacted more quickly with a novel object. The heaviest born calves within the pair had the highest DLWG from birth to weaning, with a higher percentage of calves approaching the novel object, compared with the lightest born calf within the pair. This study shows that calves within a pair may have significantly different performance and welfare during the preweaning period, with the heavier calf outperforming and displaying less fear and more exploratory behaviour than the lighter calf within a pair. [ABSTRACT FROM AUTHOR]

The study focused on the prediction of the Temperature Vegetation Dryness Index (TVDI), an agricultural drought index, for a Mango orchard in Tamale, Ghana. It investigated the temporal relationship between the meteorological drought index, Standardized Precipitation Index (SPI), and TVDI. The SPI was calculated based on utilizing precipitation data from the World Meteorological Organization (WMO) database (2010–2022) and CMIP6 projected precipitation data (2023–2050) from 35 climate models representing various Shared Socioeconomic Pathway (SSP) climate change scenarios. Concurrently, TVDI was derived from Landsat 8/9 satellite imagery, validated using thermal data obtained from unmanned aerial vehicle (UAV) surveys. A comprehensive cross-correlation analysis between TVDI and SPI was conducted to identify lag times between these indices. Building on this temporal relationship, the TVDI was modeled as a function of SPI, with varying lag times as inputs to the Wavelet-Adaptive Neuro-Fuzzy Inference System (Wavelet-ANFIS). This innovative approach facilitated robust predictions of TVDI as an agricultural drought index, specifically relying on SPI as a predictor of meteorological drought occurrences for the years 2023–2050. The research outcome provides practical insights into the dynamic nature of drought conditions in the Tamale mango orchard region. The results indicate significant water stress projected for different time frames: 186 months for SSP126, 183 months for SSP245, and 179 months for both SSP370 and SSP585. This corresponds to a range of 55–57% of the projected months. These insights are crucial for formulating proactive and sustainable strategies for agricultural practices. For instance, implementing supplemental irrigation systems or crop adaptations can be effective measures. The anticipated outcomes contribute to a nuanced understanding of drought impacts, facilitating informed decision-making for agricultural planning and resource allocation. [ABSTRACT FROM AUTHOR]

Farming management and alterations in land cover play crucial roles in driving changes in biodiversity, ecosystem functioning, and the provision of ecosystem services. Whereas land cover corresponds to the identity of cultivated/non-cultivated ecosystems in the landscape, farming management describes all the components of farming activities within crops and grassland (i.e., farming practices, crop successions, and farming systems). Despite extensive research on the relationship between land cover and biodiversity at the landscape scale, there is a surprising scarcity of studies examining the impacts of farming management on biodiversity at the same scale. This is unexpected given the already recognized field-scale impact on biodiversity and ecosystem services, and the fact that most species move or supplement their resources in multiple patches across agricultural landscapes. We conducted a comprehensive literature review aimed at answering two fundamental questions: (1) What components of farming management are considered at the landscape scale? (2) Does farming management at the landscape scale impact biodiversity and associated ecosystem functions and services? We retrieved 133 studies through a query on the Web of Science, published from January 2005 to December 2021 addressing the broad notion of farming management at the landscape scale. The key findings are as follows: (1) The effect of farming management components at the landscape scale on biodiversity was tackled in only 41 studies that highlighted that its response was highly taxon-dependent. They reported positive effects of organic farming on pollinators, weeds, and birds, as well as positive effects of extensification of farming practices on natural enemies. (2) Most studies focused on the effect of organic farming on natural enemies and associated pests, and reported contrasting effects on these taxa. Our study underscores the challenges in quantifying farming management at the landscape scale, and yet its importance in comprehending the dynamics of biodiversity and related ecosystem services. [ABSTRACT FROM AUTHOR]

The evaluation and monitoring of drought, a complex disaster, are essential issues for the planning of agricultural activities and the operation and management of water resources. In this study, the meteorological drought of the Black Sea region in northern Turkey is evaluated with the Standardized Precipitation Index (SPI) and Reconnaissance Drought Index (RDI) methods at 3-, 6-, and 12-month time scales. Meteorological parameters obtained between 1965 and 2019 from 28 meteorological observation stations are used to analyze the drought. Drought-wet period percentages, percentages of occurrence of drought classes, critical period, and negative peak index values are investigated. As a result of the study, it is observed that the percentage of drought occurrence at all time scales is higher than 50% at two stations in the study region, which received precipitation above the average of Turkey. The sum of the extreme drought (ED) and severe drought (SD) values throughout the region is approximately 15% for the whole area. There is a high correlation coefficient, 97.8, 97.6, and 97.3 for the 3-, 6-, and 12-month time scales, respectively, between the SPI and RDIst methods in the evaluation of meteorological drought in the Black Sea region, which is generally a rainy region. It is determined that with the increase in the time scale, the percentage of ED occurrence increased and the risk level of the region around RDI and 17089 station is the highest. It has been determined that the correlation between oscillation indices and meteorological drought indices for the Black Sea region is almost non-existent. The highest correlation value between the oscillation and meteorological drought indices in the region is obtained with the Atlantic Multidecadal Oscillation (AMO). [ABSTRACT FROM AUTHOR]

Clinical lameness has an impact on animal welfare and profitability in different livestock industries. The objective of this study was to estimate the prevalence and incidence rate of clinical lameness within New Zealand dairy goat farms. Up to 3246 goats on three dairy goat farms were observed 4–5 times over one year. Data on locomotion scores and animal information were collected between June 2019 and June 2020. A 5-point (0–4) locomotion scoring scale was used, where scores 3 and 4 were classified as clinical lameness. The average herd-level prevalence of clinical lameness for farms A, B, and C were 23, 12, and 10%, respectively. The annual incidence rate of clinical lameness for farms A, B, and C were 104, 56, and 55 cases per 100 goat-years, respectively. Lameness appears to be a significant welfare issue, with incidence varying between farms and between goats. Investigating both farm-level and goat-level factors is required to understand the epidemiology of lameness and design evidence-based control and prevention measures. Further investigation should be undertaken to identify variables affecting the goat's odds of becoming clinically lame. This study sets the foundation for future study of lameness in commercial dairy goat farms nationally and internationally. [ABSTRACT FROM AUTHOR]

Context: Managing people outside the farm family unit is a new issue for many Irish dairy farmers. In the context of rapid growth, the demand for employees has increased, creating the need for Irish dairy farmers to have human resource management (HRM) skills. Aims: This paper explores the extent and type of HRM practices adopted by Irish dairy farmers and the factors that influence their adoption. Methods: A questionnaire was developed, piloted, and issued to farmers on the basis of herd size and location. Data from 203 dairy farmers who employ people were analysed to examine the adoption of different HRM practices and the influence of farm characteristics, farmer demographics and farmer attitudes on their adoption. HRM practices included compliance with employment legislation, health and safety, different approaches to recruitment, workforce management and retention. The questionnaire included one or more variables for each of these HRM practices. Where more than one variable was included, an aggregate variable was developed for that practice. Key results: Whereas, overall, there was a low level of adoption of best HRM practices, farm characteristics such as herd size and number of employees had a significant influence on farmers' adoption of compliance with employment legislation, health and safety, recruitment, workforce management and retention practices. Demographic factors such as age, level of education, and average hours worked influenced farmers compliance with employment law legislation, workforce management practices and retention practices. Conclusions: The study highlighted an overall low compliance with employment legislation and low adoption of best practices in managing staff among dairy farmers in Ireland. Implications: This study highlighted that improvement is needed in all areas of HRM on Irish dairy farms. The findings of this study would be useful to farm advisors who support dairy farmers in improving their management of their businesses. Overall, this study has contributed to a greater understanding of the challenges in managing people in agriculture and how certain factors influences the adoption of HRM practices on dairy farms. The dairy industry's recent growth in Ireland has resulted in a high demand for additional workers, increasing the requirement for farmers to be skilled in Human Resource Management (HRM). This study identified that the adoption of HRM practices is influenced by farm characteristics, in particular herd size, the number of employees on the farm. This study has contributed insights into the prevalence of specific HRM practices on Irish dairy farms, and indicated that there is a significant scope for improvement. A novel aspect of this study was the focus on the potential factors that influence the adoption of HRM practices on Irish dairy farms. The findings of this study could be used by agricultural advisors and those working in HRM to provide tailored advice to support dairy farmers and other small business owners in managing their employees. [ABSTRACT FROM AUTHOR]

Introduction: Reducing antibiotic use in production animal systems is one strategy which may help to limit the development of antimicrobial resistance. To reduce antimicrobial use in food‐producing animals, it is important to first understand how antibiotics are used on farm and what barriers exist to decreasing their use. In dairy production systems, mastitis is one of the most common reasons for administering antimicrobials. Therefore, it is important to understand the motivations and behaviours of dairy farmers in relation to the diagnosis, treatment and prevention of mastitis. Materials and methods: In this study, we interviewed a sample of dairy farmers and dairy industry professionals from the major dairying regions of eastern Australia regarding their current practices used to diagnose, treat, and control subclinical and clinical mastitis. Inductive thematic analysis was used to code interview transcripts and identify the recurrent themes. Results: Four overarching themes were identified: (1) the challenges associated with the detection and diagnosis of clinical mastitis, including with laboratory culture, (2) the motivations behind treatment decisions for different cases, (3) decisions around dry cow therapy and the role of herd recording, and (4) concerns regarding the development of antimicrobial resistance. Discussion: This study identifies several challenges which may limit the ability of Australian dairy farmers to reduce antimicrobial use on farm, such as the need for rapid and reliable diagnostic tests capable of identifying the pathogenic causes of mastitis and the difficulties associated with conducting herd recording for the implementation of selective dry cow therapy. Industry professionals were concerned that farmers were not using individual cow records to aid in treatment decisions, which could result in unnecessary antimicrobial use. The results of this study can act as the basis for future research aimed at assessing these issues across the broader Australian dairy industry. [ABSTRACT FROM AUTHOR]

Mycobacterium avium ssp. paratuberculosis (MAP) is the causative agent of bovine paratuberculosis, also known as Johne's disease. This infection is responsible for negative effects, ranging from reduction of milk production to reproductive compromise and increased susceptibility to other diseases such as mastitis. Contradictory information on the association between this infection and reproductive performance has been reported in dairy cows. The aim of this work was to investigate associations between individual cow MAP seropositivity and lifetime reproduction and production performance. The MAP serum ELISA (IDEXX MAP Ac) results from all the 13,071 adult cows present on 191 farms and corresponding birth- and calving-date records obtained from the National Association for Genetic Improvement of Dairy Cattle were used. Cows and farms were classified as positive or negative, based on ELISA results. Outcomes assessed were age at first calving (AFC), intercalving intervals (ICI) from first to fourth interval, and average milk production per day of productive cycle (Milk-305/ICI, a ratio between 305-d corrected milk production and the number of days of the respective calving interval). Multilevel mixed models were used to investigate the association of cow MAP status with AFC, ICI, and Milk-305/ICI. Three levels were considered in the models: "measurement occasion," the first level, was nested within cows and cows were nested within farms. The "measurement occasion" is the time point to which all the observed measures (between 2 successive parturitions, such as milk production and somatic cell count) were referred. Our results indicate that MAP-positive cows have a significantly lower 14-d mean AFC than MAP-negative cows. The overall average ICI in our study was 432.5 d (standard deviation: 94.6). The average ICI, from first to fourth, was not significantly affected by MAP seropositivity. No significant effect of MAP positivity was found on the overall ICI. In relation to Milk-305/ICI, MAP-positive cows did not produce significantly less milk than negative cows across their productive lifetime. We observed higher but nonsignificant Milk-305/ICI (kg/d) in MAP-positive cows. In our study, the proportion of MAP-positive cows within lactations remained similar across all lactations, suggesting that seropositivity did not increased drop-off rate. [ABSTRACT FROM AUTHOR]

On-farm welfare assessment is time-consuming and costly. Assessing welfare using routinely collected herd data has been proposed as a more economical alternative. The online Animal Welfare Indicator (AWI), developed by a Norwegian dairy cooperative, applies an algorithm to routinely collected health, production, and management data to "indicate" aspects of animal welfare at herd level. The overall AWI score is based on 10 AWI subindicator scores, representative of elements of animal welfare such as claw health, udder health, and mortality. Our cross-sectional study explored 2 ways in which the AWI may enable more efficient welfare assessment of Norwegian dairy herds. First, we investigated using the AWI to reduce the duration of on-farm assessments by replacing on-farm measures. Second, we examined reducing the number of on-farm welfare assessments by using the AWI to predict which herds have poorer welfare with respect to specific on-farm measures. Using Spearman rank analyses, we investigated if the AWI scores for 157 herds were associated with 24 on-farm welfare variables measured contemporaneously by Welfare Quality assessment. The mortality AWI subindicator score and the percentage mortality in the previous 12 mo were moderately correlated, as were the udder health AWI subindicator score and the percentage high somatic cell count (SCC) in the previous 3 recordings. Only negligible or weak correlations were found between the other AWI scores and the on-farm assessment variables. We built Generalized Linear Models using AWI scores as independent variables to predict herds with poorer welfare. Herds were classified as having poorer welfare based on their results in specific on-farm welfare measures. We evaluated the models' predictive ability and accuracy. Moderately accurate models were built for predicting poorer herds with respect to high SCC, mortality, and moderate or severe lameness. The other models were less accurate. The AWI scores were generally unsuitable as replacements of on-farm welfare measures. The AWI subindicators for udder health and mortality could replace the on-farm welfare measures related to those 2 topics, but there was some overlap in the data used to calculate them. Despite a lack of independence, the use of those 2 AWI subindicators may marginally reduce the duration of on-farm assessments. A prediction model based on AWI scores showed potential for identifying herds with poorer welfare in terms of moderate or severe lameness, facilitating more efficient use of resources for on-farm lameness assessment. As a consequence of the data used in the AWI, it was only reflective of health-related welfare outcomes. [ABSTRACT FROM AUTHOR]

Optimal early-life care of surplus calves born on dairy farms is critical for health and welfare. This cross-sectional study aimed to describe the marketing practices of male dairy calves, differences in the colostrum management between male and female calves on dairy farms, and the relationship between discrepant colostrum practices and dairy producers' attitudes toward male calf care. United States dairy producers (n = 1,000) in the states of Florida, Michigan, Ohio, Vermont, and Wisconsin were selected using stratified random sampling. A questionnaire containing questions about farm demographics, colostrum management (including quantity and timeliness of colostrum delivery), and producers' attitudes toward male calf care was mailed in February 2021. Attitudes toward male calf care were assessed using 5-point Likert scales for 10 statements regarding perceptions of the value of male calves and barriers in providing optimal care. Producer responses to questions about the quantity and timeliness of colostrum delivery between male and female calves were compared using a nonparametric Wilcoxon rank-sum test. Multivariable logistic regression models were used to investigate the association between differences in colostrum management and producers' attitudes. By May 2021, 953 surveys were delivered and 315 (33.1%) were returned with complete responses. Most producers (>90%) reported feeding equal volumes of colostrum and performing the first postbirth feeding within a similar time frame for male and female calves. However, compared with females, male calves had a longer delay to the first colostrum feeding. Approximately 40% of producers marketed their male calves through auctions, and over half (54.6%) of farms sold the male calves between 3 and 10 d of age. Large farms (≥500 lactating cows) were found to market male calves at a younger age (≤3 d of age). Most producers (>78%) believed their male calves were receiving optimal care and did not consider the workload and financial costs as obstacles to providing good care to male calves. However, those who viewed the workload as an obstacle to good care and produced organic products were marginally more likely to feed a lower volume of colostrum to male calves in the first feeding after birth. These findings suggest that interventions to improve colostrum practices should be more broadly targeted to all calves born on dairy farms, and that age at transport is markedly different between large and small farms. [ABSTRACT FROM AUTHOR]

Most US dairy calves are raised in individual hutches for biocontainment purposes and to facilitate monitoring and handling of calves. However, individual hutches typically restrict calves' activity and social interactions. Previous studies showed that group housing (GH) is beneficial to calf welfare and is associated with social benefits. The adoption of GH on dairies is hindered by several concerns, with the primary concern being the potential for increased transmission of diseases due to heightened calf-to-calf contact. In light of this, our study aimed to compare the behavior, health, and growth outcomes of calves housed in groups of 3 to individually housed (IH) calves during the preweaning period. A total of 42 Holstein heifer calves on a commercial dairy in Northern California were enrolled in groups of 3 to different housing treatments; IH (n = 21) or GH (n = 21) between July and October 2020. Each treatment was composed of 7 groups of 3 calves each. Calves in the GH treatment were housed in groups of 3 from 6 to 10 d until 70 d of age. Individual pens consisted of one polyethylene hutch with a 1.5 m × 1.2 m outside exercise area. Group pens were constructed by assembling 3 polyethylene hutches with a 1.5 m × 3.6 m outside exercise area of wire panel fencing. Calves were weighed and measured for height at birth and weaning. Diarrhea and bovine respiratory disease (BRD) scores were recorded daily throughout the preweaning period. Cumulative incidence and hazard ratios were estimated for BRD and diarrhea for GH and IH. A mixed model with pen as a random effect was specified to evaluate the effect of treatment. Group-housed calves gained 0.64 ± 0.02 kg/d while IH calves gained 0.65 ± 0.02 kg/d. Similarly, there was no evidence for treatment differences in withers height gain in GH calves (0.22 ± 0.01 cm/d) compared with IH calves (0.21 ± 0.01 cm/d). The cumulative incidence of BRD based on the California scoring system in GH calves was 75 ± 9.68% compared with 66.66 ± 10.28% in IH calves. Group-housed calves had a BRD hazard of 1.14 times that of IH calves (95% CI: 1.21–2.40). The cumulative incidence of diarrhea (fecal score 3) in GH calves was 100% in comparison to 95.20% ± 4.66% in IH calves. The mean proportion of scan observations of calves feeding on concentrates was significantly higher in GH (0.145 ± 0.004/h) compared with IH calves (0.076 ± 0.003/h) during the preweaning period. The study results provide evidence that this simplified GH system provides benefits of GH without detrimental short-term effects on calf growth and health during the preweaning period. [ABSTRACT FROM AUTHOR]

The present study aimed to use detailed phenotyping for the claw disorder digital dermatitis (DD) considering specific DD stages in 2 housing systems (conventional cubicle barns [CON] and compost-bedded pack barns [CBPB]) to infer possible genotype × housing system interactions. The DD stages included 2,980 observations for the 3 traits DD-sick, DD-acute, and DD-chronic from 1,311 Holstein-Friesian and 399 Fleckvieh-Simmental cows. Selection of the 5 CBPB and 5 CON herds was based on a specific protocol to achieve a high level of herd similarity with regard to climate, feeding, milking system, and location, but with pronounced housing-system differences. Five other farms had a "mixed system" with 2 subherds, one representing CBPB and the other one CON. The CBPB system was represented by 899 cows (1,530 observations), and 811 cows (1,450 observations) represented the CON system. The average disease prevalence was 20.47% for DD-sick, 13.88% for DD-acute, and 5.34% for DD-chronic, with a higher prevalence in CON than in CBPB. After quality control of 50K genotypes, 38,495 SNPs from 926 cows remained for the ongoing genomic analyses. Genetic parameters for DD-sick, DD-acute, and DD-chronic were estimated by applying single-step approaches for single-trait repeatability animal models considering the whole dataset, and separately for the CON and CBPB subsets. Genetic correlations between same DD traits from different housing systems, and between DD-sick, DD-chronic, and DD-acute, were estimated via bivariate animal models. Heritabilities based on the whole dataset were 0.16 for DD-sick, 0.14 for DD-acute, and 0.11 for DD-chronic. A slight increase of heritabilities and genetic variances was observed in CON compared with the "well-being" CBPB system, indicating a stronger genetic differentiation of diseases in a more challenging environment. Genetic correlations between same DD traits recorded in CON or CBPB were close to 0.80, disproving obvious genotype × housing system interactions. Genetic correlations among DD-sick, DD-acute and DD-chronic ranged from 0.58 to 0.81. SNP main effects and SNP × housing system interaction effects were estimated simultaneously via GWAS, considering only the phenotypes from genotyped cows. Ongoing annotations of potential candidate genes focused on chromosomal segments 100 kb upstream and downstream from the significantly associated candidate SNP. GWAS for main effects indicated heterogeneous Manhattan plots especially for DD-acute and DD-chronic, indicating particularities in disease pathogenesis. Nevertheless, a few shared annotated potential candidate genes, that is, METTL25, AFF3, PRKG1 , and TENM4 for DD-sick and DD-acute, were identified. These genes have direct or indirect effects on disease resistance or immunology. For the SNP × housing system interaction, the annotated genes ASXL1 and NOL4L on BTA 13 were relevant for DD-sick and DD-acute. Overall, the very similar genetic parameters for the same traits in different environments and negligible genotype × housing system interactions indicate only minor effects on genetic evaluations for DD due to housing-system particularities. [ABSTRACT FROM AUTHOR]

We evaluate the potential economic impact of using high-oleic soybeans (HOS) in dairy rations based on a synthesis of results from 5 prior feeding trials. Milk income less feed costs (MILFC) per cow per day is calculated based on assumed increases in milkfat production and increased cost of rations including HOS. The effects of changes in MILFC are evaluated for herds with different numbers of milking cows, and the total volume of HOS required to support different proportions of US dairy cows is calculated. A dynamic supply-chain model assesses the potential market impacts of increases in butterfat supply. The increase in milkfat from the substitution of 5% of ration dry matter with whole HOS (1.4 kg/cow per day) has the potential to increase MILFC by up to $0.27/cow per day or increase the average value of milk by $0.29/45.4 kg for a cow producing 41 kg/d. Changes in MILFC are highly correlated with the price of butter but were positive for butter prices observed from January 2014 to September 2020. The effects of HOS on MILFC suggest the potential for increases in farm profitability of $33,000/yr for a dairy feeding 500 milking cows. Scaled-up use of HOS by US dairy farmers would increase butterfat supplies and lower the butterfat price to a small extent, but these aggregated effects do not offset the positive effects of MILFC at the farm level. [ABSTRACT FROM AUTHOR]

Respiratory tract infections remain a major problem during calf rearing, especially among milk (formula)-fed veal. Preconditioning of calves through appropriate colostrum management and vaccination could be helpful to address this issue. The objective of this study was to investigate whether the presence of serum antibodies against major respiratory tract pathogens (bovine respiratory syncytial virus, parainfluenza 3 virus, bovine coronavirus, Mycoplasmopsis bovis, Histophilus somni, Pasteurella multocida , and Mannheimia haemolytica) and total serum IgG concentration in calves upon arrival at the veal facility were associated with the occurrence of clinical bovine respiratory disease (BRD) or lung consolidation in the first 3 wk, as assessed by both the Wisconsin BRD scorecard (based on 5 clinical signs: cough, rectal temperature, ear position, and nasal and ocular discharge) and by quick thoracic ultrasound scanning. Additionally, the association between calves' serostatus production parameters were explored. A prospective cohort study was conducted among 442 male dairy calves on a large veal calf facility in Belgium. Both clinical scoring and quick thoracic ultrasound scanning were performed on all calves at 4 key moments in the production cycle: arrival at the facility, initiation of first metaphylactic antimicrobial treatment at peak incidence of BRD (wk 1), end of the first metaphylactic treatment (short-term evaluation) and at wk 10 (long-term evaluation). Mixed effects logit regression models were fitted to quantify relationships. The outcomes of interest were clinical respiratory disease (Wisconsin BRD scorecard positive), lung consolidation (≥1 cm or ≥ 3 cm), average daily weight gain, and cold carcass weight. In the first week of production, incidence of lung consolidation (≥1 cm) quickly increased from 14.9% upon arrival to 43.0% at the peak of the BRD incidence, while clinical BRD increased from 3.6% to 16.1%. The main finding of this study was that calves who were seropositive for bovine respiratory syncytial virus and bovine coronavirus at arrival had reduced odds of developing lung consolidation at the peak of the outbreak, 0.58 odds ratio (95% CI: 0.38–0.89) and 0.37 odds ratio (95% CI: 0.20–0.69), respectively. No relationships between serum IgG concentration at arrival and the development of lung consolidations or clinical respiratory disease were found. Nevertheless, on average, throughout the first 10 wk of the fattening cycle, calves with failed transfer of passive immunity (serum IgG < 7.5 g/L) gained 40 g/d (95% CI: 10–70 g/d) less weight (average daily gain). Hence, ensuring that calves have a positive serostatus for these respiratory tract pathogens before entering the facility may help lower the incidence of lung consolidations, subsequently reducing treatment incidence and the adverse effects on primary economic outcomes. [ABSTRACT FROM AUTHOR]

This closed cohort study aimed to identify the associations between dairy calf management practices and herd-level perinatal calf mortality risk. From February 2020 to June 2021, predominantly Holstein dairy farms in Québec (n = 1,832) and New Brunswick (n = 52), Canada, that were registered in the dairy herd improvement program were visited once. A questionnaire covering all aspects of precalving, calving, and colostrum management was administered. Data regarding perinatal mortality were retrieved from the dairy herd improvement program database for each farm for 2021. Perinatal mortality was calculated for each farm as the proportion of calves dead at birth or dying within 24 h after birth. A multivariable negative binomial model was used to assess herd-level factors associated with the risk of perinatal mortality. The final model included the lying surface in the calving area, the typical time to first colostrum intake, typical cow-calf contact time, the proportion of males born, the proportion of assisted calvings, and herd size. Herd-level perinatal mortality risk ranged from 0% to 38.1% (mean ± SE = 7.6% ± 0.1%). A greater proportion of males born, a higher proportion of assisted calvings, and delayed colostrum feeding were associated with increased herd-level perinatal mortality. Factors associated with a decreased herd-level perinatal mortality risk were having a typical cow-calf contact time between 7 and 12 h after calving compared with reduced cow-calf contact time, soft lying surfaces in the calving area compared with concrete and mat-lying surfaces, and an increased number of calvings per year. Our results show that although some of the significant risk factors are not well understood (i.e., calving area lying surface, typical cow-calf contact time), Canadian farmers could focus on the factors under their control (i.e., time to first colostrum feeding, proportion of difficult calvings, males born, and calvings per year) to reduce the risk of perinatal mortality. Future work should focus on qualitative research to understand the dairy farmer motivations and limitations to implementing practices identified in this and other studies to reduce perinatal mortality. [ABSTRACT FROM AUTHOR]

This study aims to develop predictive models for rice yield by applying multivariate techniques. It utilizes stepwise multiple regression, discriminant function analysis and logistic regression techniques to forecast crop yield in specific districts of Haryana. The time series data on rice crop have been divided into two and three classes based on crop yield. The yearly time series data of rice yield from 1980–81 to 2020–21 have been taken from various issues of Statistical Abstracts of Haryana. The study also utilized fortnightly meteorological data sourced from the Agrometeorology Department of CCS HAU, India. For comparing various predictive models' performance, evaluation of measures like Root Mean Square Error, Predicted Error Sum of Squares, Mean Absolute Deviation and Mean Absolute Percentage Error have been used. Results of the study indicated that discriminant function analysis emerged as the most effective to predict the rice yield accurately as compared to logistic regression. Importantly, the research highlighted that the optimum time for forecasting the rice yield is 1 month prior to the crops harvesting, offering valuable insight for agricultural planning and decision-making. This approach demonstrates the fusion of weather data and advanced statistical techniques, showcasing the potential for more precise and informed agricultural practices. [ABSTRACT FROM AUTHOR]

Salmonella Dublin is a bovine-adapted bacterial pathogen that primarily affects dairy cattle. The incidence of S. Dublin has been increasing across North America, including strains that are multidrug resistant. In British Columbia, the Ministry of Agriculture's Animal Health Center (AHC) reported an increase in cases since 2015, warranting an investigation into how S. Dublin is spreading within the province. The objectives of this study were to make use of historical data collected from dairy farms across the province to (1) describe S. Dublin cases diagnosed at the AHC between 2007 and 2021, (2) identify risk factors for S. Dublin transmission across British Columbia dairy farms, and (3) identify any potential biases associated with passive laboratory-based data that may apply to our results. We found that S. Dublin cases diagnosed at the AHC have been increasing over time. Over half of the cases had respiratory symptoms; however, clinical signs tended to be highly variable. The prevalence of respiratory symptoms was mirrored by florfenicol treatment and was suggested to be due to using a first-line antibiotic for more common causes of pneumonia when presented with an S. Dublin case. Calves were 38 times more likely to have S. Dublin when compared to adults (odds ratio = 38.43, confidence interval = 7.26–203.64), and given the sample population (postmortem cases), it is reasonable to conclude clinical disease is most severe in this age group. Farm premise accounted for a large amount of variability within our model (92% of unexplained variance), suggesting that farm-level management practices may be the most important risk factor for S. Dublin infection. In total, only 54% of BC dairy farms submitted to the laboratory between 2007 and 2021; however, proximity to the laboratory did not appear to influence submissions as proportionally; farms within the Fraser Valley submitted as frequently as farms from other regions. We strongly suggest that future work explore factors associated with farm management practices, given our findings regarding the clustering by premises. [ABSTRACT FROM AUTHOR]

Bovine mastitis is a widespread and costly disease that affects dairy farming globally, characterized by mammary gland inflammation. Bovine intramammary gland infection has been associated with more than 135 different pathogens of which Staphylococcus aureus is the main etiology of sub-clinical mastitis (SCM). The current study was designed to investigate the prevalence, antibiotic resistance pattern, and the presence of antibiotic resistance genes (mecA, tetK, aacA-aphD and blaZ) in S. aureus isolated from the raw milk of cows with subclinical mastitis. A total of 543 milk samples were collected from lactating cows such as Holstein Friesian (n = 79), Sahiwal (n = 175), Cholistani (n = 107), and Red Sindhi (n = 182) from different dairy farms in Pakistan. From the milk samples microscopic slides were prepared and the somatic cell count was assessed to find SCM. To isolate and identify S. aureus, milk was streaked on mannitol salt agar (MSA) plates. Further confirmation was done based on biochemical assays, including gram staining (+ coccus), catalase test (+), and coagulase test (+). All the biochemically confirmed S. aureus isolates were molecularly identified using the thermonuclease (nuc) gene. The antibiotic resistance pattern of all the S. aureus isolates was evaluated through the disc diffusion method. Out of 543 milk samples, 310 (57.09%) were positive for SCM. Among the SCM-positive samples, S. aureus was detected in 30.32% (94/310) samples. Out of 94 isolates, 47 (50%) were determined to be multidrug resistant (MDR). Among these MDR isolates, 11 exhibited resistance to Cefoxitin, and hence were classified as methicillin-resistant Staphylococcus aureus (MRSA). The S. aureus isolates showed the highest resistance to Lincomycin (84.04%) followed by Ampicillin (45.74%), while the least resistance was shown to Sulfamethoxazole/Trimethoprim (3.19%) and Gentamycin (6.38%). Polymerase chain reaction (PCR) analysis revealed that 55.31% of the isolates carried blaZ gene, 46.80% carried tetK gene, 17.02% harbored the mecA gene, whereas, aacA-aphD gene was found in 13.82% samples. Our findings revealed a significant level of contamination of milk with S. aureus and half (50%) of the isolates were MDR. The isolated S. aureus harbored various antibiotic resistance genes responsible for the absorbed phenotypic resistance. The alarmingly high prevalence of MDR S. aureus isolates and MRSA strains in these cases possess a serious risk to public health, emphasizes the urgent need to address this issue to protect both human and animal health in Pakistan. [ABSTRACT FROM AUTHOR]

Simple Summary: Simple Summary: Pig tracking provides strong support for refined management in pig farms and can assist in realizing customized, automated, and intellectualized management. However, there are many complex factors in actual production that result in pigs not being tracked consistently over time. To address this issue, we proposed a long-term video tracking method for group-housed pigs based on improved StrongSORT. The experimental results proved that our study demonstrates high practicality, catering to the needs of practical production. It improved the efficiency of farming personnel and lays the foundation for the automated monitoring of pigs. Additionally, it is worth mentioning that we have also released a dataset specifically designed for long-term pig tracking in this paper. Pig tracking provides strong support for refined management in pig farms. However, long and continuous multi-pig tracking is still extremely challenging due to occlusion, distortion, and motion blurring in real farming scenarios. This study proposes a long-term video tracking method for group-housed pigs based on improved StrongSORT, which can significantly improve the performance of pig tracking in production scenarios. In addition, this research constructs a 24 h pig tracking video dataset, providing a basis for exploring the effectiveness of long-term tracking algorithms. For object detection, a lightweight pig detection network, YOLO v7-tiny_Pig, improved based on YOLO v7-tiny, is proposed to reduce model parameters and improve detection speed. To address the target association problem, the trajectory management method of StrongSORT is optimized according to the characteristics of the pig tracking task to reduce the tracking identity (ID) switching and improve the stability of the algorithm. The experimental results show that YOLO v7-tiny_Pig ensures detection applicability while reducing parameters by 36.7% compared to YOLO v7-tiny and achieving an average video detection speed of 435 frames per second. In terms of pig tracking, Higher-Order Tracking Accuracy (HOTA), Multi-Object Tracking Accuracy (MOTP), and Identification F1 (IDF1) scores reach 83.16%, 97.6%, and 91.42%, respectively. Compared with the original StrongSORT algorithm, HOTA and IDF1 are improved by 6.19% and 10.89%, respectively, and Identity Switch (IDSW) is reduced by 69%. Our algorithm can achieve the continuous tracking of pigs in real scenarios for up to 24 h. This method provides technical support for non-contact pig automatic monitoring. [ABSTRACT FROM AUTHOR]

Simple Summary: One key factor in the emergence of antimicrobial resistance (AMR) in microorganisms is antimicrobial usage in veterinary and human medicine. In dairy cattle, the prevalence of AMR E. coli is age-dependent, with a higher prevalence detected during the early stages of life. In veal calf fattening herds, the high degree of commingling calves from different farms of origin can lead to the rapid spread of infections within the farm. This can cause severe health issues, necessitating greater use of antimicrobial agents. Antimicrobial use has been reported to be higher in the veal calf fattening sector compared to the other production branches of livestock production. This represents an unquantified risk to human health, as antimicrobial-resistant bacteria and the genetic elements mediating resistance can potentially spread through foodborne transmission or environmental dissemination. This surveillance study was conducted, using data available from routine diagnostic activity, to: (i) determine the proportion of antimicrobial-resistant strains and AMR profiles of E. coli isolated from the intestinal contents of veal and dairy calves in the Veneto Region (Northeaster Italy); (ii) investigate potential variation in the AMR profiles of isolates between the two categories of calves and, (iii) identify potential AMR variations over the period considered (2017–2022). This surveillance study aimed to estimate the proportion of antimicrobial resistant strains and antimicrobial resistance (AMR) profiles of E. coli isolates detected from the intestinal contents of veal and dairy calves in the Veneto Region, Northeaster Italy. Additionally, we investigated the differences in AMR profiles between dairy and veal calves over the period 2017–2022. Overall 1150 E. coli isolates were tested from calves exhibiting enteric disease, with 868 from dairy and 282 from veal calves. The percentage of resistant isolates to nine antimicrobials was notably higher in veal calves compared to dairy calves, except for ampicillin. Throughout the study period, we observed a significant increase in the proportion of resistant isolates to florfenicol, gentamycin, paromomycin, tetracycline and trimethoprim/sulfamethoxazole in dairy calves, while we did not detect any significant increase in the proportion of resistant isolates among veal calves. A substantial proportion (75.9%) of the isolated E. coli exhibited multi-drug resistance (MDR). The proportion of multi-drug resistant isolates was significantly higher in veal calves (91.7%) compared to dairy calves (74.3%) all through the surveillance period (2017–2022), with no significant variation in MDR proportion among veal calves between 2017 and 2022 but a significant increase among dairy calves. [ABSTRACT FROM AUTHOR]

Simple Summary: Sheep farmers face increasing pressure to produce more in order to meet market demands, while consumers have more interest in animal welfare status and the environment. The aim of this paper was to categorize the on-farm welfare risks using the ClassyFarm protocol and to identify if welfare risk changed according to farm size. The critical issues we found were the low number of stockpersons, the small areas available for the animals, the lack of udder cleaning procedures during milking, and the lack of prevention plans for the most important infectious ovine diseases. As the number of animals within the farm increased, the management of the flock improved; on the other hand, the number of animal inspections decreased and the hygiene of the water worsened. The objective of the present work was to categorize the risks in the on-farm welfare of dairy sheep in semi-extensive systems in order to highlight if risks in welfare vary according to the farm size. To the best of our knowledge, this study constitutes one of the few categorizations of the risks in the welfare of dairy sheep reared semi-extensively. The survey was conducted on 12 semi-extensive dairy sheep farms in Tuscany (Central Italy), which were classified according to flock size: <500, from 500 to 1000, and >1000. The results showed an adequate rating for all the farms included in the study. The most critical issues concerned the ratio between the number of stockpersons and the number of animals within the farms, the small decubitus areas, the lack of udder cleaning procedures during milking operations, and, in terms of biosecurity, the lack of prevention, control, and eradication plans for the most important infectious ovine diseases. The results show that different items in the five areas evaluated, including the assessments of management of the flock, the number of daily inspections, and the hygiene of the water supplies are associated with the farm size. In large farms, the assessment of management of the flock was better, but the number of daily inspections and the hygiene of the water supplies were worse. [ABSTRACT FROM AUTHOR]

Precise and prompt predictions of crop yields are crucial for optimising farm management, post-harvest operations, and marketing strategies within the agricultural sector. While various machine learning approaches have been employed to forecast crop yield, their application to grain quality, particularly head rice yield (HRY), is less explored. This research collated crop-level HRY data across four seasons (2017/18–2020/21) from Australia's rice-growing region. Models were developed using the XGBoost algorithm trained at varying time steps up to 16 weeks pre-harvest. The study compared the accuracy of models trained on datasets with climate data alone or paired with vegetative indices using two- and four-week aggregations. The results suggest that model accuracy increases as the harvest date approaches. The dataset combining climate and vegetative indices aggregated over two weeks surpassed industry benchmarks early in the season, achieving the highest accuracy two weeks before harvest (LCCC = 0.65; RMSE = 6.43). The analysis revealed that HRY correlates strongly with agroclimatic conditions nearer harvest, with the significance of vegetative indices-based features increasing as the season progresses. These features, indicative of crop and grain maturity, could aid growers in determining optimal harvest timing. This investigation offers valuable insights into grain quality forecasting, presenting a model adaptable to other regions with accessible climate and satellite data, consequently enhancing farm- and industry-level decision-making. [ABSTRACT FROM AUTHOR]

Background: Clostridium perfringens, a common environmental bacterium, is responsible for a variety of serious illnesses including food poisoning, digestive disorders, and soft tissue infections. Mastitis in lactating cattle and sudden death losses in baby calves are major problems for producers raising calves on dairy farms. The pathogenicity of this bacterium is largely mediated by its production of various toxins. Results: The study revealed that Among the examined lactating animals with a history of mastitis, diarrheal baby calves, and acute sudden death cases in calves, C. perfringens was isolated in 23.5% (93/395) of the total tested samples. Eighteen isolates were obtained from mastitic milk, 59 from rectal swabs, and 16 from the intestinal contents of dead calves. Most of the recovered C. perfringens isolates (95.6%) were identified as type A by molecular toxinotyping, except for four isolates from sudden death cases (type C). Notably, C. perfringens was recovered in 100% of sudden death cases compared with 32.9% of rectal swabs and 9% of milk samples. This study analyzed the phylogeny of C. perfringens using the plc region and identified the plc region in five Egyptian bovine isolates (milk and fecal origins). Importantly, this finding expands the known data on C. perfringens phospholipase C beyond reference strains in GenBank from various animal and environmental sources. Conclusion: Phylogenetic analyses of nucleotide sequence data differentiated between strains of different origins. The plc sequences of Egyptian C. perfringens strains acquired in the present study differed from those reported globally and constituted a distinct genetic ancestor. [ABSTRACT FROM AUTHOR]

Fowlpox is a re-emerging and economically significant viral disease in poultry. Fowlpox is a complex virus contains a double-strand DNA genome of approximately 300 kb and largest among all pox viruses. In the present study, a clinical case of fowlpox virus (FPV) infection was investigated and a Real-Time PCR (RT-PCR) assay was developed for confirmatory diagnosis of fowl pox and quantification of viral load. Clinical sample was collected from infected bird reared in the organized poultry farm management system and the viral infection was confirmed using conventional PCR amplification of the P4b gene of fowl pox virus. Following that, a single-step SYBR green based Real-Time PCR assay was developed by targeting the same gene of fowlpox virus. The fowl pox viral load in the infected bird was found to be 7.33 ± 0.044 (Log Mean ± SD). The lower detection limit achieved was 134 copies per microliter (µL) with a corresponding threshold cycle (Ct) value of 32.59. Thus, the single-step SYBR green based RT-PCR assay targeting the P4b gene of fowl pox virus reported in this study was highly sensitive, specific and reproducible for the detection and quantitation of fowl pox virus nucleic acids. [ABSTRACT FROM AUTHOR]

Rumen flukes cause heavy economic losses in the ruminant industry worldwide, especially in tropical and subtropical countries. This study estimated the prevalence of rumen flukes in buffaloes, identified the species diversity, and determined risk factors associated with rumen fluke prevalence in Perak, Peninsular Malaysia. A cross-sectional study was conducted, and 321 faecal samples were collected from six buffalo farms. A structured questionnaire was developed, and farmers were interviewed to obtain information regarding risk factors associated with rumen fluke infection. The faecal samples were examined using sedimentation and Flukefinder® techniques. Genomic DNA was extracted from the fluke eggs recovered using the Flukefinder® method, and the internal transcribed spacer 2 (ITS2) fragment was amplified and sequenced to facilitate species identification. The results showed that the overall prevalence of rumen fluke across the sampled farms was 40.2% (129/321). Three rumen fluke species were identified, namely, Fischoederius elongatus, F. cobboldi, and Orthocoelium streptocoelium. Several management factors had a significant association (P < 0.05) with rumen fluke prevalence, including production type, cleaning of the stable, drinking water system, flooding around the farm, grazing system, pasture sharing with other livestock, and deworming program. This work constitutes the first attempt to understand the epidemiology of rumen fluke infection in the region and suggests that good farm management, pasture management, choosing appropriate drugs, and proper husbandry practices may improve buffalo health and production in areas where rumen flukes are prevalent. [ABSTRACT FROM AUTHOR]

Simple Summary: The "PraeRi" study, conducted by three German veterinary universities from 2016 to 2020, was aimed at enhancing dairy health and welfare. With 765 visited dairy farms and 101,307 animals examined, the designed study provided an opportunity for improving animal well-being. Researchers applied good epidemiologic practice and concepts proven in large-scale studies, in a study comprising three different regions in Germany with varying farm characteristics. A sample size of 250 farms per region, determined through stratified sampling based on farm size, ensured representative estimates. According to the information provided by the farmers, mastitis was the most frequently occurring disease in their herds (14.2% to 16.3% of the herd—depending on the region). For most disorders, prevalence data were lowest for the region South compared with the two remaining regions. Statistical analyses identified risk factors, with results communicated through individual reports and benchmarking flyers to participating farmers. Challenges arose from managing practical procedures and communication due to the project's vast scale. Harmonizing data management and hypothesis testing across involved parties added complexity. Despite challenges, the PraeRi study considerably contributed to advancing dairy health and welfare practices. From 2016 to 2020, the "PraeRi" study, conducted by three German veterinary universities, was aimed at enhancing animal health and welfare in dairy farms. With 765 dairy farms visited and 101,307 animals examined, this study provided a basis for improving animal health and welfare. The study population comprised three different regions representing a broad variety of characteristics. To ensure representative estimates, a sample size of 250 farms was determined for each region, employing a stratified sampling plan based on farm size. According to the information provided by the farmers, the most commonly occurring disease in their herds was mastitis without general disorder (14.2% to 16.3% of the herd—depending on the region). For most disorders, prevalence data were lowest for the region South compared with the two remaining regions. Multivariable regression analyses were performed to identify risk factors for various target variables, and the results were communicated through individual reports and benchmarking flyers to participating farmers. The authors encountered challenges in management and communication due to the project's size in terms of personnel, data, and farms examined. Harmonizing data management and hypothesis testing across all involved parties added complexity. [ABSTRACT FROM AUTHOR]

Simple Summary: Q fever is an infection caused by the bacterium Coxiella burnetii. It can be transmitted from animals to humans, and the infection is usually airborne. In cattle, infection with Coxiella burnetii can lead to increased abortions, premature births or stillbirths, and weak calves. Since 2010, it has been possible to vaccinate cows against Q fever with the vaccine COXEVAC® (Ceva Santé Animale). It was the aim of this study to examine whether the usage of this vaccine could reduce the consumption of antibiotics in Q-fever-positive dairy farms. Antimicrobial use and detailed information on herd data, nutrition, milking management, housing, and animal health were documented and evaluated on 36 vaccinated and 13 non-vaccinated dairy farms. The findings of the present study suggest that more antibiotics were used on non-vaccinated dairy farms than on vaccinated dairy farms. Neither herd size nor milk yield level influenced the consumption of antibiotics in the study herds. Floor type and udder-cluster disinfection while milking were associated with a lower and higher therapy frequency, respectively. Further studies are necessary to elucidate the cause–effect relationship between vaccination and the consumption of antibiotics on dairy farms in Northern Germany. It was the aim of this study to examine whether the usage of the vaccine COXEVAC® (Ceva Santé Animale) could reduce the consumption of antibiotics in Q-fever-positive dairy farms. Additionally, the effects of other herd-level factors on the consumption of antibiotics were investigated. A total of 36 farms with vaccination and 13 farms without vaccination participated in this longitudinal cohort study. In all herds, Coxiella burnetii had been directly or indirectly diagnosed. To compare the treatment frequency of antibiotics between the vaccinated group and the non-vaccinated group, the consumption of antibiotics for each farm was collected using the veterinary documents about the application and delivery of antibiotics. To gather detailed information about herd data, nutrition, milking management, housing, and animal health, the farmers were interviewed with the help of a questionnaire. The results thereof suggest that there might be an association between the vaccination against Q fever and a reduced consumption of antibiotics. Neither herd size nor milk yield level influenced the consumption of antibiotics in the study herds. Type of flooring and udder-cluster disinfection while milking were associated with a lower and higher therapy frequency, respectively. Further studies are necessary to elucidate the cause–effect relationship between vaccination and the consumption of antibiotics. [ABSTRACT FROM AUTHOR]

Simple Summary: In the process of calf rearing, it is inevitable to encounter issues of illness and death among calves. Often, due to the inability to detect sicknesses such as diarrhoea in a timely fashion, these sicknesses lead to the calves' demise. This research starts from the practical application needs, and proposes the development of a monitoring system using deep learning technology to monitor the daily standing and lying behaviour of calves to predict their condition and adaptation to the environment. By analysing the standing and lying time of calves, the system can provide early warnings about calves' condition and health status. This research helps to promptly grasp calves' condition and growth status, thereby improving their welfare and management, enhancing the health condition of reared calves, ensuring the quality and safety of meat and milk, and reducing production costs. This research method also offers a new idea for the construction of smart ranches, as the construction of precision and smart ranches is not only a demand of consumers but also an inevitable direction for the development of the breeding industry. Standing and lying are the fundamental behaviours of quadrupedal animals, and the ratio of their durations is a significant indicator of calf health. In this study, we proposed a computer vision method for non-invasively monitoring of calves' behaviours. Cameras were deployed at four viewpoints to monitor six calves on six consecutive days. YOLOv8n was trained to detect standing and lying calves. Daily behavioural budget was then summarised and analysed based on automatic inference on untrained data. The results show a mean average precision of 0.995 and an average inference speed of 333 frames per second. The maximum error in the estimated daily standing and lying time for a total of 8 calf-days is less than 14 min. Calves with diarrhoea had about 2 h more daily lying time (p < 0.002), 2.65 more daily lying bouts (p < 0.049), and 4.3 min less daily lying bout duration (p = 0.5) compared to healthy calves. The proposed method can help in understanding calves' health status based on automatically measured standing and lying time, thereby improving their welfare and management on the farm. [ABSTRACT FROM AUTHOR]

Simple Summary: Bovine Respiratory Disease (BRD) is a major health issue in dairy farming worldwide. It commonly affects lactating and recently weaned calves, but dairy cows can also be impacted resulting in significant losses to the milk production chain. This research aimed to investigate the serological status of dairy cows for the four main bovine respiratory viruses. This study took place in the central-eastern mesoregion of the state of Paraná, which has the highest milk productivity in Brazil. A total of 497 serum samples were assessed from unvaccinated dairy cows from 39 herds. This study aimed to determine the presence of antibodies to bovine alphaherpesvirus 1 (BoAHV1), bovine viral diarrhea virus (BVDV), bovine parainfluenza virus 3 (BPIV3), and bovine respiratory syncytial virus (BRSV) using virus neutralization tests. The frequencies of BoAHV1, BVDV, BPIV3, and BRSV seropositive cows and herds were 71.4, 56.3, 96.8, and 63.4%, and 79.5, 82.0, 100, and 84.6%, respectively. Rates of more than 50% of cows and herds seropositive for the 4 viruses indicate that these respiratory pathogens are endemic in dairy herds in the region evaluated. In this region for BRD prevention, we recommend implementing cow vaccination programs that provide passive immunity in calves and active immunity in cows. This study aims to determine the serological profile of high-yielding dairy cows for four main viruses (bovine alphaherpesvirus 1 (BoAHV1), bovine viral diarrhea virus (BVDV), bovine parainfluenza virus 3 (BPIV3), and bovine respiratory syncytial virus (BRSV)) related to bovine respiratory disease (BRD) in cattle herds worldwide. In this survey, 497 blood serum samples were collected from non-vaccinated dairy cows without clinical respiratory signs in 39 herds in the central-eastern mesoregion of Paraná State, South Brazil. The presence of neutralizing antibodies was determined by virus neutralization (VN) tests. VN antibodies against BoAHV1, BVDV, BPIV3, and BRSV were detected in 355 (71.4%), 280 (56.3%), 481 (96.8%), and 315 (63.4%) serum samples, respectively. The frequencies of seropositive herds for BoAHV1, BVDV, BPIV3, and BRSV were 79.5 (n = 31), 82.0 (n = 32), 100 (n = 39), and 84.6% (n = 33), respectively. The frequencies of seropositive cows varied according to the type of herd management and the number of cows in the herd. The detection of VN antibodies in unvaccinated dairy cattle herds demonstrated the endemic circulation of the four viruses in the herds evaluated. For BRD prevention, it is recommended to implement a vaccination program for cows that provides passive immunity in calves and active immunity in cows. [ABSTRACT FROM AUTHOR]

Field experimentation was conducted to evaluate the comparative performance of integrated crop management, organic management and natural farming on crop growth, productivity, profitability and soil health under basmati rice-wheat system in Upper Indo-Gangetic Plains. Treatments comprised of different management practices viz. integrated crop management (ICM), organic management, natural farming (NF) and control (no nutrient) were used in experimentation. Plant height, number of effective tillers, SPAD meter reading, panicle weight, filled grains/panicle, fertility percentage and 1000-grains weight of basmati rice and wheat were observed highest under ICM followed by organic management. A significant reduction in growth and yield attributes was recorded under NF as compared to ICM and organic management. Grain yield of basmati rice was reduced by 15.2%, 51.2% and 53.9% under organic management, NF and control as compared to ICM, respectively. Similarly, 49.5%, 58.6%, and 63.8% reduction in grain yield of wheat was recorded under organic management, NF and control as compared to ICM, respectively. In comparison to ICM, system rice equivalent yield (REY) was reduced by 32.6%, 55.0%, and 59.0% under organic management, NF and control, respectively. Further, net return was 44.1% and 67.2% lower under organic management and NF as compared to ICM, respectively. Highest soil organic carbon (0.60%), available N, P, and K were found in organic management. Significantly highest soil microbial population, glomalin content and different soil enzyme activities were recorded under organic management. Overall, the integrated crop management provided balanced and continuous supply of the nutrient that resulted in higher productivity and profitability of basmati rice-wheat system. [ABSTRACT FROM AUTHOR]

Context: Australia is renowned for its climate variation, featuring years with drought and years with floods, which result in significant production and profit variability. Accordingly, to maximise profitability, dryland farming systems need to be dynamically managed in response to unfolding weather conditions. Aims: The aim of this study is to identify and quantify optimal tactical livestock management for different weather-years. Methods: This study employed a whole-farm optimisation model to analyse a representative mixed enterprise farm located in the Great Southern region of Western Australia. Using this model, we investigated the economic significance of five key livestock management tactics. These included timing of sheep sales, pasture-area adjustments, rotational grazing, crop grazing and sheep nutrition adjustments. Key results: The results showed that, on the modelled dryland mixed-enterprise farm in the Great Southern region of Western Australia, short-term adjustments to the overall farm strategy in response to unfolding weather conditions increased expected profit by approximately 16%. Each tactic boosted profit by between A$7704 and A$53,171. However, we outline several complexities that farmers must consider when implementing tactics. Conclusions: The financial gains from short-term tactical management highlighted their importance and farmers' need to develop and apply those skills. The tactical skills promote business resilience and adaptability in the face of climate uncertainties. Implications: The study highlighted the economic value of dynamic livestock management in response to climate variations, offering farmers in the Great Southern region the means to underpin profitable and sustainable farm practices. Under Australia's renowned climate variation, it is profitable for farmer to implement short-term tactical management adjustments in response to the unfolding weather conditions. This paper has identified and quantified optimal tactical livestock management for different weather-years for a mixed-farming system in the Great Southern region of Western Australia. [ABSTRACT FROM AUTHOR]

Background: Digital dermatitis (DD) is a contagious hoof infection affecting cattle worldwide. The disease causes lameness and a reduction in animal welfare, which ultimately leads to major decreases in milk production in dairy cattle. The disease is most likely of polymicrobial origin with Treponema phagedenis and other Treponema spp. playing a key role; however, the etiology is not fully understood. Diagnosis of the disease is based on visual assessment of the feet by trained hoof-trimmers and veterinarians, as a more reliable diagnostic method is lacking. The aim of this study was to evaluate the use of an enzyme-linked immunosorbent assay (ELISA) on bulk tank milk samples testing for the presence of T. phagedenis antibodies as a proxy to assess herd prevalence of DD in Swedish dairy cattle herds. Results: Bulk tank milk samples were collected in 2013 from 612 dairy herds spread across Sweden. A nationwide DD apparent prevalence of 11.9% (8.1–14.4% CI95%) was found, with the highest proportion of test-positive herds in the South Swedish regions (31.3%; 19.9–42.4% CI95%). Conclusions: This study reveals an underestimation of DD prevalence based on test results compared to hoof trimming data, highlighting the critical need for a reliable and accurate diagnostic method. Such a method is essential for disease monitoring and the development of effective control strategies. The novelty of ELISA-based diagnostic methods for DD, coupled with the disease's polymicrobial origin, suggests an avenue for improvement. Developing an expanded ELISA, incorporating antigens from various bacterial species implicated in the disease, could enhance diagnostic accuracy. The significance of this study is underscored by the extensive analysis of a substantial sample size (612). Notably, this investigation stands as the largest assessment to date, evaluating the application of ELISA on bulk tank milk for DD diagnosis at the herd level. [ABSTRACT FROM AUTHOR]

The existing literature has extensively explored the causes of farmer–herder conflicts in Ghana. However, there has been limited investigation into the relationship between royal hegemony over customary lands and the persistent nature of farmer–herder conflicts in the country. This study contributes to the understanding of agrarian conflicts in Ghana by examining the interconnectedness of cultural and social practices of land access with the intractability of farmer–herder conflicts in Agogo. The study utilised a qualitative research approach, involving 33 participants recruited through maximum variation purposive sampling. Data was gathered through interviews and focus group discussions. Inductive thematic analysis revealed that social practices of land access hold greater influence than legal provisions, granting significant power over lands to traditional authorities in Agogo. We argue that the on-going intransigence of traditional rulers regarding land access, coupled with the persistent resistance from smallholder farmers through attempts to evict Fulani herders, as well as the resistance demonstrated by the Fulani herders themselves, are key factors contributing to the intractable nature of farmer–herder conflicts in Agogo. This study emphasises the need for a deeper understanding of the cultural and social dimensions underlying land access practices and their impact on farmer–herder conflicts. [ABSTRACT FROM AUTHOR]

The source of infection of digital dermatitis (DD), an infectious lameness condition, is still uncertain. In this cross-sectional study, we aimed to identify potential reservoirs of DD bacteria in dairy cattle body sites with different stages of the disease and farm environments. We collected skin swabs from 85 dairy cows from 5 herds, 3 with and 2 without DD, from foot, hock, and udder cleft skin (with lesions or not), saliva, urine, and feces. We also obtained environmental samples. Real-time quantitative PCR targeted Treponema phagedenis , Treponema medium , Treponema pedis , Porphyromonas levii , Bacteroides pyogenes , Fusobacterium necrophorum , and Fusobacterium mortiferum. Digital dermatitis-associated Treponema spp. were exclusively detected in DD-affected herds in DD-foot and other skin lesions, healthy skin, saliva, and environmental samples. In contrast, the non- Treponema spp. were found in samples from both DD-negative and affected herds. As expected, DD lesions had higher bacterial loads than healthy skin. Interestingly, similar counts were observed in udder cleft lesions, indicating a potential opportunistic behavior on compromised skin. None of the targeted species were detected in fecal samples, but P. levii , B. pyogenes , and F. necrophorum were detected in urine. All 7 species were detected in saliva, although in low quantities. No associations were observed between the presence of each bacterial species in DD lesions and urine; however, there was an association between the presence of DD- Treponema spp. in lesions and saliva, hock, and udder skin. Feces and urine do not seem to be a DD bacteria primary source, but saliva and other skin lesions may play a role. Longitudinal studies would improve our understanding of DD-associated bacteria's transient or persistent presence in these sites. Investigating the sources of DD-associated bacteria will guide future interventions to minimize bacterial shedding and transmission, ultimately more effectively reducing bacterial load, transmission, and sources of infection in dairy herds. [ABSTRACT FROM AUTHOR]

The use of veterinary drugs is of similar importance to that of human drugs in addressing health challenges. In this context, pharmaceuticals and their metabolites inevitably enter soil and water in unknown quantities. Therefore, this study collects and analyzes drug data from 2020 for 50 dairy farms located in Germany. The most frequently used substance group is antibiotics (40.13%), followed by antiphlogistics (18.86%), antiparasitics (13.09%), and hormones (9.29%). Treatment frequencies record the number of days per year on which an average animal on a farm was treated with a substance. The calculated values range from 0.94 to 21.69 d/yr and are distributed heterogeneously across farms. In this study, on average, a cow was treated on 6 d in 2020: 2.34 d with antibiotics, 1.07 d with antiphlogistics, 0.76 d with antiparasitics, and 0.41 d with hormones. In addition to individual farm management practices, other factors are related to treatment frequency. Farms with a veterinary care contract used more hormonal substances than farms without a care contract. In addition, higher milk yield coincides with more frequent treatments with antiphlogistic or hormonal substances. Other related factors include grazing, longevity, farm size, and use of a claw bath. Our study represents an important first step in describing the amounts and determinants of veterinary drugs used in livestock farming. Such insights on magnitudes and farm parameters are essential to estimate potential environmental effects and derive strategies to reduce veterinary drug use. [ABSTRACT FROM AUTHOR]

Precision dairy tools (PDT) can provide timely information on individual cow's physiological and behavioral parameters, which can lead to more efficient management of the dairy farm. Although the economic rationale behind the adoption of PDT has been extensively discussed in the literature, the socio-psychological aspects related to the adoption of these technologies have received far less attention. Therefore, this paper proposes a socio-psychological model that builds upon the theory of planned behavior and develops hypotheses regarding cognitive constructs, their interaction with the farmers' perceived risks and social networks, and their overall influence on adoption. These hypotheses are tested using a generalized structural equation model for (a) the adoption of automatic milking systems (AMS) on the farms and (b) the PDT that are usually adopted with the AMS. Results show that adoption of these technologies is affected directly by intention, and the effects of subjective norms, perceived control, and attitudes on adoption are mediated through intention. A unit increase in perceived control score is associated with an increase in marginal probability of adoption of AMS and PDT by 0.05 and 0.19, respectively. Subjective norms are associated with an increase in marginal probability of adoption of AMS and PDT by 0.009 and 0.05, respectively. These results suggest that perceived control exerts a stronger influence on adoption of AMS and PDT, particularly compared with their subjective norms. Technology-related social networks are associated with an increase in marginal probability of adoption of AMS and PDT by 0.026 and 0.10, respectively. Perceived risks related to AMS and PDT negatively affect probability of adoption by 0.042 and 0.16, respectively, by having negative effects on attitudes, perceived self-confidence, and intentions. These results imply that integrating farmers within knowledge-sharing networks, minimizing perceived risks associated with these technologies, and enhancing farmers' confidence in their ability to use these technologies can significantly enhance uptake. [ABSTRACT FROM AUTHOR]

Antimicrobial use (AMU) is critical to preserving animal health and welfare. However, the development of antimicrobial resistance (AMR) represents a public health threat. Although most antimicrobials used on the farm require a veterinarian prescription, farmworkers make daily on-farm treatment decisions. Therefore, farmworker training is vital to promote responsible AMU. This research project aimed to evaluate the effect of farmworker antimicrobial stewardship (AMS) training on the quantity of AMU on dairy farms in Ohio and California. We hypothesized that farms receiving AMS training would have reduced AMU in dairy cattle compared with farms where training wasn't administered. We designed a quasiexperimental study with 18 conventional dairy farms enrolled in Ohio and California. Twelve farms received AMS training, and 6 farms did not. The AMS program included a 12-wk training focused on accurate identification of cows requiring antimicrobial treatment. We quantified AMU by collecting used drug containers, manually counted by researchers during farm visits. Treatment incidence (TI) was calculated using animal daily doses (ADD), and Poisson regression models were used to analyze the TI data. Disease incidence rate (DIR) in lactating cows was 2.2, 1.5, 1.0, 0.4, 0.3, 0.2, and 0.03/1,000 cow-days for mastitis, lameness, metritis, pneumonia, retained placenta, diarrheas, and other diseases (e.g., conjunctivitis, injuries), respectively. The highest TI by antimicrobial class (provided in ADD/1,000 cow-days) was cephalosporin (5.9), penicillin (5.2), tetracyclines (0.4), lincosamides (0.2), and sulfonamides (0.1). Among the trained farms using a within-treatment group analysis, no significant differences were observed in TI pre-intervention (10.9 ADD/1,000 cow-days) compared with TI postintervention (10.3 ADD/1,000 cow-days). Treatment incidence from the training group was 10.8 ADD/1,000 cow-days and although numerically lower, it was not significantly different compared with TI in the control groups at 13.9 ADD/1,000 cow-days (rate ratio = 0.77, CI = 0.25–2.38). Future research on AMS should incorporate farmworker training with social science approaches to overcome barriers and promote on-farm responsible use. [ABSTRACT FROM AUTHOR]

The objective of this diagnostic accuracy study was to develop and validate an alert to identify calves at risk for a diarrhea bout using milk feeding behavior data (behavior) from automated milk feeders (AMF). We enrolled Holstein calves (n = 259) as a convenience sample size from 2 facilities that were health scored daily preweaning and offered either 10 or 15 L/d of milk replacer. For alert development, 132 calves were enrolled and the ability of milk intake, drinking speed, and rewarded visits collected from AMF to identify calves at risk for diarrhea was tested. Alerts that had high diagnostic accuracy in the alert development phase were validated using a holdout validation strategy of 127 different calves from the same facilities (all offered 15 L/d) for −3 to 1 d relative to diarrhea diagnosis. We enrolled calves that were either healthy or had a first diarrheal bout (loose feces ≥2 d or watery feces ≥1 d). Relative change and rolling dividends for each milk feeding behavior were calculated for each calf from the previous 2 d. Logistic regression models and receiver operator curves (ROC) were used to assess the diagnostic ability for relative change and rolling dividends behavior relative to alert d) to classify calves at risk for a diarrhea bout from −2 to 0 d relative to diagnosis. To maximize sensitivity (Se), alert thresholds were based on ROC optimal classification cutoff. Diagnostic accuracy was met when the alert had a moderate area under the ROC curve (≥0.70), high accuracy (Acc; ≥0.80), high Se (≥0.80), and very high precision (Pre; ≥0.85). For alert development, deviations in rolling dividend milk intake with drinking speed had the best performance (10 L/d: ROC area under the curve [AUC] = 0.79, threshold ≤0.70; 15 L/d: ROC AUC = 0.82, threshold ≤0.60). Our diagnostic criteria were only met in calves offered 15 L/d (10 L/d: Se 75%, Acc 72%, Pre 92%, specificity [Sp] 55% vs. 15 L/d: Se 91%, Acc 91%, Pre 89%, Sp 73%). For holdout validation, rolling dividend milk intake with drinking speed met diagnostic criteria for one facility (threshold ≤0.60, Se 86%, Acc 82%, Pre 94%, Sp 50%). However, no milk feeding behavior alerts met diagnostic criteria for the second facility due to poor Se (relative change milk intake −0.36 threshold, Se 71%, Acc 70%, and Pre 97%). We suggest that changes in milk feeding behavior may indicate diarrhea bouts in dairy calves. Future research should validate this alert in commercial settings; furthermore, software updates, support, and new analytics might be required for on-farm application to implement these types of alerts. [ABSTRACT FROM AUTHOR]

Milk replacers (MR) for calves contain alternative fat sources as substitute for milk fat. This substitution leads to differences in fat properties, such as the fatty acid profile and the triglyceride structure. This study evaluated how fat composition in MR affects gastrointestinal health, blood redox parameters, and postprandial metabolism in calves fed twice daily. Forty-five individually housed male Holstein-Friesian calves (2.3 ± 0.85 d of age) were assigned to 1 of 15 blocks based on the age and the day of arrival. Within each block, calves were randomly assigned to 1 of 3 experimental diets and received their respective diet from arrival until 35 d after arrival. The 3 experimental diets (n = 15 per treatment group) consisted of an MR with a blend of vegetable fats containing rapeseed and coconut (VG), an MR with only animal fats from lard and dairy cream (AN), and an MR containing a mixture of animal and vegetable fats including lard and coconut (MX). The fatty acid profile of each MR was formulated to resemble that of bovine milk fat while using only 2 fat sources. All MR were isoenergetic, with 30% fat (% DM), 24% crude protein, and 36% lactose. Chopped straw and water were available ad libitum from arrival onward but no starter feed was provided. Daily milk allowances were 6.0 L from d 1 to 5, 7.0 L from d 6 to 9, and 8.0 L from d 10 to 35, divided into 2 equal meals and prepared at 135 g/L (13.5% solids). Fecal appearance was scored daily; calves were weighed and blood was drawn on arrival and weekly thereafter. Urine and feces were collected over a 24-h period at wk 3 and 5 to determine apparent total-tract digestibility and assess gastrointestinal permeability using indigestible markers. Postprandial metabolism was evaluated at wk 4 by sequential blood sampling over 7.5 h, and the abomasal emptying rate was determined by acetaminophen appearance in blood. Fat composition in MR did not affect growth, MR intake, gastrointestinal permeability, nor nutrient digestibility. The percentage of calves with abnormal fecal scores was lower at wk 2 after arrival in calves fed VG than MX, whereas AN did not differ from the other treatments. Calves fed AN and MX had higher thiobarbituric acid reactive substances measured in serum than VG, whereas plasma ferric-reducing ability was greater in calves fed MX than VG. Postprandial acetaminophen concentrations did not differ across treatment groups, but the area under the curve was smaller in calves fed VG than in the other 2 treatments, which is indicative of a slower abomasal emptying. Postprandial serum triglyceride concentration was greater in calves fed AN than VG, whereas MX did not differ from the other treatments. Based on these outcomes, all 3 fat blends can be considered suitable for inclusion in MR for calves. [ABSTRACT FROM AUTHOR]

It aims to improve the application efficiency of modern science and technology in farm operation, enhance the prediction effect of machine learning and blockchain technology on farm supply and demand issues, and help enterprise managers to better manage and operate enterprise projects. First, the agricultural super business model under the blockchain + Internet of Things (IoT) is analysed, and the farm management system of the IoT + blockchain is constructed. Then, the demand forecasting model of agricultural products is established. Autoregressive Integrated Moving Average model (ARIMA) and Support Vector Machine (SVM) models are used to predict demand. Finally, the characteristics of the two models in prediction are discussed. The results show that the ARIMA model can reach 99.2% in the application efficiency evaluation of farm operation. Moreover, in the case of proper selection of model indicators, the prediction result is close to the actual value, the prediction error fluctuation is small, and the maximum error value is 0.4318. The local error of SVM model in predicting the demand of farm supply chain is slightly larger, and the maximum error value is 8.5430. By comparing the error results of the two models, the prediction accuracy of ARIMA model is higher than that of SVM model. The ARIMA model designed in this work can provide effective product demand prediction for farm operation and provide a strong technical reference for farm operation. The research not only provides technical support for machine learning and blockchain technology to predict farm supply and demand, but also contributes to the integrated management and sustainable development of enterprises. [ABSTRACT FROM AUTHOR]

This study detected Anaplasma marginale in calvesusing blood smears and nested PCR (nPCR) and to compare the results with the clinical signs presented by calves on a dairy farm in the municipality of Castanhal, located northeast of the state Pará (1°07'19.1"S and 47°53'53.0"W), eastern Amazon. To this end, 192 blood samples were collected from 24 animals at 1-20, 21-41 and 42-60 days of age. Blood smears and nPCR with primers for the msp5 gene were performed. The prevalence of A. marginale was 61.5% (118/192) for the blood smear technique and nPCR (msp5). The manifestation of clinical signs of anaplasmosis also increased significantly over the course of the study (P < 0.0001), being lower in animals aged 1-20 days, but increasing among those aged 21-41 and 42-60 days. These signs were characterized by apathy, fever, weight loss, diarrhea, dehydration, and hypochromic mucous membranes. Regarding the evaluation of the diagnostic techniques, no significant difference was observed in the detection of A. marginale between the blood smear and nPCR (P = 0.995), but the agent's rickets increased on Day 47 (P < 0.01) in both tests, thereby demonstrating a near-linear pattern of increase in rickets over the 60 days, with a consequent decrease in globular volume. This shows that of the 24 animals studied, 21 were infected at some point during the study period. Additionally, there was no significant difference between blood smears and nPCR, probably due to medium and high parasitemia, which were directly related to the clinical signs and decrease in globular volume. [ABSTRACT FROM AUTHOR]

Previous research shows that feeding and activity behaviours in combination with machine learning algorithms has the potential to predict the onset of bovine respiratory disease (BRD). This study used 229 novel and previously researched feeding, movement, and social behavioural features with machine learning classification algorithms to predict BRD events in pre-weaned calves. Data for 172 group housed calves were collected using automatic milk feeding machines and ultrawideband location sensors. Health assessments were carried out twice weekly using a modified Wisconsin scoring system and calves were classified as sick if they had a Wisconsin score of five or above and/or a rectal temperature of 39.5 °C or higher. A gradient boosting machine classification algorithm produced moderate to high performance: accuracy (0.773), precision (0.776), sensitivity (0.625), specificity (0.872), and F1-score (0.689). The most important 30 features were 40% feeding, 50% movement, and 10% social behavioural features. Movement behaviours, specifically the distance walked per day, were most important for model prediction, whereas feeding and social features aided in the model's prediction minimally. These results highlighting the predictive potential in this area but the need for further improvement before behavioural changes can be used to reliably predict the onset of BRD in pre-weaned calves. [ABSTRACT FROM AUTHOR]

Modern dairy farm management requires meaningful data and careful analysis to maximize profitability, cow health, and welfare. Current data platforms, such as DairyComp, lack robust integrated data analysis tools. Producers and consultants need dedicated tools to turn collected data sets into assets for informed decision-making processes. The DairyCoPilot app allows users to rapidly extract health and production data from DairyComp, then compile and analyze the data using a menu-driven point-and-click approach. Prospects for training consultants in applied data analysis skills make DairyCoPilot a tool to identify farm management bottlenecks with less time spent for data analysis, improving cow health, and dairy production. The DairyCoPilot Dashboard R Shiny application is published using RStudio Connect: https://connect.doit.wisc.edu/dairy-copilot/. [ABSTRACT FROM AUTHOR]