Improved Livestock Management Research Articles

IoT-based livestock tracking: Addressing challenges in Somali livestock farming

Livestock plays a vital role in Somalia's economy, contributing more than 60% of the country's gross domestic product. However, livestock production in Somalia faces many challenges, including conflict, insecurity, climate change and environmental degradation. These challenges can lead to livestock losses, which can significantly affect the livelihoods of livestock owners. This paper proposes an Internet of Things (IoT)-based livestock tracking system to help farmers locate their lost livestock. The system uses GPS and GSM/GPRS technology to track the location of livestock in real-time. The system also includes a boundary restriction feature that can be used to ensure that livestock remains within a designated area. The IoT-based livestock tracking system has the potential to address a number of challenges facing livestock production in Somalia. The system can help reduce livestock losses, improve livestock management practices, and increase productivity. The system is currently being field-tested in Somalia. The system successfully detects livestock crossing the border and transmits the livestock's location in real-time. Field test results show successful real-time tracking of livestock. The test data will be used to improve the system and assess its effectiveness in helping farmers locate their lost livestock.

OPTIMIZATION OF LIVESTOCK MONITORING SYSTEM IN OUTDOOR BASED ON INTERNET OF THINGS (IOT)

Livestock businesses are often underestimated by the public because they are associated with less hygienic working environments. However, the demand for livestock products such as meat and milk is increasing, providing significant business opportunities. Several obstacles, such as livestock loss and the capital required for cage construction, are barriers to starting a livestock business. Livestock losses, especially in outdoor farms, often occur because of the lack of proper monitoring and data collection. Therefore, technology is required to overcome this problem. The application of IoT technology is an effective solution for overcoming this problem. By utilizing sensors, such as GPS, temperature, and heart rate, farmers can monitor farm animals remotely using Android applications. In this study, a U-blox Neo6m GPS sensor was used to track the location of farm animals, a temperature sensor was used to monitor the temperature conditions of farm animals, and a heart rate sensor was used to determine the health of farm animals that had been tested. The use of a 1500 mAh LI-ION LITHIUM battery as a power source proved to be sufficient for 7 h. The results showed that this IoT-based Outdoor Livestock Monitoring System can provide information on the last location of livestock as well as real-time heart rate and temperature data in the database. This innovation opens opportunities for farmers to improve livestock management and monitoring efficiently, minimize losses, and increase the productivity of their livestock business

Epidemiological Studies of Subclinical Mastitis in Dairy Goats in Lumajang Regency, East Java, Indonesia

Subclinical mastitis is an economically important disease in dairy goat farming. Lumajang is a center for dairy goats in East Java. However, routine examination of subclinical mastitis for screening tests has no data. This study aimed to provide prevalence data and identification factors that influenced subclinical mastitis. Therefore, this study was carried out as part of the national surveillance program. The research design is a cross-sectional study with simple random sampling. Samples came from 19 farms with a total individual sample of 224 dairy goats. Detection of subclinical mastitis using an undirect test with the California Mastitis Test (CMT). Identification of management factors and characteristics that can influence subclinical mastitis in dairy goat farms using a structured questionnaire. The results showed that the prevalence of subclinical mastitis in Lumajang District was 36.2%. There was a significant difference in subclinical mastitis in each village (p<0.05). The highest prevalence of subclinical mastitis was in Kandangtepus village. A farmer's characteristic factor that significantly influences subclinical mastitis is the farmer's experience. The aspect of livestock management that significantly affects subclinical mastitis is structured work management. Subclinical mastitis was prevalent in dairy goats in Lumajang District and requires prevention efforts. Prevention approach through education for farmers to increase knowledge, attitude, and socialization to improve livestock management.

66 Emerging Precision Ranching Technology Is Enabling the Development of a “smart” Biome

Abstract Precision ranching technology is revolutionizing remote data collection from livestock and the land base they depend on, greatly improving our ability to assess the entire biome. Remotely Piloted Aircraft System (RPAS or drone) based remote sensing to date has been used primarily to assess intensive cropping; but RPAS systems equipped with interchangeable cameras: high-resolution visual, thermal, LiDAR, and multi/hyperspectral imagers are now being deployed on rangelands, to monitor subtle changes in the visible, near infrared and infrared spectrums (radiation) that both plants and animals reflect. A single RPAS system can now be used simultaneously for high-quality vegetation mapping and behavioral analysis of animals, providing a suite of comprehensive data-collection tools for studying livestock in a variety of landscapes and rugged terrain. For example, we have used RPAS systems to measure behavioral and physiological indicators of cattle heat stress in feedlots and on pasture (Mufford et al., 2021). These same drones can be utilized for RPAS collection of high-resolution imagery (using multi/hyperspectral imagers and LiDAR) for vegetative and topographical mapping, greatly improving our ability to visualize and characterize habitat attributes such as forage availability, quality (stage of growth) and accessibility. Equipping cattle with new tracking technology, including "smart" GPS ear tags, rumen boluses, and wireless fencing collars (based on low-earth orbit satellites and cellular networks) enable animals to be readily identified and tracked on the landscape, while providing invaluable physiological data, such as internal body temperature to monitor estrous, heat stress, or the onset of disease (Figure 1). Additionally, rapid advances in wireless fencing systems have the potential to improve livestock management through autonomous mustering or the implementation of advanced rotational grazing for use in regenerative agriculture efforts. Wireless fencing may decrease production (infrastructure) costs, while also providing a strategy to better align forage demands with use, and thereby enhance pasture condition at the habitat and landscape level. Finally, non-invasive pasture weighing systems, enabled with or without RPAS technologies, are capable of monitoring key livestock production metrics year-round. Together, these technological advances enabled by this new "smart biome" will improve animal health and welfare while ultimately enhancing the sustainability of extensive livestock production systems.

A teacher-to-student information recovery method toward energy-efficient animal activity recognition at low sampling rates

Automated animal activity recognition (AAR) has advanced greatly through recent advances in sensing technologies and deep learning, and improved livestock management efficiency, animal health, and welfare monitoring. In practical automated AAR systems where animals need to be monitored over a long period, the sampling rate dramatically affects the energy consumption and battery life of sensing devices due to continuous data collection and transmission. Considering real-world benefits, existing works have often lowered the sampling rate to reduce energy costs. However, when the sampling rate falls below a threshold, the AAR performance degrades rapidly due to many relevant signals being missed. Therefore, this study proposed a novel method, dubbed teacher-to-student information recovery (T2S-IR), to improve the performance of AAR at low sampling rates. This approach effectively leverages the knowledge obtained from high-sampling-rate data, to assist in recovering the missing information in features extracted by the classification network trained on low-sampling-rate data. The workflow of the T2S-IR contains two main steps. (1) we utilize high-sampling-rate data for training teacher classification and reconstruction networks sequentially. (2) Then, we train a student classification network using low-sampling-rate data, while promoting its performance by exploiting the knowledge learned by trained teacher networks via two novel modules, namely the reconstruction-based information recovery (RIR) module and the correlation-distillation-based information recovery (CDIR) module. Specifically, the RIR module employs the pretrained teacher reconstruction network to enforce the student classification network to learn complete and descriptive features. The CDIR module enforces the feature maps of student network to mimic internal correlations within feature maps of pretrained teacher classification network along temporal and sensor axes directions. To validate our proposed T2S-IR, we conducted experiments on two public datasets acquired for horses and goats using triaxial accelerometers and gyroscopes with an initial sampling rate of 100 Hz. Data having low sampling rates were obtained by downsampling the original data at different frequencies (i.e., 50, 25, 12.5, 10, 5, and 2 Hz). The results demonstrated that our method remarkably boosted the classification network trained on low-sampling-rate data (e.g., percentage-point increments in the precision, recall, F1-score, and accuracy of 3.33%, 3.58%, 3.45%, and 2.19%, respectively, for the 12.5-Hz horse data and 7.6%, 4.44%, 6.9%, and 0.79%, respectively, for the 5-Hz goat data) while outperforming existing knowledge distillation methods. The enhanced classification network can be directly applied in practical AAR tasks with low sampling rates, significantly beneficial for scenarios with constrained energy sources for wearable devices.

Adoption of improved management practices of livestock: Case of small-scale farmers in rural Bangladesh

This study examines the drivers of improved livestock management practices (ILMP) adoption in rural Bangladesh using data from the International Food Policy Research Institute's (IFPRI) Bangladesh Integrated Household Survey (BIHS). This study investigated four improved management practices: artificial insemination, concentrate feed, vaccination, and deworming. The binary logit and multivariate probit (MVP) models were used to analyse the data. According to the findings, approximately 65% of farmers practiced deworming, but only about 20% of farmers vaccinated their livestock. Logit regression analysis suggested that rural households with mobile phones and televisions were 5.2% and 3.8% more likely to adopt. Furthermore, compared to their peers, farmers who have maintained contact with livestock extension agents are 11% more likely to adopt. The MVP model indicated that likelihood of using concentrate feed increases with income, while artificial insemination is more prevalent among farmers who raise livestock for sale. Policy implication included the need for more extension agent-delivered awareness development programmes to educate livestock farmers on the benefits of ILMP. Scale-appropriate management practices can also play an important role. Farmers should be guaranteed of the availability of livestock feed and veterinary services at reasonable prices to promote adoption.

Twenty years of lion conservation in a commercial rangeland

Lion populations in Africa declined precipitously in the twentieth century outside of protected areas but the commercial cattle ranches of Laikipia County, Kenya, have been a unique exception, with low livestock stocking rates, careful range management, large populations of wild ungulates, and a full complement of large carnivores, including lions at a stable density of about 6/100 km2. The Laikipia Predator Project, later Living With Lions, started in 1997 with two primary objectives: improving livestock husbandry to reduce lion predation losses and subsequent killing of lions, and studying behavioral adaptations of lions to human activities and persecution. We initially interviewed ranch owners and managers on lion numbers, losses to all mortality factors, husbandry methods, costs, and lion control measures. Studies of husbandry and control methods led to improved livestock management, which gradually reduced losses and retaliatory lion killing. Persecuted lions are secretive and nocturnal, so behavioral research was dependent upon radio collaring, requiring development an effective capture technique. Collars introduced ranchers to their lions as individuals, decreasing their propensity to shoot them after livestock predation. The most important breakthrough was the development of “lion-proof” mobile bomas (corrals) which dramatically reduced night time losses and retaliatory killing. Global positioning system (GPS)-Iridium collars for research into lion movements, allowed development of a Lion Early Warning System to inform ranchers of morning lion locations, allowing them to avoid lions during day time grazing. These measures reduced retaliatory lion killing by 90% between 1998 and 2017. Development of simple and inexpensive hyena-proof bomas for traditional pastoralists dramatically reduced their losses and motivation to poison predators. Studies of lion movements and ecological energetics in relation to human activities have revealed patterns of diel avoidance of humans/livestock by day and predation of wild prey near bomas at night, showing that lions partition their activities temporally in order to utilize high quality hunting habitat while minimizing risk of encountering humans. Studies of predation ecology suggest that lion predation does not have a significant impact on Laikipia’s important population of endangered Grevy’s zebra. Several other carnivore research and conservation projects in Kenya arose out of the initial work in Laikipia.

Elevation gradient drives distribution of soil carbon in a semiarid grassland of British Columbia

A sequence of Brown, Dark Brown and Black Chernozems spanning a 600 m elevation gradient in a semiarid bunchgrass ecosystem (Lac du Bois Grassland) near Kamloops, British Columbia was first described in 1961. More soil organic carbon (SOC) at higher elevations along the sequence was attributed to increasing effective precipitation with increasing elevation. Since the 1961 study, plant community composition has shifted toward the desired climax community due to improved livestock management instituted in the 1970s; however, changes in soil carbon stocks remain unknown. The objective of this study was to quantify SOC and soil inorganic carbon (SIC) stocks using the same site selection criteria as used in 1961. SOC stocks (kg m−2 ± SD; 0–60 cm) were similar for Brown (5.73 ± 1.7) and Dark Brown Chernozems (5.87 ± 0.76) but increased sharply (10.11 ± 2.5) for the higher elevation Black Chernozems. SIC increased with depth in all three soil zones, representing 33%–50% of total C from the 30–60 cm soil depth. To evaluate changes in SOC (0–20 cm) from the 1961 measurements, three different approaches for calculating SOC stocks were used based on the inclusion or exclusion of coarse fragments. Results varied across the three soil zones from no change to a 20% increase in the Brown, an increase of 7% to a reduction of 26% in the Dark Brown, and a decrease of 12% to 35% in the Black soil zone. Information about soil coarse fragments and the distribution of SOC and SIC stocks within the soil profile is crucial for accurate comparisons across studies or resampling events.

Global investment gap in agricultural research and innovation to meet Sustainable Development Goals for hunger and Paris Agreement climate change mitigation

This paper provides estimates of the global investment gap in agricultural research and development (R&D) and innovation. The investment gap is defined as the additional annual investments required to end hunger in 2030 (Sustainable Development Goal SDG2) and to put agriculture on the pathway to the Paris Agreement target for 1.5°C increase over pre-industrial temperature levels. The investment gap is projected relative to a reference scenario with projections to 2030 using an integrated economic-biophysical model of the global agri-food system. In addition to showing the impacts on hunger, the modeling results are used to simulate the effect of the gap-closing investments on greenhouse gas (GHG) emissions from agriculture. In addition to projecting the impacts of overall investment in agricultural R&D on productivity and environmental outcomes, the analysis assesses the contributions of different types of innovative technologies and farming systems to the environmental outcomes, especially technologies that contribute to sustainability outcomes. Sustainability-oriented technologies and management practices examined include conservation tillage, nitrogen-use efficiency, improved livestock management, and other climate-smart technologies. The projected results show that additional agricultural R&D investments of USD 4 billion per year above baseline investments together with USD 6.5 billion per year invested in technical climate-smart options, can reduce hunger to 5% globally and achieve 2030 GHG emission reductions consistent with the Paris Agreement 2°C and 1.5°C pathways to 2030.

Resource Selection of Domestic Sheep on Mountainous Summer Habitat in Utah, United States

Past research has documented livestock grazing patterns and dynamics across pastoral landscapes. We used spatial locations of domestic range sheep (Ovis aries) obtained from Global Positioning System collars to study habitat selection on summer mountain habitat North of Scofield Reservoir Utah, United States. Data were collected between the months of July to September 2020. We developed a resource selection function to determine the influence of slope, distance to water, aspect, ruggedness, elevation, and vegetation types on habitat selection by sheep while grazing on summer mountain habitat. We found sheep selected for sites closer to water, with more gentle terrain, higher in elevation, and north-facing slopes. Vegetation types were less predictive, ostensibly due to the lack of species composition information in available geographic information system layers and the possibility of sheep being herded to avoid areas of overuse. Although it is often assumed that sheep use slopes more than their heavier and larger cattle counterparts, overall they tended to avoid steep slopes compared with all other predictor variables. This information on selection for higher elevations and avoidance of steep slopes can be used to improve livestock management practices including flock management that increases sheep foraging patterns and energy efficiency.

Measuring the Economic Value of the Negative Externality of Livestock Malodor in South Korea

The South Korean livestock industry has increased in scale and production, generating positive impacts on the national economy. However, livestock externalities, primarily malodor, have subsequently led to increased conflicts between producers and affected communities. This study estimated Korean households’ willingness-to-pay (WTP) for government subsidies to help address livestock malodor using a contingent valuation method (CVM) derived from a double-bounded dichotomous choice model. The annual average household WTP was estimated at 29,206 Korean won (KRW) (USD 25). This was slightly higher than the respondents’ self-reported average amount of KRW 25,457 (USD 22). The estimated economic value nationally is KRW 628 billion (USD 546 million) annually, for a total of KRW 3.14 trillion (USD 2.73 billion) over a proposed five-year period. The public’s estimated WTP can be leveraged to improve livestock management practices, more efficient waste disposal techniques, and improved husbandry methods to address conflicts between producers and surrounding communities.

Technology, infrastructure and enterprise trade-off: Strengthening smallholder farming systems in Tamil Nadu State of India for sustainable income and food security

The complexities of smallholder farming systems pose a challenge in demonstrating the potential benefits or risks of new technologies and policies. Using Integrated Analysis Tool, a rule-based dynamic simulation model, this study tried to improve the performance of major farming systems in the Tamil Nadu State of India. Amongst the four major farming systems viz. Black gram-based (BFS), Paddy-based (PFS), and Integrated Farming Systems (IFS) in Villupuram district and Dryland Farming System (DFS) in Virudhunagar district, IFS was found to be the most profitable and resilient based on their performance simulated for a 3-year rotation. Setting IFS as a benchmark, potential interventions were evaluated under other farming systems to improve their relative performance. The analysis allowed understanding the interactions in smallholder farming systems and the potential impact of interventions in a whole farm way considering the cash flows, cost intensity, and input-output trade-offs. While multi-bloom technology in black gram increased the net profit of BFS without much stress on input and labour, area expansion under rainfed groundnut incurred high expenditure. Trading-off paddy with maize and groundnut significantly increased the net profit of PFS but replacing sugarcane with tapioca and turmeric was not remunerative. Improved livestock management practices have substantially increased the net profit of DFS wherein crop yield could not be enhanced substantially without the prospects of good irrigation infrastructure. The irrigation endowed PFS has achieved 90% performance, whereas the water-starved BFS and DFS could achieve only 65% performance of IFS. We conclude that agricultural policy must not only focus on potential interventions that are profitable but also consider what is acceptable to the farmer, considering synergies and trade-offs between competing resources at the farm level.

Horizon Scan of Transboundary Concerns Impacting Snow Leopard Landscapes in Asia

The high-altitude region of Asia is prone to natural resource degradation caused by a variety of natural and anthropogenic factors that also threaten the habitat of critical top predator species, the snow leopard (Panthera uncia). The snow leopard’s landscape encompasses parts of the twelve Asian countries and is dominated by pastoral societies within arid mountainous terrain. However, no investigation has assessed the vulnerability and pathways towards long-term sustainability on the global snow leopard landscape scale. Thus, the current study reviewed 123 peer-reviewed scientific publications on the existing knowledge, identified gaps, and proposed sustainable mitigation options for the longer term and on larger landscape levels in the range countries. The natural resource degradation in this region is caused by various social, economic, and ecological threats that negatively affect its biodiversity. The factors that make the snow leopard landscapes vulnerable include habitat fragmentation through border fencing, trade corridor infrastructure, non-uniform conservation policies, human–snow leopard conflict, the increasing human population, climatic change, land use and cover changes, and unsustainable tourism. Thus, conservation of the integrated Socio-Ecological System (SES) prevailing in this region requires a multi-pronged approach. This paper proposes solutions and identifies the pathways through which to implement these solutions. The prerequisite to implementing such solutions is the adoption of cross-border collaboration (regional cooperation), the creation of peace parks, readiness to integrate transnational and cross-sectoral conservation policies, a focus on improving livestock management practices, a preparedness to control human population growth, a readiness to mitigate climate change, initiating transboundary landscape-level habitat conservation, adopting environment-friendly trade corridors, and promoting sustainable tourism. Sustainable development in this region encompasses the political, social, economic, and ecological landscapes across the borders.

Design and Field Test of a Low-cost Device for Real-time Livestock Tracking Using GPS/LoRa Communication

Highlights Monitoring movement is crucial to improve livestock management. GPS livestock tracking method using LoRa with an effective medium access control mechanism. Adaptive data collection with near real-time monitoring. GPS data were collected for improving home-range management. Low implementation costs with increasing lifespan of the devices. Abstract. Extensive livestock grazing systems are in line with agroecological principles. However, these systems are particularly complex to manage. Developing accurate and reliable monitoring of livestock movements and activities is a promising tool to improve the global performances of these systems. Various livestock management systems have been developed over the past decades, culminating in sophisticated systems in intensive controlled environments that allow the real-time monitoring of movements, behaviors, health and production parameters for livestock individuals/herds (e.g. dairy cattle). However, extensive and semi-extensive systems for which the animals are ranging freely outdoors at least part of the time, are presenting specific challenges for combined tracking data acquisition and communication. In this article, we present a GPS livestock tracking method using LoRa communication with a new medium access control mechanism. The node lifespan and performance of the system were evaluated in real on-farm conditions in three different locations in Thailand and Vietnam. The results showed that our system performed adequately well in terms of position accuracy and timeliness. The accuracy of GPS data collected are compatible with their usage for improved rangeland management, monitoring livestock movements and impacts on the environment, and for back-tracking epidemiological movements and contacts of individuals/herds to control diseases outbreaks. The communication system via LoRa allowed to some extent real-time location of livestock herds by farmers due to instant position updates to the Internet, although the performance depended largely on the relief of the landscape surrounding the rangeland used. Finally, reducing costs and increasing the lifespan of the devices remain critical objectives to foster the adoption of such system by farmers and by certification groups to provide field-based evidence for the traceability and quality control of livestock and animal products raised under healthy and environmental-friendly productions systems. Our current design, if produced in a large quantity of at least 100 units, would cost approximately $65 USD per unit, with an average lifetime of 20 days. Keywords: Cattle, GPS, LoRa, Tracking system.

Nitrogen Fate and Adaptation of the Microbial Community Responsible for Ammonia Removal in a Biofilter Treating Waste Gas from Livestock Manure Composting

Treating NH3-loaded gases is necessary for improved livestock management. Nitrification, the sequential oxidation of NH3 to NO3− via NO2−, is an important microbial process for effective long-term NH3 removal. Denitrification, a microbial respiration process that reduces NO3− and NO2− to N2 under anaerobic conditions, can also contribute to nitrogen conversion in biofiltration systems. Understanding these microbial processes is imperative to control NH3 removal better and achieve nitrogen balance in biofiltration. In this review, we discuss the functions and compositions of the microbial community responsible for nitrification and denitrification in a biofiltration system, along with the relationship between these processes and the nitrogen mass balance. Our results indicate that both nitrification and denitrification could be achieved by a consortium of microbes well adapted to the ecosystem in a full-scale biofilter. Moreover, the microbial community was controlled by substrate availability. Nitrogen removal potential was up to 39% in a laboratory-scale biofilter with intermittent water recirculation, and the unknown nitrogen loss was considered mainly denitrified. Under gradual accumulation of nitrogenous compounds, the gamma proteobacterial group contributes to NH3 oxidization. These findings will improve our understanding of microbial fluctuations and the complex behavior of nitrifiers and denitrifiers within an NH3-loaded biofiltration system.

How to make noncoherent problems more productive: Towards an AMR management plan for low resource livestock sectors

Global policy for managing antimicrobial resistance (AMR) is underpinned by a standardised and coherent global framework for reducing antibiotic use in clinical health, veterinary health, and food production sectors. Within the framework, problematic antibiotic use (a significant driver of AMR) is treated as a knowledge deficit on the part of users and prescribers, which can be remedied by educating them to make better informed treatment decisions. This narrow approach to AMR management conceals the socioeconomic and material drivers of antibiotic decision-making, creating challenges for low resource regions that rely on antibiotic therapies to manage uncertainty and precarity. Thus, there is a need for a global AMR policy that acknowledges the diversity of sociomaterial arrangements and practices that antibiotics form part of, if their use is to be reduced without undermining productivity or the attainment of poverty reduction indicators. Drawing upon research of antibiotic use in West Africa’s livestock sector, this article analyses the interrelation of antibiotics, AMR action plans, and production management strategies in ecologies of livestock breeding practices. We apply the STS-influenced perspective of noncoherence to analyse how seemingly contradictory practices and institutional logics productively coalesce. We argue that observing noncoherent practices increases our understanding of antibiotic use in relation to local breeding conditions that are frequently not of the producers’ making, whilst drawing attention to context-specific possibilities for improving livestock management capacities and reducing reliance on antibiotic therapies in low-resource settings. The article concludes by calling for an AMR global policy that is more responsive to local specificity rather than enforcing universal standardisation.

Presumed killers? Vultures, stakeholders, misperceptions, and fake news

AbstractVultures and condors are among the most threatened avian species in the world due to the impacts of human activities. Negative perceptions can contribute to these threats as some vulture species have been historically blamed for killing livestock. This perception of conflict has increased in recent years, associated with a viral spread of partial and biased information through social media and despite limited empirical support for these assertions. Here, we highlight that magnifying infrequent events of livestock being injured by vultures through publically shared videos or biased news items negatively impact efforts to conserve threatened populations of avian scavengers. We encourage environmental agencies, researchers, and practitioners to evaluate the reliability, frequency, and context of reports of vulture predation, weighing those results against the diverse and valuable contributions of vultures to environmental health and human well‐being. We also encourage the development of awareness campaigns and improved livestock management practices, including commonly available nonlethal deterrence strategies, if needed. These actions are urgently required to allow the development of a more effective conservation strategy for vultures worldwide.

Rotavirus in Calves and Its Zoonotic Importance.

Rotavirus is a major pathogen responsible for diarrheal disease in calves, resulting in loss of productivity and economy of farmers. However, various facets of diarrheal disease caused by rotavirus in calves in the world are inadequately understood, considering that diarrheal disease caused by rotavirus is a vital health problem in calves that interrupts production benefits with reduced weight gain and increased mortality, and its potential for zoonotic spread. The pathological changes made by rotavirus are almost exclusively limited to the small intestine that leads to diarrhea. It is environmentally distributed worldwide and was extensively studied. Reassortment is one of the important mechanisms for generating genetic diversity of rotaviruses and eventually for viral evolution. So, the primary strategy is to reduce the burden of rotavirus infections by practicing early colostrum's feeding in newborn calves, using vaccine, and improving livestock management. Rotaviruses have a wide host range, infecting many animal species as well as humans. As it was found that certain animal rotavirus strains had antigenic similarities to some human strains, this may be an indication for an animal to play a role as a source of rotavirus infection in humans. Groups A to C have been shown to infect both humans and animals. The most commonly detected strains in both human and animals are G2, G3, G4, and G9, P [6]. Therefore, this review was made to get overview epidemiology status and zoonotic importance of bovine rotavirus.

English

Climate change poses a major threat to agricultural production and food security in Ethiopia. Temperature rise and variability in rainfall patterns have had serious consequences on crop and livestock production. Climate-Smart Agriculture (CSA) is one of the solutions that simultaneously address the issues of food security, climate change and agricultural productivity. The objective of this study was to examine trends and variability of temperature and rainfall, identify local CSA practices and their implications to food security. The study was conducted using mixed methods approaches, in which 368 randomly selected households were surveyed, 10 key informants were interviewed, and 6 focus group discussions participants were held. The analysis was based on survey data and a binary logistic regression model was used. Findings revealed that highly adopted CSA practices were conservation agriculture, integrated soil fertility management, small scale irrigation, and improved livestock management. Factors determining CSA practices were also explored such as household size, farming system, off-farm income, access to irrigated farm, distance to market, farm size, and access to agricultural credit. It was evident that CSA practices had a great potential to solve challenges and highest implication to food security. The maximum and minimum annual temperature of the study area has increased by 0.98 and 0.46ºC while the trend of average annual temperature has increased by about 0.72ºC. Annual rainfall has increased significantly by 153.73 mm, in small rainy season (Belg) has decreased by 30.78 mm, and in main rainy season (Kiremt) has increased significantly by 120.96 mm in the past three decades. The study also concludes that a large proportion of respondents were aware of most of the practices, but adoption of CSA practices examined was very low. Therefore, as a recommendation, sensitization of farmers on reality of climate change and the need to adopt CSA practices towards reduction of adverse effect of climate change should continue. Policy and support program should focus on dissemination of CSA practices to a larger proportion of smallholder farmers. Key words: Climate smart agriculture, climate change, food security

Isolation and Characterization of Coronavirus and Rotavirus Associated with Calves in Central Part of Oromia, Ethiopia.

Background Coronavirus and rotavirus are most commonly associated etiologies for calves' diarrhoea, resulting in loss of productivity and economy of farmers. However, various facets of diarrheal disease caused by coronavirus and rotavirus in calves in Ethiopia are inadequately understood. A cross-sectional study was conducted with the aim of isolation and molecular characterization of coronavirus and rotavirus from calves in the central part of Oromia (Bishoftu, Sebata, Holeta, and Addis Ababa), Ethiopia, from November 2018 to May 2019. The four study areas were purposively selected and faecal samples were collected by simple random sampling for diagnosis of coronavirus and rotavirus infection by using the antigen detection enzyme-linked immunosorbent assay (Ag-ELISA) kit. In addition, this study was carried out to have insight in prevalence and associated risk factors of coronavirus and rotavirus infection in calves. Result During the study, 83 diarrheic and 162 nondiarrheic faecal samples collected from calves less than 4 weeks of age were screened for coronavirus and rotavirus. Of the 83 diarrheic samples, 1 sample (1.2%) was positive for coronavirus antigen and 6 samples (7.2%) were found to be positive for rotavirus antigen by Ag-ELISA. All the nondiarrheic samples were negative for both coronavirus and rotavirus Ag. The overall prevalence of coronavirus and rotavirus infection in calves was estimated at 0.4% (1/245) and 2.45% (6/245), respectively. All samples (7) of ELISA test positive of both coronavirus and rotavirus were propagated in Madin-Darby bovine kidney (MDBK) cells. After 3 subsequent passages, progressive cytopathic effect (CPE), i.e., rounding, detachment, and the destruction of monolayer cell of five samples (1 sample of coronavirus and 4 samples of rotavirus) (71.4%) were observed. At the molecular stage, reverse transcriptase polymerase chain reaction (RT-PCR) technique was used to determine the presence of coronavirus and rotavirus nucleic acid by using specific primers. The 5 samples that were coronavirus and rotavirus antigen positive by ELISA and develop CPE on cell culture were also positive on RT-PCR technique. The prevalence of infection peaked at 1st and 2nd weeks of age in male calves. Conclusion Diarrheal disease caused by coronavirus and rotavirus has a great health problem in calves that interrupts production benefits with reduced weight gain and increased mortality and its potential for zoonotic spread. So, the present findings show coronavirus and rotavirus infection in calves in Ethiopia that needs to be addressed by practising early colostrum feeding in newborn calves, using vaccine, or improving livestock management.