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BACKGROUND AND OBJECTIVES: The livestock sector contributes to increasing greenhouse gas emissions. The emissions generated from livestock mainly originate from enteric fermentation, which is strongly influenced by feed quality. The utilization of fermented rice straw as a source of crude fiber for animal feed is one solution for providing high-quality feed. Central Java is one of the centers of cattle farming and rice production in Indonesia. The purpose of this study was to determine the contribution of greenhouse gas emissions resulting from fermented straw feed formula commonly practiced by cattle farmers in Central Java.METHODS: Greenhouse gas production was conducted in vitro using three formulas arranged in a completely randomized design with six replications. The three feed formula treatments were: 30 percent king grass + 35 percent rice bran+ 35 percent wheat bran (treatment one), 30 percent fermented rice straw + 35 percent rice bran + 35 percent wheat bran (treatment two), and 30 percent fermented rice straw + 70 percent concentrate (treatment three). Feed nutrient content and enteric gas production were analyzed to determine the quality of the feed formula as well as to determine feed digestibility and greenhouse gas production during the digestion process. The gas production was measured at regular intervals of 8, 16, 24, 36, and 48 hours. The methane, nitrous oxide, and carbon dioxide contents were analyzed using gas chromatography. Data on nutrient content and digestibility of dry matter and organic matter were analyzed using analysis of variance, and the estimated greenhouse gas emissions were calculated using the ideal gas equation approach.FINDINGS: The quality of the feed formula influences the amountof greenhouse gases emission produced by enteric fermentation processes. The feed quality of treatment one was equivalent to that of treatment two. The treatment three feed formulation had a crude protein content approximately 3 percent higher than that of treatment one and treatment two. The digestibility of dry matter and organic matter values did not show significant differences between the treatments. The feed formula treatment two can reduce potential greenhouse gas emissions by 1.81 percent from treatment one, whereas treatment three can reduce potential greenhouse gas emissions by 27.78 percent from treatment one and by 26.4 percent from treatment two. These results indicate that feed formulas with higher crude protein content have greater potential to reduce greenhouse gas emissions. This finding can be used to mitigate and develop strategies to improve feed quality by utilizing agricultural waste as a broader low greenhouse gas emission livestock management effortCONCLUSION: Utilization of fermented straw has the potential to reduce greenhouse gas emissions resulting from enteric fermentation and contamination of unutilized straw waste and has the opportunity to reduce land use and greenhouse gas emissions from forage plants. Efforts to utilize fermented straw as a low greenhouse gas emission feed need to be followed by improvements in feed quality. More comprehensive studies need to be carried out on the variations in feed formulas based on differences in regional resources, the economic feasibility of utilizing fermented straw combined with various feed ingredients, and the life cycle assessment of straw utilization as a feed ingredient based on geographical, social, economic, technological, and environmental dimensions.

Abstract Background Livestock keeping is one of the potential factors related to malaria transmission. To date, the impact of livestock keeping on malaria transmission remains inconclusive, as some studies suggest a zooprophylactic effect while others indicate a zoopotentiation effect. This study assessed the impact of livestock management on malaria transmission risks in rural Tanzania. Additionally, the study explored the knowledge and perceptions of residents about the relationships between livestock keeping and malaria transmission risks in a selected village. Methods In a longitudinal entomological study in Minepa village, South Eastern Tanzania, 40 households were randomly selected (20 with livestock, 20 without). Weekly mosquito collection was performed from January to April 2023. Indoor and outdoor collections used CDC-Light traps, Prokopack aspirators, human-baited double-net traps, and resting buckets. A subsample of mosquitoes was analysed using PCR and ELISA for mosquito species identification and blood meal detection. Livestock's impact on mosquito density was assessed using negative binomial GLMMs. Additionally, in-depth interviews explored community knowledge and perceptions of the relationship between livestock keeping and malaria transmission risks. Results A total of 48,677 female Anopheles mosquitoes were collected. Out of these, 89% were Anopheles gambiae sensu lato (s.l.) while other species were Anopheles funestus s.l., Anopheles pharoensis, Anopheles coustani, and Anopheles squamosus. The findings revealed a statistically significant increase in the overall number of An. gambiae s.l. outdoors (RR = 1.181, 95%CI 1.050–1.862, p = 0.043). Also, there was an increase of the mean number of An. funestus s.l. mosquitoes collected in households with livestock indoors (RR = 2.866, 95%CI: 1.471–5.582, p = 0.002) and outdoors (RR = 1.579,95%CI 1.080–2.865, p = 0.023). The human blood index of Anopheles arabiensis mosquitoes from houses with livestock was less than those without livestock (OR = 0.149, 95%CI 0.110–0.178, p

Virtual fence (VF) technology uses GPS-enabled collars to manage cattle movement through audio cues and electrical pulses, offering a potential alternative to traditional physical fencing. The performance of Nofence VF collars was evaluated while in operational mode and deployed on cattle grazing within the northern temperate climate of central Alberta, Canada. Technical parameters such as network connectivity, collar failures, battery performance, and solar charging capabilities of the VF collars were evaluated across four grazing trials, three conducted in summer and one in winter. The network connection intervals, defined as the time between successive connection events, ranged from 8.1 (± 6.2) to 9.4 (± 5.4) minutes throughout the trials, remaining well within the optimal 15-minute interval, highlighting the favourable interactivity with end-users. Poor network connections occurred less than 1 % of the time, demonstrating robust coverage across the entire area. Fourteen collars experienced a network connection failure that did not persist after a manual reset. Four cattle physically lost their collars, which were then recovered and promptly redeployed. Although the mean solar charging rate was lower during the winter trial (3.1 ± 10.8 mA h-1) than the summer trials (7.9 ± 18.0 to 12.4 ± 22.1 mA h-1), mean battery charge remained greater than 96 % for all trials, even during winter when daylight was limited. While reliable cellular network access is crucial, these results indicate that Nofence VF collars can effectively function in diverse environmental conditions, and may be suitable for broader adoption by cattle producers grazing in relatively cold climates, including those of western Canada.

Abstract This review outlines the current state of anthelmintic resistance (AHR) of gastrointestinal nematodes (GINs) among cattle in Argentina and Brazil, emphasizing the economic repercussions, animal health and welfare. The analysis explores factors associated with AHR and proposes a potential solution: the use of drug combinations. Both countries are grappling with a severe AHR scenario in cattle, having progressed through incipient, established, and advanced phases, leading to extreme cases of animal mortality due to ineffective control strategies. Genera such as Cooperia and Haemonchus have the highest reports of resistance, with Oesophagostomum radiatum also posing significant problems. While oral benzimidazoles and levamisole remain effective in most herds, moxidectin is entering an advanced resistance phase, and avermectins are increasingly deemed ineffective. The review explores the impact ofclimate, mixed grazing, animal movement and other husbandry practices, and the relationship between ectoparasite control and the emergence of resistant helminths. Notably, the discussion includes the strategic use of drug combinations as a valuable approach to address resistant GINs control in livestock, highlighting its significant potential to mitigate the challenges posed by AHR in the cattle industry of these countries.

This study investigates gender-based differences in the gut microbiota of Simmental cattle, focusing on bacterial, archaeal, and fungal communities. Fecal samples were collected and analyzed using high-throughput sequencing, with taxonomic classification performed through the SILVA and UNITE databases. Alpha and beta diversity metrics were assessed, revealing significant differences in the diversity and composition of archaeal communities between males and females. Notably, females exhibited higher alpha diversity in archaea, while beta diversity analyses indicated distinct clustering of bacterial and archaeal communities by gender. The study also identified correlations between specific microbial taxa and hematological parameters, with Treponema and Methanosphaera showing gender-specific associations that may influence cattle health and productivity. These findings highlight the importance of considering gender in microbiota-related research and suggest that gender-specific management strategies could optimize livestock performance. Future research should explore the role of sex hormones in shaping these microbial differences.

The forage-livestock balance is an important component of natural grassland management, and realizing a balance between the nutrient energy demand of domestic animals and the energy supply of grasslands is the core challenge in forage-livestock management. This study was performed at the Xieertala Ranch in Hulunbuir City, Inner Mongolia. Using the GRAZPLAN and GrazFeed models, we examined the forage-livestock energy balance during different grazing periods and physiological stages of livestock growth under natural grazing conditions. Data on pasture conditions, climatic factors, supplemental feeding, and livestock characteristics, were used to analyze the metabolizable energy (ME), metabolizable energy for maintenance (MEm), and total metabolizable energy intake (MEItotal) of grazing livestock. The results showed that the energy balance between forage and animals differed for adult cows at different physiological stages. In the early lactation period, although the MEItotal was greater than MEm, it did not meet the requirement for ME. MEItotal was greater than ME during mid-lactation, but there was still an energy imbalance in the early and late lactation periods. In the late lactation period, MEItotal could meet ME requirements from April–September. Adult gestational lactating cows with or without calves were unable to meet their ME requirement, especially in the dry period, even though MEItotal was greater than MEm. Adult cows at different physiological stages exhibited differences in daily forage intake and rumen microbial crude protein (MCP) metabolism, and the forage intake by nonpregnant cows decreased as follows: early lactation > mid-lactation > late lactation, pregnant cows’ lactation > dry period. For the degradation, digestion and synthesis of rumen MCP, early-lactation cows were similar to those in the mid-lactation group, but both were higher than those in the late-lactation group, while pregnant cows had greater degradation, digestion, and synthesis of MCP in the lactation period relative to the dry period. For lactating cows, especially those with calves, grazing energy requirements, methane emission metabolism and heat production were highest in August, with increased energy expenditure in winter. Overall, grazing energy, methane emissions and heat production by dry cows were low. In the context of global climate change and grassland degradation, managers must adopt different strategies according to the physiological stages of livestock to ensure a forage-livestock balance and the sustainable utilization and development of grasslands.

This study explores the critical challenges the livestock sector faces, particularly those related to biosecurity, animal welfare, and antibiotic use restrictions. It highlights the need to implement advanced information and communication technologies to enhance operational sustainability and decision-making. We introduce the Biorisk® External platform, a cloud-based visit control system designed to optimize biosecurity management by accurately tracking visitor activity through QR codes and GPS geolocation. During a 6-month study period from July to December 2023, we analyzed visits to 142 different swine production sites and 30 vehicle movement patterns. The analysis revealed trends in visitation patterns and compliance with biosecurity SOPs. The software categorized visits as authorized (A), not authorized with access (NAWA), and not authorized without access (NAWOA), providing a framework to assess biosecurity risks. Additionally, network analysis identified interconnected farms, which were classified as ‘superspreaders’, highlighting their considerable risk of disease transmission. This study advocates for the integration of digital systems in livestock operations to improve biosecurity measures, facilitate real-time data input, and support informed decision-making. By enhancing biosecurity protocols through technology, the livestock industry can better safeguard animal health, increase operational efficiency, and reduce potential economic losses associated with disease outbreaks.

The agricultural sector is responsible for a significant proportion of global anthropogenic methane (CH4) emissions, with enteric CH4 produced from ruminant livestock representing approximately 28% of the total. The development of effective mitigation strategies necessitates the accurate and actionable monitoring of CH4 emissions. However, a considerable research gap remains concerning real-time monitoring techniques capable of supporting on-farm enteric CH4 mitigation strategies. To bridge this research gap, this study explores the current status of real-time enteric CH4 emission monitoring techniques and technologies for ruminants. The study achieves this by reviewing key biomarkers and proxies for ruminant emissions, examining established animal-based measurement techniques, exploring emerging technologies, and critically assessing technological limitations and opportunities. By shedding light on this research area, this study aims to assist stakeholders in developing a viable pathway for on-farm emission monitoring, with the hope of facilitating a meaningful reduction in GHG emissions from the livestock sector.

Subclinical mastitis is a common and economically significant disease that affects dairy sheep production. Thermal imaging presents a promising avenue for non-invasive detection, but existing methodologies often rely on simplistic temperature differentials, potentially leading to inaccurate assessments. This study proposes an advanced algorithmic approach integrating thermal imaging processing with statistical texture analysis and t-distributed stochastic neighbor embedding (t-SNE). Our method achieves a high classification accuracy of 84% using the support vector machines (SVM) algorithm. Furthermore, we introduce another commonly employed evaluation metric, correlating thermal images with commercial California mastitis test (CMT) results after establishing threshold conditions on statistical features, yielding a sensitivity (the true positive rate) of 80% and a specificity (the true negative rate) of 92.5%. The evaluation metrics underscore the efficacy of our approach in detecting subclinical mastitis in dairy sheep, offering a robust tool for improved management practices.

This research article focuses on the evolution of a Mediterranean landscapes and the intricate interplay between natural and human-induced processes in the context of the Italian Anti-Apennine mountains. The study employs a multi-temporal approach to analyze changes in land use and landscape ecology, livestock activities, and agro-pastoral practices over seven decades. We noted a 18% decrease in animal units, particularly in goat and pig farming, accompanied by a 10% reduction in horse populations. Farmers’ adaptation strategies involve increasing animals per farm, aligning with broader agricultural trends toward intensification and specialization. In parallel, we observed a 22% reduction in grassland surfaces juxtaposed with an overall 15% increase in woodlands and shrublands, a 13% decreasing trend in habitat edge, and an overall 18% increase in patches aggregation at the landscape scale. The decline in anthropogenic pressures linked to depopulation triggered secondary successions, resulting in a 25% increase in homogeneous closed woodlands. These landscape alterations contribute to a 19% decrease in ecosystem heterogeneity and complexity, favoring ecological connectivity for forest-linked species but posing challenges for open meadow species. This, coupled with the loss of biocultural heritage, including traditional settlements dating back to the Bronze Age and Roman times, as well as pastoral traditions and knowledge, underscores the need to rethink future development strategies with a focus on retaining younger generations and preventing the loss of crucial ecosystem services.

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.

Abstract Livestock depredation by brown bears is one of the main source of human–wildlife conflict in rural Eastern Europe. Thus, identifying environmental and anthropogenic drivers of human–bear conflict, and developing spatial predictions for predation intensity are critical to mitigate such conflicts. We used 756 records of bear‐caused livestock predation collected between 2008 and 2016 in the Romanian Carpathians and evaluated predictors and spatial distribution of bear livestock predation events (BPEs) using separate binomial generalized linear mixed models for cows, sheep, and other livestock. Despite differences in the direction and magnitude of the effect, the prevalence of BPE for all livestock was driven by the interaction between environmental drivers along with relative bear abundance. Distance from forest was a strong negative predictor for cows and sheep, while distance to villages was a strong negative predictor for cows. Landscape heterogeneity was positively associated with cow and other livestock predation and negatively associated with sheep. Relative bear abundance data collected by wildlife managers was a positive predictor for predation on all livestock. Livestock damage was more prevalent near villages, showcasing plasticity of food resources sought by bears. Our work informs brown bear and livestock management strategies to develop awareness and implement damage prevention measures.

The ease of use and advancements in drone technology is resulting in the widespread application of Unmanned Aerial Vehicles (UAVs) to diverse fields, making it a booming technology. Among UAVs’ several applications, livestock agriculture is one of the most promising, where UAVs facilitate various operations for efficient animal management. But the field is characterized by multiple environmental, technical, economic, and strategic challenges. However, the use of advanced technological techniques like Artificial Intelligence (AI), Internet of Things (IoT), Machine Learning (ML), Deep Learning (DL), advanced sensors, etc., along with the assurance of animal welfare while operating the UAVs, can lead to widespread adoption of drone technology amongst livestock farmers. This paper discusses livestock management research where UAVs monitor farm animals via detection, counting, tracking animals, etc. In this article, an attempt has been made to elucidate different aspects and broader issues around livestock management while highlighting the associated challenges, opportunities, and prospects. This work is the first review paper on the subject matter with all the necessary information and analysis, to the best of our knowledge. Therefore, the article promises to provide interested researchers with detailed information about the field, guiding future research.

This paper concerns the management and protection of livestock using Indigenous Technical Knowledge among the Maasai of Kenya with an ultimate goal of promoting agricultural development. A sample of 120 households were selected from four Sub-locations of Loita ward in Narok County and subjected to questionnaire surveys. Additional qualitative data were collected through Key Informant Interviews and Focused Group Discussions. Results from this study show that the Maasai still rear three types of livestock, namely, cattle, sheep and goats. These animals provide them with food (99.2%) and other livestock byproducts. Study findings also reveal that the Maasai still predominantly use traditional methods based on indigenous technical knowledge to manage livestock feeding (85.8%), livestock diseases (89.9%), livestock breeding (74.2%) and livestock protection against predators and other incidental accidents. These findings are also supported by qualitative information from Focused Groups Discussions and Key Informants Interviews. In conclusion, the study established that the use of indigenous technical knowledge to manage and protect livestock among the Maasai have enabled them to sustain high-quality breeds of livestock for food security and income as well as environmental protection. The study recommends that as a policy, the Kenya government should put emphasis on mainstreaming indigenous technical knowledge systems in its agriculture extension programme and scientific knowledge base for sustainable well being and agricultural development.

The functions of non-agricultural crops unearthed from archaeological sites mainly pertain to their usage as livestock feed. However, the studies of livestock feed have predominantly relied on qualitative analysis, which often lacks descriptive objectivity and relies heavily on subjective feelings and experiences. In this paper, we aim to address this gap by focusing on quantitative analysis, utilizing macro-plant remains from the data of seventy-five archaeological settlements and one archaeological investigation in northern China spanning the Neolithic Age to the Bronze Age, as well as stable isotope analyses of carbon and nitrogen. This research delves into various aspects, including the exploration of the plant resources and livestock farming and the categorization of feed types for cattle and pigs in captivity. By employing quantitative analysis, we can gain a more comprehensive and objective understanding of these subjects. This approach aligns with studies on ancient livestock management and feed diversity. In essence, the discussion of civilization development and social changes during the Pre-Qin period holds significant value when considering forage analysis, just as crop analysis has proven insightful. By focusing on the quantitative analysis of non-agricultural crops and their role as livestock feed, we can shed light on important aspects of ancient societies and their agricultural practices.

The techniques of agriculture and animal husbandry at Tell Humeida, a Middle Uruk Period (Late Chalcolithic) site on the middle Syrian Euphrates, were studied using stable isotopes of bone collagen of domestic and wild mammals and from cereal and ruderal plant seeds. Two archaeological campaigns in 2009 and 2011 yielded a small collection of bones, most of which were taxonomically indeterminable. The work had to be interrupted due to the political conflict. The faunal study comprised collagen peptide fingerprinting for taxonomic identification, followed by isotopic analysis. Multiple 14C dating were performed to date the infill to around 3600 cal BC. An isotopic analysis of the sparse plant remains suggested that irrigation and manuring were common practices. Sheep and equids predominated in the faunal assemblage. Sheep grazed on manured soils, and their diet could include millet or another C4 plant, of which, however, no carpological remains were found. The diet of equids differed from that of sheep but also that of other wild ungulates (cervids/gazelles). Their isotopic signatures indicated that they grazed in humid areas, near the watercourse. These finds indicated a settlement that was closely linked to the availability of water, which made it possible to grow crops in an almost desert-like area, and the rearing of sheep.

The transformation of forests into agricultural and livestock systems negatively affects the ecological dynamics and the ecosystem services provided by different groups of insects, including dung beetles, which stand out for their importance in recycling livestock dung. Since the 1980s, farmers in different regions of the world have been using Ivermectin to control parasites that affect cattle. The main route of elimination of this molecule and its metabolites is through manure, which affects the richness, abundance, and biomass of dung beetles when they use dung from treated animals. To quantify this effect, we carried out an experimental design in the field in the Colombian Caribbean, where nine cattle farms were evaluated, of which three were taken for each of the different cattle management practices most used in the region: (i) Ivermectin not applied, (ii) two doses of Ivermectin at 1% applied per year and (iii) two doses of Ivermectin at 3.15% applied per year. To assess the richness, abundance, biomass, and functional groups of dung beetles, during the dry and wet seasons, 30 pitfall traps were baited on each farm with fresh cattle manure with the same management doses described above. A total of 25,441 individuals belonging to 19 genera and 30 species were collected. The richness, abundance, and biomass of beetle assemblages decreased along the gradient represented by management without using Ivermectin and management where Ivermectin was used. Paracoprid beetles were the functional group that was most negatively affected in cattle farms with Ivermectin use. In cattle farms where Ivermectin was not used, there was a greater diversity and higher functional structure of dung beetle assemblages than in those where this veterinary medicinal product was used. Using Ivermectin generates short- and long-term effects on the richness, abundance, biomass, and functional groups of dung beetles in livestock systems in the Colombian Caribbean. Therefore, we suggest using integrated treatment management to prevent the recycling fauna from being affected.

Images taken by drones often must be preprocessed and stitched together due to the inherent noise, narrow imaging breadth, flying height, and angle of view. Conventional UAV feature-based image stitching techniques significantly rely on the quality of feature identification, made possible by image pixels, which frequently fail to stitch together images with few features or low resolution. Furthermore, later approaches were developed to eliminate the issues with conventional methods by using the deep learning-based stitching technique to collect the general attributes of remote sensing images before they were stitched. However, since the images have empty backgrounds classified as stitched points, it is challenging to distinguish livestock in a grazing area. Consequently, less information can be inferred from the surveillance data. This study provides a four-stage object-based image stitching technique that, before stitching, removes the background’s space and classifies images in the grazing field. In the first stage, the drone-based image sequence of the livestock on the grazing field is preprocessed. In the second stage, the images of the cattle on the grazing field are classified to eliminate the empty spaces or backgrounds. The third stage uses the improved SIFT to detect the feature points of the classified images to o8btain the feature point descriptor. Lastly, the stitching area is computed using the image projection transformation.

Livestock management is an emerging area of application of the quadrotor, especially for monitoring, counting, detecting, recognizing, and tracking animals through image or video footage. The autonomous operation of the quadrotor requires the development of an obstacle avoidance scheme to avoid collisions. This research develops an obstacle avoidance-based autonomous navigation of a quadrotor suitable for outdoor applications in livestock management. A Simulink model of the UAV is developed to achieve this, and its transient and steady-state performances are measured. Two genetic algorithm-based PID controllers for the quadrotor altitude and attitude control were designed, and an obstacle avoidance algorithm was applied to ensure the autonomous navigation of the quadrotor. The simulation results show that the quadrotor flies to the desired altitude with a settling time of 6.51 s, an overshoot of 2.65%, and a steady-state error of 0.0011 m. At the same time, the attitude controller records a settling time of 0.43 s, an overshoot of 2.50%, and a zero steady-state error. The implementation of the obstacle avoidance scheme shows that the distance threshold of 1 m is sufficient for the autonomous navigation of the quadrotor. Hence, the developed method is suitable for managing livestock with the average size of an adult sheep.

In recent times, designated grazing areas/fields or routes for livestock grazing are usually defined. Hence, their herding activities’ success relies on data extracted from aerial photographs. As such, a direct and cost-effective way of monitoring livestock for perimeter coverage and in other natural situations is required. This paper presents a coverage solution involving multiple interacting unmanned aerial vehicles. The presented approach is built on a graph, with geographic coordinates set such that several Unmanned Aerial Vehicles (UAVs) can successfully cover the area. The maximum flying time determines the number of UAVs employed for coverage. The proposed solution is thought to solve some practical problems encountered during the execution of the task with actual UAVs. It is suitable for long-term monitoring of animal behavior under various weather conditions and observing the relationship between livestock distribution and available resources on a grazing field. The simulation was carried out using MATLAB and aerial images from Google Earth.

Understanding how individual grasses respond to herbivory and rainfall has been hampered by the difficulty of quantifying above- and belowground carbon (C) storage in grasses. Particularly by restoring degraded rangelands through reseeding, their C storage potential can be greatly enhanced. The responses of reseeded grasses to the effects of herbivory and precipitation were assessed to evaluate the potential of individual grasses for C storage as a technique for climate change mitigation. Clipping experiments were conducted on mature grass tufts of two native grass species, Chloris gayana and Cenchrus ciliaris, in the semi-arid Borana rangelands, Ethiopia. Further, above- and belowground C storage of young grasses of the same species in pot and field plot trials was experimentally quantified under simulated grazing and variable rainfall. The results showed that aboveground C was significantly 4 times lower in the clipped compared to unclipped mature grasses. In contrast, 3 times higher C was found in young reseeded grasses that were clipped compared to unclipped ones. Clipping and irrigation in combination significantly influenced belowground C in young grasses, with reduced irrigation overriding clipping effects. The paper concludes that moderate grazing should be encouraged to enhance CO2 uptake, consequently contributing to climate change mitigation in rangelands.

Animal wastes present in the form of manure, urine, feed, hatchery by product, blood, feather, bone, horn, and rumen material. Unmanaged animal waste contributes to environment problems. Animal wastes consist of nitrogen, phosphate, pathogen and organic material. Over absorption of nitrogen affect to melkomoglobinemia, meanwhile eutrophication happened due to over phosphate on the water bodies. Pathogen cause infection and diseases, and furthermore less oxygen due to over organic material in water decreasing fish population. Applying feed enzyme may increase availability of nutrition, performance, and decrease pollution impact due to manure. Well-management of livestock take consideration of environmental aspects, such as awareness of environment risk, balancing nutrition content of the waste animal, waste management, neighbor awarness, understand and obeying the regulation, and consider to the physical factors and applying land evaluation for livestock-site selection. This article responds to the impact of livestock on the environment and discusses factors related to environmental friendly of livestock management.

Introduction: E. coli is a ubiquitous bacterium commonly used as a sentinel in antimicrobial resistance studies. Here, E. coli was isolated from three groups (sick calves, healthy calves and bedding material), to assess the presence of antimicrobial resistance, describe resistance profiles, and compare these resistances among groups. Material and methods: Samples were collected from calves and calving pens from 20 dairy farms. Using the disc diffusion method, E. coli isolates were screened for antimicrobial resistance against seven antimicrobials: Amoxicillin, Ceftiofur, Gentamicin, Enrofloxacin, Trimethoprim–sulfamethoxazole, Florfenicol and Oxytetracycline. Isolates resistant to all these seven antimicrobials were tested again against an extended 19 antimicrobial drug panel and for the presence of the most common E. coli pathogenicity genes through PCR. Results & discussion: Three hundred forty-nine E. coli isolates were obtained; most isolates were resistant to a single antimicrobial, but 2.3% (8) were resistant to 16 to 19 of the antimicrobials tested. The group with the highest percentage of multiresistant isolates was the calves with diarrhea group. Younger calves provided samples with higher antimicrobial resistance levels. Conclusions: There is a high rate of antimicrobial resistance in dairy farms calving pens. These bacteria could not only be a resistance gene reservoir, but also could have the potential to spread these determinants through horizontal gene transfer to other susceptible bacteria. Measures should be taken to protect colonization of younger calves, based on hygienic measures and proper management.

Rudimentary non-market-oriented pig rearing systems have been implicated in the persistence of Taenia solium cysticercosis, an endemic disease of high public health concern in Uganda. We investigated the seroprevalence and key predisposing factors of the disease in Moyo and Lira, two pig-producing districts in Northern Uganda. Cross-sectional serosurveys were conducted in 428 pig farms (Moyo, 262; Lira, 166). Farmers kept on average two adult pigs per herd. Tethering was a common practice in rural areas; free-ranging less so. Confinement of pigs in pens was characteristic of periurban farming systems. Pigs were mainly fed crop residues and forages in the rainy season, and swill and crop residues in the dry season. The majority of farmers of the survey were women (55%) above 45 years old, and 51% of farmers had attained primary school education. A total of 723 pig serum samples were collected, 403 in Moyo, and 320 in Lira. They were analyzed for Taenia spp. antigens using B158C11A10/B60H8A4 Antigen-ELISA. The overall animal seroprevalence of Taenia spp. serum antigen was 10.4% (95% confidence interval [CI]: 4.9–17.6), with 13.2% (95% CI: 7.1– 21.2) the highest in Moyo vs 6.9% (95% CI: 2.9–13.9) in Lira. The herd-level seroprevalence was estimated at 13.7% (95% CI: 9.8–18.5) in Moyo and 11.4% (95% CI: 7.0–17.2) in Lira. Out of 12 explanatory variables assessed for association with the observed seroprevalence, only the district of origin was significant (p = 0.01). Pigs originating from Lira were a protective factor against Taenia spp. cysticercosis (odds ratio: 0.54). These findings highlight the urgent need for an awareness campaign with prevention and control measures to minimize the risk of transmission to pork consumers in these districts.

In the pig, intrauterine crowding can greatly affect postnatal characteristics, among which birth weight and locomotion. In a previous study, we discovered that piglets with a low birth weight/low vitality (L piglets) have a reduced motor performance compared to piglets with a normal birth weight/normal vitality (N piglets). A possible explanation is that L piglets lack the energy to increase their motor performance to the level of that of N piglets. Blood glucose levels (GLU) and glycogen concentrations in skeletal muscle of the front (GLYFRONT) and hind leg (GLYHIND) and the liver (GLYLIVER) at birth and during the first 96 h postpartum were compared between L and N piglets. GLU at birth was the same for both groups. After birth, GLU immediately increased in N piglets, whereas it only increased after 8 h in L piglets. L piglets showed a lower GLYHIND at birth and did not use this glycogen during the first 8 h postpartum, while N piglets showed a gradual depletion. GLYLIVER at birth was 50% lower for L piglets and was unused during the studied period while N piglets consumed half of their GLYLIVER during the first 8 h. Based on these results, it is possible that lower glycogen concentrations at birth, the delayed increase in GLU and the lower use of glycogen during the first 8 h after birth negatively affect motor performance in L piglets. However, based on this study, it is unclear whether the low mobilization of glycogen by L piglets is a consequence, rather than a cause of their lower motor performance.

This paper examines the problem of food security in the Republic of Kazakhstan over the past 10 years. Based on statistical data, an assessment was made of the prevalence of malnutrition among the population of the country, including children under 5 years of age. There has been a trend towards for an improvement in the nutrition of the population for a few indicators; however, further optimization of food security indicators is required to achieve the goals of sustainable development (SDGs) of the FAO WHO Agenda for the period up to 2050 in Kazakhstan and in its individual regions. The paper reflects data on demographic changes over the past 10 years and its self-sufficiency in basic foods for 2019. A high degree of self-sufficiency in meat products (117.6%) is revealed in the population of the Republic of Kazakhstan. However, self-sufficiency in dairy products is at an extremely low level (0.1%). Camel breeding has been successfully developing in the country over the past 10 years. However, the number of camels in the country is still at a low level. Camel milk can be considered as a great source of macronutrients, its daily consumption partially facilitates the problem of Food Security in Kazakhstan.

The digital transformation of agriculture has evolved various aspects of management into artificial intelligent systems for the sake of making value from the ever-increasing data originated from numerous sources. A subset of artificial intelligence, namely machine learning, has a considerable potential to handle numerous challenges in the establishment of knowledge-based farming systems. The present study aims at shedding light on machine learning in agriculture by thoroughly reviewing the recent scholarly literature based on keywords’ combinations of “machine learning” along with “crop management”, “water management”, “soil management”, and “livestock management”, and in accordance with PRISMA guidelines. Only journal papers were considered eligible that were published within 2018–2020. The results indicated that this topic pertains to different disciplines that favour convergence research at the international level. Furthermore, crop management was observed to be at the centre of attention. A plethora of machine learning algorithms were used, with those belonging to Artificial Neural Networks being more efficient. In addition, maize and wheat as well as cattle and sheep were the most investigated crops and animals, respectively. Finally, a variety of sensors, attached on satellites and unmanned ground and aerial vehicles, have been utilized as a means of getting reliable input data for the data analyses. It is anticipated that this study will constitute a beneficial guide to all stakeholders towards enhancing awareness of the potential advantages of using machine learning in agriculture and contributing to a more systematic research on this topic.

Agricultural grasslands provide vital habitats for many species. Yet despite representing a significant proportion of European land use, they are disproportionately understudied compared to arable systems. Increases in productivity and intensification have led to changes in management practices, which are likely to affect grassland habitats and the ecological communities that they support. This study simultaneously monitored three trophic levels to assess the impacts of permanent versus temporary pasture (leys) on vegetation composition, carabid and dung beetle abundance, and the activity of beetle-feeding bats. Leys had lower abundances of soil-inhabiting dung beetles, which may be explained by the more recent exposure to tilling compared with permanent pasture. Beetle-feeding bat activity was also greater in leys, with positive relationships between E. serotinus activity and Onthophagus abundance across both pasture types. However, the lack of any positive relationships between beetle-feeding bat activity and Aphodius, a well-known prey genus, suggests that other key prey orders (Lepidoptera) may be of more influence on bat activity. As well as the management of pasture, differences in cattle management between pasture types can have a significant impact on vegetation and soil structure, which influence invertebrate communities and potentially dictate habitat suitability for bats.

Introduction. Precision Livestock Farming (PLF) is spreading rapidly in intensive cattle farms. It is based on the monitoring of individuals using different kinds of sensors. Applied to grazing animals, PLF is mainly based on the recording of three parameters: the location, the posture and the movements of the animal. Until now, several techniques have been used to discriminate grazing and ruminating behaviors with accuracies over 90% on average, when compared to observations, providing valuable tools to improve the management of pasture and grazing animals. However, bites and jaw movements are still overlooked, even though they are of utmost importance to assess the animal grazing strategies for various pasture types and develop future techniques allowing better estimation of their intake. Literature. The goal of this review is to explore the possibility of monitoring the individual jaw movements and the differentiation of bites in grazing animals. For this purpose, (1) the mechanisms of forage intake in cattle are explained briefly in order to understand the movements performed by the cow, especially during grazing, (2) the various sensors that have been proposed to monitor jaw movements of ruminants such as mechanical sensors (pressure sensors), acoustic sensors (microphone) and electromyography sensors are compared and (3) finally the relationship between jaw movements, biting behavior and forage intake is discussed. Conclusions. The review clearly demonstrated the abilities of mechanical, acoustic and electromyography sensors to classify the difference types of jaw movements. However, it also indicated a wide range of accuracies and different observation windows required to reach these accuracies when compared to the observed movement. This classification purpose could lead to a better detection of more specific behavior, e.g. bite detection, and their exact location on pasture.

Abstract Whether interactions between wildlife and livestock are competitive or facilitative is context dependent. Intermediary factors that explain how context (seasonal or regional characteristics of the ecological community) affects these interactions are rarely reported. We compared activity time and density in vicuñas (Vicugna vicugna) introduced into the Chimborazo Faunal Production Reserve (CFPR), Ecuador, to describe how they interact with livestock. We compared vicuña density in wetlands and uplands (two landscape structures) with and without livestock (two conditions) using an isodar approach. We measured, over two seasons, vicuña forage abundance, composition, preference and accessibility, time vicuñas spent vigilant, and their flight distances on approach. We tested optimal foraging theory relating to the hypothesis that time mediates behavior, and found that vicuñas were no less frequently vigilant, nor were flight distances greater, during a wet season or in habitats of greater forage abundance and accessibility. We also found no evidence that vicuña behavior was density dependent; instead, we found that more time was spent vigilant by vicuñas when they foraged near livestock in rainy regions during the dry season. Although forage abundance was similar throughout CFPR during a dry season, better forage quality in areas occupied by livestock may constitute an effect of their facilitating vicuñas. A puzzling finding, because it was not explained by any of the other variables we measured, was that at low densities vicuñas selected habitat irrespective of livestock, and where their density was higher, it was doubly so adjacent to livestock. We conclude that in the CFPR, spatial heterogeneity in habitat quality determines the interactions between livestock and vicuñas. To support recommendations that minimize competition between wildlife and livestock, and to expand on descriptions of the contexts that determine the direction of species interactions, future study may require a wider sampling of the densities of sympatric large herbivores in general, and, in the CFPR, a closer resolution of spatial heterogeneity in forage plant quality.

The dairy industry represents 13% of the turnover of the European food industry and north-west Europe produces 60% of the European milk. However, in 2014 the milk market has experienced a substantial fall in milk prices of some 50%. At these lower prices for milk the business of many milk producers is not sustainable. Due to recent advances, the mid-infrared (MIR) analysis of milk performed within milk recording (MR) promises more information than used traditionally. Beside the established MR parameters (protein, fat, lactose, and urea), the spectra could provide additional information on cows' status for a range of characteristics (e.g. fertility, health, energy balance, feeding and methane emission). Thus, the spectra routinely obtained from the MIR analysis of milk offer a possibility to develop novel, cost-effective tools which enable milk producers to improve the management of their dairy herds and in turn reduce the costs for milk production. The OptiMIR project aims to improve the sustainability of the dairy sector by developing and providing innovative, economical and standardized MIR-based tools for the management of dairy herds. Additionally, the project aims to create and promote a framework for the cross-border exchange of information and practices to enhance the service of milk recording organizations (MROs) in north-west Europe and to strengthen their competitiveness. In order to achieve these objectives, in 2011 the European OptiMIR project was officially launched for a 5-year-period. The INTERREG IV B funded OptiMIR project is a cooperation between three research centers, three universities, 11 MROs, and one laboratory from six north-western European countries. To accomplish the goals, the different processes from the identification of the priority areas to the development, validation, and implementation of the novel tools were outlined in three working packages comprising 10 actions. A common transnational database combines the phenotypic data of the cows and the MIR spectra from the European MR, which enables the detection of relevant phenotypic traits and their reflection in the MIR spectra. Additionally, a standardization has been installed among all instruments of the milk analyzing laboratories involved in the OptiMIR project to ensure a stable prediction over time and a correction of deviations. Due to the monthly standardization process the developed prediction equations can be used in routine on all instruments taking part in the standardization. Different models for the prediction of the pregnancy status, energy balance, the methane emission as well as the detection of ketosis and acidosis have been developed within OptiMIR. It is worth mentioning, that those models predict the status of the animal with different accuracies and that progress on development and implementation differs between the models. Some of the tools developed within OptiMIR are already used in the field and provide dairy farmers with useful information e.g. about the health status or methane emission of a certain cow. The OptiMIR project also resulted in a collaborative planning on an economic interest group formation of the participating MROs. The final OptiMIR scientific and expert meeting disseminates the results obtained through OptiMIR more detailed and also provides an overview of recent advances in the development of management tools for the dairy sector. Initial application of the MIR-based tools has shown their potential for providing dairy farmers with information to improve their herd management in a cost-effective way. However, further research and development is required to finish a greater extend of MIR-based tools so that north-western European stakeholders can acquire competitive advantage in the dairy sector.

Grazing extensification and intensification are among the main problems affecting European grasslands. We analyze the impact of grazing intensity (low and moderate) and the use of veterinary medical products (VMPs) on the dung beetle community in the province of Pesaro-Urbino (Italy). Grazing intensity is a key factor in explaining the diversity of dung beetles. In the case of the alpha diversity component, sites with a low level of grazing activity—related in a previous step to the subsequent abandonment of traditional farming—is characterized by a loss of species richness (q = 0) and a reduction in alpha diversity at the levels q = 1 and q = 2. In the case of beta diversity, sites with a different grazing intensity show remarkable differences in terms of the composition of their species assemblages. The use of VMPs is another important factor in explaining changes in dung beetle diversity. In sites with a traditional use of VMPs, a significant loss of species richness and biomass is observed, as is a notable effect on beta diversity. In addition, the absence of indicator species in sites with a historical use of VMPs corroborates the hypothesis that these substances have a ubiquitous effect on dung beetles. However, the interaction between grazing activity and VMPs when it comes to explaining changes in dung beetle diversity is less significant (or is not significant) than the main effects (each factor separately) for alpha diversity, biomass and species composition. This may be explained if we consider that both factors affect the various species differently. In other words, the reduction in dung availability affects several larger species more than it does very small species, although this does not imply that the former are more susceptible to injury caused by the ingestion of dung contaminated with VMPs. Finally, in order to prevent negative consequences for dung beetle diversity, we propose the maintenance of a moderate grazing intensity and the rational use of VMPs. It is our view that organic management can prevent excessive extensification while providing an economic stimulus to the sector. Simultaneously, it can also prevent the abuse of VMPs.

Improvements after precision dietary management of nitrogen rejection in two commercial dairy farms in Wallonia. Two dairy farms located in Pays de Herve and in Ardennes were followed at regular intervals in order to assess levels of nitrogen rejection. In Farm 1, the cows were divided into two groups: group HP contained high production cows and group BP contained cows with a lower production yield. Each group was offered a specific basal diet. In Farm 2, only one group of cows was assessed. The feed rations on both farms were characterized by a imbalance between the yields allowed by the energy or the nitrogen supplies and by an extremely high OEB balance of 794, 582 and 726 g, respectively, in groups HP and BP and in the Farm 2 group. Dietary changes were proposed in order to balance milk yields and to reduce the hypothesized nitrogen balance. The yield and urea content data from each milk record, along with data regarding nitrogen rejection, were statistically analyzed using a mixed model, which included an autoregressive covariance. The data from records 2, 3, 4 and 5 were then compared to the data from record 1. The advised changes implemented in the feeding management plan maintained milk yields at values similar to the yields observed in record 1 – 36.2, 24.3 and 23.0 l of 4% fat-corrected milk expressed for fixed days in milk produced by groups HP and BP and the Farm 2 group. The changes induced a significant reduction in the milk urea content (220 vs 300 mg·l-1) and a significant reduction in nitrogen rejection, whether expressed in terms of g per day per cow, g·l-1 or kg per year per cow. The cows in the Farm 2 group rejected less nitrogen in absolute terms (217.9 vs 260.1 g per day). However, it is interesting to note that the management approach in Farm 1 was more efficient in terms of nitrogen rejection since the level was on average 9 g·l-1 in comparison with 10 g·l-1 in Farm 2. In conclusion, it appears that, for either farm, whether an intensive or extensive management regime was being employed, the provision of well balanced feed rations led to a reduction in nitrogen rejection. It should, however, be noted that management advice needs to be provided on a farm by farm basis.

The main objective of this paper is the use of milk composition data as a management tool. Milk composition, and in particular, milk fat content and fatty acid profiles may be significantly altered due to a variety of factors. These factors are reviewed in the literature; they include diet, animal (genetic) selection, management aspects and animal health. Changes in milk composition can be used as an indicator of the animal's metabolic status or the efficiency of the feed management system. The advantages of using this kind of data as a management tool would be to allow the early detection of metabolic or management problems. The present review suggests that milk and, especially milk fat composition may be used as a sustainability management tool and as a monitoring and prevention tool for several pathologies or health disorders in dairy cattle. Further, due to the use of mid-infrared spectrometry (MIR) technology, these tools may be easily implemented in practice and are relatively cheap. In the field, milk labs or milk recording agencies would be able to alert farmers whenever threshold values for disease were reached, allowing them to improve their dairy production from an economic, ecological and animal (welfare) point of view.

The Livestock Farm Networks system is dedicated to the development of her­bivore farming. As the Networks result from the history of French agricultural development, they are found throughout France and are organized at local level. The originality of the system lies in the partnerships between farmers, cham­bers of agriculture and the French Livestock Institute, and in that it uses a global approach to take into account the diversity of livestock farming regions and the study of livestock farming systems. The aim is not to be exhaustive, but to be representative of herbivore farming systems based on the selection of the studied systems. The aim is also to assess the evolution of these systems and to dissemi­nate the benchmarks obtained from the monitoring of 1900 farms by 210 cham­ber-of-agriculture agents, guided by 35 project leaders from the French Livestock Institute, and financed and supported by public authorities and the professional agriculture bodies. The regional and national enhancement of the Networks are aimed at different audiences: farmers, advisers, teachers (for advice or training), individuals or collectives, and local and national decision makers to improve their understanding of livestock farming systems and to measure the impact of new farming policies and lead their implementation. We also show the capac­ity of the Networks to mobilize themselves on emerging themes. Sustainability, competitiveness, working conditions or even environmental issues have been covered by the study fields of the system, well before sustainable development became a central theme. The Networks as a partnership system are sometimes complex to manage and may appear costly, but the strong and well-recognized partnership has made them a valuable resource and ensures their recognition and legitimacy. The variety of farming productions and the heterogeneous nature of the farming systems are good promoters of innovations and enable French agriculture to adapt to new challenges. The Networks not only enable the obser­vation of these evolutions, but they also act as their catalyst and guide, and help disseminate them.

Horse grazing systems may affect productivity and biodiversity of understory developed under Pinus radiata D. Don silvopastoral systems, while acting as a tool to reduce the risk of fire. This study compared continuous and rotational grazing systems effect upon biomass, fractions of stem, sprouts, leaves and woody parts of Ulex europaeus L. and alpha (Species Richness, Shannon-Wiener) and beta (Jaccard and Magurran) biodiversity for a period of four years in a P. radiata silvopastoral system. The experiment consisted of a randomized block design of two treatments (continuous and rotational grazing). Biomass, and species abundances were measured - biodiversity metrics were calculated based on these results for a two years of grazing and two years of post-grazing periods. Both continuous and rotational grazing systems were useful tools for reducing biomass and, therefore, fire risk. The rotational grazing system caused damage to the U. europaeus shrub, limiting its recovery once grazing was stopped. However, the more intensive grazing of U. europaeus plants under rotational had a positive effect on both alpha and beta biodiversity indexes due to the low capacity of food selection in the whole plot rather than continuous grazing systems. Biomass was not affected by the grazing system; however the rotational grazing system is more appropriate to reduce U. europaeus biomass and therefore forest fire risk at a long term and to enhance pasture biodiversity than the continuous grazing system.

Potohar plateau is a mountainous and rocky region, covered with scrub forest, interspaced with flat lying plains; the north and north-east consist of softly undulating plain areas along with some rocky patches. Realizing the need for the quantification of women participation in livestock management, a study was conducted to assess the level of participation and need of training in areas of interest. Chakwal, the third most populated district of barani Potohar, was selected as the universe of this research. Like other districts of Pakistan, all livestock species were reared in Potohar region including Chakwal district. Among total livestock population in the district, the decreasing order of species began with goats, followed by cattle, sheep, buffaloes, asses, camels, horses and mules. Although rural women had productive role in livestock management, yet they neither received adequate advice not had adequate access to modern technology that could benefit them in their livestock management activities. It was revealed from the study that more frequently carried out activities by rural women were livestock management, animal production, protection and poultry husbandry. Rural women were interested to get their training in livestock management, animal production, protection, poultry husbandry and marketing of animals to boost up the livestock productivity.

Ghana is predominantly an agricultural country with a clear majority of its population depending partly or fully on agriculture for their livelihoods. Pork consumption in Ghana is on the increase and the livestock industry is a key sector of alternative agri-business for farmers looking for profitable business ventures and household income. The growth of Ghana’s domestic piggery industry has been impeded by several constraints such as inadequate information, lack of improved breeding stock, land limitations, rising feed cost and water availability. In this research, systems models provide an understanding of the interconnectedness and relationships present within the piggery industry of Ghana. The Industry’s problems were pooled together and key factors identified, whose behavior over time causes problems by developing various individual two-loop system archetypes coupled with a list of sustainable management strategies. Also, the individual variables affecting the industry were consolidated to obtain a causal loop structure and behavior-over-time graph of the piggery industry. The system archetype developed here is generic enough to explain any productivity decline and business rivalry behavior of any agribusiness industry. The proposed archetype can also help farm managers and producers to make various decisions. The system archetypes contribute effectively to understanding the root cause of challenges rather than providing quick fixes ‘now’ which gives rise to a much bigger problem to fix ‘later’. Application of CLDs models and system archetypes can help farmers and policy makers understand the behaviour of the entire complex piggery systems that will aid in more clarity and consistency in decisions and policy objectives. This will close the gap of inadequate information both to farmers and policy makers and governance. Through the archetypes and the CLDs, it has been identified that using a systemic approach in addressing the problems could lead to the provision of adequate data and management strategies for effective decision making for improving the piggery/livestock industry.

Machine learning has emerged with big data technologies and high-performance computing to create new opportunities for data intensive science in the multi-disciplinary agri-technologies domain. In this paper, we present a comprehensive review of research dedicated to applications of machine learning in agricultural production systems. The works analyzed were categorized in (a) crop management, including applications on yield prediction, disease detection, weed detection crop quality, and species recognition; (b) livestock management, including applications on animal welfare and livestock production; (c) water management; and (d) soil management. The filtering and classification of the presented articles demonstrate how agriculture will benefit from machine learning technologies. By applying machine learning to sensor data, farm management systems are evolving into real time artificial intelligence enabled programs that provide rich recommendations and insights for farmer decision support and action.

This work was conducted to study alternatives for reduction of the bull:cow ratio in the Brazilian lowland and, therefore, lower the production costs for the local beef cattle industry. The ratios 1:10, 1:25, and 1:40 were used in native pastures with a mean stocking rate of 0.27 mature animal unit per hectare over two consecutive breeding seasons. Statistical analysis did not show any effect (P>0.05) of year (P = 0.2097), animal category (P = 0.0773), bull:cow ratio (0.8134) on reproductive performance. However, the pregnancy rate in a multiple bull system was higher (P = 0.0228) than in the individual bull system. An evaluation of the economic impact of this management system in the extensive Lowland herds showed that at the ratio of 1:10 the bulls were sub utilized.

Os objetivos deste estudo foram desenvolver um sistema computacional que efetue o dimensionamento e a evolução de rebanhos bovinos e criar uma ferramenta que possibilite ao usuário efetuar simulações em um sistema de produção de carne e/ou leite. Foi utilizada a linguagem CA Clipper. As rotinas foram desenvolvidas de forma conversacional, com acesso aos diversos programas, por meio de menus auto-explicativos. O sistema desenvolvido pode auxiliar o técnico e o pecuarista no dimensionamento e na evolução de um rebanho bovino com precisão e considerável rapidez; possibilita ao usuário efetuar inúmeras simulações; e constitui -se em importante ferramenta no auxílio da tomada de decisões.The objectives of this study were to develop a software that accomplishes both the dimensioning and evolution of cattle herds and develop a tool which makes it possible for the user to perform simulations with production systems of milk and or beef. The language employed was CA Clipper. The routines have been developed in a conversational form, with an access to the several programs by means of self-explicative menus. The developed system can aid both the technician and the raiser in dimensioning and evolution of a cattle herd with precision and outstanding rapidity; it allows to the user to perform a number of simulations; and it is considered an important tool in the assistance to decision-making.

The arrangement of divided space dictates to some extent the activities that take place within the smaller spaces created by such division. Access analysis of Hut Platform 4 at the Bronze Age site at Black Patch, combined with study of the artefacts and ecofacts from the site, gives some insight into the relationship between the constructed spaces and the way they were used. The accessibility of places in which activities occur affects and is affected by the perceived status of these activities. The question of whether or not all of the huts and fences on the hut platform were contemporary has been the subject of some debate; this investigation attempts to establish which configurations of huts and fences fit most closely with the distribution of diagnostic artefacts and ecofacts across the spaces in which they were used. This is achieved by generating control and real relative asymmetry values from permeability maps of the spaces in a number of possible configurations, which are converted into visual form for comparison with the distribution of relevant finds. In order to understand the use of space at the site it is important to consider it in an agrarian context; control of movement between spaces is necessary for certain aspects of livestock farming. A degree of flexibility in the permeability of boundaries allows this control to be exerted. Thus, the fences of Hut Platform 4 may have been erected for practical reasons, rather than to create psychological divisions between 'occupants' of the huts. Individual roundhouses were not necessarily thought of by their users in the same way as 'houses' are thought of today the arrangement of structures at the site was perhaps less influenced by ideas about kinship than the excavator supposed. A possible 'fence corridor' could have had a functional use, as similar arrangements of fences are used today for the control of livestock. Access analysis demonstrates the great range of possibilities for control of movement if all fences were contemporary.