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The adoption potential of alley farming as an agro-intervention system capable of providing fodder to small ruminant livestock in southern parts of Nigeria is evaluated in this paper. Data were collected from a total of 240 respondents through the use of structured questionnaire in some selected communities of the south-western (SW) and south-eastern (SE) parts of Nigeria where the agro-intervention had been introduced in the past. Data analysis showed that ownership of small ruminants is more popular among households in savannah zone than forest zone, and among current and former alley farmers than non-alley farmers with browse being the most preferred feed given to the livestock. The management indicators showed that the care of the animals is generally the responsibility of all family members. The data suggest that the introduction of alley farming to produce supplemental feed for livestock may not gain quick adoption in areas with local sources of browse notably in the forest zone. The paper then concluded that the introduction of alley farming to produce supplemental fodder may be an innovation more suited to livestock owners' needs in the mid-term future, rather than immediately.

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.

During food fermentation, the digestive system of bovines generates methane gas as agricultural waste. Considering this, this study intended to evaluate different relationships between production type and management technologies, with enteric methane and nitrous oxide emissions, from beef cattle systems in the southern region of the San Luis province. To achieve this objective, 30 semi-structured surveys were conducted with regional producers. The producers were generally characterized, and the emissions were estimated through the application of the IPCC Level 2 protocols. Then, considering various techniques for technology management and adoption, these emissions were analyzed and compared. The production systems resulted to be heterogeneous in area, number of cattle, rodeo management, livestock unit, production, and other aspects. The estimated emission values were also variable depending on the form of expression, the management strategy adopted, and the production system applied. From a reductionist perspective of the aspects that characterize the extensive livestock systems evaluated, greenhouse gases emission values (GHG) are relative to the interaction of some predictive variables with the key factors of the production system and management techniques applied. Thus, when considering the emissions per kg sold, cow-calf+backgrounding or backgrounding systems, are environmentally more friendly than those of cow-calf, being the bull category the most sensitive to gas emissions. However, moderate or very good management in the cow-calf systems, tend to reduce them. Since the characteristics of the systems are so diverse, even for the same region, a broader and more integrated view is proposed for the expression of emissions, given by the set of variables that reflect the integral behavior of the system. Los bovinos, dado su sistema digestivo, generan gas metano como residuo durante la fermentación del alimento consumido. El objetivo de este estudio fue evaluar relaciones entre tipo de producción y tecnologías de manejo con las emisiones de metano entérico y óxido nitroso generado por el ganado bovino en sistemas extensivos del sur de San Luis. Para ello, se realizaron 30 encuestas semiestructuradas a productores de la región. Se realizó una caracterización general de los productores, se estimaron las emisiones mediante la aplicación de los protocolos del Nivel 2 del IPCC y se analizaron y relacionaron las emisiones teniendo en cuenta diversas técnicas de adopción y manejo de tecnologías. Se trata de sistemas productivos heterogéneos en sus distintas dimen-siones (superficie, cantidad de ganado, manejo del rodeo, carga animal, producción etc.). Los valores de las emisiones estimadas también fueron variables dependiendo de la forma de expresión, el manejo adoptado y el sistema productivo aplicado. Desde una mirada reduccionista de los aspectos que caracterizan los sistemas ganaderos exten-sivos evaluados, los valores de emisiones de gases de efecto invernadero (GEI) son relativos a la interacción de algunas variables predictivas con los factores tipo de sistema de producción y técnicas de manejo aplicadas. Así, al considerar las emisiones por kg vendido, los sistemas cría+recría o recría resultan más amigables con el ambiente que los de cría, siendo la categoría toro la más sensible a las emisiones de gases. Sin embargo, un manejo moderado o muy buen manejo en los sistemas de cría conduce a reducirlas. Al ser tan diversas las características de los sistemas, aún para una misma región, se propone una visión más amplia e integrada para la expresión de las emisiones, dada por el conjunto de variables que reflejan el comportamiento integral del sistema. EEA Catamarca Fil: Nieto, Maria Isabel. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Catamarca; Argentina Fil: Frigerio, Karina Laura. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria San Luis; Argentina Fil: Reiné, Ramón. Universidad de Zaragoza. Escuela Politécnica Superior. Departamento de Ciencias Agrarias y del Medio Natural; España Fil: Barrantes, Olivia. Universidad de Zaragoza. Facultad de Veterinaria. Departamento de Ciencias Agrarias y del Medio Natural; España. Instituto Agroalimentario de Aragón; España Fil: Privitello, Liliana. Universidad Nacional de San Luis. Facultad de Ingeniería y Ciencias Agropecuarias. Departamento de Ciencias Agropecuarias; Argentina

A North American livestock industries are diverse and of high value, consisting of very different animals and industries: beef cattle are raised for calves, meat, and leather; dairy animals for milk and veal; swine for pork; poultry for eggs and meat; and sheep for meat and wool. R. C. Axtell classifies livestock production systems as pasture or range, outdoor confined, and indoor confined. Detailed descriptions of the biology, taxonomy, host range, and management of livestock pests are available and should be consulted before starting a sampling program. Thresholds for many parasites in livestock production systems remain to be studied. Techniques for sampling arthropods in livestock systems have been previously summarized. Various livestock pests have free-living stages or periods in their life cycle. A diversity of domestic animals and management systems constitute livestock industries in Canada and the US As in other agricultural sectors, a variety of sampling approaches have been used to achieve management and research objectives.

Introduction to Sampling Arthropod Populations (L.P. Pedigo). Sampling Principles: Arthropod Sampling in Agricultural Landscapes: Ecological Considerations (D.A. Landis). Statistics for Describing Populations (P.M. Davis). Bias and Variability in Statistical Estimates (D.E. Legg and R.D. Moon). Sampling Techniques and Initial Program Development: Techniques for Sampling Arthropods in IPM (S.H. Hutchins). Developing a Primary Sampling Program (G.D. Buntin). Improving Sampling Program Efficiency: Initiating Sampling Programs (L.G. Higley and R.K.D. Peterson). Sequential Sampling for Classifying Pest Status (M.R. Binns). Sequential Estimation and Classification Procedures for Binomial Counts (V.P. Jones). Sequential Sampling to Determine Population Density (W.D. Hutchison). Sampling to Predict or Monitor Biological Control (J.P. Nyrop and W. van der Werf). Time-Sequential Sampling for Taking Tactical Action (L.P. Pedigo). Sampling Programs: Sampling Methods for Insect Management in Alfalfa (R. Berberet and W.D. Hutchison). Sampling Pest and Beneficial Arthropods of Apple (E.H. Beers, L.A. Hull, and V.P. Jones). Sampling Arthropod Pests in Citrus (J.D. Hare). Sampling Arthropod Pests in Corn (J.J. Tollefson and D.D. Calvin). Estimating Abundance Impact, and Interactions among Arthropods in Cotton Agroecosystems (L.T. Wilson). Sampling Arthropods in Livestock Management Systems (T.J. Lysyk and R.D. Moon). Sampling Programs for Soybean Arthropods (M.R. Zeiss and T.H. Klubertanz). Sampling Arthropod Pests in Vegetables (J.T. Trumble). Sampling Arthropod Pests of Wheat and Rice (N.E. Elliott, G.L. Hein, and B.M. Shepard). Implementation of Sampling Programs: Training Specialists in Sampling Procedures (G.W. Cuperus and R. Berberet). Designing and Delivering In-The-Field Scouting Programs (E.J. Bechinski).

Under the National Innovations in Climate Resilient Agriculture (NICRA) project, demonstrating site-specific technology packages on farmers’ fields with their active participation for adapting to current climate risks and building up the capacity of the farmers in climate resilient agriculture, activities were planned and executed under natural resource management, crop production, livestock management and institutional intervention modules during the years from 2011 to 2018 at Telangi village of Kinnaur, Himachal Pradesh by Krishi Vigyan Kendra, Kinnaur. Different need-based interventions were implemented through the village climate risk management committee and were evaluated in terms of measurable indicators alongwith critical evaluation for economic implications. Adoption of successful interventions has been replicated in the villages adjoining the NICRA village resulting into formation of NICRA cluster.

The Agricultural sector is dominant in Uganda’s economy. There are pertinent issues in the sector that need to be regulated for the sector to be effectively managed. The regulation in the agriculture sector starts with land management and then deals with the unique legal issues associated with the sector. These include regulation of land for agriculture purposes, soil governance, livestock management, crop production and management, regulation of water for agriculture, pesticides control, fertiliser management, regulation of investment in the agriculture sector and taxation. Without the legal and institutional arrangements that regulate the agriculture sector, it is difficult to promote incentives in the sector. The main purpose of this chapter is to review the legal and regulatory framework for the agricultural sector in Uganda. It reviews policies, the laws and regulations that relate to legal issues in the sector.

Farming is facing many economic challenges in terms of productivity and cost-effectiveness. Labor shortage partly due to depopulation of rural areas, especially in Europe, is another challenge. Domain specific problems such as accurate monitoring of soil and crop properties and animal health are key factors for minimizing economical risks, and not risking human health. The ECSEL AFarCloud (Aggregate Farming in the Cloud) project will provide a distributed platform for autonomous farming that will allow the integration and cooperation of agriculture Cyber Physical Systems in real-time in order to increase efficiency, productivity, animal health, food quality and reduce farm labor costs. Moreover, such a platform can be integrated with farm management software to support monitoring and decision-making solutions based on big data and real-time data mining techniques. A special thanks to all the AFarCloud consortium people that have worked on the AFarCloud proposal on which this paper is based on. The AFarCloud project is funded from the ECSEL Joint Undertaking under grant agreement n◦783221, and from several National funding agencies. It is worth noting some ECSEL projects that have provided background and/or reusable results taken into account in AFarCloud: MegaM@rt2 [34], SafeCOP [35], and AQUAS [36].

La ganadería bovina es una de las principales fuentes de emisiones antropogénicas de gases de efecto invernadero (GEI). A nivel internacional, regional y nacional existe una gran diversidad de estudios relacionados con la búsqueda de estrategias de mitigación de esos gases. El objetivo de este trabajo fue analizar el efecto de la aplicación de tecnologías estratégicas sobre las emisiones de GEI en sistemas productivos ganaderos típicos de la región sur de San Luis. Para ello se analizaron 6 casos de estudios en sus características actuales (SPA) y se plantearon y simularon dos propuestas mejoradoras de sus sistemas productivos (SPM1 y SPM2), se estimaron emisiones de CH4 por fermentación entérica y N2O de suelos gestionados. Se caracterizaron las emisiones y se realizó una comparación de emisiones de GEI de los sistemas entre sus tres estados (SPA, SPM1 y SPM2) a través de un ANOVA. Las “emisiones por ternero” fueron significativamente superiores (P

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., Agriculture; Microbiology; Animal science; Cattle; Livestock management; Veterinary medicine; Animal breeding; Ruminant; Antimicrobial resistance; Dairy; E. coli; Calf.

Bull-calves of the Kazakh white-headed breed play leading role in the development of beef cattle farming in Kazakhstan. Therefore, its improvement affects the production volume of high quality beef. The article describes some technological aspects of livestock management in the semidesert zone of the Naryn Sands of Kazakhstan. The authors determined the level of economic traits of the Kazakh white-headed bull-calves, their clinical and physiological parameters as well as the characteristics of hair-coat cover under the conditions of semidesert zone of the Naryn Sands. Three experimental groups of 10 calves in each group were selected for the tests. Bull-calves were selected based on the method of group analogues. According to the research conducted, when implementing management based on traditional technology of livestock, adopted for the Naryn Sands climatic conditions, it is recommended to feed bull-calves aged from 9 to 12 months with supplementary 3 kg of concentrated feedstuff during the growing period to achieve high live weight. Besides, based on data analysis, it was concluded that under the conditions of the Naryn Sands, there is no need to build facilities for beef cattle management that is economically advantageous. The analysis of the obtained data on hair-coat covering and clinical and physiological parameters suggests strong adaptive capacity of the Kazakh white-headed bull-calves at the conventional management technology typical for the Naryn Sands.

Broiler house systems are operated for the primary purpose of providing the appropriate conditions suitable to have a significant efficiency of animal production. The major environmental conditions in the poultry building are controlling the hygro-thermal parameters (temperature and relative humidity) and contaminant gases (NH3, CO2). In this paper, a poultry house prototype is monitored and controlled using the Supervisory Control and Data Acquisition (SCADA) tool like LabVIEW. A full prototype is designed and an efficient hybrid control strategy is implemented to control in real-time the poultry house climate. In the suggested approach, a Multi-Input Multi-Output (MIMO) fuzzy logic controller (FLC) is combined with a proportional, integral, derivative (PID) controller tuned by fuzzy rules. The proposed method, fuzzy logic, and On/Off controllers were tested by experimental measures and studies in a prototype model over 30 days during hot climates. The comparison results showed that the root mean square error of temperature and relative humidity response with the MFLPID controller (0.8 °C, 1.34%) were lower than that of FLC (1.16 °C, 1.86%) and On/Off controller (2.09 °C, 3.08%). The mean value of CO2 concentration with MFLPID (2461 ppm) was lower than that of FLC (3294 ppm) and On/Off controller (3624 ppm). However, the mean value of NH3 concentration was limited in small value (, Agriculture; Electrical engineering; Energy; Energy conservation; Process monitoring; Animal breeding; Livestock management; Green engineering; SCADA; Poultry farming; MIMO fuzzy; Energy efficiency.

The sustainability of the livestock sector in sub-Saharan Africa is negatively affected by limited access to high-quality fodder in adequate quantities. The effects of climate change further exacerbate feed availability. Therefore, there is a need to develop feasible cost-effective strategies for improving the year-round feed supply. Improved planted forages such as Brachiaria grass have been recommended as one of the strategies of alleviating feed scarcity, especially in drier agro-ecological zones. This study analyses the socio-economic determinants of adoption and the impact of adopting Brachiaria grass for feed sufficiency and increased milk production. Propensity Score Matching (PSM) method was used to assess the determinants and impact of the adoption of Brachiaria grass. Empirical results indicate that the adoption of Brachiaria grass led to a significant increase in milk production by 27.6% and feed sufficiency by 31.6%. The positive impact of Brachiaria grass is consistent with the role of agricultural technologies in improving the productivity, income, and welfare of smallholder farmers. The adoption of Brachiaria grass is influenced by age of farmer, tropical livestock unit (TLU), type of animal breed, perceived benefits of the technology, access to extension, and farmer group membership. The study recommends holistic policy approaches that promote the widespread adoption of Brachiaria grass. There is also a need for an effective information dissemination pathway for Brachiaria grass., Brachiaria grass; feed sufficiency, milk productivity; propensity score matching; planted fodder technology; climate-smart; agricultural policy; Animal Nutrition; Cattle; Livestock Management; Agricultural Economics; Agricultural Policy; Agricultural Technology; Economics

Unmanned aircraft systems (UAS) applications in production agriculture include applications in soil and water, plant emergence, and plant growth and development. UAS imagery is also useful for livestock management. The high spatial, temporal, and spectral resolution of results in large quantities of data requiring significant computing power to process the data. Basic knowledge of remotes sensing is essential to make use of UAS imagery. Selecting UAS equipment includes acquiring knowledge of both unmanned aerial vehicles and cameras.

Women play substantial roles in farming systems and are vigorously involved in farm and livestock management, but their contribution in farming systems is generally overlooked and undervalued which has reflected them as invisible workers. The farm women of are engaged in labour intensive, time consuming, arduous, monotonous, repetitive, manual operations resulting in fatigue and drudgery. Considering the issue as imperative, a survey was conducted in three districts of Western plain zone of Uttar Pradesh i.e Meerut and Saharanpur and Bulandshahar in the year 2015-2016. The total sample comprises a random sample of 180 households i.e. (3 District x 3 blocks/district x 2 villages/ block x 10 households) using a stratified sampling frame. A total of 180 households were selected for the study. Crop + Horticulture (vegetables) + Dairy (FS­3­) and Horticulture + Crop + Dairy (FS4) can be tagged as gender sensitive farming systems due to the higher amount of drudgery prone feminine farm operations. Carrying of dung through basket as headload depicted by their highest drudgery score (62.58) was a feminine farm operation performed by (88%) in FS3 followed by (83%) in FS4.

The more man has advanced towards technology, more and more problems affecting Mother Nature have aroused. ‘Not now, then when? Not earth, then where? Not we, then who’ are all the rhetoric questions that in themselves stress the need for us to become more aware about Global Warming. Global Warming has vastly affected different human sectors but the worst of the effects are seen in the Agricultural sector where the unpredictable climatic changes are causing to be of great trouble due to which many losses have been incurred. There were days back when our ancestors could predict the climate through ancient methods and to our surprise; most of their predictions did turn out to be true. Now that there are sudden climate changes, the previously used prediction methods have proven futile. There is an acute need to develop more sophisticated prediction methods using technology where more accurate decisions can be made. Using Embedded Systems and IOT, we aim at bringing sophistication to the crop prediction techniques to enhance the agricultural productivity even while the climatic trends keep on changing continuously. Adding on to the utility of this project is the Livestock Management module which further adds value to the project.

In western countries buffaloes are emerging as an alternative species for dairy product differentiation. In the near future dairy enterprises will have to meet increasing environmental regulations. Life Cycle Assessment has been widely used to assess the environmental impact of different milk production systems. We aimed to examine the environmental consequences of two dairy buffalo heifer farming systems using the Life Cycle Assessment approach. The primary data were collected from 32 subjects aged 7–8 months at the start of the experiment until they reached the age of puberty in about 12 months (i.e. at the age of 19–20 months). Sixteen animals were group-housed and confined in an indoor slatted floor pen (4 m2/animal) with an outdoor paddock (4 m2/animal); 16 others free-ranged on a Mediterranean natural pasture. The environmental charges for global warming potential expressed in terms of total emissions of carbon dioxide equivalent (CO2-eq) was 35.7% less in the free-ranging system as compared with the confined system. The main source of pollution for the confined system was biogenic methane (total amount produced = 2012 kg CO2-eq) followed by CO2 from fossil fuels (total amount produced = 1006 kg CO2-eq). The environmental charges for acidification potential, eutrophication potential and non-renewable energy use were 86.3%. 60.0% and 81.4% lower in the free-ranging system compared with the confined system, respectively. In the confined system the largest pollutant in terms of acidification potential was ammonia, whereas nitrate leaching in water (total amount produced = 3311 g SO2-eq) and the use of crude oil (total amount consumed = 5684 MJ-eq) were the most relevant for eutrophication potential and non-renewable energy use, respectively. Our results represent the first example of study comparing the environmental impact of an intensive dairy farming system with an alternative natural pasture based system in the Mediterranean region and suggest that the conduction of the unproductive part of the cycle on natural pasture can promote the reduction of several sources of pollution both in atmosphere and in water. Conversely, land occupation was higher in the free-ranging system as compared with the confined system (20,349 vs 1381 m2 year, respectively). However, the software and the database used for this calculation only considered duration of land use and yield per area unit, whereas no relevance was given to the quality of land use in terms of animal welfare promotion, contribution to biodiversity conservation, and maintenance of economically active social communities. Therefore, we suggest that the estimation of the impact categories related to land occupation would include aspects concerning the nature of the land.

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 study aimed to determine appropriate strategies and policies for empowerment of duck farming business in Brebes Sub-District, Brebes Regency. The method of this study was survey using stratified random sampling with the sample size of 52 laying duck farmers. Data taken in the form of primary and secondary data were analyzed using SWOT analysis. The result indicated that duck farming business did not have Economic Institutions, it was an individual, dependent and unprofessional business because it depended on the middlemen. It can be said that duck farming business in Brebes Regency was a livestock labor business. The strategies and policies for empowerment of duck farming business in Brebes sub-district Brebes Regency included the provision of livestock area facility, waste management, capital, livestock management and development of marketing centers for processed duck meat and eggs products.Keywords: Duck, Institution, Cooperation, Strategy, Policy.

There has been an increasing focus on providing better weather, climate, and resource information for decision making in drylands. This study explores what kind of information pastoralists in the Sahel received in 2013 and how they responded to this information. Moreover, the study assesses whether the disseminated information corresponds to the actual needs of pastoralists. The overall objective is thus to identify the outcome of providing weather, climate, and resource information to pastoralists and thereby to explore whether and how various products may guide their mobility and decision-making patterns. The results show that few of the interviewed pastoralists receive the seasonal rainfall forecasts, which have been produced since 1998 by the Climate Outlook Forum for West Africa. The pastoralists who did receive the forecasts used the information to adjust their crop cultivation strategies rather than to support livestock management decisions. To do the latter, pastoralists need information pertaining to the availability of grazing resources in various areas, the onset date of the rains, flooding events, and finescale information on rainfall amount during the first weeks of the rainy season. Such information could be used to adjust the purchase of supplementary fodder, to make qualified choices on transhumance destinations, and to make changes in herd composition. As pastoralists primarily acquire this information by calling friends and family in nearby areas, the results point to a strong disconnect between the parameters and scale of information that pastoralists need and those currently provided.

Excavations at the Iron Age settlement of La Hoya in north-central Iberia, which was attacked between the mid-4th and the late 3rd centuries BC, provided fossilized scenes of devastation and death but also an extraordinary opportunity to analyze lifeways. Here, we conduct stable carbon and nitrogen isotope analyses of human, animal and plant remains to reconstruct aspects of subsistence. The results indicate a mainly C3-based subsistence economy, focused on the cultivation of cereals and the herding of domestic animals, particularly pigs, as the archaeological data support. Although C4 plants are less abundant, they may have played a key role in infant and child feeding practices. Inferred differences in livestock management, as well as in manuring intensity and management in relation to water resources between crops, suggest a well-established farming economy. Inter-household variability in crop-cultivation and land-use suggests household production and subsistence autonomy, and suggests the existence of socio-economic inequalities within the community.

Precision approaches to farming are already having a big impact in many areas of agricultural production. Although dairy cattle farming has been at the forefront of developments in ruminant livestock production, technologies such as electronic identification, walk over weighing and automatic shedding gates are starting to have an impact in sheep production systems. A variety of new technologies are in development, and these have the potential to make a significant impact on sheep production systems in the future. These should not only improve the efficiency of production but also improve sheep welfare. Farmers need to be aware of both the limitations of these emerging technologies and also the fact they cannot replace good stockmanship.

The relationship between agricultural practices and biodiversity has become an important topic in European and American research and policies. Although most of the research has been on row-crop agriculture, grazing has recently received attention. We consider bird population responses to grazing intensity as an example of the potential of conservation grazing. We use North American Great Plains bird populations as an example and explore research and management possibilities of conservation grazing for the Canary Islands as they are a hot spot of biodiversity in Europe and have an important and growing goat population.

Crop monitoring play an important role in the management of agricultural production. This paper presents an integrated platform of crop condition monitoring and diagnosis based on internet of things, as well as its structure and function design. The platform adopted the technology of the internet of things; it achieved fine management of seed and cultivates process by the means of agriculture information real-time collection and monitoring. The platform has certain application value in many agriculture activities, such as livestock management, aquaculture and other and so on.

The present article characterizes the local model of nature management by the Buryat people inhabiting the eastern foothills of the Sayan Mountains. The author describes traditional types of nomadic pastoralism, their transformation at forest-steppe, piedmont, and high-mountain areas with an integrated economy. Various forms of animal husbandry practised by the Eastern Sayan Buryats are distinguished. The differences are determined by natural landscape environment peculiarities, pasture sizes, livestock quantity and breeds, as well as farming development level. The culture of the Eastern Sayan Buryats preserved its animal husbandry orientation in the course of structural and character changes of their day-to-day operating activities and operating cycles.

Conflict between farmers and large carnivores exists on Namibian rangelands and farmers continue to remove large carnivores indiscriminately. An appreciation for the economic and ecological roles of large carnivores cannot be expected to improve if the correct information is lacking and misconceptions persist. Conservancies are growing in importance in the conservation of Namibia's wildlife outside protected areas and may be important structures for information dissemination and improving wildlife management. This study investigated the role that farming enterprise (livestock and mixed livestock/game farming) and conservancy membership played in human–large carnivore conflict on commercial farms in Namibia. Our study found that the attitude towards large carnivores was similar between farming enterprises but that conservancy members within each enterprise were more likely to be tolerant of large carnivores and to use livestock management options to reduce conflict, than non-conservancy members. C...

This article reviews 25 years of literature focused on the adoption of agricultural best management practices (BMPs) in the United States to examine general trends in the categories of capacity, awareness, attitudes and farm characteristics. The study uses a vote count methodology and counts every instance of positive, negative and insignificant relationships in 55 studies. Education levels, capital, income, farm size, access to information, positive environmental attitudes, environmental awareness, and utilization of social networks emerge as some of the variables that are more often positively, rather than negatively, associated with adoption rates. The type of statistical analysis used in the studies has a negligible effect on the results. When different types of BMPs are examined in similar groupings, the aggregated findings generally hold true. The study concludes that farmer adoption rates can be improved by focusing on the generally consistent determinants of agricultural BMP adoption. This paper also highlights future areas of research that are needed including a focus on the determinants of adoption of water and livestock management BMPs and more study of the role of tenure and farm proximity to a river or stream.

This research addressed the hypothesis that spring precipitation data can be used to detect agricultural drought early in the growing season. The Rangetek range model was used to simulate yearly forage data based on historical precipitation and temperature records from the USDA-ARS Fort Keogh Livestock and Range Research Laboratory (Miles City, MT) and the Agriculture and Agri-Food Canada Manyberries Substation (Lethbridge, AB, Canada). Monthly total precipitation and monthly average maximum and minimum temperatures were used to develop regression equations predicting growing season forage production at the Fort Keogh Laboratory and Manyberries Substation. At Fort Keogh Laboratory, a combination of fall (October and November) and spring (April and May) precipitation were predictors of simulated forage yield index (P < 0.01, R2 = 0.84). At Manyberries Substation, April and May precipitation were predictors of simulated forage yield index (P < 0.01, R2 = 0.44). Using the actual forage data from Manyberries Substation yielded similar results, in that April, May, and June were predictors of forage production (P < 0.01, R2 = 0.50). Although the regression equation for actual forage production data from Manyberries Substation did indicate that July precipitation was a significant predictor, adding July precipitation did not increase the ability of the equation to detect reduced forage production. These results imply that annual forage production can be estimated with considerable confidence by July 1 and that forage produced by early July is a good indicator of total growing season forage production. Early season detection of drought effects on forage production provides much-needed flexibility in devising management alternatives to minimize the negative impacts of drought on rangelands and beef enterprises.

In Western Europe, at the turn of our era, the emergence of the Roman economic and agropastoral model is considered as the trigger for morphological changes experienced by livestock. This assumption is now undermined, reviving questions of the origin and mechanism of these changes as well as the influence of Gaul's agricultural particularities in the process. To investigate this question we used a geometric morphometric approach to study the phenotypic relationships of almost 600 dental remains of pigs (Sus scrofa domesticus) from 11 Gallic and Italian sites, and pinpoint evidence of Roman or indigenous signature on the livestock. The comparison of these different samples allowed us to demonstrate that the link between the Roman and Gallic pigs is weak, and, more importantly, that each of the two territories seem to follow its own livestock management model. Furthermore, each region or settlement within Gaul adopted their own particular pastoral or supplying strategies; apart from two urban sites of central Gaul which showed clear phenotypic relationships with southern populations. These results suggest that the pigs' morphology depended mainly on agricultural and economic characteristics of the different territories, within Gaul and Italy, except perhaps on some urban sites with different supply strategies. It seems, therefore, that the changing economic environment impacted both provinces independently, or at least differently, since it cannot be excluded that there may have been some commercial relationships between them.

Rural women play a vital role in farm and home system. She contributes substantially in the physical aspects of farming, livestock management, post-harvest and allied activities. Women entrepreneurs are a significant part of the global expedition for sustained economic development and social progress. The present study was conducted at the main campus of Punjab Agricultural University, Ludhiana in Punjab (India) on 90 members of PAU Kisan Club (ladies wing) which were selected randomly from 150 active members. Data were collected through personal interview during monthly meetings of the PAU Kisan Club. Findings revealed that about 67 percent of respondents had adopted the enterprises at commercial level to get economic benefit and were motivated from members of PAU Kisan club and themselves. Majority of the respondents (53.33percent) were doing enterprise individually due to small-scale enterprises and also for personal economic gains. On the other hand 41.67 and 35.00 percent of the respondents have adopted the preservation of fruits and vegetables, and vegetable cultivation, respectively. Majority of the respondents (65.00 percent) had medium extent of adoption of entrepreneurial activities means these respondents have adopted 2–3 enterprises out of selected sixteen entrepreneurial activities. All the respondents were selling their produce at household level. But out of that about 53.00 percent, respondents were selling their produce at Kisan Mela also. It was noticed that 66.67 and 58.33 percent of the respondents faced problem regarding frequent power cut and unable to purchase modern machinery due to inadequate capital.

This study entitled ‘The Role of Rural Women in Household Food Security Activities and Livestock Management in Mizoram’ was undertaken with the objectives to find out the role of women in household food security activities, livestock rearing activities and their participation in decision-making. A total of 120 respondents from three districts of Mizoram, that is, Aizawl, Kolasib and Mamit, were selected by using the stratified random sampling technique and interviewed personally to collect data. The result obtained from the study indicated that the participation of rural women in household activities was the highest in cleaning the house, and in the case of livestock activities, cleaning of animal sheds was the highest. Rural women's decision was considered in different household activities and in livestock activities. The correlation analysis showed that education had a positive and significant association with participation of rural women in household food security activities, while education, farming experience and extension contact had a positive and significant association with the participation of rural women in livestock activities. Women played a major role infood security activities but the control and access on resources remains with the male counterparts in the household.