Farm Location Research Articles

Seroepidemiology, molecular detection, and isolation attempts of Toxoplasma gondii in dairy goats from Rio de Janeiro, Brazil.

Goats are the one of the most susceptible domestic species to toxoplasmosis affecting animal health and production. The present study aimed to determine the seroprevalence of T. gondii infection in dairy goats from Rio de Janeiro, Brazil, as well as to evaluate associated risk factors, parasitic DNA detection in raw goat milk samples, and attempts to isolate the parasite from raw goat milk samples. Between October 2020 and December 2022, blood samples were collected from 460 goats, and 220 milk samples were taken from goats raised in the Rio de Janeiro state, Brazil. The serum samples were tested for anti-T. gondii IgG antibodies using IFAT. The milk samples were tested for parasitic DNA detection using nPCR, and attempts were made to isolate the protozoan in mice. For risk factor analysis, the farmers answered a semi-structured questionnaire covering various epidemiological variables. Overall, 24.1% tested positive for anti-T. gondii IgG in serum samples. Risk factors included farm location, age group, rearing system, presence of cats, grazing, and access of cats to water sources. In nPCR, 38.6% were positive, but none were positive in the bioassay. However, 3.2% of the mice inoculated with goat milk seroconverted. This study found that the exposure of dairy goats in Rio de Janeiro to T. gondii is driven by ineffective management practices in preventing and controlling the parasite in these animals. Moreover, despite the detection of parasitic DNA in raw goat milk, the shedding of viable parasites in milk from naturally exposed goats appears to be low.

Validation of the Ensemble Generalized Analog Regression Downscaling (En-GARD) Model to Downscale Near-Surface Wind Speed for the Northeast United States

Abstract Wind, often overlooked in climate change impact assessments, is now a crucial atmospheric variable due to our imminent reliance on renewable energy sources like wind energy. Therefore, establishing a wind speed database in higher temporal and spatial resolution is of great importance to assess wind power in historical periods and future projections. This study focuses on enhancing wind data representation and reliability of statistically downscaled model outputs by refining grid spacing from coarser to a desirable finer scale. Employing the Ensemble Generalized Analog Regression Downscaling (En-GARD) technique, we downscaled near-surface wind speed across a northeast (NE) U.S. domain that combines onshore and offshore wind farm areas. We tested multiple atmospheric variable combinations and identified near-surface wind speed (wind speed at 10 m), longitudinal and latitudinal wind at 10 m, and atmospheric temperature at 2 m, as the set that effectively guides the selection of analog days for the analog regression downscaling approach. Validation involved using ERA5 atmospheric reanalysis products (31 km) and high-resolution (4 km) Weather Research and Forecasting (WRF) Model simulations. Downscaling was conducted using a leave-one-year-out approach over 12 years (2001–12). Statistical analysis of the downscaled output over this period demonstrated a significant correlation and low error metrics (less than 20% for normalized RMSE and 16% for normalized MAE), indicating the reliability of the method and paving the way for its future application to downscale climate projection outputs. Significance Statement Wind speed has become a significant atmospheric variable due to our society’s imminent reliance on renewable energy resources like wind power. Often overlooked in climate change assessments, wind speed at a local scale over wind farm locations plays a crucial role in assessing and planning wind power resources in a future climate. We are providing the successful validation of a statistical downscaling methodology for near-surface wind speed at 4-km grid spacing using reanalysis data. The validity of the methodology gives confidence to downscale climate projection models and assess changes in wind speed for future climate scenarios in a follow-up study.

Design Of A 2 MW wind turbine for a proposed wind farm project in Nigeria using WT-PERF

This paper presents the results of a 2 MW wind turbine design carried out for the Langtang wind Farm project in Plateau State, Nigeria using the WT_PERF software. Selection of turbine rotor parameters is done in line with recommendations from the National Renewable Energy Lab (NREL) as well as available data from commercial turbine manufacturers. Due to availability of large wind resource in the proposed farm location, a turbine rotor radius of 22 m at a hub height of 40 m is chosen. Airfoils based on design by Dan Somers are selected for the design and an optimum blade planform is selected. The variation of rotor power generation with wind speeds as well as the application of varying blade pitch on power generation are discussed.

Территориальные аспекты развития органического сельского хозяйства в регионе

Abstract. The purpose of the study was to study the peculiarities of the territorial distribution of agricultural producers and the impact of their location on the development of regional organic agriculture in the future. The information base was the results of a questionnaire survey of 100 agricultural producers of the Leningrad region, representing mainly peasant (farming) farms in the region. To assess the impact of the territorial factor on the possibilities of developing organic production, 4 groups of respondents were identified, depending on the remoteness of the farm from the regional center – Saint Petersburg, as well as district centers. Results. Based on the analysis of the typological characteristics of the respondents and their answers, it was concluded that the participants of the first group (up to 50 km from Saint Petersburg) and at the distance of the farm from the regional center from 101 to 200 km show greater interest in organic production. This confirms the thesis that the territorial factor increases the risks of entrepreneurial activity in agriculture. However, there was no close dependence of farmers' motivation on the location of farms. The multidirectional influence of territorial remoteness on interest in organic production has been established, which is associated with a complex of stimulating or limiting factors. It was determined that in each of the groups of respondents (except the first) there is a large proportion (from 20 to 40 %) of people who found it difficult to answer about their intention to switch to organic status, which allows them to be considered possible participants in this sector in the future, if there are more comfortable conditions of activity. The scientific novelty of the study is to identify the peculiarities of the influence of the territorial factor on the interest of small businesses in the transition to organic production, which will allow them to be taken into account when implementing appropriate regional programs to mitigate existing barriers to entrepreneurial activity in the agricultural sector.

Validation of the effectiveness of pig farm repopulation protocol following African swine fever outbreaks in the Philippines

The African swine fever (ASF) epidemic has severely challenged the Philippines’ swine industry since 2019. The National African Swine Fever Prevention and Control Program (NASFPCP), launched in 2021, aims to provide guidance for managing ASF through surveillance, monitoring, and swine repopulation. This study evaluates the effectiveness of post-outbreak disinfection protocols and government-mandated measures for repopulation standard. Surveillance data from three repopulation phases—(I) depopulation, cleaning, and disinfection; (II) downtime (20 days); and (III) sentinel animals (40 days)—were collected from February 2020 to December 2021 in the province of Batangas. Time-to-detection of positive events were analyzed for different farm types, seasons, or location using survival analysis modeling. Probability of detecting infected farms at different sampling times was estimated in terms of sensitivity of the sampling time. Data from 145 swine farms, including 99 backyard and 46 commercial farms, revealed positive rates of 10.1 and 8.7%, respectively. The failure rate during repopulation surveillance was 9.66%, whereas 90.34% farms remained ASF negative. Sensitivity estimate increased from 18–21 to 89% by day 27, with sentinel animals on that day exhibiting the highest estimated sensitivity. This highlights the importance of sentinel pigs in the NASFPCP for effective ASF control in the Philippines. Survival analysis showed no statistically significant differences in the results between either farm type, season, or municipality level. Geographic mapping of surveyed farms and those with positive detections identified high-risk locations including San Juan and Lipa City as key areas of concern. Enhancing targeted surveillance is critical for improving an early ASF detection and national response in the Philippines.

The location of solar farms within England's ecological landscape: Implications for biodiversity conservation.

A global energy transition to using sustainable renewable sources is being driven by global agreements. Simultaneously there is a call for increased biodiversity conservation. This creates a green-green dilemma, where the expansion of renewables could lead to the demise of biodiversity if not carefully assessed, managed and monitored. Recognition of the dilemma is central to the development of Sustainable Development Goals. It is therefore important to understand whether renewable energy sources such as solar farms are being sited in areas where they have minimal impact on biodiversity. If solar farms were sited with minimal impacts on biodiversity, we hypothesised that they would be less likely to be sited close to ecologically sensitive areas than near random points. We used Geographic Information System methods to explore the density of solar photovoltaic (PV) farms in England and assessed their siting relative to sensitive ecological features, including priority habitat types, designated sites, and land conservation initiatives. We compared the area of 25 sensitive ecological features around solar farms and random points across three spatial scales (100m, 1000m, and 6000m radius scales). Solar farms were distributed throughout England, with the highest concentration in South West England. Solar sites were primarily surrounded by habitats with anthropogenic influences, such as agricultural and urban settings. Priority habitats, such as woodland, grassland, wetland and heathland, were more extensive around random points across spatial scales (except for woodland at the largest scale). Most designated sites were significantly more extensive around random points. We conclude that, under current planning regulations, solar sites in England are being placed appropriately with regard to sensitive ecological habitats, and are often sited in areas already impacted by farming and development. Adaptive planning should be implemented to ensure that the evolving research around biodiversity and solar farms is incorporated into decision making, and monitoring is completed across the lifespan of solar farms to assess impacts and effective mitigation.

Optimizing Sorghum for California: A Multi-Location Evaluation of Biomass Yield, Feed Quality, and Biofuel Feedstock Potential

Sorghum cultivars, particularly those used for forage and biomass, present significant potential as drought-resistant crops suitable for animal feed and biofuel production. This study evaluated 59 sorghum hybrids over five years (2019–2023) across three University of California research farm locations in the Central Valley: Kearney REC (KARE), West Side REC (WSREC), and Davis. The primary aim was to identify genotypes that exhibit high yield and stability across diverse environments in California, which is crucial for meeting the state’s significant feed needs associated with dairy operations and animal production. The evaluation focused on biomass yields, forage quality traits such as Relative Feed Quality (RFQ) and milk yield per ton (milk/ton), and biofuel-relevant chemical compositions like Neutral Detergent Fiber (NDF) and starch. A multi-trait stability index was employed to pinpoint superior genotypes that combine high yield with desirable quality traits. Results indicated significant genotypic, environmental, and genotype-by-environment (GxE) interaction effects for all traits except fat and water-soluble sugars. Eight hybrids were notable for maintaining high and stable biomass yields across different locations. Additionally, high fat and starch content were found to correlate with improved milk/ton potential, while lower fiber content (ADF, NDF) was associated with enhanced RFQ. Specifically, nine hybrids were identified as optimal for dairy forage due to their combination of high yield, RFQ, and milk/ton. Furthermore, distinct hybrids were identified for first-generation (starch-based) and second-generation (NDF-based) biofuel strategies. Three hybrids stood out as having desirable traits for both feed and biofuel applications, underscoring their versatility. This study highlights the utility of a multi-trait stability index in selecting superior sorghum genotypes for specific trait combinations. The identified candidates for forage and biofuel use, especially the multipurpose varieties, offer valuable insights that can aid growers and industry stakeholders in developing more sustainable and versatile sorghum production systems in California. Findings from this study contribute significantly to the development of more resilient sorghum production systems. By identifying hybrids that excel in both yield and quality across various environments, this research supports future cropping decisions aimed at enhancing water use efficiency and drought resilience in sorghum cultivation. These advancements are crucial for maintaining competitive dairy operations and advancing biofuel production in the face of climate change-induced challenges.

Multi-Criteria Decision Making (MCDM) Approach for Identifying Optimal Solar Farm Locations: A Multi-Technique Comparative Analysis

This study explores the spatial suitability for solar farm placement using Geographic Information System (GIS) techniques (ArcGIS Pro 3.0.2) coupled with Muti-Criteria Decision-Making (MCDM) methods. Nine evaluation criteria significantly impacting solar farm placement in Erbil, Iraq were selected, and the Analytic Hierarchy Process (AHP) was utilized to assign proper weights to these criteria. Suitability maps were derived and classified using three MCDM methods: Weighted Overlay (WO), TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution), and SAW (Simple Additive Weighting) to establish comparisons. Discrepancies were noticeable between the outcomes of these methods, with distinctions observable across most categories. The validation process illustrated superior performance by SAW model, closely followed by TOPSIS model, while the weighted overlay model showed significant differences. The southeastern region of Erbil governorate was identified as the most suitable area for solar farm construction due to favorable criteria values and potential for future expansion. This approach massively facilitates locating and evaluating ideal areas for solar farm construction, thereby minimizing the time, financial resources, and efforts dedicated towards this endeavor.

Molecular detection and genetic characterization of hemotropic mycoplasmas in goats and fleas from Thailand

Arthropod vectors play a crucial role in the transmission of hemotropic mycoplasmas, small bacteria that infect red blood cells in a wide range of animals and humans globally, leading to intravascular infections. Traditional Giemsa-stained thin blood smears, used for diagnosing hemotropic mycoplasmas through microscopic examination, have low sensitivity and are effective only when bacteremia levels are high. This study aimed to employ molecular methods to detect and genetically characterize hemotropic mycoplasmas in goats as well as investigate the potential role of fleas as vectors. Blood and flea samples were collected concurrently from goats on 16 farms across seven provinces in Thailand from January 2017 to October 2023. The 16 S rRNA, 23 S rRNA, and rnpB genes of hemoplasmas were amplified and sequenced. All fleas were identified morphologically and molecularly through DNA barcoding of the cytochrome oxidase I gene. A total of 78 out of 500 goats (15.6%), three pooled flea samples (3/6, 50%), and one individual flea (1/49, 2.04%) tested positive for hemoplasmas and all fleas were identified as Ctenocephalides orientis. BLASTN searches utilizing the three genetic markers revealed that the hemoplasmas detected in this study showed 97.81–100% similarity to Mycoplasma ovis and Candidatus Mycoplasma haemovis, which have been previously reported in sheep, goats, and humans, suggesting their zoonotic potential. The sequences were grouped into 28 unique nucleotide sequence types (ntSTs) based on minor variations in the 16 S rRNA gene. Hemotropic mycoplasma infection was significantly associated with farm locations and seasonality of sample collection (p < 0.0001), indicating that farm management practices or environmental conditions may play a critical role in the epidemiology of these infections. This study represents the first report of hemotropic mycoplasmas in goats in Thailand, confirms their presence in fleas, and provides valuable insights for farm management, such as guiding the rational use of insecticides and antibiotics.

Study of underwater sound propagation and attenuation characteristics at the Yangjiang offshore wind farma

The rapid growth of offshore wind farms has become a global priority, with both new and total installed capacities increasing sharply. Consequently, underwater noise generated with these developments has garnered significant attention. This study investigated the signals produced by 5.5 MW wind turbines at the Yangjiang offshore wind farm, focusing on various distances and depths. Results showed that the primary energy of the underwater noise was concentrated below 1500 Hz. At the same distance, deeper waters had lower noise levels than shallower waters. The discrete spectrum near the wind farm has a dominant frequency of 44 Hz. The peak sound pressure levels reach 93.76 dB at a depth of 10 m and 81.55 dB at 20 m, measured 50 m from the turbine. Horizontally, the sound pressure level of the dominant frequency decreased consistently as the distance from the wind farm increased. The sound transmission loss within 1 km is less than 10 dB, reaching 16.39 dB at 4 km, with noise levels nearing ambient ocean noise. A segmented spectral wide-angle parabolic equation was used to simulate the spatial sound field of the underwater noise, considering seabed topography. The noise propagation and attenuation models were validated against the measured data. Understanding noise propagation and attenuation with distance is crucial for selecting suitable offshore wind farm locations. Mitigating the impact of elevated underwater noise on sound-dependent species is essential for their survival.

"A fairly good crop for white men:" The political ecology of agricultural science and settler colonialism between the US and Palestine

From 1919 through the early 1950s, agricultural scientists affiliated with the University of California and agricultural scientists setting up settlements in Mandatory Palestine traveled between California and Palestine on a series of research trips. Building on conversations in historical political ecology and critical political ecologies of settler colonialism and racial capitalism, this article sets out to answer: how was agricultural science part of the project of settler colonialism in both California and Palestine in the first half of the twentieth century? Through an analysis of archival materials – field notes, professional and personal correspondence, and scholarly and popular media publications by US and European Jewish Zionist scientists – I argue that these scientists naturalized and made universal racial hierarchies through transnational technoscientific collaboration. US and Zionist scientists engaged in exchange and debate in two topics: the proper physical organization of and location of farms, and; the concept of carrying capacity of the land of historic Palestine. In both, agricultural science was used as an objective reason to elevate Western ideologies of proper cultivation and capitalist yield. This justified the dispossession of Palestinians from their land because they were "poor stewards." This historical case study holds implications for contemporary issues around land and population by Zionists in Israel today, and related debates in global sustainable development at large.

Farm Crime Experiences and Effects on Livelihood in Awendo Sub County, Kenya

This study dealt with farm crime experiences and effects on livelihood in Awendo sub County in Kenya. The study employed a descriptive survey design, using the mixed methods research approach, with a sample of 384 respondents. The study used a questionnaire, an Interview schedule and Focus Group Discussion as sources of data. Data was analysed using descriptive statistics and thematic approach. Based on the findings, the study concluded that distinct patterns of farm crime victimization existed in Awendo. They involved offences like night attacks on isolated farms. The study found a rising trend in farm-related crimes, mainly when crops are ready for harvest. In response, local authorities and community leaders should implement targeted security patrols and community watch programs, focused on vulnerable farm locations, especially at night. Law enforcement agencies should raise farmers' awareness of the importance of environmental security measures, including improved lighting and fencing, especially during high-risk times.

Assessment of electricity production and coastal protection of a nearshore 500 MW wave farm in the north-western Portuguese coast

Wave energy can contribute towards the “green” energy transition, but complementary applications like coastal protection are equally pertinent. However, viable commercialization should entice large wave energy farms of significant capacity, which may raise conflicts with coastal industries and/or protected areas. Such matters are addressed in this paper's numerical case study of a dual wave farm for a nearshore Portuguese site. It incorporates two parks of 75 bottom-fixed oscillating flap units, each. The farm's configuration, orientation, layout, and rating were evaluated for varying wave conditions and water levels, based on a statistically representative clustering technique. The farm's location was selected to minimize marine space conflicts. The numerical modelling was executed with SNL-SWAN, from which it was found that a staggered configuration – “W” – would yield better results than an aligned configuration – “III”. The “shadowing” effect of one park onto the other was equally observed, but with limited impact. Greater farm unit spacing and rated power benefited the annual energy production, with values of nearly 345 GWh/yr being achieved. However, the capacity factors were generally greater for lower power ratings, as pondered mean values varied between 0.078 (3.332 MW) to 0.144 (1 MW). Wave power absorption ratios between wave farms and cumulative standalone units (q-factors) were always below 1, pointing towards a destructive interference pattern. Important significant wave height reductions were observed (above 30 %, at times), albeit increments were punctually identified near two shallow water areas. Lastly, increasing the tidal level did not impact the farm's performance considerably, but benefited the nearshore impact.

Utilizing Fuzzy DANP to Rank Factors for Optimal Siting of Renewable Energy Farms

Energy consumption, much higher than the global average in developing countries, witnessed a growing and alarming trend in past years. An accepted reality for human communities is that the world’s energy demand is hastily increasing, and cheap fossil energy resources will gradually, yet certainly, be exhausted in future decades. To conserve these worthy fossil resources for future generations, prevent environmental damages due to burning these fuels, and respond to the increasing demand for energy, humans should use clean and renewable energies and discover proper locations to generate renewable energies. Today, locating studies prevail to determine the sites of renewable energy farms and reach industrial development. These studies consider various criteria to select the best location for establishing renewable energy farms. The present research attempted to identify and rank factors influencing the location of renewable energy farms using the fuzzy DANP approach.

Economic Justice in the Design of a Sugarcane-Derived Biofuel Supply Chain: A Fair Profit Distribution Approach

Background: In agricultural supply chains, unequal bargaining power often leads to economic inequality, particularly for farmers. The fair profit distribution (FPD) approach offers a solution by optimizing supply chain flows (materials, information, and money) to promote economic equity among members. However, our literature review highlights a gap in applying the FPD approach to the facility location-allocation problem in supply chain network design (SCND), particularly in sugarcane-derived biofuel supply chains. Methods: Consequently, we propose a multi-period optimization model based on FPD to design a sugarcane biofuel supply chain. The methodology involves four steps: constructing a conceptual model, developing a mathematical model, designing a solution strategy, and generating insights. This model considers both investment (crop development, biorefinery construction) and operational phases over a long-term planning horizon, focusing on farm location and crop allocation. Results: By comparing the FPD model to a traditional centralized planning supply chain (CSC) approach, we examine the impact of the planning horizon, number of farms, and sugarcane prices paid by biorefineries on financial performance. While the FPD model results in lower overall system profits, it fosters a fairer economic scenario for farmers. Conclusions: This study contributes to economic justice in supply chains and offers insights to promote fair trade among stakeholders.

Revolutionizing dairy waste: emerging solutions in conjunction with microbial engineering.

The dairy industry is grappling with significant challenges in managing effluent due to environmental concerns and stringent regulatory demands, necessitating innovative solutions. The paper investigates how microbial engineering is transforming the treatment of dairy wastewater, offering advanced methods to minimize environmental impact and enhance sustainability. It delves into the current challenges faced by the dairy industry, such as regulatory compliance and the limitations of traditional treatment technologies, and introduces microbial engineering as a promising solution for effluent management. Microbial engineering leverages genetic engineering techniques and microorganisms to enhance the efficiency of treatment processes like bioaugmentation and bioremediation. The environmental and economic benefits of microbial engineering, highlighting its potential to reduce pollution and lower operational costs for the dairy industry. The specific figures can vary based on factors like farm size and location, studies suggest that microbial engineering can reduce wastewater pollution by up to 50% and nutrient runoff by 30%. It also identifies key challenges and there are still areas including strains for specific pollutants (drugs, hormones), enhance degradation pathways, and increase microbes' stability (stress tolerance, long-term viability) that require further innovation to maximize its benefits. Through case studies and success stories, the paper demonstrates practical applications of microbial engineering in managing dairy effluent, illustrating how it can revolutionize industrial practices for a more sustainable future.

Hatchery type influences the gill microbiome of Atlantic farmed salmon (Salmo salar) after transfer to sea

BackgroundSalmon aquaculture involves freshwater and seawater phases. Recently there has been an increase in multifactorial gill health challenges during the seawater phase which has led to an urgent need to understand the gill microbiome. There is a lack of understanding on what drives the composition of the gill microbiome, and the influence the freshwater stage has on its long-term composition. We characterise the gill microbiome from seven cohorts of Atlantic salmon raised in six different freshwater operational systems—recirculating aquaculture system (RAS), flowthrough (FT) and loch-based system, prior to and after transfer to seven seawater farms, over two different input seasons, S0 (2018) and S1 (2019).ResultsUsing the V1-V2 region of the 16S rRNA gene, we produced amplicon libraries absent of host contamination. We showed that hatchery system influenced the gill microbiome (PERMAOVA R2 = 0.226, p < 0.001). Loch and FT systems were more similar to each other than the three RAS systems, which clustered together. On transfer to sea, the gill microbiomes of all fish changed and became more similar irrespective of the initial hatchery system, seawater farm location or season of input. Even though the gill microbiome among seawater farm locations were different between locations (PERMAOVA R2 = 0.528, p < 0.001), a clustering of the gill microbiomes by hatchery system of origin was still observed 7–25 days after transfer (PERMAOVA R = 0.164, p < 0.001). Core microbiomes at genera level were observed among all fish in addition to freshwater only, and seawater only. At ASV level core microbiomes were observed among FT and loch freshwater systems only and among all seawater salmon. The gill microbiome and surrounding water at each hatchery had more shared ASVs than seawater farms.ConclusionWe showed hatchery system, loch, FT or RAS, significantly impacted the gill microbiome. On transfer to sea, the microbiomes changed and became more similar. After transfer, the individual sites to which the fish were transferred has a significant influence on microbiome composition, but interesting some clustering by hatchery system remained. Future gill disease mitigation methods that target enhancing the gill microbiome may be most effective in the freshwater stage, as there were more shared ASVs between water and gill at hatchery, compared to at sea.

A Spatial Decision-Support System for Wind Farm Site Selection in Djibouti

The escalating energy demand in Djibouti requires the investigation of renewable energy sources, with wind energy emerging as a promising solution. To ensure the long-term efficiency and sustainability of wind energy projects, it is imperative to determine suitable sites for wind farm construction. When selecting a suitable site for a wind farm, there are multiple criteria to consider, such as wind velocity, ground slope, and distance to urban areas. Nevertheless, the current body of the literature reveals that no previous research has been conducted to explore an approach which involves multiple criteria to determine suitable sites for wind farms in Djibouti, as opposed to solely considering wind energy potential. This study proposes a spatial decision-support system to address the research gap in the selection of wind farm sites. Seven criteria are simultaneously evaluated in this system, including wind velocity, changes in wind direction, ground slope, distance to urban areas, distance to road network, distance to energy transmission networks, and land use. The CRITIC (Criteria Importance Through Intercriteria Correlation) method is used to objectively calculate the weights of the criteria. According to the results of performing the CRITIC method, wind velocity and distance to energy transmission networks were determined to be the most important criteria, while ground slope and land use were determined to be the least important criteria in comparison to others. A final suitability map showing the possible locations of wind farms in Djibouti was generated by considering the said criteria and their respective weights. The final suitability map reveals that the most suitable sites for the development of wind farms in Djibouti are located in the northeastern area between Obock and Khor-Angor, the southeastern area encompassing Lakes Ghoubet and Bara, and the southwestern area stretching from Lake Abbe to the Hanlé region. Using the proposed spatial decision-support system, decision makers would be empowered to make strategic and well-informed decisions when selecting the most suitable site for a wind farm in Djibouti.

THE PERCEIVED EFFECT OF RURAL TRANSPORTATION ON AGRICULTURAL PRODUCE IN IGBARA-OKE, NIGERIA

This study examines the perceived effects of rural transportation on agriculture produce in Igbara-Oke, Ifedore Local Government area Ondo State Nigeria. Case study research design was adopted while both primary and secondary data were utilized. Using a purposive multi-stage sampling technique, the total populations of farmers (2,139) at Igbara-oke, was determined and a 15% sample size was taken. Questionnaire was administered to 337 respondents. Focus Group Discussion (FGD) were held across the study area. Both descriptive and inferential statistics were used to analyzed the data at p value ≤ 0.05, while the qualitative data were content analyzed. Based on the ranking of the effect of transportation on agriculture, spoilage of farm produce was the highest (25.4%). Chi-square revealed a significant difference between the scale of agricultural engagement and transportation accessibility to farm locations (0.258). Transportation had a significant negative effect on agricultural produce, therefore, there should be rehabilitation of more rural feeder roads from farmlands to the markets is recommended.

Macromineral, micromineral and metal concentration of bovine colostrum samples from Salzburg, Austria

BackgroundBesides immunoglobulins which are essential for the calf to prevent Failure of Transfer of Passive Immunity (FTPI) colostrum contains multiple other constituents such microminerals, macrominerals and metals. The concentration of the minerals seems to be higher in colostrum than in normal milk. The aims of this study were to describe macromineral, micromineral and metal concentration of bovine colostrum samples from Salzburg, Austria and to see if there are differences in the concentrations between different cow feeding strategies and farm locations. MethodsTherefore, 1050 individual colostrum samples were collected from 72 dairy farms from different districts of Salzburg. All colostrum samples were analysed for macromineral (K, Mg, Na), micromineral (Co, Cu, Fe, I, Mg, Se, Zn) andmetal (As, Ba, Cd, Li, Mo, Ni, Pb, Sr, Tl, U) concentrations by inductive coupled plasma mass spectrometry. ResultsThe mean K, Mg and Na levels were 1218.71 mg l-1, 245.44 mg l-1 and 358.62 mg l-1, respectively. The micromineral concentrations of I, Se, Co and Zn were significantly higher in colostrum from dairy cows feeding a Total-Mixed-Ration during the lactation period in comparison to cows receiving microminerals by hand feeding, transponder feeding or via a licking bucket or licking stone. The metal analysis showed that in three farms, most of the colostrum samples showed Pb levels above the limit of 5 µg l-1. ImplicationsHerd-level factors need to be addressed to elevate micromineral concentrations and to reduce metal concentrations in colostrum from dairy cows from Salzburg, Austria. ConclusionThe results show that the macrominerals K, Mg and Na are within the range of published concentrations. For the microminerals, Co, Cu, Fe, I, Mg, Se and Zn the concentrations were significantly different depending on the mineral feeding strategies during the lactation and dry period. Metal concentrations of As, Ba, Cd, Li, Mo, Ni, Pb, Sr, Tl and U differed between the districts of Salzburg.