Pre-slaughter handling of pigs has been documented to affect the quality of meat though no studies have investigated this relationship in the Kenyan context. This study aimed to determine the ...prevalence of gross lesions and practices related to sub-optimal welfare in pigs presented for slaughter while analyzing the relationship between occurrence of these lesions and meat quality. A cross-sectional study was conducted at a medium scale, non-integrated pig abattoir supplying to the Nairobi market, with a capacity to slaughter approximately 40 pigs a day. Data on welfare-associated lesions and handling practices were obtained from 529 pig carcasses and traders respectively. 387 pork samples were collected, and their quality evaluated by measuring their pH, meat color and drip loss. These three parameters were used to classify pork into four recognized categories namely: Red, Firm, Non-exudative (RFN), Pale Soft Exudative (PSE), Dark Firm Dry (DFD) and Red Soft Exudative (RSE). Almost all pigs were inefficiently stunned as evidenced by the presence of consciousness post-stunning. The majority of pigs (82.97%) having one or more welfare-associated gross lesions. Other animal welfare malpractices observed were high loading density and inadequate rest periods between transport and slaughter. A quarter of the pork samples were of sub-optimal quality including: RSE (11.36%), PSE (2.58%) and DFD (2.58%). Multinomial logistic regression revealed that pork originating from pigs transported at a high loading density had increased odds of being classified as DFD (OR 13.41, 95% CI 2.59–69.46). The findings indicate the need to educate stakeholders in the pork value chains on improved pig handling before and during slaughter to enhance pig welfare pre-slaughter and pork quality post-slaughter. Animal welfare legislation enforcement and implementation was observed to be insufficient. There is a need to educate key stakeholders on its importance of being put into practice both from economic and welfare perspectives.
Mapping of land use/ land cover (LULC) dynamics has gained significant attention in the past decades. This is due to the role played by LULC change in assessing climate, various ecosystem functions, ...natural resource activities and livelihoods in general. In Gedaref landscape of Eastern Sudan, there is limited or no knowledge of LULC structure and size, degree of change, transition, intensity and future outlook. Therefore, the aims of the current study were to (1) evaluate LULC changes in the Gedaref state, Sudan for the past thirty years (1988-2018) using Landsat imageries and the random forest classifier, (2) determine the underlying dynamics that caused the changes in the landscape structure using intensity analysis, and (3) predict future LULC outlook for the years 2028 and 2048 using cellular automata-artificial neural network (CA-ANN). The results exhibited drastic LULC dynamics driven mainly by cropland and settlement expansions, which increased by 13.92% and 319.61%, respectively, between 1988 and 2018. In contrast, forest and grassland declined by 56.47% and 56.23%, respectively. Moreover, the study shows that the gains in cropland coverage in Gedaref state over the studied period were at the expense of grassland and forest acreage, whereas the gains in settlements partially targeted cropland. Future LULC predictions showed a slight increase in cropland area from 89.59% to 90.43% and a considerable decrease in forest area (0.47% to 0.41%) between 2018 and 2048. Our findings provide reliable information on LULC patterns in Gedaref region that could be used for designing land use and environmental conservation frameworks for monitoring crop produce and grassland condition. In addition, the result could help in managing other natural resources and mitigating landscape fragmentation and degradation.
Zoonoses account for most of the emerging and re-emerging infections in Kenya and in other low to medium-income countries across the world. The human-livestock-wildlife interface provides a nexus ...where transmission and spread of these zoonotic diseases could occur among communities farming in these areas. We sought to identify perceptions of the community living near the Lake Nakuru National Park in Kenya.
We used participatory epidemiology techniques (PE) involving Focus Group Discussion (FGD) among community members and Key Informant Interviews (KII) with the health, veterinary, and administration officers in July 2020. We used listing, pairwise matching, and proportional piling techniques during the FGDs in the randomly selected villages in the study area from a list of villages provided by the area government officers. Kruskal-Wallis test was used to compare the median scores between the zoonotic diseases, source of information, and response to disease occurrence. Medians with a z-score greater than 1.96 at 95% Confidence Level were considered to be significant. Content analysis was used to rank qualitative variables.
We conducted seven FGDs and four KIIs. A total of 89 participants took part in the FGDs with their ages ranging from 26 to 85 years. Common zoonotic diseases identified by participants included anthrax, rabies, and brucellosis. Anthrax was considered to have the greatest impact by the participants (median = 4, z>1.96), while 4/7 (57%) of the FGDs identified consumption of uninspected meat as a way that people can get infected with zoonotic diseases. Community Health Volunteers (Median = 28, z = 2.13) and the government veterinary officer (median = 7, z = 1.8) were the preferred sources of information during disease outbreaks.
The participants knew the zoonotic diseases common in the area and how the diseases can be acquired. We recommend increased involvement of the community in epidemio-surveillance of zoonotic diseases at the human-wildlife-livestock interface.
Livestock keeping is the mainstay for the pastoral community while also providing social and cultural value. This study ranked main production constraints and cattle diseases that impacted livelihood ...and estimated herd prevalence, incidence rate, and impact of diseases on production parameters in a semiarid pastoral district of Narok in Kenya. Data collection employed participatory techniques including listing, pairwise ranking, disease incidence scoring, proportional piling, and disease impact matrix scoring and this was disaggregated by gender. Production constraints with high scores for impact on livelihood included scarcity of water (19 %), lack of extension services (15 %), presence of diseases (12 %), lack of market for cattle and their products (10 %), and recurrent cycle of drought (9 %). Diseases with high scores for impact on livelihood were East Coast fever (ECF) (22 %) and foot and mouth disease (FMD) (21 %). High estimated incidence rates were reported for FMD (67 %), trypanosomosis (28 %), and ECF (15 %), while contagious bovine pleuropneumonia (CBPP) had an incidence rate <1 %. Milk yield was affected by FMD, ECF, and trypanosomosis, while ECF was the cause of increased mortality. FMD, ECF, CBPP, and brucellosis caused increased abortion, while effect of gender and location of study was not significant. Despite CBPP being regarded as an important disease affecting cattle production in sub-Sahara Africa, its estimated incidence rate in herds was low. This study indicates what issues should be prioritized by livestock policy for pastoral areas.
Aflatoxin contamination of maize is a threat to food security and public health for households that depend on farming in developing countries. The objective of this study was to determine levels of ...total aflatoxins in maize from farms adopting different artisanal aflatoxin control methods. A cross-sectional study was conducted with 315 maize farmers who provided maize samples for aflatoxin analysis and additional data on artisanal aflatoxin control methods applied at farm level. Maize grains were ground, and levels of aflatoxins were determined using competitive enzyme-linked immunosorbent assay. Data were analyzed by computing descriptive statistical measures, and binary logistic regression was used to determine the relationship between levels of aflatoxin in maize and artisanal control methods applied in different farms. Aflatoxin was detected in 98% of maize samples with a mean total aflatoxin level of 12.86 μg/kg which was above the maximum tolerable limits. There was a significant difference in total aflatoxin levels in maize obtained from farms which practiced minimum tillage compared to those practicing deep tillage (p = 0.015). Drying maize on bare ground had a higher likelihood of aflatoxin contamination than drying maize on tarpaulin (p = 0.005). One-third of maize samples had aflatoxin levels exceeding the set maximum limit, with maize samples from lowland areas having high proportions of aflatoxin-positive cases as compared to uplands. Artisanal aflatoxin control technologies such as land tillage, types of platforms for drying maize, and sources of maize seed significantly influence the level of aflatoxins in maize samples. We recommend targeted active surveillance for aflatoxins, continuous public education, and adoption of farm-level mitigation measures to reduce the impact of aflatoxin contamination in farming communities.
Identification of risk factors is crucial in Foot-and-mouth disease (FMD) control especially in endemic countries. In Rwanda, almost all outbreaks of Foot-and-Mouth Disease Virus (FMDV) have started ...in Eastern Rwanda. Identifying the risk factors in this area will support government control efforts. This study was carried out to identify and map different risk factors for the incursion, spread and persistence of FMDV in Eastern Rwanda. Questionnaires were administered during farm visits to establish risk factors for FMD outbreaks. Descriptive statistical measures were determined and odds ratios were calculated to determine the effects of risk factors on the occurrence of FMD. Quantum Geographic Information System (QGIS) was used to produce thematic maps on the proportion of putative risk factors for FMD per village.
Based on farmers' perceptions, 85.31% (with p < 0.01) experienced more outbreaks during the major dry season, a finding consistent with other reports in other parts of the world. Univariate analysis revealed that mixed farming (OR = 1.501, p = 0.163, CI = 95%), and natural breeding method (OR = 1.626; p = 0.21, CI = 95%) were associated with the occurrence of FMD indicating that the two risk factors could be responsible for FMD outbreaks in the farms. The occurrence of FMD in the farms was found to be significantly associated with lack of vaccination of calves younger than 12 months in herds (OR = 0.707; p = 0.046, CI = 95%).
This is the first study to describe risk factors for persistence of FMDV in livestock systems in Rwanda. However, further studies are required to understand the role of transboundary animal movements and genotypic profiles of circulating FMDV in farming systems in Rwanda.
Lumpy Skin Disease (LSD) is an emerging disease of cattle that causes substantial economic loss to affected regions. However, factors favouring transmission under field conditions and farm-level ...impacts are poorly quantified. This was a retrospective case-control study of cattle farms in Nakuru, Kenya to determine risk factors associated with lumpy skin disease and the farm-level economic impacts of an outbreak. Data were collected using questionnaires administered through personal interview. Collected data included herd sizes, age, and sex structures, breeds, sources of replacement stock, grazing systems, and costs (direct and indirect) incurred when LSD outbreaks occurred. Farm-level risk factors were examined through univariable and multivariable logistic regression and a final model built using backward stepwise regression and likelihood ratio tests. The factors associated with LSD outbreaks on univariable analysis included breed (exotic vs. indigenous, OR = 15.01,
= 0.007), source of replacement stock (outside the herd vs. within the herd, OR = 8.38,
< 0.001) and herd size (large >10 cattle vs. small 1-3 cattle, OR = 3.51,
= 0.029). In the multivariable logistic regression model, only breed (exotic vs. indigenous, OR = 14.87, 95% CI 1.94-113.97,
= 0.009) and source of replacement stock (outside the herd vs. within the herd OR = 8.7, 95% CI 2.80-27.0,
< 0.001) were associated with outbreaks. The economic impact was compared between farms keeping purely indigenous (
= 10) or exotic (
= 29) breeds of cattle which indicated mean farm-level losses of 12,431 KSH/123 USD and 76,297 KSH/755 USD, respectively. The mean farm-level losses from reduction in milk yield and mortality were estimated at 4,725 KSH/97 USD and 3,103 KSH/31USD for farms keeping indigenous breeds whilst for farms keeping exotic breeds the equivalent losses were 26,886 KSH/266 USD and 43,557 KSH/431 USD, respectively. The indirect losses from treatments and vaccinations were proportionately much higher on farms with indigenous breeds at 4,603 KSH/46 USD making up ~37% of the total costs compared to ~8% (5,855 KSH/58 USD per farm) of the total costs for farms with exotic breeds. These findings indicate that LSD caused significant economic losses at the farm level in Nakuru County. This justifies implementation of disease control measures including quarantine of cattle post-purchase and the need for effective vaccinations of susceptible cattle herds.
East Coast fever (ECF) is a cattle disease caused by a protozoan parasite called
Theileria parva
(
T. parva
).
Theileria parva
is transmitted among cattle by ticks. It is endemic in parts of central, ...eastern, and southern Africa and imposes an economic burden through illness and death of approximately a half of a billion U.S. dollars annually. This paper reviews existing science on the economics of ECF. We utilize a conceptual model that defines primary categories of economic costs due to ECF and use it to organize a synthesis of the literature on aggregate and micro level direct costs of the disease and the costs and benefits related to various ECF management strategies. We then identify knowledge gaps to motivate for future research.
It is projected that, on average, annual temperature will increase between 2 °C to 6 °C under high emission scenarios by the end of the 21st century, with serious consequences in food and nutrition ...security, especially within semi-arid regions of sub-Saharan Africa. This study aimed to investigate the impact of historical long-term climate (temperature and rainfall) variables on the yield of five major crops viz., sorghum, sesame, cotton, sunflower, and millet in Gedaref state, Sudan over the last 35 years. Mann–Kendall trend analysis was used to determine the existing positive or negative trends in temperature and rainfall, while simple linear regression was used to assess trends in crop yield over time. The first difference approach was used to remove the effect of non-climatic factors on crop yield. On the other hand, the standardized anomaly index was calculated to assess the variability in both rainfall and temperature over the study period (i.e., 35 years). Correlation and multiple linear regression (MLR) analyses were employed to determine the relationships between climatic variables and crops yield. Similarly, a simple linear regression was used to determine the relationship between the length of the rainy season and crop yield. The results showed that the annual maximum temperature (Tmax) increased by 0.03 °C per year between the years 1984 and 2018, while the minimum temperature (Tmin) increased by 0.05 °C per year, leading to a narrow range in diurnal temperature (DTR). In contrast, annual rainfall fluctuated with no evidence of a significant (p > 0.05) increasing or decreasing trend. The yields for all selected crops were negatively correlated with Tmin, Tmax (r ranged between −0.09 and −0.76), and DTR (r ranged between −0.10 and −0.70). However, the annual rainfall had a strong positive correlation with yield of sorghum (r = 0.64), sesame (r = 0.58), and sunflower (r = 0.75). Furthermore, the results showed that a longer rainy season had significant (p < 0.05) direct relationships with the yield of most crops, while Tmax, Tmin, DTR, and amount of rainfall explained more than 50% of the variability in the yield of sorghum (R2 = 0.70), sunflower (R2 = 0.61), and millet (R2 = 0.54). Our results call for increased awareness among different stakeholders and policymakers on the impact of climate change on crop yield, and the need to upscale adaptation measures to mitigate the negative impacts of climate variability and change.
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