Ageing threatens sustainability of smallholder farming in China.

Rapid demographic ageing substantially affects socioeconomic development1-4 and presents considerable challenges for food security and agricultural sustainability5-8, which have so far not been well understood. Here, by using data from more than 15,000 rural households with crops but no livestock across China, we show that rural population ageing reduced farm size by 4% through transferring cropland ownership and land abandonment (approximately 4 million hectares) in 2019, taking the population age structure in 1990 as a benchmark. These changes led to a reduction of agricultural inputs, including chemical fertilizers, manure and machinery, which decreased agricultural output and labour productivity by 5% and 4%, respectively, further lowering farmers' income by 15%. Meanwhile, fertilizer loss increased by 3%, resulting in higher pollutant emissions to the environment. In new farming models, such as cooperative farming, farms tend to be larger and operated by younger farmers, who have a higher average education level, hence improving agricultural management. By encouraging the transition to new farming models, the negative consequences of ageing can be reversed. Agricultural input, farm size and farmer's income would grow by approximately 14%, 20% and 26%, respectively, and fertilizer loss would reduce by 4% in 2100 compared with that in 2020. This suggests that management of rural ageing will contribute to a comprehensive transformation of smallholder farming to sustainable agriculture in China.

Improving nutritional accuracy and economics through a multiple ration-grouping strategy.

The objective of this study was to develop a model application to systematize nutritional grouping (NG) management in commercial dairy farms. The model has 4 sub-sections: (1) real-time data stream integration, (2) calculation of nutritional parameters, (3) grouping algorithm, and (4) output reports. A simulation study on a commercial Wisconsin dairy farm was used to evaluate our NG model. On this dairy farm, lactating cows (n = 2,374 ± 185) are regrouped weekly in 14 pens according to their parity and lactation stage, for which 9 diets are provided. Diets are seldom reformulated and nutritional requirements are not factored to allocate cows to pens. The same 14 pens were used to simulate the implementation of NG using our model, closely following the current farm criteria but also including predicted nutritional requirements (net energy for lactation and metabolizable protein; NEL and MP) and milk yield in an attempt to generate more homogeneous groups of cows for improved diet accuracy. The goal of the simulation study was to implement a continuous weekly system for cows' pen allocation and diet formulation. The predicted MP and NEL requirements from the NG were used to formulate the diets using commercial diet formulation software and the same feed ingredients, feed prices, and other criteria as the current farm diets. Diet MP and NEL densities were adjusted to the nutritional group requirements. Results from the simulation study indicated that the NG model facilitates the implementation of an NG strategy and improves diet accuracy. The theoretical diet cost and predicted nitrogen supply with NG decreased for low-nutritional-requirement groups and increased for high-nutritional-requirement groups compared with current farm groups. The overall average N supply in diets for NG management was 15.14 g/cow per day less than the current farm grouping management. The average diet cost was $3,250/cow per year for current farm management and $3,219/cow per year for NG, which resulted in a theoretical $31/cow per year diet cost savings.

The Internet of Things enhancing animal welfare and farm operational efficiency.

The growth in wirelessly enabled sensor network technologies has enabled the low cost deployment of sensor platforms with applications in a range of sectors and communities. In the agricultural domain such sensors have been the foundation for the creation of decision support tools that enhance farm operational efficiency. This Research Reflection illustrates how these advances are assisting dairy farmers to optimise performance and illustrates where emerging sensor technology can offer additional benefits. One of the early applications for sensor technology at an individual animal level was the accurate identification of cattle entering into heat (oestrus) to increase the rate of successful pregnancies and thus optimise milk yield per animal. This was achieved through the use of activity monitoring collars and leg tags. Additional information relating to the behaviour of the cattle, namely the time spent eating and ruminating, was subsequently derived from collars giving further insights of economic value into the wellbeing of the animal, thus an enhanced range of welfare related services have been provisioned. The integration of the information from neck-mounted collars with the compositional analysis data of milk measured at a robotic milking station facilitates the early diagnosis of specific illnesses such as mastitis. The combination of different data streams also serves to eliminate the generation of false alarms, improving the decision making capability. The principle of integrating more data streams from deployed on-farm systems, for example, with feed composition data measured at the point of delivery using instrumented feeding wagons, supports the optimisation of feeding strategies and identification of the most productive animals. Optimised feeding strategies reduce operational costs and minimise waste whilst ensuring high welfare standards. These IoT-inspired solutions, made possible through Internet-enabled cloud data exchange, have the potential to make a major impact within farming practices. This paper gives illustrative examples and considers where new sensor technology from the automotive industry may also have a role.

Evaluating technical efficiency of hair goat farms in Turkey: the case of Mersin Province.

This study aims to determine the efficiency levels of hair goat farms and to investigate the effect of socio-economic factors on efficiency. The data were collected from 110 hair goat farmers operating in Mersin province of Turkey, in the year 2019. An input-oriented data envelopment analysis (DEA) was used to estimate technical efficiency scores and Tobit regression was employed to determine effective factors on technical efficiency. DEA results showed under the constant and variable returns to scale assumptions that the mean efficiency scores were estimated as 0.67 and 0.76, respectively. The present results indicated that farmers were overusing inputs and they can reduce the inputs by 33% and 24% in order to produce the same level of output. The results further show that farmers' education (p < 0.05), the number of goats (p < 0.01), income (p < 0.05) and cooperative membership (p < 0.10) are statistically significant factors influencing the technical efficiency of hair goat farms. Technical efficiency of farms should be improved by focusing on the education and extension services for optimum input use, adopting new technologies by encouraging farmers to join cooperatives.

Invited review: Examining farmers' personalities and attitudes as possible risk factors for dairy cattle health, welfare, productivity, and farm management: A systematic scoping review.

We aimed to determine how research regarding farmers' personalities and attitudes as risk factors is reported (methodological approaches to assessing, extracting, and processing data and analyzing risk factors) and to explore evidence for the effect of farmers' attitudes and personalities on dairy cattle health, welfare, productivity, and management. Therefore, we conducted a systematic review of studies on personality and attitude as risk factors for dairy cattle health, welfare, productivity, and farm management. Database searches captured 1,144 records, and 38 were finally included in the review. Thirty-three manuscripts assessed farmers' attitudes, 1 assessed their personalities, and 4 assessed both as risk factors. These potential risk factors were checked for relationships with more than 50 different outcome variables regarding farm management (17 manuscripts), animal health (13 manuscripts), animal productivity (11 manuscripts), and animal welfare (4 manuscripts). The approaches to assessing risk factors and processing and interpreting data varied greatly; thus, drawing conclusions regarding the effects of attitude and personality as risk factors is impeded because manuscripts are difficult to compare. Our findings highlight the need for harmonization of attitudes and personality assessments in future research. Furthermore, researchers should carefully consider which depth of detail to apply when planning and evaluating related research. Nevertheless, results highlight the importance of the effect of personality and attitude on outcomes. Farmers' personality and attitudes are associated with dairy cattle health, welfare, productivity, and management. In general, attitudes indicating higher degrees of technical knowledge, affection with problems, perceived responsibility, perception of control of a situation, a better human-animal relationship, or a positive evaluation of the benefits of management decisions tended to affect outcomes in a beneficial way. "Agreeableness" and "conscientiousness" were shown to promote better farm performance, whereas "neuroticism" had a negative effect. Therefore, further research on attitude and personality and their consideration by professionals and decision-makers within the dairy sector and politics is strongly recommended. This might provide the chance to better understand the needs of dairy farmers and therefore develop tailored advice and support strategies to improve both satisfactory and constructive cooperation.

State-of-the-art technologies in precision agriculture: a systematic review.

BACKGROUND: The socio-economic status of the countries is ever-changing due to the increasing population. 'Green Revolution', a paradigm shift towards technology driven agriculture, has ensured a good quality of life to some extent for this increasing population. However, it brings in several negative impacts on the environment, which poses a threat to the sustainability of agriculture and natural resources. Precision agriculture (PA) is a state-of-the-art concept of site-specific farm management that helps to overcome this threat in a smart way using modern information and communication technologies. It reduces the indecorous use of resources, pollution and hence improves quality of life, which in turn helps to achieve sustainable development goals. RESULTS: The objective of this systematic review is to understand the present status, benefits, and limitations of the state-of-the-art technologies used in PA. A total 67 articles are identified following the PRISMA guideline to inspect the technical innovations at different components of PA. The articles are examined based on the novelties, measured parameters, technologies, and field of applications. CONCLUSION: This analysis results in a significant understanding about the present knowledge gap and identification of the potential future research opportunities for sustainable agronomy. © 2019 Society of Chemical Industry.

The Impact of Federal and State Conservation Programs on Farmer Nitrogen Management.

The U.S. federal government, as well as many state and local governments, operate a number of conservation programs aimed at ameliorating the environmental problems associated with agriculture. While motives and barriers to conservation program participation and adoption of conservation practices have been extensively studied, the direct impacts of programs on ongoing farm operations remains underexplored. To examine the effects of conservation programs on nitrogen management, an aspect of crop production with significant environmental impacts we conducted interviews with 154 corn producers in three Midwestern U.S. states with a range of program experiences. We found that programs shifted farmer N management behavior through three social processes: (1) engaging farmers in the conservation system by introducing them to the state and federal conservation agencies, (2) incentivizing trialing of specific N management practices, and (3) increasing practice adoption through continued program engagement. Working-lands programs were far more effective at shifting on-farm nutrient management practices than land retirement, certification, or outreach-based programs, though all programs had the indirect benefit of increasing farmer familiarity with conservation agencies and programs. Working-lands programs directly motivated practice adoption; including soil testing regimes, implementing nutrient management plans, and splitting nitrogen applications to improving availability; by reducing producer risk and providing technical assistance, especially whole-farm planning. The additional benefits of all programs were moderated by participant selection bias, in particular that program participants were more predisposed to conservation efforts by existing stewardship and innovation attitudes.

Risk for Low Pathogenicity Avian Influenza Virus on Poultry Farms, the Netherlands, 2007-2013.

Using annual serologic surveillance data from all poultry farms in the Netherlands during 2007-2013, we quantified the risk for the introduction of low pathogenicity avian influenza virus (LPAIV) in different types of poultry production farms and putative spatial-environmental risk factors: distance from poultry farms to clay soil, waterways, and wild waterfowl areas. Outdoor-layer, turkey (meat and breeder), and duck (meat and breeder) farms had a significantly higher risk for LPAIV introduction than did indoor-layer farms. Except for outdoor-layer, all poultry types (i.e., broilers, chicken breeders, ducks, and turkeys) are kept indoors. For all production types, LPAIV risk decreased significantly with increasing distance to medium-sized waterways and with increasing distance to areas with defined wild waterfowl, but only for outdoor-layer and turkey farms. Future research should focus not only on production types but also on distance to waterways and wild bird areas. In addition, settlement of new poultry farms in high-risk areas should be discouraged.

Robotic milking: Technology, farm design, and effects on work flow.

Robotic milking reduces labor demands on dairy farms of all sizes and offers a more flexible lifestyle for farm families milking up to 250 cows. Because milking is voluntary, barn layouts that encourage low-stress access by providing adequate open space near the milking stations and escape routes for waiting cows improve milking frequency and reduce fetching. Because lame cows attend less often, preventing lameness with comfortable stalls, clean alley floors, and effective foot bathing warrants special emphasis in robotic dairies. Variable milking intervals create challenges for foot bathing, sorting and handling, and dealing with special-needs cows. Appropriate cow routing and separation options at the milking stations are needed to address these challenges and ensure that the expected labor savings are realized. Protocols and layout and gating should make it possible for a herd worker to complete all handling tasks alone. Free traffic and guided traffic systems yield similar results when excellent management is applied or when the number of cows is well below capacity. In less ideal circumstances, guided traffic and the use of commitment pens result in longer standing times and stress, particularly for lower ranking cows, and poor management with free traffic results in more labor for fetching.

Economic effect of reducing nitrogen and phosphorus mass balance on Wisconsin and Québec dairy farms.

Our objective was to explore the trade-offs between economic performance (farm net income, FNI) and environmental outcomes (whole-farm P and N balances) of dairy farms in Wisconsin (WI; United States) and Québec (QC; Canada). An Excel-based linear program model (N-CyCLES; nutrient cycling: crops, livestock, environment, and soil) was developed to optimize feeding, cropping, and manure management as a single unit of management. In addition to FNI, P and N balances model outputs included (1) the mix of up to 9 home-grown and 17 purchased feeds for up to 5 animal groups, (2) the mix of up to 5 crop rotations in up to 5 land units and c) the mix of up to 7 fertilizers (solid and liquid manure and 5 commercial fertilizers) to allocate in each land unit. The model was parameterized with NRC nutritional guidelines and regional nutrient management planning rules. Simulations were conducted on a typical WI farm of 107 cows and 151 ha of cropland and, a Southern QC farm of 87 cows and 142 ha of cropland and all results were expressed per kg of fat- and protein-corrected milk (FPCM). In absence of constraints on P and N balances, maximum FNI was 0.12 and 0.11 $/kg of FPCM for WI and QC, respectively, with P and N balances of 1.05 and 14.29 g/kg of FPCM in WI but 0.60 and 15.70 g/kg of FPCM in QC. The achievable reduction (balance at maximum FNI minus balance when the simulation objective was to minimize P or N balance) was 0.31 and 0.54 g of P/kg of FPCM (29 and 89% reduction), but 2.37 and 3.31 g of N/kg of FPCM (17 and 24% reduction) in WI and QC, respectively. Among other factors, differences in animal unit per hectare and reliance on biological N fixation may have contributed to lower achievable reductions of whole-farm balances in WI compared with QC. Subsequent simulations to maximize FNI under increasing constraints on nutrient balances revealed that it was possible to reduce P balance, N balance, and both together by up to 33% without a substantial effect on FNI. Partial reduction in P balance reduced N balance (synergetic effect) in WI, but increased N balance (antagonistic effect) in QC. In contrast, reducing N balance increased P balance in both regions, albeit in different magnitudes. The regional comparison highlighted the importance of site-specific conditions on modeling outcomes. This study demonstrated that even when recommended guidelines are followed for herd nutrition and crop fertilization, the optimization of herd feeding, cropping, and manure spreading as a single unit of management may help identify management options that preserve FNI, while substantially reducing whole-farm nutrient balance.

Farm business and operator variables associated with bulk tank somatic cell count from dairy herds in the southeastern United States.

Mastitis is a worldwide problem in dairy cows and results in reduced milk production, the culling of cows, and other economic losses. Bulk tank somatic cell count (BTSCC) over 200,000 cells/mL often indicates underlying subclinical mastitis in dairy herds. Several preventative measures that can be implemented to help improve the incidence of mastitis exist, but surveys find these practices not fully adopted by producers. The goal of this research was to analyze the farm and operator characteristics associated with BTSCC in dairy herds by analyzing a survey of dairy producers in the southeastern United States. We examined this region because it has experienced a decline in the number of dairy farms, dairy cows, and milk production over the past 2 decades. The southeast region is also associated with higher BTSCC levels than the national average. Dairy farms in Georgia, Mississippi, Kentucky, North Carolina, South Carolina, Tennessee, and Virginia were surveyed. Producers were asked questions about the BTSCC at which they take action to address BTSCC, the information sources they use to learn about and manage BTSCC, farm structure and management characteristics, and attitudinal variables associated with profitability, managerial control, and planning horizon. Least squares regression was used to determine how these factors were associated with BTSCC levels across the 7-state region. Concern over mastitis, financial consequences of mastitis, and increased previous-year BTSCC were associated with higher current BTSCC levels. Obtaining information about mastitis from veterinarians and extension personnel, taking action against mastitis at a BTSCC less than 300,000 cells/mL, and perceived ability to control processes and mastitis incidence were associated with reduced BTSCC. We found average BTSCC was lower in North Carolina and Virginia. These results suggest that proactive producers (i.e., those that perceive they can control BTSCC and seek information from reliable sources), were more likely to report lower BTSCC. As a result, it may be possible to achieve improved milk quality, evident from lowered BTSCC, across the region.

Simulation of Optimal Decision-Making Under the Impacts of Climate Change.

Climate change causes transformations to the conditions of existing agricultural practices appointing farmers to continuously evaluate their agricultural strategies, e.g., towards optimising revenue. In this light, this paper presents a framework for applying Bayesian updating to simulate decision-making, reaction patterns and updating of beliefs among farmers in a developing country, when faced with the complexity of adapting agricultural systems to climate change. We apply the approach to a case study from Ghana, where farmers seek to decide on the most profitable of three agricultural systems (dryland crops, irrigated crops and livestock) by a continuous updating of beliefs relative to realised trajectories of climate (change), represented by projections of temperature and precipitation. The climate data is based on combinations of output from three global/regional climate model combinations and two future scenarios (RCP4.5 and RCP8.5) representing moderate and unsubstantial greenhouse gas reduction policies, respectively. The results indicate that the climate scenario (input) holds a significant influence on the development of beliefs, net revenues and thereby optimal farming practices. Further, despite uncertainties in the underlying net revenue functions, the study shows that when the beliefs of the farmer (decision-maker) opposes the development of the realised climate, the Bayesian methodology allows for simulating an adjustment of such beliefs, when improved information becomes available. The framework can, therefore, help facilitating the optimal choice between agricultural systems considering the influence of climate change.

Factors Affecting Public Preferences for Grassland Landscape Heterogeneity in the Great Plains.

Agricultural intensification has fragmented rangelands in the Great Plains, which has contributed to uniform and homogeneous landscapes and decreased biodiversity. Alternative land management practices involving fire-grazing interactions can help maintain biodiversity without affecting livestock productivity. A survey was designed to understand the factors that influence preferences among the general population towards grassland landscape heterogeneity. Given the ordinal nature of survey responses, requisite data were analyzed using a generalized ordinal logit model. Results suggested that respondents who valued open space and those who recognized a need for a varying mix of uniform grasses and grasslands preferred landscape heterogeneity. Female respondents were about two times as likely to prefer heterogeneous landscapes compared to male respondents. In contrast, population groups that preferred wildlife habitat did not desire heterogeneous landscapes. Results suggest the need for extension and outreach activities to educate certain segments of the general population regarding benefits of alternative management practices that support landscape heterogeneity in the Great Plains.

Climate Change Perceptions of NY State Farmers: The Role of Risk Perceptions and Adaptive Capacity.

Climate change is expected to severely impact agricultural practices in many important food-producing regions, including the Northeast United States. Changing climate conditions, such as increases in the amount of rainfall, will require farmers to adapt. Yet, little is known with regard to farmers' perceptions and understandings about climate change, especially in the industrialized country context. This paper aims at overcoming this research limitation, as well as determining the existing contextual, cognitive, and psychological barriers that can prevent adoption of sustainable practices of farmers in New York State. The study is framed within the adaptive capacity and risk perception literature, and is based on a qualitative analysis of in-depth interviews with farmers in 21 farms in two counties in Central New York. The results reveal diverging views about the long-term consequences of climate change. Results also reveal that past experience remains as the most important source of information that influences beliefs and perceptions about climate change, confirming previous research.

Characterization of the fecal microbiota of sows and their offspring from German commercial pig farms.

Strategies to combat microbiota-associated health problems are of high interest in pig production. Successful intervention strategies with beneficial long-term effects are still missing. Most studies on pig microbiota have been conducted under standardized experimental conditions, but the situation in commercial farms differs dramatically. This study describes the fecal microbiota in German commercial pig farms under practical conditions. The study is part of the larger project "Optibiom" that aims to use bacterial composition and farm metadata to formulate tailor-made solutions for farm-specific health maintenance strategies. Special consideration is given to the sow-piglet relationship. Fecal samples from sows and their piglets were collected at two time points each in 20 different farms (sows ante- and postpartum and piglets before and after weaning). The extracted DNA was sequenced with Illumina 16S rDNA sequencing. For data analysis and visualization, differential abundance analyses, as well as hierarchical clustering and nonmetric multidimensional scaling (NMDS) were performed. A new "family unit" was implemented to compare farms based on the association between the microbiota in sows and their offspring. There are distinct changes in the microbial communities in sows before and after birth as well as in suckling and post-weaning piglets. The suckling pig microbiota is particularly different from all other groups and shows a lower bacterial diversity. While dominant genera in antepartum sows further displace the abundance of non-dominant genera postpartum, the opposite was true for piglets, where non-dominant bacteria in the suckling phase became dominant after weaning. The family unit for sows and their piglets led to separate cluster formation for some farms. The results indicate that the sow-piglet relationship is one driving force for the observed differences of the pig farms. The next step in the analysis will be the combination of metadata (feeding, housing and management practices) to find farm-specific differences that can be exploited to formulate a farm-specific health maintenance strategy.

Influence of farm management on the dynamics of Salmonella enterica serovar Infantis shedding and antibiotic resistance during the growing period of broiler chickens.

BACKGROUND: Salmonella enterica serovar Infantis is a zoonotic pathogen isolated in broilers causing great economic losses in the European poultry sector. It is demonstrated that an investment in management measures at farm level could directly affect the control of food chain microorganisms. The aim of this study was to investigate the development of S. Infantis antimicrobial resistance (AMR) patterns during the growing period, according to flock density and ventilation management, without antibiotic administration. METHODS: The experiment was performed in two identical poultry houses, evaluating commercial and optimal farm conditions. At 24 h of rearing, 20% of the animals were orally infected with a S. Infantis strain susceptible to all the antibiotics tested. To study Salmonella shedding, faeces samples from each experimental group were taken weekly and analysed as per ISO/TS 6579-2:2017. Antibiotic susceptibility was assessed according to Decision 2013/653. RESULTS: Salmonella shedding showed that the lowest counts were observed in the first week post-infection and highest at slaughter day for both groups. Moreover, 100% of the isolates were multi-resistant. CONCLUSION: The acquisition of AMR by S. Infantis starts at the onset of the production cycle and is maintained until the end, demonstrating the importance of transmission of AMR in zoonotic bacteria at farm level.

Cooling Interventions Among Agricultural Workers: A Pilot Study.

BACKGROUND: Adverse health effects among agricultural workers due to chronic heat exposure have been characterized in the literature as not only due to high ambient temperatures but also due to intensive manual labor in hot and humid conditions. The aim of this study was to use biomonitoring equipment to examine the effectiveness of selected cooling devices at preventing agricultural workers from exceeding the core body temperature threshold of 38.0°C (Tc38) and attenuating heat-related illness symptoms. METHODS: A convenience sample of 84 agricultural workers in Florida was randomized to one of four groups: (a) no intervention, clothing as usual; (b) cooling bandana; (c) cooling vest; and (d) both the cooling bandana and cooling vest. Biomonitoring equipment worn by the participants included core body temperature monitor and an accelerometer to capture physical activity. FINDINGS: A total of 78 agricultural workers completed one intervention workday trial. Compared with the control group, the bandana group had lower odds of exceeding Tc38 (odds ratio [OR] = 0.7, 90% confidence interval [CI] = [0.2, 3.2]) and the vest group had higher odds of exceeding Tc38 (OR = 1.8, 90% CI = [0.4, 7.9]). The simultaneous use of cooling vest and bandana showed an effect little different from the control group (OR = 1.3, 90% CI = [0.3, 5.6]). CONCLUSION/APPLICATION TO PRACTICE: This is the first field-based study to examine cooling intervention among agricultural workers in the United States using biomonitoring equipment. This study found that using a bandana while working in a hot agricultural environment has the potential to be protective against exceeding the recommended Tc38 threshold.

Diet type influences the gut microbiome and nutrient assimilation of Genetically Improved Farmed Tilapia (Oreochromis niloticus).

Nile tilapia, Oreochromis niloticus is the third most commonly farmed finfish species in the world, accounting for nearly 5% of global aquaculture production. In the past few decades much of the success of this species has been attributed to the development and distribution of Genetically Improved Farmed Tilapia (GIFT). Despite the increasing availability of GIFT, the productivity of small-scale farming remains highly variable, particularly in developing nations. Commercial fish-feed pellets can increase fish farm productivity; however, many small-scale farmers rely on other means of feeding fish due to the high cost and limited availability of commercial fish feed pellets. Therefore, understanding how locally-sourced feeds affect the production of GIFT is an important step towards improving feeding practices, particularly for farmers with low financial capital. This study used stable isotope analysis (SIA) and 16S rRNA gene sequencing to compare the effects of a locally-sourced vegetable-based diet and commercial pellet-based diets on the relative condition, nutrient assimilation patterns and gastrointestinal microbiota of GIFT. GIFT fed a locally-sourced diet were smaller, and in a significantly poorer condition than those fed with commercial fish feeds. SIA showed no differences in dietary carbon between the two diets; however, δ13C, poor fish condition and the abundance of specific bacterial taxa (of such as Fusobacteria) were correlated. SIA revealed that GIFT fed locally-sourced diets that predominantly consisted of vegetables were significantly enriched in δ15N despite a perceived lack of dietary protein. This enrichment suggests that GIFT fed a locally-sourced diet may be supplementing their diet via cannibalism, a behaviour representative of poor farming practice. Overall this study highlights the need to increase the availability of suitable GIFT feeds in developing nations. The development a low-cost feed alternative could improve the success of small-scale GIFT farmers in PNG, increasing both food and income security within the region.

Long-term efficacy of BCG vaccination in goat herds with a high prevalence of tuberculosis.

Vaccination of goats against tuberculosis (TB) has been promoted as an ancillary tool for controlling the disease in infected livestock herds. A three-year trial to assess the efficacy of BCG vaccine was carried out in five goat herds. At the beginning of the trial (month 0), all animals were tested for TB using thee different diagnostic tests. Animals negative to all tests were vaccinated with BCG and all replacement goat kids were also systematically vaccinated throughout the trial. All animals were tested by Interferon-gamma release assay (IGRA) using vaccine compatible reagents at months 6, 12, 24, and 36. The risk factors for TB infection were also evaluated. At the end of the study, four out of five farms showed variable reductions of the initial prevalence (93.5%, 28.5%, 23.2%, and 14.3% respectively), and an overall incidence reduction of 50% was observed in BCG vaccinated goats, although adult vaccinated goats showed higher incidences than vaccinated goat kids. The unvaccinated positive animals remaining in herds and adult BCG vaccinated goats significantly enhanced the risk of infection in vaccinated animals. A systematic vaccination of goats with BCG, together with the removal of positive unvaccinated animals, may contribute to reducing the TB prevalence in goat herds.