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.

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.

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.

Innovating within or outside dominant food systems? Different challenges for contrasting crop diversification strategies in Europe.

Innovations supporting a shift towards more sustainable food systems can be developed within the dominant food system regime or in alternative niches. No study has compared the challenges faced in each context. This paper, based on an analysis of 25 cases of European innovations that support crop diversification, explores the extent to which barriers to crop diversification can be related to the proximity of innovation settings with dominant food systems. Drawing on a qualitative analysis of interviews and participatory brainstorming, we highlight 46 different barriers to crop diversification across the cases, at different levels: production; downstream operations from farm to retailing, marketing and consumers; and contracts and coordination between actors. To characterise the diversity of innovation strategies at food system level, we introduce the concept of "food system innovation settings" combining: (i) the type of innovative practice promoted at farm level; (ii) the type of value chain supporting that innovation; and (iii) the type of agriculture involved (organic or conventional). Through a multiple correspondence analysis, we show different patterns of barriers to crop diversification according to three ideal-types of food system innovation settings: (i) "Changing from within", where longer rotations are fostered on conventional farms involved in commodity supply chains; (ii) "Building outside", where crop diversification integrates intercropping on organic farms involved in local supply chains; and (iii) "Playing horizontal", where actors promote alternative crop diversification strategies-either strictly speaking horizontal at spatial level (e.g. strip cropping) or socially horizontal (arrangement between farmers)-without directly challenging the vertical organisation of dominant value chains. We recommend designing targeted research and policy actions according to the food systems they seek to develop. We then discuss further development of our approach to analyse barriers faced in intermediate and hybrid food system configurations.

A model of crop diversification under labor shocks.

As demands on agriculture increase, food producers will need to employ management strategies that not only increase yields but reduce environmental impacts. Modeling is a powerful tool for informing decision-making about current and future practices. We present a model to evaluate the effects of crop diversification on the robustness of simulated farms under labor shocks. We use an example inspired by the Florida production system of high-value, labor-intensive fruits. We find that crop diversification to high-value crops is a robust strategy when labor shocks are mild, and that crop diversification becomes less valuable as more simulated farms practice it. Based on our results, we suggest that crop diversification is a useful management strategy under specific conditions, but that policies designed to encourage crop diversification must consider broad effects as well as farm-level benefits.

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.

Review: Precision livestock farming: building 'digital representations' to bring the animals closer to the farmer.

Economic pressures continue to mount on modern-day livestock farmers, forcing them to increase herds sizes in order to be commercially viable. The natural consequence of this is to drive the farmer and the animal further apart. However, closer attention to the animal not only positively impacts animal welfare and health but can also increase the capacity of the farmer to achieve a more sustainable production. State-of-the-art precision livestock farming (PLF) technology is one such means of bringing the animals closer to the farmer in the facing of expanding systems. Contrary to some current opinions, it can offer an alternative philosophy to 'farming by numbers'. This review addresses the key technology-oriented approaches to monitor animals and demonstrates how image and sound analyses can be used to build 'digital representations' of animals by giving an overview of some of the core concepts of PLF tool development and value discovery during PLF implementation. The key to developing such a representation is by measuring important behaviours and events in the livestock buildings. The application of image and sound can realise more advanced applications and has enormous potential in the industry. In the end, the importance lies in the accuracy of the developed PLF applications in the commercial farming system as this will also make the farmer embrace the technological development and ensure progress within the PLF field in favour of the livestock animals and their well-being.

Improving the management procedures in farms infected with the Porcine Reproductive and Respiratory Syndrome virus using PDP models.

Pig meat production need to be built up in the future due to the increase of the human population worldwide. To address this challenge, there is plenty of room for improvement in terms of pig production efficiency that could be severely hampered by the presence of diseases. In this sense, Porcine Reproductive and Respiratory Syndrome Virus (PRRSV) is one of the most costly disease present in industrial pork production in Europe and North America. We have developed a model to analyze the effect of different management procedures to control this important virus in different epidemiological scenarios. Our results clearly suggest that no cross-fostering during lactation and the maintaining of litter integrity significantly decrease the number of sick and dead animals during the rearing period compared to scenarios where cross-fostering and no litter integrity are practiced. These results highlight the relevance of different management strategies to control PRRSV and quantify the effect of limiting cross-fostering and avoiding mixing animals from different litters in PRRSV positive farms to optimize animal production. Our findings will allow pig farmers to apply these management procedures to control this disease under field conditions in a very cost-effective way.

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.

Capturing farm diversity with hypothesis-based typologies: An innovative methodological framework for farming system typology development.

Creating typologies is a way to summarize the large heterogeneity of smallholder farming systems into a few farm types. Various methods exist, commonly using statistical analysis, to create these typologies. We demonstrate that the methodological decisions on data collection, variable selection, data-reduction and clustering techniques can bear a large impact on the typology results. We illustrate the effects of analysing the diversity from different angles, using different typology objectives and different hypotheses, on typology creation by using an example from Zambia's Eastern Province. Five separate typologies were created with principal component analysis (PCA) and hierarchical clustering analysis (HCA), based on three different expert-informed hypotheses. The greatest overlap between typologies was observed for the larger, wealthier farm types but for the remainder of the farms there were no clear overlaps between typologies. Based on these results, we argue that the typology development should be guided by a hypothesis on the local agriculture features and the drivers and mechanisms of differentiation among farming systems, such as biophysical and socio-economic conditions. That hypothesis is based both on the typology objective and on prior expert knowledge and theories of the farm diversity in the study area. We present a methodological framework that aims to integrate participatory and statistical methods for hypothesis-based typology construction. This is an iterative process whereby the results of the statistical analysis are compared with the reality of the target population as hypothesized by the local experts. Using a well-defined hypothesis and the presented methodological framework, which consolidates the hypothesis through local expert knowledge for the creation of typologies, warrants development of less subjective and more contextualized quantitative farm typologies.

A stochastic bio-economic pig farm model to assess the impact of innovations on farm performance.

Recently developed innovations may improve the economic and environmental sustainability of pig production systems. Generic models are needed to assess the impact of innovations on farm performance. Here we developed a stochastic bio-economic farm model for a typical farrow-to-finish pig farm to assess the impact of innovations on private and social profits. The model accounts for emissions of greenhouse gases from feed production and manure by using the shadow price of CO2, and for stochasticity of economic and biological parameters. The model was applied to assess the impact of using locally produced alternative feed sources (i.e. co-products) in the diets of finishing pigs on private and social profits of a typical Brazilian farrow-to-finish pig farm. Three cases were defined: a reference case (with a standard corn-soybean meal-based finishing diet), a macaúba case (with a macaúba kernel cake-based finishing diet) and a co-products case (with a co-products-based finishing diet). Pigs were assumed to be fed to equal net energy intakes in the three cases. Social profits are 34% to 38% lower than private profits in the three cases. Private and social profits are about 11% and 14% higher for the macaúba case than the reference case, whereas they are 3% and 7% lower for the co-products case, respectively. Environmental costs are higher under the alternative cases than the reference case suggesting that other benefits (e.g. costs and land use) should be considered to utilize co-products. The CV of farm profits is between 75% and 87% in the three cases following from the volatility of prices over time and variations in biological parameters between fattening pigs.

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.

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.

State-of-the-art practices in farmland biodiversity monitoring for North America and Europe.

Policy makers and farmers need to know the status of farmland biodiversity in order to meet conservation goals and evaluate management options. Based on a review of 11 monitoring programs in Europe and North America and on related literature, we identify the design choices or attributes of a program that balance monitoring costs and usefulness for stakeholders. A useful program monitors habitats, vascular plants, and possibly faunal groups (ecosystem service providers, charismatic species) using a stratified random sample of the agricultural landscape, including marginal and intensive regions. The size of landscape samples varies with the grain of the agricultural landscape; for example, samples are smaller in Europe and larger in North America. Raw data are collected in a rolling survey, which distributes sampling over several years. Sufficient practical experience is now available to implement broad monitoring schemes on both continents. Technological developments in remote sensing, metagenomics, and social media may offer new opportunities for affordable farmland biodiversity monitoring and help to lower the overall costs of monitoring programs.