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.

Precision feeding of lactating sows: implementation and evaluation of a decision support system in farm conditions

Precision feeding (PF) aims to provide the right amount of nutrients at the right time for each animal. Lactating sows generally receive the same diet, which either results in insufficient supply and body reserve mobilization, or excessive supply and high nutrient excretion. With the help of online measuring devices, computational methods, and smart feeders, we introduced the first PF decision support system (DSS) for lactating sows. Precision (PRE) and conventional (STD) feeding strategies were compared in commercial conditions. Every day each PRE sow received a tailored ration that had been computed by the DSS. This ration was obtained by blending a diet with a high AA and mineral content (13.00 g/kg SID Lys, 4.50 g/kg digestible P) and a diet low in AAs and minerals (6.50 g/kg SID Lys, 2.90 g/kg digestible P). All STD sows received a conventional diet (10.08 g/kg SID Lys, 3.78 g/kg digestible P). Before the trial, the DSS was fitted to farm performance for the prediction of piglet average daily gain (PADG) and sow daily feed intake (DFI), with data from 1,691 and 3,712 lactations, respectively. Sow and litter performance were analyzed for the effect of feeding strategy with ANOVA, with results considered statistically significant when P < 0.05. The experiment involved 239 PRE and 240 STD sows. DFI was similarly high in both treatments (PRE: 6.59, STD: 6.45 kg/d; P = 0.11). Litter growth was high (PRE: 2.96, STD: 3.06 kg/d), although it decreased slightly by about 3% in PRE compared to STD treatments (P < 0.05). Sow body weight loss was low, although it was slightly higher in PRE sows (7.7 vs. 2.1 kg, P < 0.001), which might be due to insufficient AA supply in some sows. Weaning to estrus interval (5.6 d) did not differ. In PRE sows SID Lys intake (PRE: 7.7, STD: 10.0 g/kg; P < 0.001) and digestible P intake (PRE: 3.2, STD: 3.8 g/kg; P < 0.001) declined by 23% and 14%, respectively, and feed cost decreased by 12%. For PRE sows, excretion of N and P decreased by 28% and 42%, respectively. According to these results, PF appears to be a very promising strategy for lactating sows.

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.

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.

Incorporating Health Outcomes into Land-Use Planning

The global trend toward increased agricultural production puts pressure on undeveloped areas, raising the question of how to optimally allocate land. Land-use change has recently been linked to a number of human health outcomes, but these are not routinely considered in land-use decision making. We review examples of planners' currently used strategies to evaluate land use and present a conceptual model of optimal land use that incorporates health outcomes. We then present a framework for evaluating the health outcomes of land-use scenarios that can be used by decision makers in an integrated approach to land-use planning.

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.

Predicting badger visits to farm yards and making predictions available to farmers

The use of agricultural resources or environments by wildlife may result in opportunities for transmission of infections amongst wild animals, livestock and humans. Targeted use of biosecurity measures may therefore reduce disease risks, although this requires practical knowledge of where such measures would be most effective, and effective means of communicating risks so that stakeholders can make informed decisions about such investment. In parts of Europe, the European badger Meles meles may act as a wildlife reservoir for Mycobacterium bovis, the causative agent of bovine tuberculosis, and badger visits to farmyards may provide potential opportunities for transmission of M. bovis to cattle. Biosecurity measures are effective in reducing badger activity in farmyards, although it is unclear which farms should be targeted with such measures. We used cameras to monitor badger activity in 155 farmyards in south west England and Wales, and related variations in the presence and frequency of badger visits to farm characteristics. Badgers were recorded on camera in 40% of farmyards monitored. However, the frequency of visits was highly variable, with badgers recorded on >50% of nights in only 10% of farms. The presence of badgers in farmyards was positively associated with the density of badger setts, the number of feed stores and the number of cattle sheds, and negatively associated with the distance to the nearest active badger sett, the presence of a house/dwelling and the number of cattle housed on the farm. The frequency of visits was negatively associated with the distance to the nearest active badger sett and the number of cattle housed. Models predicted the presence/absence of badgers in farmyards with 73% accuracy (62% sensitivity, 81% specificity, using a cut off value of 0.265). Models could not distinguish between farms with low/high frequency of visits, although farms predicted as having badgers present typically had a higher frequency of visits than those that were not. We developed and present an interactive web based application: the Badger Farm Assessment Tool (BFAT), to allow users to enter the characteristics of a farm and generate a relative risk score describing the likelihood of badger visits.

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.

Evaluating and predicting the effectiveness of farmland consolidation on improving agricultural productivity in China

Food security has always been a focus issue in China. Farmland consolidation (FC) was regarded as a critical way to increase the quantity and improve the quality of farmland to ensure food security by Chinese government. FC projects have been nationwide launched, however few studies focused on evaluating the effectiveness of FC at a national scale. As such, an efficient way to evaluate the effectiveness of FC on improving agricultural productivity in China will be needed and it is critical for future national land consolidation planning. In this study, we selected 7505 FC projects completed between 2006 and 2013 with good quality Normalized Difference Vegetation Index (NDVI) as samples to evaluate the effectiveness of FC. We used time-series Moderate Resolution Imaging Spectroradiometer NDVI from 2001 to 2013, to extract four indicators to characterize agricultural productivity change of 4442 FC projects completed between 2006 and 2010, i.e., productivity level (PL), productivity variation (PV), productivity potential (PP), and multi-cropping index (MI). On this basis, we further predicted the same four characteristics for 3063 FC projects completed between 2011 and 2013, respectively, using Support Vector Machines (SVM). We found FC showed an overall effective status on improving agricultural productivity between 2006 and 2013 in China, especially on upgrading PL and improving PP. The positive effect was more prominent in the southeast and eastern China. It is noteworthy that 27.30% of all the 7505 projects were still ineffective on upgrading PL, the elementary improvement of agricultural productivity. Finally, we proposed that location-specific factors should be taken into consideration for launching FC projects and diverse financial sources are also needed for supporting FC. The results provide a reference for government to arrange FC projects reasonably and to formulate land consolidation planning in a proper way that better improve the effectiveness of FC.

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.

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.

Biosecurity practices on Australian commercial layer and meat chicken farms: Performance and perceptions of farmers

This paper describes the level of adoption of biosecurity practices performed on Australian commercial chicken meat and layer farms and farmer-perceived importance of these practices. On-farm interviews were conducted on 25 free range layer farms, nine cage layer farms, nine barn layer farms, six free range meat chicken farms and 15 barn meat chicken farms in the Sydney basin bioregion and South East Queensland. There was a high level of treatment of drinking water across all farm types; town water was the most common source. In general, meat chicken farms had a higher level of adoption of biosecurity practices than layer farms. Cage layer farms had the shortest median distance between sheds (7.75m) and between sheds and waterbodies (30m). Equipment sharing between sheds was performed on 43% of free range meat chicken farms compared to 92% of free range layer farms. There was little disinfection of this shared equipment across all farm types. Footbaths and visitor recording books were used by the majority of farms for all farm types except cage layer farms (25%). Wild birds in sheds were most commonly reported in free range meat chicken farms (73%). Dogs and cats were kept across all farm types, from 56% of barn layer farms to 89% of cage layer farms, and they had access to the sheds in the majority (67%) of cage layer farms and on the range in some free range layer farms (44%). Most biosecurity practices were rated on average as ‘very important’ by farmers. A logistic regression analysis revealed that for most biosecurity practices, performing a practice was significantly associated with higher perceived farmer importance of that biosecurity practice. These findings help identify farm types and certain biosecurity practices with low adoption levels. This information can aid decision-making on efforts used to improve adoption levels.

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.

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.

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.

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.