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    About

Agricultural Systems

Elsevier

1976-

ISSN: 0308-521X (1873-2267)
Agriculture, Multidisciplinary - Animal Science and Zoology - Agronomy and Crop Science

Recent articles

1 show abstract
0308-521X * * 27127645
Publication date: Available online 26 February 2018

Source: Agricultural Systems
Author(s): Thomas Reardon, Ruben Echeverria, Julio Berdegué, Bart Minten, Saweda Liverpool-Tasie, David Tschirley, David Zilberman



Developing regions' food system has transformed rapidly in the past several decades. The food system is the dendritic cluster of R&D value chains, and the value chains linking input suppliers to farmers, and farmers upstream to wholesalers and processors midstream, to retailers then consumers downstream. We analyze the transformation in terms of these value chains' structure and conduct, and the effects of changes in those on its performance in terms of impacts on consumers and farmers, as well as the efficiency of and waste in the overall chain. We highlight the role of, and implications for agricultural research, viewed broadly as farm technology as well as research pertaining to all aspects of input and output value chains.

2 show abstract
0308-521X * * 27127646
Publication date: Available online 13 February 2018

Source: Agricultural Systems
Author(s): Thomas P. Tomich, Preetmoninder Lidder, Mariah Coley, Douglas Gollin, Ruth Meinzen-Dick, Patrick Webb, Peter Carberry



This introduction to the special issue deploys a framework, inspired by realist synthesis and introduced in Section 1, that aims to untangle the contexts, mechanisms, and outcomes associated with investments that link poverty reduction and rural prosperity within a broad agri-food systems perspective. Section 2 considers changes in contexts: Where are agricultural research investments most likely to be an engine of poverty reduction' Over the past 25 years, there have been profound changes in the development context of most countries, necessitating an update on strategic insights for research investment priorities relevant for the economic, political, social, environmental, and structural realities of the early 21st Century. Section 2 briefly surveys changes in these structural aspects of poverty and development processes in low-income countries, with particular attention to new drivers (e.g., urbanization, climate change) that will be of increasing salience in the coming decades. In Section 3, we turn to mechanisms: What are the plausible impact pathways and what evidence exists to test their plausibility' Poor farmers in the developing world are often the stated focus of public sector agricultural research. However, farmers are not the only potential beneficiaries of agricultural research; rural landless laborers, stakeholders along food value chains, and the urban poor can also be major beneficiaries of such research. Thus, there are multiple, interacting pathways through which agricultural research can contribute to reductions in poverty and associated livelihood vulnerabilities. This paper introduces an ex ante set of 18 plausible impact pathways from agricultural research to rural prosperity outcomes, employing bibliometric methods to assess the evidence underpinning causal links. In Section 4, we revisit the concept of desired impacts: When we seek poverty reduction, what does that mean and what measures are needed to demonstrate impact' The papers in this special issue are intended to yield insights to inform improvements in agricultural research that seeks to reduce poverty. History indicates that equity of distribution of gains matters hugely, and thus the questions of “who wins'” and “who loses'” must be addressed. Moreover, our understanding(s) of “poverty” and the intended outcomes of development investments have become much richer over the past 25 years, incorporating more nuance regarding gender, community differences, and fundamental reconsideration of the meaning of poverty and prosperity that are not captured by simple head count income or even living standard measures.

3 show abstract
0308-521X * * 27127647
Publication date: Available online 1 February 2018

Source: Agricultural Systems
Author(s): James Hansen, Jon Hellin, Todd Rosenstock, Eleanor Fisher, Jill Cairns, Clare Stirling, Christine Lamanna, Jacob van Etten, Alison Rose, Bruce Campbell



Climate variability is a major source of risk to smallholder farmers and pastoralists, particularly in dryland regions. A growing body of evidence links climate-related risk to the extent and the persistence of rural poverty in these environments. Stochastic shocks erode smallholder farmers' long-term livelihood potential through loss of productive assets. The resulting uncertainty impedes progress out of poverty by acting as a disincentive to investment in agriculture – by farmers, rural financial services, value chain institutions and governments. We assess evidence published in the last ten years that a set of production technologies and institutional options for managing risk can stabilize production and incomes, protect assets in the face of shocks, enhance uptake of improved technologies and practices, improve farmer welfare, and contribute to poverty reduction in risk-prone smallholder agricultural systems. Production technologies and practices such as stress-adapted crop germplasm, conservation agriculture, and diversified production systems stabilize agricultural production and incomes and, hence, reduce the adverse impacts of climate-related risk under some circumstances. Institutional interventions such as index-based insurance and social protection through adaptive safety nets play a complementary role in enabling farmers to manage risk, overcome risk-related barriers to adoption of improved technologies and practices, and protect their assets against the impacts of extreme climatic events. While some research documents improvements in household welfare indicators, there is limited evidence that the risk-reduction benefits of the interventions reviewed have enabled significant numbers of very poor farmers to escape poverty. We discuss the roles that climate-risk management interventions can play in efforts to reduce rural poverty, and the need for further research on identifying and targeting environments and farming populations where improved climate risk management could accelerate efforts to reduce rural poverty.

4 show abstract
0308-521X * * 27569865
Publication date: Available online 29 August 2018

Source: Agricultural Systems
Author(s): Anamika Dey, Anil K. Gupta, Gurdeep Singh



Harnessing innovative potential of individual and communities in high risk environments provides an entrepreneurial approach to poverty alleviation. The access to resources and the ability of communities to transform these resources technologically depends on the matrices of institutional assurances and attitude to take risks to convert ecological variability into entrepreneurial opportunities for investments. These innovations can emerge endogenously or sourced exogenously or might be a blend of both. The Honey Bee Network has evolved several instruments for scouting, documenting, validating and value-adding, financing and disseminating innovations for, from and with grassroots.
Climatic fluctuations produce four kinds of household portfolios depending upon the average income or productivity and variance around it: a) high mean-low variance, b) high mean-high variance, c) low mean-low variance and d) low mean-high variance. Category d comprises the most vulnerable community members; but the challenge before agriculture scientist is to recognize that the economically poorest people may not be intellectually or institutionally poor. The grassroots innovations often remain localized and underdeveloped. Blending and/or bundling formal and informal knowledge systems can generate viable, investible choices for individuals, communities or a combination thereof. Innovation can take place in terms of various combinations of products, processes, services and systems (PPSS). The conventional agricultural system has not focused on creating or augmenting innovation capabilities or potential by modifying the interplay between existing institutions, technologies and resources. in the age of mass customization, the standardized solutions and packages have no place. Without enhancing local capabilities to interpret climatic and other sources of fluctuations, we cannot generate dynamic household portfolios of private, common and public resource based survival strategies.
Innovations in instruments of engagement between formal and informal system are as important as technological and other innovations. The microfinance has to evolve into micro venture innovation finance so that communities and individuals can take risk to generate viable social and economic enterprises. Incentives to experiment, explore and fail may not work effectively without risk absorption mechanisms at different levels. While conventional intellectual property protection system is useful for market based economies, the concept of Technology Commons may be more apt for network based economies, promoting open sharing among communities but sharing with commercial firms through licensing.
The proposed inclusive innovation ecosystem focuses at strengthening the coping strategies of marginal farmers, particularly women by 1) harnessing social & ethical capital by pooling and sharing of resources and associated knowledge, 2) converting access to resources and knowledge into episodic and/or perennial enterprises 3) overcoming climatic or market induced fluctuations through innovations in PPSS; 4) building self-designed, self-governed institutions i.e. autopoietic institutions for continuous learning and experimentation to overcome poverty; 5) encouraging third party interventions through heteropoietic institutions only for short term so as not to dissipate long term autopoietic potential for sustainability by having permeable and fuzzy boundaries to facilitate exchange of expertise, feedback and other resources as and when needed, and 6) fostering distributed, decentralized and diversified innovation-based portfolio of enterprises contributing to social, economic and ecological resilience.

5 show abstract
0308-521X * * 28787337
Publication date: Available online 21 December 2018

Source: Agricultural Systems
Author(s): Thomas P. Tomich, Preetmoninder Lidder, Jeroen Dijkman, Mariah Coley, Patrick Webb, Maggie Gill



Drawn from numerous sources, including papers in this special issue, this concluding paper synthesizes evidence on the relationship between agricultural research for development and poverty reduction, with particular emphasis on agri-food systems perspectives in shaping programs aimed at rural prosperity. Following our introduction in section 1, we revisit the ex ante set of 18 pathways in section 2 (which were laid out in our introductory paper for this SI), posing some critical questions: Can a manageable set of impact pathways be identified' How are they inter-related' Rather than independent linear pathways, is it better (both conceptually and for clarity of communication) to represent these as impact networks rather than linear pathways' These insights lead to very different and more inclusive partnerships and contain their own implications for program design in section 3. The challenges facing the world today are complex, and no single organization or sector can hope to effectively confront these issues alone. Not only is partnership increasingly seen as a multi-stakeholder phenomenon rather than a bilateral one, but there also is a discernible move towards a network framing (e.g., as “innovation systems” or “boundary spanning”). This change is driven by the progressive inclusion of agricultural research goals as part of the wider development agenda, where complexity and systemic change are central. In turn, this requires more appropriate strategies for knowledge creation, innovation, and partnership. Section 4 presents implications for program design and priority-setting that follow from foregoing insights on the interplay of pathways and partnerships.

6 show abstract
0308-521X * * 29361255
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Oyakhilomen Oyinbo, Jordan Chamberlin, Bernard Vanlauwe, Liesbet Vranken, Yaya Alpha Kamara, Peter Craufurd, Miet Maertens



Agricultural extension to improve yields of staple food crops and close the yield gap in Sub-Saharan Africa often entails general recommendations on soil fertility management that are distributed to farmers in a large growing area. Site-specific extension recommendations that are better tailored to the needs of individual farmers and fields, and enabled by digital technologies, could potentially bring about yield and productivity improvements. In this paper, we analyze farmers' preferences for high-input maize production supported by site-specific nutrient management recommendations provided by an ICT-based extension tool that is being developed for extension services in the maize belt of Nigeria. We use a choice experiment to provide ex-ante insights on the adoption potentials of site-specific extension services from the perspective of farmers. We control for attribute non-attendance and account for class as well as scale heterogeneity in preferences using different models, and find robust results. We find that farmers have strong preferences to switch from general to ICT-enabled site-specific soil fertility management recommendations which lend credence to the inclusion of digital technologies in agricultural extension. We find heterogeneity in preferences that is correlated with farmers' resource endowments and access to services. A first group of farmers are strong potential adopters; they are better-off, less sensitive to risk, and are more willing to invest in a high-input maize production system. A second group of farmers are weak potential adopters; they have lower incomes and fewer productive assets, are more sensitive to yield variability, and prefer less capital and labor intensive production techniques. Our empirical findings imply that improving the design of extension tools to enable provision of information on the riskiness of expected outcomes and flexibility in switching between low-risk and high-risk recommendations will help farmers to make better informed decisions, and thereby improve the uptake of extension advice and the efficiency of extension programs.

7 show abstract
0308-521X * * 29361256
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Rishabh Gupta, Ashok Mishra



An innovative approach of using agro-ecological zones (AEZs), instead of using political boundaries, has been adopted for climate change impact analysis on rice production of India. The analysis has been carried out by using a process-based Crop Simulation Model (CSM)-CERES-Rice fed with improved state of art bias corrected climate projections from eight Global Climate Models (GCMs) for four expected climatic scenarios- Representative Concentration Pathways (RCP 2.6, 4.5, 6.0 and 8.5). Using weather-soil-crop information along with year-wise effect of CO2 increase assumption for different RCPs as input to the crop model, simulations were performed for the base period (1976–2005) as well as three future periods (2020s: 2006–2035, 2050s: 2036–2065, and 2080s: 2066–2095) for insight understanding of climate change impact on rice yield. Model simulated rice yields of future periods were compared with that of the base period to quantify the climate change impact. Results based on multi-GCM ensemble show expected increase in rice yield of most of the AEZs in RCP 2.6 but as on moving towards RCP 8.5 through RCP 4.5 and 6.0, the positive impact on rice yield in RCP 2.6, in major rice producing zones, is expected to mitigate and lead to the negative impact by 2080s. Large spatiotemporal variability is expected in most of the zones with humongous variability in arid and hilly zones. The overall change in spatial rice yield in India taking all used GCM-RCP combinations in consideration is expected to vary from 1.2 to 8.8%, 0.7 to 12.6% and −2.9 to 17.8% due to the expected climate change in 2020s, 2050s and 2080s, respectively.

8 show abstract
0308-521X * * 29392222
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): N. Andrieu, G. Blundo-Canto, G.S. Cruz-Garcia



The Peruvian Amazon is undergoing rapid and uneven economic growth, alongside alarming rates of deforestation, increasing land use change and food security concerns. Although it has been widely acknowledged that food insecurity is intrinsically linked with deforestation, the links have not been thoroughly documented. The aim of this paper is to analyse the trade-offs and synergies between food security and forest exploitation at household level in mestizo communities in Ucayali, one of the regions with the highest deforestation rates in the Peruvian Amazon. To this end, 24 farmers were interviewed, surveys were conducted with a sample of 58 households, and an ad-hoc simulation modelling tool was developed and applied. Four main types of mestizo farming households were identified based on their crop and livestock diversity. For all farm types, the forest mainly represented a set aside area to support a potential increase in agricultural production. However, simulations showed that the different types of households, with different decision rules, lead to different rates of deforestation. The results of this study showed that the most diversified farming households presented the smallest trade-offs between food security and forest conservation, as they are the ones most likely to preserve the forest while ensuring their food security.

9 show abstract
0308-521X * * 29392223
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Lenora Ditzler, Adam M. Komarek, Tsai-Wei Chiang, Stéphanie Alvarez, Shantonu Abe Chatterjee, Carl Timler, Jessica E. Raneri, Natalia Estrada Carmona, Gina Kennedy, Jeroen C.J. Groot



Farm models have the potential to describe farming systems and livelihoods, identify trade-offs and synergies, and provide ex-ante assessments of agricultural technologies and policies. We developed three new modules related to budget, labor, and human nutrition for the bio-economic whole-farm model ‘FarmDESIGN’. The expanded model positions the farming enterprise within the farm household. We illustrate the model's new capabilities for farm households in two villages in Northwest Vietnam, where we conducted multi-objective optimization to identify options for improving the farm households' current performance on key sustainability and livelihood indicators. Modeling results suggest trade-offs between environmental, economic, and social objectives are common, although not universal. The new modules increase the scope for modeling flows of resources (namely cash, labor, and food) between the farm enterprise and the farm household, as well as beyond the farm gate. This allows conducting modeling explorations, optimization routines, and scenario analyses in farming systems research.



Graphical abstract







10 show abstract
0308-521X * * 29476617
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Honglin Zhong, Laixiang Sun, Günther Fischer, Zhan Tian, Zhuoran Liang



Unsustainable overexploitation of groundwater for agricultural irrigation has led to rapid groundwater depletion and severe environmental damage in the semi-arid Hebei Plain of China. Field experiments have recommended annual winter fallowing (i.e., forgoing winter wheat production) as the most effective way to replenish groundwater. However, adopting the recommendation across the Hebei Plain would lead to a significant reduction in total wheat production. This research aims to find the most favorable water-sustainable cropping systems for different localities in the Hebei Plain, which at the regional aggregation level maintains the uppermost overall levels of wheat and grain production respectively. Our simulations indicate that in the Hebei Plain, an optimal allocation of a wheat-early maize relay intercropping system and an early maize-winter fallow cropping system across the Hebei Plain could lead to significant water savings while minimizing grain production losses to around 11%. Compared to the prevailing wheat and summer maize cropping system, to prevent a drop in the water table, 39% of the current wheat cropping land would need to be fallowed in winter, reducing irrigation water use by 2639 × 106 m3. Replacing the prevailing wheat and summer maize cropping system with our optimized allocation system could lead to a 36% increase in total maize production and 39% decrease in total wheat production, resulting in total agricultural irrigation water savings of 2322 × 106 m3 and a total grain production reduction by 11%. The findings indicate the potential benefits of our cropping system adaptation method to meet the challenge of recovering local groundwater level with the least possible reduction of wheat and total grain production in the Hebei Plain.

11 show abstract
0308-521X * * 29476618
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Ty L. Tinsley, Steven Chumbley, Clay Mathis, Richard Machen, Benjamin L. Turner



Sustainable ranching operations require access to adequate forage reserves and suitable means to market livestock, both of which are critical determinants of adaptive capacity (defined here as the ability to manipulate stocking rate). Ranch adaptive capacity is most relevant during times of forage shortages from drought. Unfortunately for island beef production systems, traditional adaptive measures used in continental systems are unavailable, such as transporting livestock to less affected areas, importing feed resources (cost prohibitive), intensive grazing practices or stockpiling forage (since forages mature too rapidly and are generally low quality), or destocking through cull cow sales (due to limited marketing and processing capacities). Located on an island of Hawaii, the case study ranch investigated here is challenged by each of these environmental and market constraints. The ranch resides on the leeward side of its island such that it receives minimal rainfall and forage productivity is similar to semi-arid rangelands in the western United States. The ranch's livestock management problem is compounded during drought, since island slaughter capacity is limited and there is no financially feasible means of marketing and transporting culled livestock off the island. Therefore, when forage is limited, managers are forced to retain ownership of culled mature cows, who are moved into a terminal herd to await the next available harvest or shipping availability. Terminal herds occupy areas with lower quality forages to conserve the most productive pastures for higher valued calves. This backlog of cull cows creates extended periods of stress on forage resources, since grazing pressure is not relieved as drought intensifies and increases operational expenses. A simulation model was created in an effort to identify key leverage points within the ranching operation that have the greatest impact on forage availability, herd size and net income. Upon completion of the model, sensitivity analyses were conducted to identify key drivers of model behaviors and several what-if scenarios were run based on questions provided by island ranch managers. Results showed that reducing terminal herd size through increased island processing capacity would not relieve forage pressure or eliminate the backlog of terminal cull cows, although net income was improved through greater cow sales. Several follow up tests were then run to evaluate changes to internal ranch decision making, which showed that reductions in heifer retention would provide a wider array of ecological and economic benefits. The ranch's ability to manipulate heifer retention rates, rather than cull cow rates, terminal herd shipping, or island processing capacity, was shown to be the critical aspect which drives ranch adaptive capacity.

12 show abstract
0308-521X * * 29507703
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Kefei Chen, Rebecca A. O'Leary, Fiona H. Evans



Yield prediction is a major determinant of many management decisions for crop production. Farmers and their advisors want user-friendly decision support tools for predicting yield. Simulation models can be used to accurately predict yield, but they are complex and difficult to parameterise. The goal of this study is to build a simple and parsimonious model for predicting wheat yields that can be implemented in a decision tool to be used by farmers at a paddock level.
A large yield data set accumulated from trials on commonly grown varieties in Western Australia is used to build and validate a generalised additive model (GAM) for predicting wheat yield. Explanatory variables tested included weather data and derivatives, geolocation, soil type, land capability, and wheat varieties. Model selection followed a forward stepwise approach in combination with cross-validation to select the smallest set of explanatory variables. The predictive performance is also evaluated using independent data.
The final model uses seasonal water availability, location and year to predict wheat yield. Because the GAM model has minimal inputs, it can be easily employed in a decision tool to predict yield throughout the growing season using rainfall data up to the prediction date and either climatological averages or seasonal forecasts of rainfall for the remainder of the growing season. It also has the potential to be used as an input to agronomic models that predict the effect on yield of various management choices for fertiliser, pest, weed and disease management.

13 show abstract
0308-521X * * 29507704
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): D. Villalba, B. Díez-Unquera, A. Carrascal, A. Bernués, R. Ruiz



A decision support tool for sheep farming systems (PASTOR-DSS) was developed to investigate trade-offs between economic and environmental objectives on Spanish dairy sheep farms. The tool combines a hierarchical stochastic simulation model at three levels with a multi-objective optimisation procedure based on genetic algorithms. The first level of simulation includes rumen, reproduction and nutrient balance submodels. These three submodels are integrated into an animal model, which constitutes the second level. The third level is the farm, which includes the flock, the feeding and reproductive management, the availability of feeding resources, and the farm economics. The multi-objective genetic algorithm applies to the farm level. The tool was validated for the different levels of simulation, with outputs having an acceptable level of accuracy and representing correctly the links between feeding and reproduction. The tool was used to optimise the Latxa breed farming systems of the Basque Country (Spain). Two farm types were simulated: a COAST farm located in low-altitude Atlantic conditions and longer grazing period, and the INLAND farm located in mountain areas with a shorter grazing period. The optimisation provided a set of optimal solutions with different economic and environmental (N excretion) performances. The optimal solutions increased the financial margin over feed costs in both farms (+24% and + 22% for COAST and INLAND, respectively). The final space of solutions showed a clear trade-off between the economic and environmental performance (nitrogen excretion). The difference in the financial margin over feed costs between the solutions could be interpreted as the opportunity cost of greening in policy design, i.e., the payment that farmers should receive to change their farming methods to reduce nitrogen pollution.

14 show abstract
0308-521X * * 29507705
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): David J. Parsons, Dolores Rey, Maliko Tanguy, Ian P. Holman



Drought has wide ranging impacts on all sectors. Despite much effort to identify the best drought indicator to represents the occurrence of drought impacts in a particular sector, there is still no consensus among the scientific community on this. Using a more detailed and extensive impact dataset than in previous studies, this paper assesses the regional relationship between drought impacts occurrence in British agriculture and two of the most commonly used drought indices (SPI and SPEI). The largest qualitative dataset on reported drought impacts on British agriculture for the period 1975–2012 spanning all major recent droughts was collated. Logistic regression using generalised additive models was applied to investigate the association between drought indices and reported impacts at the regional level. Results show that SPEI calculated for the preceding six months is the best indicator to predict the probability of drought impacts on agriculture in the UK, although the variation in the response to SPEI6 differed between regions. However, this variation appears to result both from the method by which SPEI is derived, which means that similar values of the index equate to different soil moisture conditions in wet and dry regions, and from the variation in agriculture between regions. The study shows that SPEI alone has limited value as an indicator of agricultural droughts in heterogeneous areas and that such results cannot be usefully extrapolated between regions. However, given the drought sensitivity of agriculture, the integration of regional predictions within drought monitoring and forecasting would help to reduce the large on-farm economic damage of drought and increase the sector's resilience to future drought.

15 show abstract
0308-521X * * 29507706
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Andreas Meyer-Aurich, Yusuf Nadi Karatay



The role of nitrogen (N) fertilizer in mitigating economic risks in agriculture is under debate with contrasting views. This study contributes to an analysis of the economic response in wheat production to N fertilizer with respect to price premium structures for grain qualities from eight field experiments across Germany. Optimal N fertilizer levels were determined by different algorithms, based on average response, expected profit, and certainty equivalents with different attitudes toward risk aversion. The inherent uncertainty of yield response and crop quality response consistently resulted in higher expected profit with higher N rates than a management based on average response. Profit maximizing N rates based on maximum expected profit were substantially higher than economic optimal N rates based on average response data at 6/8 sites. Expected profit remained high over a large range of N fertilizer rates without a substantial downside risk and opportunity costs of deviating from optimal N rates within a range of 50 kg/ha. Protein price premiums reduce the riskiness of higher N rates and it is possible to apply higher N rates without increasing risk considerably.

16 show abstract
0308-521X * * 29542391
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Olivier M. Joffre, P. Marijn Poortvliet, Laurens Klerkx



Over the course of just a few years, shrimp farming has become a major aquaculture production system in coastal areas of several developing countries across the globe. However, farmers are facing a variety of risks related to disease, market, and climate, which influence risk management strategies and adoption of new technologies. This paper looks at three practices related to pond management: (1) water quality management to ensure a good environment for shrimp growth; (2) adequate feed input; and (3) disease control practices in order to mitigate the risk of disease outbreak in the pond. We investigated adoption of these three practices in smallholder shrimp farms in the Mekong Delta, by exploring how and whether membership into a producer's cluster influences access to knowledge and perception of risk in the adoption process. The results show that, after controlling for farm characteristics, farm clustering has a positive relationship with the adoption of water quality management, feed inputs, and disease control practices. Results also indicate that increasing interaction frequency with public sector and private sector's actors, as well as the perceived degree of market risk, positively influences the adoption of the three pond management practices under study. Mediation analyses show that being a member of a farmer cluster influences adoption of farming practices via two underlying processes: frequency of interaction with public and private sector's actors, and perception of market risk, both of which ultimately promote the adoption of practices. We conclude that clustering is a promising avenue for fostering interactions between farmers and key supporting actors in aquaculture, and impacts both the formation of specific aqua-related risk perceptions and subsequent practice adoption. As such, clusters – by fostering linkages and facilitating interactions between different knowledge sources – can promote adoption of practices toward sustainable intensification. However, to more effectively deploy a cluster approach a key policy and practice implication is to take into consideration local idiosyncrasies defined by their social interactions, risk perception and spatial dimensions in order to better facilitate local linkages between farms (horizontal coordination) and a better integration with the value chain (vertical coordination).

17 show abstract
0308-521X * * 29572294
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Solène Pissonnier, Arnaud Dufils, Pierre-Yves Le Gal



A redesign process at the farm level may be required for agricultural production systems to evolve in a manner that reduces their environmental and health impacts. This process leads to imagining configurations described as “radical” because they reach beyond the limits posed by the substitution of synthetic inputs by natural ones. An assessment of the possible effects of these configurations on farm functioning and performance is required to inform stakeholders about the advantages of testing and implementing them. This study describes an approach for designing and assessing such configurations that involves researchers, technicians and farmers. Some of these stakeholders can play the role of designers, who lead the redesign process, and/or experts, who provide references and knowledge throughout the exercise. The approach is based on six principles (evaluation, plausibility, precision, flexibility, diversity, iteration) and includes eight steps. Based on a diagnosis of the production context (step 1), some ideas of radical production system are imagined (step 2), which define the kind of experts to be involved (step 3). A farm, virtual or real, then is selected and characterized as a case study (step 4), and the specific objectives driving the farm's redesign process are described (step 5). Scenarios are then designed and characterized (step 6), quantitatively assessed using a simulation tool dedicated to the kind of production system studied (step 7), and compared in order to feed debates between designers and experts on the merits and limits of the various options designed (step 8). Steps 6 through 8 may be repeated as new ideas emerge. This methodology is illustrated with the case of a farm specialized in apple production on which a sheep unit is introduced to reduce pesticide use by ensuring grass management and reducing pest pressure. Two scenarios are designed according to the kind of sheep management. CoHort software was used to assess the two scenarios in terms of economic performance, frequency of pesticide use, and farm work organization. The limits and values of this redesign process are discussed regarding the hypothesis that must be made to characterize virtual biodiversity-based systems, the kind of involvement expected from farmers, and the opportunities provided by moving from the farm to territory scale in the case of crop-livestock systems. This redesign approach can potentially be applied to many topics, ranging from the consistent combination of agroecological practices to futuristic scenarios involving robots.

18 show abstract
0308-521X * * 29572295
Publication date: June 2019

Source: Agricultural Systems, Volume 172
Author(s): Ruth Meinzen-Dick, Agnes Quisumbing, Cheryl Doss, Sophie Theis



This paper reviews the literature on women’s land rights (WLR) and poverty reduction. It uses the Gender, Agriculture and Assets Project (GAAP) conceptual framework to identify pathways by which WLR could reduce poverty and increase wellbeing of women and their households in rural areas. It uses a systematic review search methodology to identify papers for inclusion, but adopts a more synthetic approach to assess the level of agreement and the amount of evidence within this literature. The paper examines the evidence from qualitative as well as quantitative studies on each of these pathways. Owing to the scarcity of experimental studies, the review of empirical work is based mostly on observational studies. We find some evidence on these relationships, but many of the key pathways have not been empirically analyzed. The evidence is strong for relationships between WLR and bargaining power and decision-making on consumption, human capital investment, and intergenerational transfers. There is a high level of agreement, but weaker evidence on the relationship between WLR and natural resource management, government services and institutions, empowerment and domestic violence, resilience and HIV risk, and consumption and food security. There is less agreement and insufficient evidence on the associations between WLR and other livelihoods, and a higher level of agreement, but still limited evidence on associations between WLR and credit, technology adoption, and agricultural productivity. Notably, we find no papers that directly investigate the link between WLR and poverty. Many gaps in the evidence arise from a failure to account for the complexity of land rights regimes, the measurement of land rights at the household level, the lack of attention paid to gender roles, and the lack of studies from countries outside Africa. Many studies are limited by small sample sizes, the lack of credible counterfactuals, lack of attention to endogeneity and selection bias, and possible response bias on questions of domestic violence and empowerment. There are very few rigorous evaluations of reforms that strengthened WLR. The paper concludes that gaps in the evidence should not deter the careful design and implementation of programs and policies to strengthen WLR, given the ongoing land tenure reforms in many countries. Different modalities and mechanisms for strengthening WLR could be tested, with appropriate counterfactuals. Program designers and evaluators can strategically identify pathways and outcomes where evidence gaps exist, and deliberately design studies to close those gaps.

19 show abstract
0308-521X * * 29572296
Publication date: June 2019

Source: Agricultural Systems, Volume 172
Author(s): Meine van Noordwijk



Poverty has many faces and poverty reduction many pathways in different contexts. Lack of food and income interact with lack of access to water, energy, protection from floods, voice, rights and recognition. Among the pathways by which agricultural research can increase rural prosperity, integrated natural resource management deals with a complex nexus of issues, with tradeoffs among issues that are in various stages of denial, recognition, analysis, innovation, scenario synthesis and creation of platforms for (policy) change. Rather than on a portfolio of externally developed ‘solutions’ ready for adoption and use, the concept of sustainable development may primarily hinge on the strengths and weaknesses of local communities to observe, analyse, innovate, connect, organize collective action and become part of wider coalitions. ‘Boundary work’ supporting such efforts can help resolve issues in a polycentric governance context, especially where incomplete understanding and knowledge prevent potential win-win alternatives to current lose-lose conflicts to emerge. Integrated research-development approaches deal with context (‘theory of place’) and options (‘theory of change’) in multiple ways that vary from selecting sites for studying pre-defined issues to starting from whatever issue deserves prominence in a given location of interest. A knowledge-to-action linkage typology recognizes three situations of increasing complexity. In Type I more knowledge can directly lead to action by a single decision maker; in Type II more knowledge can inform tradeoff decisions, while in Type III negotiation support of multiple knowledge + multiple decision maker settings deals with a higher level of complexity. Current impact quantification can deal with the first, is challenged in the second and inadequate in the third case, dealing with complex social-ecological systems. Impact-oriented funding may focus on Type I and miss the opportunities for the larger ultimate impact of Type II and III involvements.

20 show abstract
0308-521X * * 29572297
Publication date: June 2019

Source: Agricultural Systems, Volume 172
Author(s): Jeffrey Alwang, Elisabetta Gotor, Graham Thiele, Guy Hareau, Moti Jaleta, Jordan Chamberlin



Innovations to improve staple crop germplasm can reduce poverty and otherwise improve farmer livelihoods through complex and multiple pathways. This paper reviews the evidence for one prominent pathway—through increased incomes (in cash and kind) for poor farmers who adopt the technology.
An important determinant of poverty reduction is the ability of poor producers to adopt productivity-enhancing varieties, and the paper analyzes recent household-level data from two African countries to examine if poor producers face unique barriers to adoption. A second determinant of poverty reduction is the area available to plant these varieties and whether the intensity of adoption is great enough to significantly reduce poverty. The paper uses a double-hurdle estimation framework to model the adoption/area planted joint decision for maize farmers in Ethiopia and sweet potato farmers in Uganda. The focus of the analysis is the effect of poverty-related variables on adoption/area planted decisions. Farmer wealth, landholding, education, location, and access to support and information services are included to understand how correlates of poverty affect adoption decisions.
We find evidence that landholding size is an important barrier to poverty reduction; poor farmers are able to adopt improved varieties, but their intensity is constrained by land availability. In Uganda, farmers at the 95th percentile of adoption area received about $0.13 per person per day from the incremental yield, covering < 50% of the mean household poverty gap. This gain only comes under optimistic assumptions and most adopters do not have sufficient area for the direct income effect to be large. The evidence suggests that direct, short-term impacts of increased productivity to increased income may be limited in magnitude. Nonetheless, we recognize that other, less direct pathways may be important, particularly over longer times. Impacts through indirect pathways are, however, more difficult to measure. This has implications for the design of M&E and the crafting of appropriate targets for outcomes of research on staple crops which should focus perhaps on the other pathways where poverty reduction is more probable.

21 show abstract
0308-521X * * 29612731
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Komlavi Akpoti, Amos T. Kabo-bah, Sander J. Zwart



Agricultural land suitability analysis (ALSA) for crop production is one of the key tools for ensuring sustainable agriculture and for attaining the current global food security goal in line with the Sustainability Development Goals (SDGs) of United Nations. Although some review studies addressed land suitability, few of them specifically focused on land suitability analysis for agriculture. Furthermore, previous reviews have not reflected on the impact of climate change on future land suitability and how this can be addressed or integrated into ALSA methods. In the context of global environmental changes and sustainable agriculture debate, we showed from the current review that ALSA is a worldwide land use planning approach. We reported from the reviewed articles 69 frequently used factors in ALSA. These factors were further categorized in climatic conditions (16), nutrients and favorable soils (34 of soil and landscape), water availability in the root zone (8 for hydrology and irrigation) and socio-economic and technical requirements (11). Also, in getting a complete view of crop’s ecosystems and factors that can explain and improve yield, inherent local socio-economic factors should be considered. We showed that this aspect has been often omitted in most of the ALSA modeling with only 38% of the total reviewed article using socio-economic factors. Also, only 30% of the studies included uncertainty and sensitivity analysis in their modeling process. We found limited inclusions of climate change in the application of the ALSA. We emphasize that incorporating current and future climate change projections in ALSA is the way forward for sustainable or optimum agriculture and food security. To this end, qualitative and quantitative approaches must be integrated into a unique ALSA system (Hybrid Land Evaluation System - HLES) to improve the land evaluation approach.

22 show abstract
0308-521X * * 29682160
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Mostafa Mardani Najafabadi, Saman Ziaee, Alireza Nikouei, Mahmoud Ahmadpour Borazjani



The economic, technical and strategic factors are the three most important factors in examining the cropping patterns in Iran. Iran is geographically located in a part of the planet with specific climate constraints. Drought is one of the constraints that has been a major challenge to agricultural development for many years and has always been the subject of discussions and investigations. On the other hand, constraints such as agricultural soils, economic factors, climate change, agricultural workforce, etc., multiply the production challenges in the country. Despite such constraints, planning a coherent and targeted program for the cultivation of crops and overcome the existing problems is inevitable. The present study introduced a model for optimization of regional cropping pattern decisions, which is one of the subsets of the Multi-Objective Structural Planning (MOSP) approach, and addressed different objectives, such as economic, social and environmental objectives, separately and jointly. However, it is important to address the exchange of crops in different areas in order to achieve the fundamental objectives of determining the optimal cropping pattern. Therefore, in the proposed model of optimal regional cropping pattern, issues such as the transportation of crops and, consequently, virtual water and energy exchanges were also considered. In order to evaluate the proposed model, agricultural arable lands located in the political-geographic divisions of 23 counties of Isfahan province (Iran) were selected for examination. The results showed that in the main groups of grains and forage, a significant reduction was observed in the optimal crop area of the multi-objective model by 26% and 5%, respectively. Increasing the crop area of horticultural products by 10% in the optimal pattern of multi-objective model was another important factor in the analysis of the results. In general, in order to achieve the economic, social and environmental objectives mentioned in this study within the framework of a multi-objective planning, a 16% reduction in the level of the crop area in Isfahan province is inevitable. The results of this measure are reduction in the irrigation water consumption by 17%, increase in the profit by 58% and increase in the production by 11%. Regarding the fact that in the structural planning of cropping pattern, different and sometimes conflicting objectives are considered and the compromise between the objectives is possible in the multi-objective structural planning model, the decision makers are recommended to use this model.

23 show abstract
0308-521X * * 29682161
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Andrea Nocentini, Andrea Monti



The deployment of dedicated energy crops and the related land-use change are topical issues, particularly in relation to carbon storage and climate change mitigation effects. In order to maximize their mitigation potential and to fully supply new biorefineries, perennial energy crops may be established, not only on former idle and grazing lands, but also on the least remunerative cropland, as indirect land use change effects are still very uncertain. Possibly becoming a future land-use change option, the carbon flows of the most common crop rotation in Europe (maize-wheat) and the perennial grass switchgrass were measured, and later included in a biogeochemical model to build possible scenarios. Yearly mean soil respiration did not statistically differ between switchgrass and the annual cereals (2.9 and 2.5 Mg CO2 ha−1 month−1, respectively), but in switchgrass the peak flux was reached during crop growth (6.1 Mg CO2 ha−1 month−1), while in the cereal system it occurred in bare soil (after harvest and soil tillage) (4.5 Mg CO2 ha−1 month−1). Harvest residues contributing to soil organic matter were highest in maize (12.4 Mg ha−1 y−1) and decreased in switchgrass (−79%) and wheat (−87%). Root biomass was much higher in switchgrass (10.0 Mg ha−1 y−1) than maize (−81%) or wheat (−94%). Model projections showed how continuous switchgrass cycles of 15 years following annual crops cultivation were capable to keep building up SOC inventories (0.24 or 0.32 Mg ha−1 y−1) up to the year 2100. On the opposite, maintaining the land under maize-wheat cultivation, depending on maize stover management, would either produce a SOC loss (−3.6 Mg ha−1) or could help the soil increasing SOC (+9.4 Mg ha−1) towards a new equilibrium after two decades.

24 show abstract
0308-521X * * 29714254
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Isabel Blanco-Penedo, Karin Sjöström, Philip Jones, Margret Krieger, Julie Duval, Felix van Soest, Albert Sundrum, Ulf Emanuelson



The aim of the present study was to classify the diversity of organic dairy farms in four European countries according to their structural characteristics and investigate the association of these farm types with implementation of herd health plans. A Multiple Correspondence Analysis (MCA), followed by Agglomerative Hierarchical Clustering (AHC), was used to classify the farms. Data for the analysis came from a survey of 192 organic farms from France, Germany, Spain and Sweden and contained farm and farmer descriptions from which the typologies were derived. Herd health plans was agreed for each farm, via a participatory approach involving the farmers, their veterinarians and other advisors (e.g. dairy advisors) by the use of an impact matrix. The MCA yielded two principal component axes explaining 51.3% of variance. Three farm groups were identified by AHC using the factor scores derived from the MCA. Cluster 1, the most numerous group (56.7% of the sample), had medium herd sizes with moderate use of pasture and moderate intensity of input use. Cluster 2, representing 17.7% of the sample, were the most extensive system and mainly of very small farm size. Cluster 3 (25.5% of the sample and only found in Sweden), had an intensive management approach, but relatively low stocking rate. The analysis also showed that organic dairy farms adopted differentiated strategies towards economic assets and animal health status, according to group membership. The typology therefore provides insights into the potential for advisory strategies relating to husbandry practices, different housing, pasture management and intensity, etc. adapted to different groups of farms. Regarding herd health plan implementation, Cluster 1 was the group with most implemented actions and Cluster 2 with lowest rate of implemented actions. These results may be used as background for directing (tailored) advice strategies, i.e. different types of organic dairy farms (clusters) may require different types of advisory services and recommendations adapted to the specific farm situation in order to deliver future improvements in animal health.

25 show abstract
0308-521X * * 29752756
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Rogério de Souza Nóia Júnior, Paulo Cesar Sentelhas



El Niño Southern Oscillation (ENSO) is one of the most important atmospheric-oceanic phenomena, responsible for climate variability in several Brazilian regions, which affects agriculture, mainly soybean – maize off-season succession. Therefore, the ENSO impacts on soybean – maize off-season double crop system can affect global food security, since Brazil is a major player as producer of these two crops, with a total production that represents 27% and 6% of world's soybean and maize production, respectively. In order to understand the risks associated to this crop system, the aim of this study was to assess the influence of ENSO phenomenon on the spatial and temporal soybean and maize off-season yield variabilities, considering simulations with three different crop models (FAO-AZM, DSSAT and APSIM) in a multi-model approach, and to determine the best sowing windows for this production system for each ENSO phase (El Niño, La Niña and Neutral) in different Brazilian producing regions. Previously calibrated and validated models were used to simulate soybean yields for 29 locations in 12 states, with sowing dates ranging from late September to early January of each growing season for a period of 34 years (1980–2013). The maize off-season sowing was done just after the soybean harvest, ranging from late January to early May. ENSO phases affected soybean and maize yields across the country, which can be minimized by choosing the best sowing window for soybean. In northern Brazil, El Niño negatively impacts soybean and maize off-season yields, making the succession of these crops risk, with the best sowing window being very short. Similar result was found for southern and central Brazil during La Niña years. On the contrary, cropping soybean and maize off-season in succession during El Niño years in center-south of and during La Niña years up north have higher chances of success.



Graphical abstract







26 show abstract
0308-521X * * 29804827
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Pratap S. Birthal, Jaweriah Hazrana



Indian agriculture is highly vulnerable to climate shocks, such as floods, droughts and heat-stress. In this paper, using a dynamic panel-data approach we have assessed the impact of rainfall-deficit and heat-stress on agricultural productivity, and subsequently evaluated effectiveness of crop diversification in mitigating their adverse effects. The findings show that both rainfall-deficit and heat-stress damage agricultural productivity, and the damage increases with increase in their severity. Nevertheless, we find crop diversification as an important ex ante adaptation measure to climatic shocks and its adaptation benefits are more apparent against severe shocks and in the long-run. Our findings reinforce the dynamic role of crop diversification in improving resilience of agricultural production systems to climatic shocks.

27 show abstract
0308-521X * * 29804828
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Celia Chaiban, Christophe Biscio, Weerapong Thanapongtharm, Michael Tildesley, Xiangming Xiao, Timothy P. Robinson, Sophie O. Vanwambeke, Marius Gilbert



In recent decades, intensification of animal production has been occurring rapidly in transition economies to meet the growing demands of increasingly urban populations. This comes with significant environmental, health and social impacts. To assess these impacts, detailed maps of livestock distributions have been developed by downscaling census data at the pixel level (10 km or 1 km), providing estimates of the density of animals in each pixel. However, these data remain at fairly coarse scale and many epidemiological or environmental science applications would make better use of data where the distribution and size of farms are predicted rather than the number of animals per pixel. Based on detailed 2010 census data, we investigated the spatial point pattern distribution of extensive and intensive chicken farms in Thailand. We parameterized point pattern simulation models for extensive and intensive chicken farms and evaluated these models in different parts of Thailand for their capacity to reproduce the correct level of spatial clustering and the most likely locations of the farm clusters. We found that both the level of clustering and location of clusters could be simulated with reasonable accuracy by our farm distribution models. Furthermore, intensive chicken farms tended to be much more clustered than extensive farms, and their locations less easily predicted using simple spatial factors such as human populations. These point-pattern simulation models could be used to downscale coarse administrative level livestock census data into farm locations. This methodology could be of particular value in countries where farm location data are unavailable.

28 show abstract
0308-521X * * 29804829
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Yu Hong, Nico Heerink, Minjuan Zhao, Wopke van der Werf



Intercropping entails the concurrent production of two or more crop species in the same field. This traditional farming method generally results in a highly efficient use of land, but whether it also contributes to a higher technical efficiency remains unclear. Technical efficiency refers to the efficiency with which a given set of natural resources and other inputs can be used to produce crops. In this study, we examined the contribution of maize-based relay-strip intercropping to the technical efficiency of smallholder farming in northwest China. Data on the inputs and crop production of 231 farms were collected for the 2013 agricultural season using a farm survey held in Gaotai County, Gansu Province, China. Controlling for other factors, we found that the technical efficiency scores of these farms were positively affected by the proportion of land assigned to intercropping. This finding indicates that the potential negative effects of intercropping on the use efficiency of labour and other resources are more than offset by its higher land-use efficiency when compared with monocropping.

29 show abstract
0308-521X * * 29804830
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Ian Kropp, A. Pouyan Nejadhashemi, Kalyanmoy Deb, Mohammad Abouali, Proteek C. Roy, Umesh Adhikari, Gerrit Hoogenboom



Sustainable intensification entails increasing the yield of existing agricultural lands while reducing the impact on the environment. Therefore, we sought to optimize irrigation and fertilizer scheduling on the farm level with respects to crop yield and environmental impact. Unlike traditional optimization, multi-objective optimization techniques provide a set of optimal solutions that collectively represent the tradeoffs between the conflicting objectives. As a result, decision makers can then prioritize and select their optimal trade-off from the global set of optimal solutions. To implement such an optimization platform, this study integrates the Unified Non-dominated Sorting Genetic Algorithm-III (U-NSGA-III) based multi-objective optimization platform with the Decision Support System for Agrotechnology Transfer crop model. The U-NSGA-III algorithm optimizes a farm level agricultural production system against a myriad of soil, crop, and climate objectives. With this platform, we were able to find irrigation and nitrogen schemes that reduced water usage by 48%, nitrogen usage by 26%, and nitrogen leaching by 51%.

30 show abstract
0308-521X * * 29804831
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Elesandro Bornhofen, Thiago Gentil Ramires, Tábata Bergonci, Luiz Ricardo Nakamura, Ana Julia Righetto



Different countries around the globe have different levels of vulnerability to risks because of several factors, e.g. degree of development, governance, infrastructure, among others. The probability of occurrence of certain risks as drought and unfavorable tax policies have a direct impact on the development of the agribusiness in a given country. Hence, the aim of this study is to combine a set of risk management indices in a global scale with agribusiness performance indicators, focusing on the 96 most relevant countries regarding the agribusiness GDP (Gross domestic product). We selected 27 indicators for risk management collected from the InfoRM database and seven for agribusiness performance from the FAOSTAT database. All data used in this research are public available. The data were scaled, and then analyzed through multivariate techniques, specifically using principal component analysis (displayed in biplots) and unsupervised K-means clustering in R software. The results suggest that monitoring the indicators of risk management (InfoRM) and the establishment of strategies to shrink them may have a positive effect on the agribusiness performance of a given country. For the agribusiness improvement, nations should elaborate strategies for the joint enhancement of the indicators discussed here, observing the existing associations. The implications of the use of risk management indexes and agricultural performance indicators are discussed.

31 show abstract
0308-521X * * 29804832
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Thai Thi Minh



Although agricultural innovation systems (AIS) have recently received considerable attention in academic and development circles, links between an AIS's regional specifications and structural-functional analysis have been neglected. This paper aims to understand how regional and structural dimensions determine systemic problems and blocking mechanisms that, in turn, hinder a regional AIS's function. From the basis of a qualitative data set, it presents an analysis of an AIS in Vietnam's Northern Uplands using an integrated regional-structural-functional framework. Results indicate that the existing AIS has six unique problems that are linked to seven blocking mechanisms, mainly belonging to three structural components: infrastructure, actors and institutions. Addressing these blocking mechanisms needs systemic instruments that help stimulate and balance investments, creating spaces for the development of actors' capability, and facilitating the institutional shift towards enabling region-oriented agriculture and demand-driven innovation processes. First, this study contributes an analysis of the integration of regional dimensions and technologies captured as a structural entity into the structural-functional framework, providing novel insights into the functioning of a regional AIS. Second, it deepens the literature on structural-functional innovation systems analysis by looking at the interconnections between structural and regional dimensions and how they create blocking mechanisms. It concludes that the regional-structural-functional analysis allows the design of integrated coherent sets of systemic instruments for a regional AIS.

32 show abstract
0308-521X * * 29873096
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Natalia Rosas-Ramos, Laura Baños-Picón, Valeria Trivellone, Marco Moretti, José Tormos, Josep D. Asís



The development of reliable evaluation schemes is essential to assess the status of biodiversity, particularly under the current scenario of biodiversity loss across agroecosystems. In these areas, ecological infrastructures contribute heavily to enhance biodiversity and underlying services, and their contribution depends on their ecological quality. Based on the questionnaire by Boller et al. (2004) for temperate areas, we propose a reliable tool for evaluating the ecological quality of woodland patches, hedges and grass strips associated with Mediterranean agroecosystems (simplified questionnaire). Since management practices and organism composition vary across geographical regions, the implementation of evaluation tools adapted to other geographical regions is deemed necessary. The development of the simplified questionnaire followed a five-steps' approach: (i) application of the Boller's questionnaire in the field; (ii) Boller's questionnaire adaptation; (iii) development of the simplified questionnaire through the assessment and simplification of Boller's questionnaire; (iv) evaluation of the simplified questionnaire effectiveness; (v) proposal of plant indicator species associated to the different quality levels obtained from applying the simplified questionnaire as an additional tool for quality assessment that complements such questionnaire. A total of 482 ecological infrastructures were evaluated in La Rioja (Spain) using the Boller's questionnaire, and their vegetation assessed by inventorying their floristic composition. We analyzed the relationship between plant species richness, as a proxy of the overall biodiversity, and the different items included in the Boller's questionnaire. According to these results, a new questionnaire was proposed, in which only variables significantly related to plant species richness were included. Our results showed that the quality groups established when applying our simplified questionnaire were more consistent than those obtained when using the Boller's questionnaire. Overall, 35 plant species resulted as significant indicators for the four levels of quality obtained from applying the simplified questionnaire. We point out that the assessment tool based on simplified questionnaire is straightforward and easy to apply by both experts and non-experts. We also propose the simplified questionnaire development procedure as a guide to create evaluation questionnaires adapted to other ecological infrastructure types.

33 show abstract
0308-521X * * 29912996
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Everton Alves Rodrigues Pinheiro, Quirijn de Jong van Lier, Jirka Šimůnek



The need for improvements in the water use efficiency by agricultural ecosystems requires a holistic assessment of the hydraulic functioning of cropped soils, taking into consideration the most relevant interactions and feedbacks that control the soil water budget. We implemented a mechanistic approach to isolate the effects of soil hydraulic properties (K-θ-h) of layered soils on water balance components and land and water productivity, adopting comprehensive scenarios of soil water availability and requirements. The agro-hydrological simulations were performed using the SWAP model integrated with the WOFOST crop growth module. The simulated scenarios included the rainfed crop growth of maize and soybean in three climate zones, evaluating the current climate scenarios as well as two future scenarios, a wetter and a drier one, totaling 108 scenarios simulated for 30 years each. Simulations were performed for six soils, grouped pairwise (3 × 2), where each pair represented the same soil group with two different long-term land uses: natural forest (proxy of a no-tillage system) and conventional agricultural use. The K-θ-h relationships were obtained simultaneously by inverse modeling for the full range of soil water contents commonly found in the domain of crop available water. The agro-hydrological simulations showed that the soil hydraulic properties affect dynamically water balance components and land productivity by relating soil hydraulic functioning to climate patterns and crop water requirements. In general, maize productivity was more sensitive to soil hydraulic properties under future climate scenarios than soybean. While land productivities of maize and soybean increased under the wetter climate scenario, water productivity of both crops was consistently reduced by both future climate scenarios. The K-θ-h of soils under conventional agricultural use over-performed their counterparts under long-term natural forest use, especially regarding land productivity during growing seasons with pronounced dry spells. Depending on the length and timing of drought stress during the growing season, the yield response is determined by soil-specific conditions strictly related to water availability. The long-term average revealed that the sampled loamy sand soils have more favorable hydraulic properties for crop growth; moreover, the reduced unproductive water losses, especially runoff, increased the dynamic water storage of those soils.

34 show abstract
0308-521X * * 29944608
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Eugene David Ungar



Carrying capacity is a fundamental concept in rangeland science and management; however, it is difficult to define, not least because it can be viewed from varied perspectives. With a view to facilitating debate, six perspectives (or definitions) of carrying capacity were formulated, representing: resource productivity; animal production; the system; animal welfare; the environment; and profit. To explore their implications semiquantitatively, Noy-Meir's simple, two-function model of a grazing system was used to simulate the annual herbage production cycle, during which a specified animal population density would be present year-round, except during an early-season grazing deferment of specified duration. The model was extended to calculate a metric for each definition of carrying capacity and then implemented for various combinations of the two key grazing-management-determined parameters: animal density and deferment duration. The metrics were mapped as a series of response surfaces. In general, grazing deferment at the start of the growth season can compensate for an increase in animal density. In other words, carrying capacity is, for most definitions, a contour line on a response surface; it divides the total space into “acceptable” and “unacceptable” regions of grazing-management practice. The contour lines that characterize the various carrying-capacity definitions can then be superimposed to examine the degree of overlap between “acceptable” regions. Two common rules-of-thumb for determining carrying capacity are examined by using this approach. The term “carrying capacity” is vague because it can address various concerns, but some of the most important concerns can be defined in reasonably precise terms and translated into quantitative metrics, based on the fundamental states and rates of a grazing system. Such an approach could facilitate dialogue among those concerned with the continuous refinement of carrying-capacity recommendations.

35 show abstract
0308-521X * * 29944609
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Thomas Böcker, Niklas Möhring, Robert Finger



Herbicide application in agricultural systems is currently critically discussed because of its possible adverse effects on the environment and human health. Currently, governments and food industry actors search for solutions to reduce herbicide use on farms. Yet, potential consequences of herbicide reductions on a farm-level are not well known. The goal of this article is to develop and apply a bio-economic modelling approach to simulate how farmers and agricultural systems react to a potential ban of glyphosate and eventually of all herbicides. We apply this approach for Swiss Extenso wheat production, which is a widespread form of wheat production in Switzerland, where pesticide use is currently limited to herbicides and seed treatments. Our modelling approach combines spatially explicit, detailed information on weed pressure, possible yield effects of weeds and efficacy and costs of 140 weed control strategies in a spatially explicit economic decision model. We assess the strategies optimal for farmers in response to i) glyphosate-free and ii) herbicide-free production requirements in terms of economic losses, yield reductions and environmental impacts. We find economic losses in the glyphosate-free production scenario of up to CHF 119/ha and in the herbicide-free scenario of up to CHF 192/ha, with respective yield reductions ranging between 0.8 and 2.7 dt/ha (i.e. of up to 6%). However, possible economic losses would be outweighed by existing Swiss agri-environmental direct payments for herbicide-free and reduced tillage production systems. We find that restrictions with respect to glyphosate and herbicide use imply trade-offs between the reduction in pesticide risks for the environment and human health versus higher energy consumption. Yet, these trade-offs can be limited if incentive schemes for glyphosate and herbicide reduction are combined with requirements to prevent more intensive tillage.

36 show abstract
0308-521X * * 29978540
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Charlotte Gerling, Astrid Sturm, Frank Wätzold



We applied an ecological-economic modelling procedure to analyse the impact of organic versus conventional management of meadows on endangered bird and butterfly species in Saxony, Germany. Applying the modelling procedure enables us to focus on two aspects that hitherto have been neglected in analysing the impact of organic farming on biodiversity. (1) Possible differences in the timing of land use between organic and conventional farming, and (2) differences in the uptake of agri-environment schemes (AES) by organic and conventional farmers. We found that for the species considered the difference in the impact of conventional and organic farming is minor, because in our case study region the timing of land use on most areas with organic farming is very similar to the timing on areas with conventional farming. We also found that in comparison with conventional farmers, organic farmers generally face lower opportunity costs when implementing AES measures. Additionally, organic farmers are offered lower payments for such measures. These factors influence organic farmers' decisions to take part in AES, which in turn has an important impact on biodiversity conservation. In order to better conserve species it may be necessary to adapt the payment structure of AES with respect to organic farming.

37 show abstract
0308-521X * * 30015485
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Tristan Senga Kiessé, Michael S. Corson, Maguy Eugène, Joël Aubin, Aurélie Wilfart



This study concerns variability in agrosystem inputs that affect greenhouse gas emissions at the farm scale, when management practices differ from average practices. Many studies of agrosystems assume average management practices. However, existence of a wide variety of farm-management practices may result in extreme variations in estimated environmental impacts. This large variation raises the need to use statistical tools to model extreme situations and their consequences on agrosystems. For instance, methane emissions generated by enteric fermentation in dairy cattle are particularly studied because they are important at a global scale. We investigated how extreme variations in feeding practices in dairy production affect predicted methane emissions, using a methane-emission model based on existing equations that is easy to apply at the farm scale. In this study, extreme variations in the time that cattle spent grazing were propagated through three different dairy-production systems. For an intensive dairy farm, predicted methane emissions decreased up to 15% (ca. 5% on average) and increased up to 11% (ca. 1% on average) under extremely long or short times spent grazing, respectively, compared to those from average variations in the time spent grazing. The range of variation in time spent grazing also reflects changes in feed rations. Farm-management practices require deep investigation to both evaluate and decrease risks of environmental impacts in dairy production.

38 show abstract
0308-521X * * 30015486
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): T. Petit, G. Martel, F. Vertès, S. Couvreur



Despite a constant decline in grassland areas between the 1970s and 2010 at the regional and national scale in France, in particular on lowlands, grasslands have been maintained locally. This raises questions about long-term changes on the farms involved in these dynamics, particularly with regard to the relation between the evolution of the role of grasslands in production processes, and farmers' perceptions of fodder systems within production systems. Our research concerned three peri-urban cantons in Brittany, where we examined grassland practices over the long term and farmers' perceptions of grasslands in a sample of 15 farms within the area where grasslands were maintained. First, we modelled pathways of the place and roles of grasslands on farms, based on criteria of quantitative presence, management, and valorisation. Second, we characterised the farmers' perceptions of grasslands and the fodder system. We then performed combined analysis of these pathways and perceptions. The maintenance of grasslands was found in a diversity of pathways in which grasslands were used to a medium and large extent in the fodder systems. These changes occurred either through a complete redesign of the fodder system or through hybridisation of practices aimed at obtaining dairy systems that were more intensive yet more agri-ecological. The pathways that gave a new place to grasslands in the fodder system were related to farmers' perceptions marked by a fading opposition between grasslands and maize farming. They attributed additional value – in terms of animal welfare, economics, or agronomy – to grasslands in a mixed maize/grassland fodder system.

39 show abstract
0308-521X * * 30041744
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): William Kaye-Blake, Chris Schilling, Ross Monaghan, Ronaldo Vibart, Samuel Dennis, Elizabeth Post



Nitrogen losses from agricultural are a key source of human impacts on the environment, and many countries have adopted policies to reduce nitrogen losses. Policy in New Zealand is being developed at the national and regional levels to address nitrogen losses and water quality. Several policy options were explored using a multi-agent simulation model of the Southland region of New Zealand in order to quantify the trade-off between the economic value of agricultural production and nitrogen losses from farming. It estimated the relative effectiveness and efficiency of alternative nitrogen mitigation policies while taking into account the heterogeneity of soil vulnerability to nitrogen leaching, land management options, and farmer behaviour. It used a hybrid modelling technique, assembling a multi-disciplinary model from outputs of other, specialised models, and using an agent-based approach to model land-use change. The policy options included uniform limits on nitrogen losses that applied across all farms, as well as differentiated policies that took into account either the propensity of a farm to leach nitrogen, past dairy conversion, or the type of land use. After 25 years, the impacts on dairy land area, nitrogen losses, agricultural production, and farm gross margin were compared with a baseline of no policy. The results suggested that policies worked better when they took account of the heterogeneity of agriculture practices and the environment. Those policies could be more effective at reducing nitrogen losses from farms, in term of the total mitigation in the region. They were also more efficient across the policies modelled: per kilogram of nitrogen mitigated, they produced the lowest economic costs. Choosing the right policy approach would be some combination of the absolute level of mitigation required, the historical patterns of land use, the variability of the absorptive capacity of the environment, the ability to spread the economic or environmental impacts across many farms and people, and the ability to specify required input or outputs. Most importantly, hybrid multi-agent simulation modelling provided a tool for examining the potential impacts of policies before they are implemented.

40 show abstract
0308-521X * * 30071210
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Efstratios Loizou, Christos Karelakis, Konstantinos Galanopoulos, Konstadinos Mattas



In any turbulent economic environment, sectors of economic activity behave and resist differently depending on the causes of the turbulence. Some sectors present a unique resistance in economic aberrations, have a resilient attitude and play the role of the stabilizer, supporting growth and employment. Such sectors are usually related with people basic needs; in the current economic crisis, the agriculture and food sector stand out. The present study endeavours to examine the potentials of agriculture in promoting an integrated development in a regional rural economy, through capturing and recording its interconnections with other sectors of economic activity. Input-Output analysis was applied along with the construction of a regional model intending to examine both the contribution of the primary sector in the regional economy, as well as the impact of the Common Agricultural Policy (CAP) reform on the entire local economy. By employing an analytical tool, it is demonstrated that the impact of the new CAP is not limited to the primary sector, but it - directly and indirectly affects other sectors, as well as the total output, employment and household income of the region. Results suggest that agriculture is an important driver of growth throughout the region, contributing to the increase of the local gross output by approximately €300mil. only by the inflow of funds, while 14% of it is diffused into sectors other than agriculture.

41 show abstract
0308-521X * * 30071211
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Jason West



Climate variability requires adaptive production systems in agriculture often resulting in significant irreversible investments. Cultivar replacement programs in horticulture orchards that substitute older varieties for more heat- and drought-resilient varieties have enterprise values that are highly sensitive to the timing of such investments. Farm-level replacement programs are subject to multiple constraints around debt serviceability, operating costs, the replacement cycle and the rate of degradation of the existing orchard. The maximization of enterprise value subject to multiple constraints can be reduced to a multi-objective optimization problem. Over long horizons this optimization process generates a very-large solution space. Using a multi-objective evolutionary algorithm we examine uncertainties around climatic effects and the timing of investments for horticultural operations and derive the optimal times to adapt using cultivar replacement techniques. We find that the investment decision using traditional valuation methods is suboptimal and can result in poor decisions, potentially undermining adaptation efforts. We further show that opposing economic and climatic conditions can adversely impact enterprise value based on mistiming the investment decision. Application of the genetic algorithm solver is demonstrated using a vector-based geographic information system to a farm where individual portions of an orchard are subject to varying rates of production, degradation and age.

42 show abstract
0308-521X * * 30125183
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Adam M. Komarek, Hoyoung Kwon, Beliyou Haile, Christian Thierfelder, Munyaradzi J. Mutenje, Carlo Azzarri



This study combined bottom-up and top-down approaches to assess the ex-ante effects of conservation agriculture (CA)-based systems in Zambia considering both biophysical and economic factors and prevailing farm systems characteristics. For continuous maize cropping we compared a CA-based system of no-tillage with crop residue retention to a control system of conventional tillage with crop residue removal. First, we simulated yield effects that were calibrated and evaluated against multiple datasets, including on-farm agronomic trials from two seasons and six sites. Next, we extrapolated our simulations to all maize-growing areas in Zambia using gridded climate and soil datasets. Then simulated yields (in kg ha−1) were combined with economic data from a nationally-representative household survey to construct economic indicators including benefit-cost ratios (based on gross benefits and variable costs both in $ ha−1) that captured the implicit value of crop residues and labor demands. The field scale (per ha) indicators were scaled out using harvested areas as an expansion factor. All indicators were calculated over 3-, 10-, and 20-year simulation periods using an interpolated sequence of historical climate data. Finally, we conducted a spatial farm typology analysis to help understand the spatial variation in our field-scale indicators and provide insights into trade-offs and the suitability of CA-based systems for farmers. Average changes in yield from using CA-based systems (compared with the control) at the district scale ranged from −37% to 70% (average 33%), with a similar range of changes in benefit-cost ratios once economic factors were included, in addition to intra-district yield variability. Combining the changes in benefit-cost ratios with maize harvested area resulted in an average annual change in district-scale net benefit ranging from US $ − 3.9 to US $9.9 million (with an average of US $1.1 million). The heterogeneity in biophysical and economic factors gave a ranking of provinces different according to biophysical or economic indicators, reinforcing the importance of coupling biophysical and economic approaches. The spatial farm typology analysis highlighted the specific contexts of farmers relevant to the suitability of CA, such as their mineral fertilizer applications rates, ownership of livestock, and prevailing soil texture and rainfall.

43 show abstract
0308-521X * * 30125184
Publication date: July 2019

Source: Agricultural Systems, Volume 173
Author(s): Davide Rizzo, Olivier Therond, Romain Lardy, Clément Murgue, Delphine Leenhardt



Land managers need spatially explicit information about agricultural practices to address issues that arise from the use of natural resources in agriculture. One main characteristic of agriculture is its great variability in space and time. However, describing the spatial distribution of “cropping systems”, i.e. crop sequences and crop management systems at the regional scale, remains a major scientific challenge. This study presents a new, simple and rapid approach to model the spatial distribution of irrigation management practices. It was developed in two large watersheds in southwestern France (about 1500 and 3000 km2). Based on a previous study consisting of 27 farmer interviews in a study area about one-sixth the size of these watersheds, we interviewed 12 key informants who had an integrative vision of the study area and spent only one-fourth as much time collecting and processing the relevant data. One major innovation was to combine knowledge from generic databases and ad-hoc intermediate objects, such as diagrams, tables and maps, to interact with the key informants. These objects helped them focus on specific local information that we had missed and facilitated data processing. Interview results were used to spatially allocate cropping systems formalized as dynamic IF-THEN decision rules. We evaluated our approach by using a cropping system model to simulate irrigation withdrawals over a ten-year period. Its predictions reproduced well annual amounts and inter-annual dynamics of irrigation water withdrawals recorded by the regional Water Agency. This approach, combining diagrams with IF-THEN rules, appears easy to adapt to study other areas and agricultural practices besides irrigation, as well as to manage annual and perennial crops.

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Impact

Journal Citation Reports (2017)

Impact factor: 3.004
Q1 (Agriculture, Multidisciplinary (3/56))

Scopus Journal Metrics (2017)

SJR: 1.156
SNIP: 1.601
Impact (Scopus CiteScore): 0.355
Quartile: Q1
CiteScore percentile: 97%
CiteScore rank: 9 out of 367
Cited by WUR staff: 1334 times. (2014-2016)

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