CGIAR modeling approaches for resource constrained scenarios: IV Models for analyzing socio‐economic factors to improve policy recommendations

International crop-related research as conducted by the CGIAR uses crop modelingfor a variety of purposes. By linking crop models with economic models andapproaches, crop model outputs can be effectively used as inputs into socioeco-nomic modeling efforts for priority setting and policy advice using ex-ante impactassessment of technologies and scenario analysis. This requires interdisciplinarycollaboration and very often collaboration across a variety of research organizations.This study highlights the key topics, purposes, and approaches of socioeconomicanalysis within the CGIAR related to cropping systems. Although each CGIARcenter has a different mission, all CGIAR centers share a common strategy of strivingtoward a world free of hunger, poverty, and environmental degradation. This meansresearch is mostly focused toward resource-constrained smallholder farmers. Thereview covers global modeling efforts using the IMPACT model to farm householdbio-economic models for assessing the potential impact of new technologies onfarming systems and livelihoods. Although the CGIAR addresses all aspects of foodsystems, the focus of this review is on crop commodities and the economic analysislinked to crop-growth model results. This study, while not a comprehensive review,provides insights into the richness of the socioeconomic modeling endeavors withinthe CGIAR. The study highlights the need for interdisciplinary approaches to addressthe challenges this type of modeling faces

Hydroponics Research Trends: A Review and Bibliometric Analysis (2008- 2018)

Hydroponic as a concept is characterized by complexity. It has long been used to grow plants, largely vegetables. On the one hand, the concept is challenging in terms of content, but it is also a multidimensional and cross-disciplinary research domain.Based on a bibliometric analysis, the purpose of this descriptive paper is to provide a macroscopic overview of the main characteristics of hydroponics publicationsbetween 2008 and 2018.The data for this study was obtained from Scopus' bibliometric database.According to the study findings, there have been 2013 scholarly publications over an 11-year period, with an average of about 183 publications per year.China, Japan, United State and Iran stand as the dominant position in Hydroponics research. Furthermore, Acta Horticulturae is the leading Journal publishing on Hydroponic research. Key authors were Pardossi, Alberto and Rodrigues, Fabrício Ávila. Chinese Academy Sciences is the productive institution/Affiliation with a total of 78 publication in this domain. It can be concluded that there is need for much more research on Hydroponic and related areas. Keywords: Hydroponics,Growing medium, Soilless cultivation, Tren

Conceptual Framework for Managing Uncertainty in a Collaborative Agri-Food Supply Chain Context

[EN] Agri-food supply chains are subjected to many sources of uncertainty. If these uncertainties are not managed properly, they can have a negative impact on the agri-food supply chain (AFSC) performance, its customers, and the environment. In this sense, collaboration is proposed as a possible solution to reduce it. For that, a conceptual framework (CF) for managing uncertainty in a collaborative context is proposed. In this context, this paper seeks to answer the following research questions: What are the existing uncertainty sources in the AFSCs? Can collaboration be used to reduce the uncertainty of AFSCs? Which elements can integrate a CF for managing uncertainty in a collaborative AFSC? The CF proposal is applied to the weather source of uncertainty in order to show its applicability.The first author acknowledges the partial support of the Program of Formation of University Professors of the Spanish Ministry of Education, Culture, and Sport (FPU15/03595). The other authors acknowledge the partial support of the Project 691249, RUC-APS: Enhancing and implementing Knowledge based ICT solutions within high Risk and Uncertain Conditions for Agriculture Production Systems, funded by the EU under its funding scheme H2020-MSCA-RISE-2015.Esteso-Álvarez, A.; Alemany Díaz, MDM.; Ortiz Bas, Á. (2017). Conceptual Framework for Managing Uncertainty in a Collaborative Agri-Food Supply Chain Context. IFIP Advances in Information and Communication Technology. 506:715-724. https://doi.org/10.1007/978-3-319-65151-4_64S715724506Taylor, D.H., Fearne, A.: Towards a framework for improvement in the management of demand in agri-food supply chains. Supply Chain Manag. Int. J. 11, 379–384 (2006)Matopoulos, A., Vlachopoulou, M., Manthou, V., Manos, B.: A conceptual framework for supply chain collaboration: empirical evidence from the agri-food industry. Supply Chain Manag. Int. J. 12, 177–186 (2007)Ahumada, O., Villalobos, J.R.: Application of planning models in the agri-food supply chain: a review. Eur. J. Oper. Res. 196, 1–20 (2009)Tsolakis, N.K., Keramydas, C.A., Toka, A.K., Aidonis, D.A., Iakovou, E.T.: Agrifood supply chain management: a comprehensive hierarchical decision-making framework and a critical taxonomy. Biosyst. Eng. 120, 47–64 (2014)van der Vorst, J.G., Da Silva, C.A., Trienekens, J.H.: Agro-industrial supply chain management: Concepts and applications. FAO (2007)Borodin, V., Bourtembourg, J., Hnaien, F., Kabadie, N.: Handling uncertainty in agricultural supply chain management: a state of the art. Eur. J. Oper. Res. 254, 348–359 (2016)van der Vorst, J.G.A.J., Beulens, A.J.M.: Identifying sources of uncertainty to generate supply chain redesign strategies. Int. J. Phys. Distrib. Logist. Manag. 32, 409–430 (2000)Klosa, E.: A concept of models for supply chain speculative risk analysis and management. J. Econ. Manag. 12, 45–59 (2013)Samson, S., Reneke, J.A., Wiecek, M.M.: A review of different perspectices on uncertainty and risk and an alternative modeling paradigm. Reliab. Eng. Syst. Saf. 94, 558–567 (2009)Backus, G.B.C., Eidman, V.R., Dijkhuizen, A.A.: Farm decision making under risk and uncertainty. Neth. J. Agric. Sci. 45, 307–328 (1997)van der Vorst, J.G.: Effective food supply chains; Generating, modelling and evaluating supply chain scenarios. (2000)Amorim, P., Günther, H.O., Almada-Lobo, B.: Multi-objective integrated production and distribution planning of perishable products. Int. J. Prod. Econ. 138, 89–101 (2012)Amorim, P., Meyr, H., Almeder, C., Almada-Lobo, B.: Managing perishability in production-distribution planning: a discussion and review. Flex. Serv. Manuf. 25, 389–413 (2013)Costa, C., Antonucci, F., Pallottino, F., Aguzzi, J., Sarria, D., Menesatti, P.: A review on agri-food supply chain traceability by means of RFID technology. Food Bioprocess Technol. 6, 353–366 (2013)Pahl, J., Voss, S.: Integrating deterioration and lifetime constraints in production and supply chain planning: a survey. Eur. J. Oper. Res. 238, 654–674 (2014)Grillo, H., Alemany, M.M.E., Ortiz, A.: A review of Mathematical models for supporting the order promising process under Lack of Homogeneity in product and other sources of uncertainty. Comput. Ind. Eng. 91, 239–261 (2016)Zwietering, M.H., van’t Riet, K.: Modelling of the quality of food: optimization of a cooling chain. In: Management Studies and the Agri-business: Management of Agri-chains, Wageningen, The Netherlands, pp. 108–117 (1994)Akkerman, R., Farahani, P., Grunow, M.: Quality, safety and sustainability in food distribution: a review of quantitative operations management approaches and challenges. Spectrum 32, 863–904 (2010)Apaiah, R.K., Hendrix, E.M.T., Meerdink, G., Linnemann, A.R.: Qualitative methodology for efficient food chain design. Trends Food Sci. Technol. 16, 204–214 (2005)Lehmann, R.J., Reiche, R., Schiefer, G.: Future internet and the agri-food sector: State-of-the-art in literature and research. Comput. Electron. Agric. 89, 158–174 (2012)Kusumastuti, R.D., van Donk, D.P., Teunter, R.: Crop-related harvesting and processing planning: a review. Int. J. Prod. Econ. 174, 76–92 (2016)Dreyer, H.C., Strandhagen, J.O., Hvolby, H.H., Romsdal, A., Alfnes, E.: Supply chain strategies for speciality foods: a Norwegian case study. Prod. Plan. Control 27, 878–893 (2016)Baghalian, A., Rezapour, S., Farahani, R.Z.: Robust supply chain network design with service level against disruptions and demand uncertainties: a real-life case. Eur. J. Oper. Res. 227, 199–215 (2013)Aggarwal, S., Srivastava, M.K.: Towards a grounded view of collaboration in Indian agri-food supply chains: a qualitative investigation. Br. Food J. 115, 1085–1106 (2016)Teimoury, E., Nedaei, H., Ansari, S., Sabbaghi, M.: A multi-objective analysis for import quota policy making in a perishable fruit and vegetable supply chain: a system dynamics approach. Comput. Electron. Agric. 93, 37–45 (2013)Opara, L.U.: Traceability in agriculture and food supply chain: a review of basic concepts, technological implications, and future prospects. J. Food Agric. Environ. 1, 101–106 (2003)Kruize, J.W., Wolfert, S., Goense, D., Scholten, H., Beulens, A., Veenstra, T.: Integrating ICT applications for farm business collaboration processes using Fl Space. In: 2014 Annual SRII Global Conference, pp. 232–240. IEEE (2014)Oriade, C.A., Dillon, C.R.: Developments in biophysical and bioeconomic simulation of agricultural systems: a review. Agric. Econ. 17, 45–58 (1997)Camarinha-Matos, L.M., Afsarmanesh, H.: Collaborative networks: value creation in a knowledge society. In: Wang, Kesheng, Kovacs, G.L., Wozny, Michael, Fang, Minglun (eds.) PROLAMAT 2006. IIFIP, vol. 207, pp. 26–40. Springer, Boston, MA (2006). doi: 10.1007/0-387-34403-9_4Prima Dania, W.A., Xing, K., Amer, Y.: Collaboration and sustainable agri-food supply chain: a literature review. MATEC Web Conf. 58 (2016)Simatupang, T.M., Sridharan, R.: The collaborative index: a measure for supply chain collaboration. Int. J. Phys. Distrib. Logist. Manag. 35, 44–62 (2005)Fischer, C., Hartmann, M., Reynolds, N., Leat, P., Revoredo-Giha, C., Henchion, M., Albisu, L.M., Gracia, A.: Factors influencing contractual choice and sustainable relationships in European agri-food supply chains. Eur. Rev. Agric. Econ. 36, 541–569 (2009

Stochastic Dominance Analysis of Soil and Water Conservation in Subsistence Crop Production in the Eastern Ethiopian Highlands: The Case of the Hunde-Lafto Area

The aim of this paper is to analyze whether investment in soil and water conservation results in a higher yield and income and/or mitigate variability in yield and income to subsistence farm households in the Hunde-Lafto area. Net returns from crop production with and without soil and water conservation (SWC) are compared based on stochastic dominance (SD) criteria. A non-parametric first order SD and normalized second order are used for data analysis. Analysis is based on the Soil Conservation Research Program (SCRP) database for the Hunde-Lafto research unit. The results of the analysis suggest that adopting a conservation strategy results in higher grain yield and net return than in not adopting. The normalized second order SD analysis results do not support the hypothesis that conservation strategy is unambiguously better than a noconservation strategy in reducing variability in yield and net return to farmers. However, conservation strategy has shown second order dominance at lower levels of yield and income that often correspond to unfavorable rainfall conditions. This makes it a preferred strategy to cope with the most prevalent risk factor of moisture shortage. Therefore, appropriate policies to help and encourage farmers to adopt SWC structures will contribute to improving the welfare of subsistence farm households in the study area and in other similar settings in the country. Designing and implementing SWC techniques that may result in unambiguous second order SD dominance will further improve the desirability and adoption of conservation measures. Copyright Springer 2005erosion, Ethiopia, net return, soil and water conservation, stochastic dominance, Q24, renewable resources and conservation,

Regional network governance and sustainable tourism

Effective governance has been identified as one of the most important factors in sustainable tourism implementation. As governance structures are increasingly becoming network-based, attention needs to be diverted to the effectiveness of partnerships in achieving sustainability in tourism. Evaluating the effectiveness of regional tourism governance in Cyprus by considering regional tourism organisations’ (RTOs) public–private network involved exploratory research whereby semi-structured interviews with key tourism stakeholders were performed. Findings reveal that network governance-related challenges interact with region-specific characteristics, inhibiting the effectiveness of regional tourism governance in implementing sustainable tourism. Specifically, RTOs represent a weak form of governance and their effectiveness in implementing sustainable tourism is limited by the continuing dependence on foreign tour operators, a system of mutual favours which complexifies the nature of tourism planning and a growing emphasis on economic interests further fuelled by recent austerity measures imposed in Cyprus. The paper concludes that network governance cannot be considered separately from the socio-cultural, economic and environmental factors of the context in which it is studied and proposes that further research reflects the horizontal relations across regional, national and global networks

On the Use of Agricultural System Models for Exploring Technological Innovations Across Scales in Africa: A Critical Review

The major challenge of the 21st century is to achieve food security under, roughly, a doubling in food demand by 2050 compared to present, and producing the additional food under marked shifts in climatic risks and with environmentally sound farming practices. Sustainable intensification of agricultural production is required that meets the dual goal of improved environmental sustainability and economic efficiency. Ex ante evaluation of technological innovations to support agricultural production and food security taking into account the various future risks can substantially contribute to achieve this. Here we perceive technological innovations as new or improved agro-technologies and –management practices, such as new breeds, integrated soil fertility practices or labour-saving technologies meeting the goals of sustainable intensification. In this report we present results from three systematic reviews: one on the use of biophysical modelling, the second and third on the use of bio-economic modelling at farm scale and agro-economic modelling at higher aggregation levels, for ex ante evaluation of the effects of (agro ) Technological Innovations (ag-TIs) on sustainable agriculture and food security indicators. To this end, we searched the SCOPUS database for journal articles published between 1996 and 2015. We considered modelling studies at different spatial scales with particular attention to local to national scale studies for the twelve PARI focal countries in Africa . But we also included studies for all other African countries as well as a few studies at supra-national/continental scale. Both, “quick wins” as well as long term benefits from ag-TIs were of interest. The various ag-TIs were furthermore grouped into four classes: (1) water/soil moisture (2) soil nutrients/conservation (3) crop/cropping system, (4) other ag-TIs or (5) combinations of 1 to 4. For each paper, we tried to identify the primary ag-TI analysed, and if there was equal emphasis to more than one, we classified them as combinations. It should be borne in mind that there is some subjectivity in classifying the papers in this way. Results. After various steps of refining “search strings”, screening on relevance and supplementing databases from additional sources, we found 140 relevant biophysical modelling studies, whereby coverage of sub-regions and ag-TIs varied markedly. Most studies were found for East and West Africa, followed by Southern Africa; hardly anything was found for Northern and Middle Africa . A similar pattern appeared for the integrated agro-economic modelling studies at farm scale, for which we found 40 relevant ones. Agro-economic modelling studies at higher aggregation levels showed a somewhat different pattern – and more generally contained little detail on technological innovations. Regarding the share of different primary agro-technologies explored in the biophysical studies we found 45 on crop management, 35 on combined agro-technologies, 31 on soil nutrient management and conservation, 23 on water/soil moisture management, and 6 on other technologies. We found similar shares among the various agro-technology groups for the integrated agro-economic modelling studies at farm scale. Looking at the outcomes from ex ante evaluations we found that many studies are (mostly) positive on effects of single and “conventional” ag-Tis. The majority of biophysical studies is performed at “field scale” and focuses on the effects on productivity (sometimes yield stability); many of these studies were performed in climate variability and change /adaptation research context. Most agro-economic modelling studies that look specifically at ex ante evaluations of ag-TIs are performed at farm or regional (sub-national) scales. While the number of biophysically oriented studies has grown exponentially over the considered period 1996-2015, this is not the case for the agro-economic modelling studies. Looking in more detail at the twelve focal countries of PARI (=Programme of Accompanying Research on Agricultural Innovations) we also find an unbalanced distribution, with most studies found in Kenya, Ethiopia, Mali and Ghana (biophysical modelling studies), and respectively in Kenya and Uganda (agro-economic modelling studies), whereas nothing or little was found for both types of studies in Togo, Zambia and Nigeria. Very few of the biophysically-oriented studies include other information than effects on crop yields, and there are few studies for both biophysical and agro-economic modelling that comprise multi-scale or higher scale analyses; if multi-scale, there are more studies that scale up from field/farm to regional/sub-national level than from field/farm to nation scale or beyond. There is definitely a need to overcome the lack of meaningful integrated multi-scale modelling along the lines proposed in chapters 5-6 of this report. Moreover, less than half of all integrated /agro-economic modelling studies at farm scale explicitly address risk – another clear shortcoming, which requires attention by the research community. A more general conclusion is that there is no application yet of true transdisciplinary research approaches in practice. Hence, there is need for participatory, collaborative (cross-sectoral) and combined modelling approaches with adequate stakeholder involvement throughout the research process. In this respect, some lessons might be learned from pioneering work conducted in Asia and Europe