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3 | CRP | Golden Egg Title | Link | What is the compelling achievement and contribution? | Transmission target (who needs to hear about this?) | Possible category, potentially aligned to OneCGIAR research organization (e.g., Science Group, Impact Area, etc.) | ||||||||||||||||||||
4 | GENDER Platform | Incorporate gender norms and agency in R4D agenda/scope of social change/development/scaling/transformation-oriented programs and projects | https://gennovate.org/; https://doi.org/10.1080/09614524.2020.1757624 | GENNOVATE gender norms and agency methodology and multi-case study based findings can contribute to identifying social change pathways/Theories of Change. Evidence from GENNOVATE supported a powerful call for changing the way development researchers work to reach greater gender equity in agricultural innovations, | all SL | Gender Inclusion Impact Platform; select ST and RAFS initiatives and projects | ||||||||||||||||||||
5 | MAIZE | Remote sensing based tools: 1) Extrapolation Suitability Index (ESI) and Impact Based Spatial Targeting (IBSTI) tool, based on a set of biophysical and socioeconomic indicators 2) mapping and identification of climate change trends & 3) monitoring land degradation trends (land cover, land productivity, soil organic carbon) | https://cgiarcsi.community/2017/12/14/spatial-targeting-for-scaling-out-maize-technologies/; https://www.tandfonline.com/doi/full/10.1080/10106049.2017.1404144; https://www.sciencedirect.com/science/article/pii/S0264837716307062; https://link.springer.com/article/10.1007/s00704-018-2712-1; https://ieeexplore.ieee.org/document/9099395/; https://www.mdpi.com/2072-4292/13/9/1754 | 1) IBSTI is a priority setting tool used to identify areas with high potential scaling impact of specific technology options (varieties & agronomy). Using the tool in scaling programs reduced the risk of failure of technologies and helped extension & development agencies to rationalize investment given limited resources (pilot area: Tanzania).2) Identifies climate change hotspots to guide spatial targeting of appropriate climate smart technologies. Applied in East, Southern and West Africa. 3) Identifies land degradation hotspots at sub-national scale, to guide targeting of sustainable land management practices (to prevent, reduce or rehabilitate). More accurate than UNCCD-recommended standard. Tool supports tracking impact of implemented sustainable land management practices, over space and time (pilot region: Tanzania). | Researchers, government ministries, NGOs, extension agencies, development organizations, funders | Resilient Agrifood Systems, Systems Transformation | ||||||||||||||||||||
6 | MAIZE A4NH | Find active ingredients needed to develop Aflasafe products that mitigate aflatoxin contamination | https://doi.org/10.3389/fmicb.2019.02069 https://doi.org/10.1111/1751-7915.12324 https://doi.org/10.3390/agronomy10040491 | Over 100,000 Aspergillus isolates from 22 African countries have been evaluated, to develop active ingredients for aflatoxin biocontrol products under the tradename Aflasafe. So far, 64 atoxigenic strains of A. flavus have been registered as active ingredients for 14 Aflasafe products used in 10 countries. The isolates database and ingredient screening process allows for testing, registration and commercialization of new Aflasafe products. Further active ingredient identification continues for 12 African countries. Aflatoxin biocontrol is recognized as one of the 50 top innovations of CGIAR based on R&D work conducted for 20 years. | Broad (select all) | All Science Groups and Initiatives neded to bring in food system context and consider consumer demand (markets, value chains, health, trade, poverty reduction, nutrition) | ||||||||||||||||||||
7 | MAIZE | Approach (framework) to assess the sustainability of technologies for crop-livestock systems | Increasing population growth demands intensification of agricultural production. Assessing the sustainability of agricultural practices requires a comprehensive, multidisciplinary framework. University of Florida and Michigan State University in partnership with Africa RISING project developed the Sustainable Intensification Assessment Framework (SIAF), to assess the sustainability of agricultural technologies under five domains (productivity, economic, environment, human and social), at different scales. Africa RISING uses SIAF to assess the sustainability of cereal-legume-livestock systems in northern Ghana. The framework and recommendations could be used more widely. | Researchers, NGOs, Development partners, Government | Resilient Agrifood Systems, Systems Transformation | |||||||||||||||||||||
8 | WHEAT | Participatory approach involving farmers from the start of a breeding research cycle (participatory selection) with a focus on crop wild relatives-derived elite lines | https://foodtank.com/news/2019/08/selection-by-stone/; https://wiley.altmetric.com/details/89697268 | The integration on farmers in the breeding selection process (from planting candidate elite lines/varieties in farmers' fields to assessing taste/processing) has raised great interest and appreciation by many development agencies (Morocco, Ethiopia, Senegal, Lebanon; barely, lentil & durum wheat). | Development agencies | Resilient Agrifood Systems, Genetic innovations | ||||||||||||||||||||
9 | MAIZE WHEAT | New knowledge management framework for agri-food innovation systems (AKM4I) that addresses the need for more inclusive and environmentally sustainable food production systems. Strong linkage with Scaling Scan, IASI partner engagement approach. | https://www.cimmyt.org/news/a-knowledge-revolution/; https://doi.org/10.1080/14778238.2021.1884010 | Challenge: How to combine traditional knowledge with state-of-the-art scientific research; to meet regional needs for improvement in farming systems with knowledge networks fostering innovative practices and technologies that increase yields and profits sustainably. Solution: Agricultural Knowledge Management for Innovation (AKM4I) that addresses the need for more inclusive and environmentally sustainable food production systems. Following systems theory principles, the model empirically describes how information is created and shared, to advance farming knowledge and produce outcomes that contribute to: Building local capacities for developing joint problem-solving abilities ; empowering farmers with site-specific knowledge; co-creating technology et al; bridging innovation barriers to drive institutional change. | ST/National Policies Initiative; Regional Integrated Initiatives designers; Global Engagement & Innovation group; Scaling network/platform | Mainly SG-ST/RAFS, or a platform cutting across | ||||||||||||||||||||
10 | MAIZE WHEAT | Revolution in evolution; making 000's of years of evolution work for breeding. | https://doi.org/10.1101/706739 https://doi.org/10.1534/g3.116.029637 https://doi.org/10.1534/g3.120.401132 https://doi.org/10.1186/s12864-015-2345-z | Leveraging the extensive landrace germplasm characterisation of the Seeds of Discovery initiative we demonstrated and validated the potential of environmental GWAS in maize for novel allele discovery & landrace-based genomic predictions in wheat and maize for use in pre-breeding. Together, these approaches represent a paradigm shift in the search for, and application of novel genetic variation in landraces, for climate change relevant traits. Further piloting and scaling of these cost-effective approaches is warranted. | Researchers in CGIAR and outside, NGOs, International Agencies | Climate change adaptation & mitigation; Environmental Health; Biodiversity | ||||||||||||||||||||
11 | MAIZE WHEAT RTB | Scaling Scan: a tool to quickly understand what it takes to scale innovations in a specific context | https://repository.cimmyt.org/bitstream/handle/10883/20505/61173.pdf?sequence=1&isAllowed=y | User-friendly tool to facilitate discussion and develop capacity of scientists, partners and local stakeholders on what it takes to responsibly and sustainably scale innovations. It was developed together with SNV development organization, and is being used by Catholic Relief Services, GIZ and CGIAR institutes (CIMMYT, ILRI, ICARDA, IWMI especially). | Researchers in CGIAR and outside, NGOs, International Agencies and especially local partners who are asked to sustain scale | All groups who aim to bridge science and development for impact | ||||||||||||||||||||
12 | WHEAT | Pre-breeding research platform for testing and translating novel traits, allowing for accumulation of traits into elite wheat parents - linked to a global multi-location testing and adapted breeding network. | https://feedthefuture.globalinnovationexchange.org/innovation/international-nurseries-containing-wheat-lines-with-outstanding-expression-of-yield-potential-related-traits-and-adaptation-made-available-and-distributed-to-breeders-and-researchers-worldwide | IWYP Hub provides functional platform for testing and translating novel traits into elite wheat parents AND facilitates accumulation of traits that would not be possible in individual, separated research projects. Best lines are subsequently made available and validated by both public and private breeders through a network of partners and testing sites worldwide (IWIN). Hub brings together ideas from international network of plant experts who conduct research on different aspects of crop science, which generates a synergy of ideas and research technologies for application in physiological pre-breeding. | GI-Initiatives design teams, in particular Accelerating Breeding & Accelerating crop improvement. | SG-GI | ||||||||||||||||||||
13 | WHEAT | Long-term investment in core breeding operations (incl continuous improvements, maintaining NARS networks etc) 'keeps all the alleles together', a critical foundation for more short-term, projectized breeding profile-driven activities. | https://doi.org/10.1016/j.fcr.2020.107742; https://marlo.cgiar.org/projects/Wheat/studySummary.do?studyID=4031&cycle=Reporting&year=2020 | Significant contribution to global average yield growth rates over decades: The resulting genetic gains impact ca. 61 million hectares on which farmers grow CGIAR-derived varieties, on a 215 million ha total global wheat area | CGIAR funders of breeding research, major NARS breeding research partners | Nutrition, Health and Food Security; Genetic Innovation | ||||||||||||||||||||
14 | MAIZE | Climate-resilient, tropical stress-resistant maize: Improved varieties faster on farmers' fields, more frequently thanks to seed systems innovations: International Maize Improvement Consortia (IMIC) & faster national variety release cycles | https://marlo.cgiar.org/projects/Maize/studySummary.do?studyID=3321&cycle=Reporting&year=2019;https://marlo.cgiar.org/projects/Maize/studySummary.do?studyID=4003&cycle=Reporting&year=2020 | More small and medium size seed companies get involved in breeding, release new varieties, increasing total high quality seeds volume. More availability and choice for farmers. Indirect positive effect on farmer variety replacement rates. | GI-Initiatives design teams, CGIAR Partnerships & Advocacy unit, NARS policy-makers responsible for seed markets | Nutrition, Health and Food Security; Genetic Innovation | ||||||||||||||||||||
15 | WHEAT | Planting time is critical! How to enable farmers to plant at the right time, again and again | https://www.sciencedirect.com/science/article/abs/pii/S0308521X19305372 | Early sowing of wheat supports climate change adaptation. High-yielding wheat varieties with early heat stress tolerance enabled farmers of North India to advance sowing by two weeks. | CGIAR integrated regional initiatives, RAFS Initiatives | RAFS and GI; Nutrition, Health & Food Security & Climate Adaptation | ||||||||||||||||||||
16 | MAIZE WHEAT | Community-based approaches (cba) to Climate-Smart Agriculture - vulnerability assessments and scaling approaches: Enable farming communities to produce their food in a more sustainable and biodiversity-friendly manner, making their livelihoods and surrounding landscapes and ecosystems more climate-resilient - | https://repository.cimmyt.org/handle/10883/20128; https://repository.cimmyt.org/handle/10883/20129 | Smallholder farmers in cereal-legume cropping systems produce up to 70% of national cereal requirements in the three countries in southern Africa. Challenge ahead: Growing cereal-legume systems taking a more sustainable land-scape approach could support reclaiming degraded lands & increasing biodiversity in the landscape, while maintaining core production functions. Previous agricultural intensification and biodiversity conservation efforts remained isolated and ad hoc. | Systems Transformation Initiative designers | SI; Climate change adaptation & Environmental Health and biodiversity | ||||||||||||||||||||
17 | MAIZE WHEAT | N-cycle in Agriculture transformation: Biological nitrification inhibition (BNI) as a genetic and agronomic mitigation pathway | https://doi.org/10.1016/j.plantsci.2017.05.004 | BNI-sorghum, -wheat, bracharia-maize rotation at validation stage. Larger aim: Keep a higher share of soil N as ammonium and select and breed crops to exploit an ammonium/nitrate balance. Great majority of N losses occur after microbial reactions have transformed ammonium in soils into nitrate. Once BNI root trait bred into crops, farmers can adopt them without added expense or major changes in management. BNIs can comprise a cocktail of phytochemicals inhibiting nitrifying bacteria in multiple ways and may be able to persist in soils and suppress nitrification year-round. | ST initiative designers; GI initiative designers (currently no pre-breeding Initiative on the table) | Climate change adaptation & mitigation; Environmental Health | ||||||||||||||||||||
18 | MAIZE WHEAT | Remote-sensing-based innovations for targeting, prioritising and impact assessment & integration of remote sensing and machine learning: Sustainable Intensification, Agronomy, Management-based practices | https://doi.org/10.1007/s13593-020-0610-2; 10.1038/s41893-019-0396-x; https://marlo.cgiar.org/summaries/Maize/projectInnovationSummary.do?innovationID=1999&phaseID=153; | Estimates adoption and impacts of farm/agronomic practices in developing countries using satellite data Remote sensing-based tool to assess nitrogen levels in farmers’ fields, to support farmers' stover + fertilizer use/management Microsatellite data to detect the impact of sustainable intensification interventions at large scales and to target the fields that would benefit the most, thereby doubling yield gains. Helps identify where and when conservation agricultural practices confers yield gain over conventional tillage praces in Southern Africa. | CGIAR, ISDC, SPIA ex ante and ex post impact assessment staff; CGIAR proposal development/feasibility experts | ST or RAFS | ||||||||||||||||||||
19 | MAIZE WHEAT | Cereal systems, agro-forestry and forest interactions at different scales: Researchable issues, analytical frameworks (e.g. avoid new silos in CGIAR Initiatives portfolio) | https://doi.org/10.1016/j.agee.2020.106888; https://doi.org/10.1017/S0014479718000297; https://doi.org/10.3389/fsufs.2019.00097; https://www.altmetric.com/details/54786924; https://doi.org/10.1016/j.gfs.2019.100331 | Landscape approaches: Contrasting of forest restoration scenarios, explore whether there are ideal configurations of forests that optimize benefits for food production. Interaction suitable varieties & agroforestry: farmers could benefit from growing hybrids in the equatorial savannahs of Rwanda. Choice between hybrid and OPV in Ethiopia simply a matter of seed costs and availability. Biodiversity and nutrition. “Forest pattern, not just amount, influences the dietary quality in five African countries,” providing further evidence that land sparing may be the best land use model for biodiversity, but not for people’s nutrition in rural areas (here fruits). Assessment of links between forest cover and dietary diversity in 7 countries (Bangladesh, Africa). How agricultural landscapes can best serve multiple purposes - maintain agricultural productivity, conserve biodiversity: human benefits and conservation values along a forest-agriculture gradient in Southern Ethiopia | ST initiative designers; CGIAR Impact Area Platform teams; non-CGIAR partners working on forestry, agro-forestry, agro-biodiversity | Not sure. Either ST or an Impact Area Platform? | ||||||||||||||||||||
20 | MAIZE WHEAT | Interactions between soil quality, health, carbon sequestration rates & management practices: The need for long-term trials, multi-location networks and comparable standards | https://doi.org/10.1007/s12665-019-8305-1; https://doi.org/10.3390/agronomy10070962; https://doi.org/10.1017/S0014479720000125; https://doi.org/10.1017/S002185961900073X; https://doi.org/10.1016/j.still.2018.02.015; https://doi.org/10.1016/j.eja.2017.08.006 | Range of long-term trials in Mexico (s. 1991), India (6 years), Malawi (s 2007), plus more short-term interventions generate important learnings about the impact of management practices on soil health/quality and SOC. | ST & RAFS Initiative designers; Science Group as a whole, re: research station network, quality of operations | ST or RAFS | ||||||||||||||||||||
21 | MAIZE WHEAT | Partner/Stakeholder engagement approaches: Integrated Agri-food Systems Initiative (IASI), building on MasAgro (2011-2020), piloted in Colombia and Mexico | MELIA S4023 / MAIZE 2020 = https://marlo.cgiar.org/projects/Maize/study.do?expectedID=4023&edit=true&phaseID=153 | Further develop and document the Integrated Agri-food Systems Initiative (IASI) approach, based on Maize for Mexico and Maize for Columbia stakeholder engagement experiences …. . Culminates in collectively agreed strategies and multi-partner tactical plans, fosters mindset shifts and stakeholder consensus on sustainable and scalable innovations that respond to real dynamics in complex agri-food systems. Paper to be published in 2021. | CGIAR regional integrated initiatives; Global Engagement & Innovation group; Science Group program management unit | Science & Global Engagement Groups cross-cutting | ||||||||||||||||||||
22 | MAIZE WHEAT | Partnership approaches (in-project) and scaling: Innovation Platforms | https://doi.org/10.1017/S0014479718000200 | Investigation about the purposes and conditions under which innovation platforms can contribute to achieving agricultural development outcomes. Could be developed further. | Regional Integrated Initiatives designers; Global Engagement & Innovation group ?? | cross-cutting for all development-/scaling-oriented Initiatives | ||||||||||||||||||||
23 | MAIZE, RTB | Integrating innovative measurement approaches in assessing the impact of CGIAR investments on 2030 UN SDG1. | https://doi.org/10.1016/j.worlddev.2019.104631; http://dx.doi.org/10.1016/j.jenvman.2017.06.058; http://dx.doi.org/10.1016/j.foodpol.2019.101742; https://doi.org/10.1016/j.worlddev.2019.05.027; https://doi.org/10.1111/1477-9552.12296; | The ultimate goal of CGIAR is to show contributions to the UN 2030 SDG. CGIAR R4D has suffered a lack of rigourous approaches to measure ultimate CGIAR impacts on SDG1. New approaches were tested and proved effective in closing this gap: Estimation of poverty effects of agricultural technologies in a partial equilibruim framework based on counterfactual analysis. | Researchers in CGIAR and beyond, Development partners | All Science Groups | ||||||||||||||||||||
24 | MAIZE | Integrated disease and pest management toolbox for maize agri-food systems, including diagnostics and surveillance methods, resistant/tolerant varieties, and other eco-friendly tactics for sustainable control of major threats (e.g., MLN in Africa; FAW in Africa and Asia) | TBD | Researchers in CGIAR and beyond, Development partners | GI & RAFS; Global Plant Health Initiative | |||||||||||||||||||||
25 | MAIZE | Nutritionally enriched maize varieties (we included climate resilient maize, but not this) for improving the nutritional well-being of maize-dependent populations in SSA, LatAm and Asia. | TBD | Researchers in CGIAR and beyond, Development partners | GI, though linkage with RAFS/ST-based Initiatives focusing on improved nutrition will be important | |||||||||||||||||||||
26 | MAIZE | A toolbox of novel technologies/approaches to accelerate genetic gains in maize, including tropicalized doubled haploidy, high-throughput phenotyping, genomics-assisted breeding, and breeding data management system. | TBD | Researchers in CGIAR and beyond, Development partners | GI | |||||||||||||||||||||
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