CONTEXTUnderstanding research collaboration in diverse scientific communities is key to building global agricultural research systems that support the UN Sustainable Development Goals. Characterizing collaboration patterns can inform decisions to enhance the structure and dynamics of research programs.OBJECTIVEWe introduce a new analytic framework for evaluating collaborative research networks based on scientific publications, and an associated conceptual framework for the role of research networks in achieving societal goals. We analyzed two CGIAR Research Programs: Grain Legumes and Dryland Cereals (GLDC) and Roots, Tubers and Bananas (RTB). The analysis provides a multi-dimensional perspective on a set of key questions related to research team composition, research management structures, and performance of scientific publications.METHODSWe quantified network structures of research collaborations at the level of authors, institutions, countries, and management structures, including use of temporal exponential random graph models. We used regression models to understand the associations between the characteristics of authors and publications, and the corresponding citation rates and Altmetric Attention Scores.RESULTS AND CONCLUSIONSWe identified key network hubs in the collaboration networks of both CGIAR programs. The proportion of women as authors in publications was less than a third, with a low likelihood of co-authorship between women. Institutional hubs were identified by institutional categories; these were often institutions that are considered CGIAR program “participants”, and a few were “planning partners”. For both GLDC and RTB, the countries that were the focus of most research coincided with the program's priority countries. Most international collaborations occurred between institutions headquartered in Global South countries, but most intercontinental collaborations occurred between Global South and Global North countries. Most institution and author co-authorships occurred in only one year and rarely lasted two or three consecutive years. High diversity in the geographic affiliations of authors, along with highly collaborative teams, as opposed to simply the number of authors, consistently were associated with more citations and higher Altmetric Attention Scores.SIGNIFICANCEThese analyses reveal key structures in research collaboration networks in GLDC and RTB research programs, with potential to guide agricultural research systems for sustainable development. Considering these outcomes from past research management can help scientists, program managers, and funders increase the success of new research projects. Specifically, future research management strategies need to fortify existing scientific capacity and development through gender parity and balanced international collaborations, working toward more impactful publications and increased development relevance, while team size increases over time.

AbstractCassava is an important crop in sub-Saharan Africa for food security, income generation, and industrial development. Business-oriented production systems require reliable supplies of high-quality seed. Major initiatives in Nigeria and Tanzania have sought to establish sustainable cassava seed systems. These include the deployment of new technologies for early generation seed (EGS) production; the promotion of new high-yielding and disease-resistant varieties; the updating of government seed policy to facilitate enabling certification guidelines; the application of ICT tools, Seed Tracker and Nuru AI, to simplify seed system management; and the establishment of networks of cassava seed entrepreneurs (CSEs). CSEs have been able to make profits in both Nigeria (US$ 551–988/ha) and Tanzania (US$ 1,000 1,500/ha). In Nigeria, the critical demand driver for cassava seed businesses is the provision of new varieties. Contrastingly, in Tanzania, high incidences of cassava brown streak disease mean that there is a strong demand for the provision of healthy seed that has been certified by regulators. These models for sustainable cassava seed system development offer great promise for scaling to other cassava-producing countries in Africa where there is strong government support for the commercialization of the cassava sector.

CONTEXT: Given the significance of climate change impacts on farming communities, large investments are made by research and development actors, including farmers themselves, to adapt agricultural systems. A data -driven approach is required to guide these investments and maximize their impact. In the African Great Lakes Region (GLR), root, tuber and banana (RT&B) crops are a vital component of smallholder farming systems, but little is known about strategies to mitigate climate change impacts on these crops.OBJECTIVE: The objective of this study was to develop a spatial prioritisation and targeting framework based on the risk of climate-related impacts to guide research investments and prioritisation in CSA for RT&B crops in the GLR.METHODS: Climate change impact data on crop suitability were layered onto other spatially-explicit biophysical and socio-economic data to map clusters of homologous regions, called socio-agroeocological homologues (SAHs). The SAHs were defined by the risk of climate-related impacts, resulting from the interaction of hazards,exposure and vulnerability. The framework was applied to RT&B crops (banana, potato, cassava and sweet -potato) in the African GLR. Its utility was illustrated by elaborating adaptation scenarios for selected SAHs of one long-duration (banana) and one short-duration (potato) RT&B crop.RESULTS AND CONCLUSION: Four SAHs were identified for banana, potato and sweetpotato and five for cassava. For each crop, SAHs were prioritised for investment in climate change adaptation based on the level of risk of climate-related impacts. Scenario analysis showed that the introduction of drought-tolerant varieties would in-crease suitability for banana from 0.30 to 0.47 under baseline conditions and from 0.54 to 0.71 under future climates in a prioritised SAH with low to moderate suitability for typical varieties. For potato, the introduction of heat-tolerant genotypes, intercropping with legumes or the combination of both would allow compensating negative impacts of climate change on crop suitability in two SAHs representing important mid-altitude potato growing areas, from an average of-0.19 and-0.16 to an average of up to +0.25 and + 0.15 respectively. Scaling approaches should consider the difference in socio-economic conditions between the two SAHs.SIGNIFICANCE: We envision the framework to be useful for a diverse range of users throughout the innovation and scaling continuum to understand where climate change impacts are expected to be most severe, what type of innovations are needed to help farmers adapt, and how these innovations should be scaled to enable uptake by considering socio-economic drivers of adoption.

AbstractCollaborative programs that facilitate innovation to deliver value at scale require attention to effective program design, management, governance, and leadership. The CGIAR has experimented with different collaborative program design options over its 50-year history, most recently with the CGIAR Research Programs (CRPs) implemented from 2012 to 2021. This chapter examines the structure and processes of the CGIAR Research Program on Roots, Tubers and Bananas (RTB). It unpacks the constituent institutional innovations that underpinned the RTB program, their key design principles, how they evolved over the 10 years of the program, the innovations achieved, and the outcomes to which they contributed. Turbulence and transformations in the CGIAR system influenced the CRPs’ emergence, design, and delivery. In this chapter, we discuss the RTB approach to collaborative governance and management as complex institutional innovations operating within this broader, dynamic system. This includes attention to opportunities, limitations, and other contextual factors influencing RTB’s work. Institutional innovations include stakeholder consultations and priority setting, a portfolio organized by aggregated innovations, or clusters of activities, articulated flagship projects, incentive funding, a dynamic interactive communication ability, and programmatic embedding of strategic and integrated gender research. RTB’s design, governance, and management innovations added value to the combined achievements of the participating centers in science and research for development outcomes, described in the following chapters.

Summary This review of the literature on varietal change in sub‐Saharan Africa looks in detail at adoption of new varieties of bananas in Uganda, cassava in Nigeria, potato in Kenya, sweetpotato in Uganda and yams in Côte d’Ivoire. The review explored three hypotheses about drivers of varietal change. There was a strong confirmation for the hypothesis that insufficient priority given to consumer‐preferred traits by breeding programmes contributes to the limited uptake of modern varieties (MVs) and low varietal turnover. Lack of evidence meant the second hypothesis of insufficient attention to understanding and responding to gender differences in consumer preferences for quality and post‐harvest traits was unresolved. The evidence on the third hypothesis about the informal seed system contributing to slow uptake of MVs was mixed. In some cases, the informal system has contributed to rapid uptake of MVs, but often it appears to be a barrier with inconsistent varietal naming a major challenge.

Context: Climate change is projected to negatively impact food systems in Sub-Saharan Africa. The magnitude of these impacts is expected to be amplified by the extensive reliance on rainfed agriculture and the prevalence of subsistence farming. In the Great Lakes Region of Central Africa, smallholder farming households are largely dependent on root, tuber and banana crops. However, the potential impacts of various climate change scenarios on these crops are not well reported. Yet, data-rich insights about the future impacts of climate change on these crops and the adaptive capacity of food systems in the Great Lakes Region is critical to inform research and development investments towards regional climate change adaptation. Objectives: We aimed to gain insights of potential impacts of climate change on root, tuber, and banana crops in the Great Lakes Region, specifically investigating changes to localised crop suitability, planting dates, and identifying potential 'climate-proof' variety types of each crop for specific geographies. Methods: We developed a modified version of the EcoCrop model to analyse the suitability of future climates for four key root, tuber, and banana crops (banana, cassava, potato, and sweetpotato) and a suite of varieties for each (typical, heat-tolerant, drought-tolerant, and early maturing). The model considers only the direct impacts of climate change on crop suitability. It does not consider how climate change impacts crop suitability by affecting the occurrence of extreme weather events or indirect effects on incidence and severity of pest and disease outbreaks. Results and conclusions: Our results demonstrate that climate change will be somewhat favourable to root, tuber, and banana-based systems, with only widespread negative impacts seen for potato. These changes should be qualified by the observation that in most cases the environmental suitability for banana, cassava, and sweet potato will remain constant or improve if farmers shift planting schedules. Location-and crop-dependent shifts to different variety types were found to be effective in improving suitability under future climates. Significance: Data driven insights generated from this work can be used as a first step in developing spatially explicit recommendations for both farmers and decision-makers on how to adapt to climate change and plan investment in the research needed to adapt root, tuber, and banana-based livelihoods and systems to those longterm changes.

Until recently, there has been little commercial sale of vegetatively propagated crop seed, except for potatoes (Solanum tuberosum). This is especially true in developing countries. However, a formal, commercial seed sector for cassava (Manihot esculenta) is emerging in Nigeria. In 2016, a project, Building an Economically Sustainable Integrated Cassava Seed System in Nigeria (BASICS), started to encourage village farmers to certify and sell cassava seed. A questionnaire survey of 30 cassava entrepreneurs across Nigeria in 2019 included some of those village-based growers as well as larger producers, including some who certified their planting material. In the long run, if there is a consistent demand for certified cassava seed, medium-sized producers may be able to satisfy some of that demand, especially if they have continued programmatic support; otherwise, these budding seed entrepreneurs may close down.

Climate-smart agriculture (CSA) is widely promoted as an approach for reorienting agricultural development under the realities of climate change. Prioritising research-for-development activities is crucial, given the need to utilise scarce resources as effectively as possible. However, no framework exists for assessing and comparing different CSA research investments. Several aspects make it challenging to prioritise CSA research, including its multi-dimensional nature (productivity, adaptation and mitigation), the uncertainty surrounding many climate impacts, and the scale and temporal dependencies that may affect the benefits and costs of CSA adoption. Here we propose a framework for prioritising agricultural research investments across scales and review different approaches to setting priorities among agricultural research projects. Many priority-setting case studies address the short- to medium-term and at relatively local scales. We suggest that a mix of actions that span spatial and temporal time scales is needed to be adaptive to a changing climate, address immediate problems and create enabling conditions for enduring change.

Breeding in the CGIAR Research Program on Roots, Tubers and Bananas (RTB) targets highly diverse biotic and abiotic constraints, whilst meeting complex end-user quality preferences to improve livelihoods of beneficiaries in developing countries. Achieving breeding targets and increasing the rate of genetic gains for these vegetatively propagated crops, with long breeding cycles, and genomes with high heterozygosity and different ploidy levels, is challenging. Cheaper sequencing opens possibilities to apply genomics tools for complex traits, such as yield, climate resilience, and quality traits. Therefore, across the RTB program, genomic resources and approaches, including sequenced draft genomes, SNP discovery, quantitative trait loci (QTL) mapping, genome-wide association studies (GWAS), and genomic selection (GS), are at different stages of development and implementation. For some crops, marker-assisted selection (MAS) is being implemented, and GS has passed the proof-of-concept stage. Depending on the traits being selected for using prediction models, breeding schemes will most likely have to incorporate both GS and phenotyping for other traits into the workflows leading to varietal development.

The CGIAR Research Program (CRP) on Roots, Tubers and Bananas (RTB) includes vegetatively propagated staple crops linked by common breeding, seed, and postharvest issues, and by the frequency with which women are involved in their production and use. RTB crops are the backbone of food security across the humid tropics in sub-Saharan Africa (SSA) and in more localized areas of Asia and Latin America. Around 300 million poor people in developing countries currently depend on RTB value chains for food security, nutrition and income. Climate change poses challenges which could undo progress in poverty reduction and markedly increase food insecurity. This article examines planning and research for climate resilience across RTB crops, with a particular focus on the contrasting potato and sweet potato cases in SSA. A six-step framework for climate-smart breeding is proposed: (1) downscaling climate change models and crop modeling; (2) identifying and understanding key climate change responsive traits; (3) breeding and varietal selection; (4) phenotyping and genomic research to accelerate gains; (5) developing management options for climate-smart varieties; and (6) deployment (seed systems). In summary, climate-smart breeding means we need to do what we already do but faster, better, and smarter.

In order to uncover the genetic basis of phenotypic trait variation, we used 448 unrelated wild accessions of black cottonwood (Populus trichocarpa) from much of its range in western North America. Extensive data from large-scale trait phenotyping (with spatial and temporal replications within a common garden) and genotyping (with a 34 K Populus single nucleotide polymorphism (SNP) array) of all accessions were used for gene discovery in a genome-wide association study (GWAS). We performed GWAS with 40 biomass, ecophysiology and phenology traits and 29 355 filtered SNPs representing 3518 genes. The association analyses were carried out using a Unified Mixed Model accounting for population structure effects among accessions. We uncovered 410 significant SNPs using a Bonferroni-corrected threshold (P < 1.7 × 10−6). Markers were found across 19 chromosomes, explained 1–13% of trait variation, and implicated 275 unique genes in trait associations. Phenology had the largest number of associated genes (240 genes), followed by biomass (53 genes) and ecophysiology traits (25 genes). The GWAS results propose numerous loci for further investigation. Many traits had significant associations with multiple genes, underscoring their genetic complexity. Genes were also identified with multiple trait associations within and/or across trait categories. In some cases, traits were genetically correlated while in others they were not.

Genetic mapping of quantitative traits requires genotypic data for large numbers of markers in many individuals. For such studies, the use of large single nucleotide polymorphism ( SNP ) genotyping arrays still offers the most cost‐effective solution. Herein we report on the design and performance of a SNP genotyping array for Populus trichocarpa (black cottonwood). This genotyping array was designed with SNP s pre‐ascertained in 34 wild accessions covering most of the species latitudinal range. We adopted a candidate gene approach to the array design that resulted in the selection of 34 131 SNP s, the majority of which are located in, or within 2 kb of, 3543 candidate genes. A subset of the SNP s on the array (539) was selected based on patterns of variation among the SNP discovery accessions. We show that more than 95% of the loci produce high quality genotypes and that the genotyping error rate for these is likely below 2%. We demonstrate that even among small numbers of samples ( n = 10) from local populations over 84% of loci are polymorphic. We also tested the applicability of the array to other species in the genus and found that the number of polymorphic loci decreases rapidly with genetic distance, with the largest numbers detected in other species in section Tacamahaca. Finally, we provide evidence for the utility of the array to address evolutionary questions such as intraspecific studies of genetic differentiation, species assignment and the detection of natural hybrids.

In plants, genes may sustain extensive pleiotropic functional properties by individually affecting multiple, distinct traits. We discuss results from three genome-wide association studies of approximately 400 natural poplar (Populus trichocarpa) accessions phenotyped for 60 ecological/biomass, wood quality, and rust fungus resistance traits. Single-nucleotide polymorphisms (SNPs) in the poplar ortholog of the class III homeodomain-leucine zipper transcription factor gene REVOLUTA (PtREV) were significantly associated with three specific traits. Based on SNP associations with fungal resistance, leaf drop, and cellulose content, the PtREV gene contains three potential regulatory sites within noncoding regions at the gene's 3' end, where alternative splicing and messenger RNA processing actively occur. The polymorphisms in this region associated with leaf abscission and cellulose content are suggested to represent more recent variants, whereas the SNP associated with leaf rust resistance may be more ancient, consistent with REV's primary role in auxin signaling and its functional evolution in supporting fundamental processes of vascular plant development.

Establishing links between phenotypes and molecular variants is of central importance to accelerate genetic improvement of economically important plant species. Our work represents the first genome-wide association study to the inherently complex and currently poorly understood genetic architecture of industrially relevant wood traits. Here, we employed an Illumina Infinium 34K single nucleotide polymorphism (SNP) genotyping array that generated 29,233 high-quality SNPs in c. 3500 broad-based candidate genes within a population of 334 unrelated Populus trichocarpa individuals to establish genome-wide associations. The analysis revealed 141 significant SNPs (α ≤ 0.05) associated with 16 wood chemistry/ultrastructure traits, individually explaining 3-7% of the phenotypic variance. A large set of associations (41% of all hits) occurred in candidate genes preselected for their suggested a priori involvement with secondary growth. For example, an allelic variant in the FRA8 ortholog explained 21% of the total genetic variance in fiber length, when the trait's heritability estimate was considered. The remaining associations identified SNPs in genes not previously implicated in wood or secondary wall formation. Our findings provide unique insights into wood trait architecture and support efforts for population improvement based on desirable allelic variants.

• Populus trichocarpa is widespread across western North America spanning extensive variation in photoperiod, growing season and climate. We investigated trait variation in P. trichocarpa using over 2000 trees from a common garden at Vancouver, Canada, representing replicate plantings of 461 genotypes originating from 136 provenance localities. • We measured 40 traits encompassing phenological events, biomass accumulation, growth rates, and leaf, isotope and gas exchange-based ecophysiology traits. With replicated plantings and 29,354 single nucleotide polymorphisms (SNPs) from 3518 genes, we estimated both broad-sense trait heritability (H(2)) and overall population genetic structure from principal component analysis. • Populus trichocarpa had high phenotypic variation and moderate/high H(2) for many traits. H(2) ranged from 0.3 to 0.9 in phenology, 0.3 to 0.8 in biomass and 0.1 to 0.8 in ecophysiology traits. Most traits correlated strongly with latitude, maximum daylength and temperature of tree origin, but not necessarily with elevation, precipitation or heat : moisture indices. Trait H(2) values reflected trait correlation strength with geoclimate variables. The population genetic structure had one significant principal component (PC1) which correlated with daylength and showed enrichment for genes relating to circadian rhythm and photoperiod. • Robust relationships between traits, population structure and geoclimate in P. trichocarpa reflect patterns which suggest that range-wide geographical and environment gradients have shaped its genotypic and phenotypic variability.

High-throughput approaches have been widely applied to elucidate the genetic underpinnings of industrially important wood properties. Wood traits are polygenic in nature, but gene hierarchies can be assessed to identify the most important gene variants controlling specific traits within complex networks defining the overall wood phenotype. We tested a large set of genetic, genomic, and phenotypic information in an integrative approach to predict wood properties in Populus trichocarpa. Nine-yr-old natural P.trichocarpa trees including accessions with high contrasts in six traits related to wood chemistry and ultrastructure were profiled for gene expression on 49k Nimblegen (Roche NimbleGen Inc., Madison, WI, USA) array elements and for 28831 polymorphic single nucleotide polymorphisms (SNPs). Pre-selected transcripts and SNPs with high statistical dependence on phenotypic traits were used in Bayesian network learning procedures with a stepwise K2 algorithm to infer phenotype-centric networks. Transcripts were pre-selected at a much lower logarithm of Bayes factor (logBF) threshold than SNPs and were not accommodated in the networks. Using persistent variables, we constructed cross-validated networks for variability in wood attributes, which contained four to six variables with 94-100% predictive accuracy. Accommodated gene variants revealed the hierarchy in the genetic architecture that underpins substantial phenotypic variability, and represent new tools to support the maximization of response to selection.

• The formation of secondary cell walls in cell types such as tracheary elements and fibers is a defining characteristic of vascular plants. The Arabidopsis transcription factor KNAT7 is a component of a transcription network that regulates secondary cell wall biosynthesis, but its function has remained unclear. • We conducted anatomical, biochemical and molecular phenotypic analyses of Arabidopsis knat7 loss-of-function alleles, KNAT7 over-expression lines and knat7 lines expressing poplar KNAT7. • KNAT7 was strongly expressed in concert with secondary wall formation in Arabidopsis and poplar. Arabidopsis knat7 loss-of-function alleles exhibited irregular xylem phenotypes, but also showed increased secondary cell wall thickness in fibers. Increased commitment to secondary cell wall biosynthesis was accompanied by increased lignin content and elevated expression of secondary cell wall biosynthetic genes. KNAT7 over-expression resulted in thinner interfascicular fiber cell walls. • Taken together with data demonstrating that KNAT7 is a transcriptional repressor, we hypothesize that KNAT7 is a negative regulator of secondary wall biosynthesis, and functions in a negative feedback loop that represses metabolically inappropriate commitment to secondary wall formation, thereby maintaining metabolic homeostasis. The conservation of the KNAT7 regulatory module in poplar suggests new ways to manipulate secondary cell wall deposition for improvement of bioenergy traits in this tree.

The western black cottonwood (Populus trichocarpa) was the first tree to have its genome fully sequenced and has emerged as the model species for the study of secondary growth and wood formation. It is also a good candidate species for the production of lignocellulosic biofuels. Here, we present and make available to the research community the results of the sequencing of the transcriptome of developing xylem in 20 accessions with high-throughput next generation sequencing technology. We found over 0.5 million putative single nucleotide polymorphisms (SNPs) in 26 595 genes that are expressed in developing secondary xylem. More than two-thirds of all SNPs were found in annotated exons, with 18% and 14% in regions of the genome annotated as introns and intergenic, respectively, where only 3% and 4% of sequence reads mapped. This suggests that the current annotation of the poplar genome is remarkably incomplete and that there are many transcripts and novel genes waiting to be annotated. We hope that this resource will stimulate further research in expression profiling, detection of alternative splicing and adaptive evolution in poplar.

Plant yield is the integrated outcome of processes taking place above and below ground. To explore genetic, environmental and developmental aspects of fruit yield in tomato, we phenotyped an introgression line (IL) population derived from a cross between the cultivated tomato (Solanum lycopersicum) and a wild species (Solanum pennellii). Both homozygous and heterozygous ILs were grown in irrigated and non-irrigated fields and evaluated for six yield components. Thirteen lines displayed transgressive segregation that increased agronomic yield consistently over 2 years and defined at least 11 independent yield-improving QTL. To determine if these QTL were expressed in the shoots or the roots of the plants, we conducted field trials of reciprocally grafted ILs; out of 13 lines with an effect on yield, 10 QTL were active in the shoot and only IL8-3 showed a consistent root effect. To further examine this unusual case, we evaluated the metabolic profiles of fruits from both the homo- and heterozygous lines for IL8-3 and compared these to those obtained from the fruit of their equivalent genotypes in the root effect population. We observed that several of these metabolic QTL, like the yield QTL, were root determined; however, further studies will be required to delineate the exact mechanism mediating this effect in this specific line. The results presented here suggest that genetic variation for root traits, in comparison to that present in the shoot, represents only a minor component in the determination of tomato fruit yield.