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Does social capital influence the intensity of conservation agriculture adoption among smallholder farmers in Malawi?
No full textAddressing persistent food insecurity requires increased and sustained agricultural productivity in spite of compounding challenges of worsening climate shocks and soil degradation. However, despite numerous initiatives by stakeholders like the Malawian government, along with strong scientific evidence supporting Conservation Agriculture (CA), adoption rates in Malawi remain lower than expected. This study examined social capital as a catalyst for the adoption of CA. It used data from 1512 randomly selected smallholder farmers to investigate how different elements of social capital influenced farmers’ decisions to adopt CA practices. The study findings revealed that social capital elements, namely, group membership and relationships with leadership positively influenced CA adoption. Additionally, factors such as cultivated land size, access to extension services, livestock ownership, and credit availability contributed to the number of CA practices adopted. While the transition to full CA adoption remained limited compared to partial adoption, the study revealed promising trends toward greater uptake. Consequently, these findings highlight the need for agricultural policies that promote farmer organizations, community engagement, and training programs to strengthen social networks and enhance the adoption of CA practices in Malawi
Genotyping by sequencing reveals the genetic diversity and population structure of Peruvian highland maize races
No full textPeruvian maize exhibits abundant morphological diversity, with landraces cultivated from sea level (sl) up to 3,500 m above sl. Previous research based on morphological descriptors, defined at least 52 Peruvian maize races, but its genetic diversity and population structure remains largely unknown. Here, we used genotyping-by-sequencing (GBS) to obtain single nucleotide polymorphisms (SNPs) that allow inferring the genetic structure and diversity of 423 maize accessions from the genebank of Universidad Nacional Agraria la Molina (UNALM) and Universidad Nacional Autónoma de Tayacaja (UNAT). These accessions represent nine races and one sub-race, along with 15 open-pollinated lines (purple corn) and two yellow maize hybrids. It was possible to obtain 14,235 high-quality SNPs distributed along the 10 maize chromosomes of maize. Gene diversity ranged from 0.33 (sub-race Pachia) to 0.362 (race Ancashino), with race Cusco showing the lowest inbreeding coefficient (0.205) and Ancashino the highest (0.274) for the landraces. Population divergence (FST) was very low (mean = 0.017), thus depicting extensive interbreeding among Peruvian maize. A cluster containing maize landraces from Ancash, Apurímac, and Ayacucho exhibited the highest genetic variability. Population structure analysis indicated that these 423 distinct genotypes can be included in 10 groups, with some maize races clustering together. Peruvian maize races failed to be recovered as monophyletic; instead, our phylogenetic tree identified two clades corresponding to the groups of the classification of the races of Peruvian maize based on their chronological origin, that is, anciently derived or primary races and lately derived or secondary races. Additionally, these two clades are also congruent with the geographic origin of these maize races, reflecting their mixed evolutionary backgrounds and constant evolution. Peruvian maize germplasm needs further investigation with modern technologies to better use them massively in breeding programs that favor agriculture mainly in the South American highlands. We also expect this work will pave a path for establishing more accurate conservation strategies for this precious crop genetic resource
A conceptual framework for the contextualization of crop model applications and outputs in participatory research
No full textContextualization of generic scientific knowledge to context-specific farmer knowledge is a necessary step in farmers’ innovation process, and it can be achieved using crop and farm models. This work explores the possibility to simulate a large number of scenarios based on farmers’ descriptions of their environment and practices in order to contextualize the discussion for each participating farmer. It presents a novel framework consisting of six actions divided in three phases, namely, phase I—reaching out to the farmers’ world: (i) project initialization; (ii) determination of the agronomical question anchored in farmers’ context; (iii) characterization of the environment, the management options, and the indicators to describe the system under consideration; phase II—within researchers’ world: (iv) crop model parametrization; (v) translation of model outputs into farmer-proposed indicators; and phase III—back to farmers’ world: (vi) exploration of contextualized management options with farmers. Two communication tools are created during the process, one containing the results of simulations to feed the discussions and a second one to create a record of it. The usefulness of the framework is exemplified with the exploration of soil fertility management with manure and compost applications for sorghum production in the smallholder context of Sudano-Sahelian Burkina Faso. The application of the framework with 15 farmers provided evidence of farmers’ and agronomists’ understanding of options to improve cropping system performance with better organic amendment management. This approach allowed farmers to identify and relate to the scenarios simulated, but highlighted interrogations on how to adapt the crop model outputs to particular situations. Though applied on issues related to tactical change at field level, the framework offers the opportunity to explore broader issues with farmers, such as farm reconfiguration
Nature-positive agriculture-a way forward towards resilient agrifood systems
No full textCurrent food production systems rely heavily on resource-poor small-scale farmers in the global south. Concomitantly, the agrifood systems are exacerbated by various a/biotic challenges, including low-input agriculture and climate crisis. The recent global food crisis further escalates the production and consumption challenges in the global market. With these challenges, coordinated efforts to address the world's agrifood systems challenges have never been more urgent than now. This includes the implementation of deeply interconnected activities of food, land, and water systems and relationships among producers and consumers that operate across political boundaries. Nature-positive agriculture represents interventions both at the farm and landscape level that include a systems approach for the management of diverse issues across the land-water-food nexus. In the present article, we focus on the history of traditional farming and how it evolved into today's nature-positive agriculture, including its limitations and opportunities. The review also explains the most impactful indicators for successful nature-positive agriculture, including sustainable management of soil, crops, seeds, pests, and mixed farming systems, including forages and livestock. Finally, the review explains the dynamics of nature-positive agriculture in the context of small-scale farming systems and how multilateral organizations like the CGIAR are converting this into transformative actions and impact. To address the climate crisis, CGIAR established the paradigm of nature-positive solutions as part of its research and development efforts aimed at transforming food, land, and water systems into more resilient and sustainable pathways
Enhancing water and food security through improved agricultural water productivity: new knowledge, innovations and applications
No full textThis open-access edited book provides a synthesis of knowledge on Water Productivity (WP) and its role in addressing global challenges related to water and food insecurity, as well as climate change. It explores how increasing WP can contribute to achieving several Sustainable Development Goals (SDGs) in the global South, with a focus on SDG 2, 6, and 12. The volume connects WP with emerging approaches such as the water-energy-food nexus, sustainable food systems, and the circular economy. It features case studies, critical analyses, and meta-analyses that bridge the science-policy-practice interface. The book also delves into WP's relation to global priorities, policies, and the empowerment of vulnerable communities, highlighting the non-negotiable rights to water and food. Governance, policies, and institutions are discussed in the context of enhancing WP in farmer-led irrigation and scaling WP technologies. The book also covers emerging methods for determining WP, assessing linkages to nutrition, health, and well-being, and integrating climate change adaptation and mitigation strategies. This is a guide for regional and international experts, professionals, and scholars interested in agricultural water management in the global south. The book has the potential to inform multi-regional and sectoral policies, particularly in Africa, and contribute to sustainable development through better resource management.391 page
Dissecting the genomic regions, candidate genes and pathways using multi-locus genome-wide association study for stem rot disease resistance in groundnut
No full textStem rot, caused by Sclerotium rolfsii Sacc., is a devastating soil-borne disease causing up to 80% yield losses in groundnut globally. To dissect the genetic basis of resistance, we evaluated a diverse minicore germplasm panel over 3 years in stem rot sick-field conditions. Multi-locus genome-wide association study with the 58K single nucleotide polymorphisms (SNPs) Axiom_Arachis array genotyping identified 13 significant genomic regions associated with resistance across eight chromosomes with logarithm of the odds (LOD) scores ranging from 4.5 to 12.4 and R2 values between 6.9% and 58%. Within these regions, 145 candidate genes were implicated, including wall-associated receptor kinases, lucine-rich repeat and NB-ARC domain proteins, and peroxidase superfamily proteins. These genes orchestrate resistance through pathogen perception (e.g., receptor-like kinases), direct inhibition (R genes), toxin detoxification, and activation of transcription factors driving protective compound synthesis for cell recovery. If these defenses are compromised, a hypersensitive response-mediated apoptosis is triggered. Notably, resistance was exclusive to Virginia-type groundnut. The identified candidate genes showed strong correlation with RNA-seq data from stem rot-infected plants, reinforcing their role in the transcriptional defense response. Three kompetitive allele-specific PCR markers, namely, SnpAH00614 (on auxin-related gene AhSR001), SnpAH00625 (on histidine triad protein gene AhSR002), and SnpAH00626 (on E3 ubiquitin ligase gene AhSR003), were validated, confirming their significant contribution to stem rot resistance. These markers may facilitate the development of stem rot-resistant varieties through direct application in breeding programs through marker-assisted selection
Genetic analysis of resistance to Puccinia triticina Erikss. In Triticum spelta L.
No full textBackground: Leaf rust caused by Puccinia triticina Erikss. is a widely distributed wheat (Triticum aestivum L.) disease. Using wild relatives, such as Triticum spelta L., as a source of desirable traits represents a good strategy for developing wheat varieties, as T. spelta L. has shown tolerance to various types of biotic and abiotic stresses. This study aimed to determine the genetic basis of resistance to leaf rust in the accession Triticum spelta 109 (PI 355580). Methods: The resistant genotype T. spelta 109 was crossed with the bread wheat variety Roelfs F2007, and 135 F3 families were generated to analyze the genetics of resistance to the MBJ/SP leaf rust race. The families were classified into three groups: (i) homozygous-resistant; (ii) homozygous-susceptible; (iii) segregating. A χ2 test was performed to compare whether the expected and observed segregation ratios fit and to determine the number of genes involved in the resistance of T. spelta 109. Results: The seedling tests in the F1 generation showed susceptibility in all plants, indicating that the resistance is conferred by a recessive gene(s). The results of the χ2 test revealed that the observed segregation ratios of the F3 families followed the expected values, suggesting that a recessive gene confers the leaf rust resistance present in T. spelta 109. According to our results and the reported recessive genes identified among the T. spelta accessions, the identified recessive gene in T. spelta 109 (PI355580) is different and most likely a novel leaf rust resistance gene. Conclusions: The genetic resistance to leaf rust of T. spelta 109 (PI 355580) is conferred by a single recessive gene. The importance and usefulness of searching for rust resistance genes from different sources and incorporating them into the genetic base of wheat breeding programs to provide diversity is confirmed
Assessing molecular diversity of tropical maize inbred lines using Single Nucleotide Polymorphic (SNP) markers
No full textAdvances in genotyping technologies have changed how breeders study and manage maize genetics. Identification of single nucleotide polymorphisms (SNPs) helped researchers understand the molecular diversity among tropical maize (Zea mays L.) inbred lines, The present study was conducted to assess the molecular diversity and population structure of 107 tropical maize inbred lines collected from working germplasm programs using SNP markers. A total of 97 genome-wide SNP markers were employed for genotyping through the KASP assay. The polymorphism information content (PIC) values ranged from 0.018 to 0.375 with an overall mean of 0.285, indicating that the majority of markers were moderately informative. Hierarchical clustering grouped the inbred lines into three major clusters, reflecting clear genetic differentiation among the tropical maize inbred lines. Principal component analysis (PCA) further validated these findings by identifying highly divergent lines Viz., AHG-122, CIMMYT-22, BHG-20 and AHG-110-1. The congruence between UPGMA clustering and PCA confirmed the robustness of the diversity analysis. These findings provide valuable insights into the genetic relationships among tropical maize inbreds and highlight the utility of SNP markers in guiding the selection of parental lines for hybrid development.490-50
Mapping novel yellow and leaf rust loci and predicting resistance in cross derived Canadian durum wheat
No full textDurum wheat (Triticum turgidum ssp. durum) suffers substantial yield losses from yellow rust (Puccinia striiformis) and leaf rust (Puccinia triticina). In this study, we employed genome-wide association studies (GWAS) to identify loci associated with rust resistance and used genomic selection (GS) to evaluate the predictive accuracy of different statistical models and phenotyping metrics (AUDPC_GDD, Angle, GDD50, and maxVar) in a Canadian durum wheat panel. The panel was evaluated in Mexico for yellow rust across three seasons near Toluca, and for leaf rust over two seasons at El Bat & aacute;n. Our GWAS identified 36 significant marker-trait associations (MTAs), including known loci (Yr30, Yr57, Yr82, YrU1, Lr16, Lr17, Lr18, and Lr65) and previously unreported regions. Yellow rust resistance was linked to loci on chromosomes 3A (602.7 Mbp) and 3B (243.4 Mbp), while leaf rust MTAs appeared on chromosomes 5A (552.8 Mbp) and 7A (570 Mbp). Candidate genes near novel MTAs encode defense-related proteins such as serine/threonine kinases and NB-ARC (nucleotide binding-Apaf-1, R proteins, and CED-4), F-box, and RIN4 (RPM1-interacting protein 4)-domain proteins. Among four scoring metrics tested, AUDPC_GDD consistently outperformed others for yellow rust, whereas maxVar was most effective for leaf rust, reflecting differences in phenotypic distribution and trait variance. Bayesian GS models (BayesB) achieved the highest prediction accuracy, but including GWAS-derived fixed effects did not improve predictions, likely due to complexities in modeling major-effect loci. These results underscore the importance of rust-specific phenotyping strategies and illustrate the difficulty of integrating GWAS into GS models to dissect complex resistance traits