ICARDA Posters

Permanent URI for this collectionhttps://hdl.handle.net/10568/51685

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Données sur la dynamique de la structure et de la fragmentation du paysage dans le transect du Kef et de Siliana
(Poster, 2024-02-13) Shiri, Zahra; Le, Quang Bao; Frija, Aymen; Ouerghemmi, Hassen; Rejeb, Hichem
Ce poster a été présenté à l'INAT dans le cadre de 4 -ème édition doctorales 2024. Les données présentées dans ce travail montrent des changements dans l'utilisation et la couverture des terres ainsi que la fragmentation des terres dans le transect de Kef et Siliana sur une période de 5 ans (2017-2022). Les informations exposées sont importantes pour la zone d'étude pour pouvoir proposer des pratiques appropriées de gestion des terres en vue d'une transition agroécologique. L'évaluation des évolutions s'appuie sur des indicateurs de métriques paysagères, offrant une vision complète des services écosystémiques à différentes échelles. L'étude se divise en trois niveaux distincts : niveau 1 évalue l'ensemble de la région intergouvernementale, niveau 2 examine les laboratoires vivants d'agroécologie en tant qu'entité holistique, et niveau 3 analyse les unités sous-spatiales au sein de six régions spécifiques des laboratoires vivants d'agroécologie. L'utilisation de données matricielles sur l'utilisation et la couverture des sols a permis d'analyser la fragmentation au niveau du paysage.
AMMI and GGE Biplot Analyses for Mega- Environment Identification and Selection of Some High-Yielding Oat (Avena sativa L.) Genotypes for Multiple Environments
(Poster, 2024-10-30) Wodebo, Kibreab; Tolemariam, Taye; Demeke, Solomon; Garedew, Weyessa; Tesfaye, Tessema; Ekule, Muluken; Gemiyu, Deribe; Bedeke, Worku; Wamatu, Jane; Mamta, Sharma
To lessen the impact of Genotype x Environment interaction and to increase the precision and reliability of genotype selection, the yield and stability of performance should be taken into account simultaneously. Two methodologies of analysis (AMMI and GGE) approved selecting ILRI_5527A/G6 for a further breeding program or for high-production growers in Adiyo, Doyogena, Chencha and Hulla locations of Central Ethiopia.
Identification of the SNP markers for drought tolerance and related agronomic traits in chickpea under multi-environments using GWAS analysis
(Poster) Istanbuli, Tawffiq; Alsamman, Alsamman M.; Nasser, Ahmed; Tawkaz, Sawsan; Hamwieh, Aladdin
Drought tolerance is a complex trait that involves numerous genes. Identifying key causal genes or linked molecular markers can facilitate the fast development of drought-tolerant varieties. Using genome-wide association study (GWAS) is a powerful approach to identifying the genetic factors underlying the intraspecific phenotypic variations. To address this, we cultivated 185 chickpea accessions in two distinct locations in Lebanon over two years, subjecting them to both irrigated and rain-fed environments. We measured 11 traits, including morphological, yield, yield components and tolerance score. SNP genotyping revealed 1344 variable SNP markers distributed across the chickpea genome. A genome-wide association study (GWAS) revealed several marker-trait associations (MTAs) associated with the traits evaluated. Within the rainfed conditions, 11 significant markers were identified, each associated with distinct chickpea traits. Another set of 11 markers exhibited associations in both rainfed and irrigated environments, reflecting shared genetic determinants across these conditions for the same trait. We identified 28 genetic regions containing SNPs significantly associated with several different drought traits, which was an indication of pleiotropic effects. Among the identified genes are CPN60-2, hsp70, GDSL(GELP), AHL16, NAT3, FAB1B, bZIP, and GL21. These genes collectively contribute to the multifaceted response of chickpea plants to drought stress.
Genomic selection for different agronomic traits in ICARDA chickpea breeding program
(Poster) Hamwieh, Aladdin; Jighly, Abdul-Qader; Kaur, Sukhjiwan; Istanbuli, Tawffiq
Chickpea (Cicer arietinum) is a crucial legume crop for food security and agricultural sustainability. Genomic selection (GS), an emerging breeding approach, enables early selection by predicting the genetic value of individuals using genome-wide markers. This study investigated the prediction accuracy of key agronomic traits using ICARDA chickpea breeding germplasm. The training population for this study was comprised of 297 genotypes, where 48% were breeding lines, 22% recombinant inbred lines (RILs), 14% of varieties, landraces, and wild types. Approximately 8% of the training population represented materials imported From Australia and India. The germplasm was genotyped using 1,922 single nucleotide polymorphism (SNP) markers covering the eight chromosomes. Field evaluation was conducted over two years (2023 and 2024) at Terbol station, Lebanon, using a replicated Alpha Lattice design. Key agronomic traits assessed included 100 seed weight (100SW), flowering time (FLWR), maturity time (MAT), and plant height (PLHT). Grain and biological yield were also measured. The prediction accuracy was calculated with and without fitting the genotype by environment interaction in the prediction model with two cross-validation strategies (CV1: predicting new individuals; and CV2: predicting complete data across environments from unbalanced field trials). The results demonstrated moderate heritability values for 100SW, FLWR, MAT, and PLHT, and high prediction accuracy values ranging from 0.51 to 0.81 for CV1, and from 0.63 to 0.90 for CV2. However, yield and yield component traits exhibited relatively lower heritabilities and accuracies ranging from 0.38 to 0.48 for CV1, and from 0.37 to 0.51 for CV2. These findings underscore the potential of GS to enhance the efficiency and accuracy of chickpea breeding programs to achieve better yield stability and adaptability in chickpea across diverse growing conditions.
Genomic Prediction in Faba bean for Heat and Herbicide Tolerance
(Poster) Abou-Khater, Lynn; Maalouf, Fouad; Hamwieh, Aladdin; Jighly, Abdul-Qader; Joukhadar, Reem; Alsamman, Alsamman M.; Ahmed, Zayed Babiker Mahgoub; Balech, Rind; Hu, Jinguo; Ma, Y.; Sanchez-Garcia, Miguel; Agrawal, Shiv Kumar
Genomic selection (GS) offers significant potential to enhance genetic gain. The present study aimed to evaluate the accuracy and potential of GS in faba bean (Vicia faba L.), and to identify areas for further improvement and better implementation in practical breeding programs. 125 diverse faba bean accessions were phenotyped for different agronomic traits under herbicide and heat stresses in 16 environments in Morocco, Lebanon, Sudan and the USA. These accessions were also genotyped. 170 SNPs highly associated with the target traits were identified. Subsequently, KASP markers were designed and validated across 4515 diverse breeding lines. Prediction accuracy (PA) was evaluated using the reproducing kernel Hilbert space model with and without considering genotype by environment interaction and considering two cross-validation strategies (CV1: predicting new lines; CV2: predicting complete records from unbalanced data). In addition, 75 KASP markers targeting heat tolerance traits were prioritized and used to estimate the PA of the models. The findings indicated comparable PA between the two models. CV1 outperformed CV2, highlighting the challenge of predicting the performance of untested lines in tested environments compared to lines that were evaluated in some environments but not in others. Furthermore, the subset size and composition of SNPs significantly influenced PA, particularly under heat stress conditions. Notably, the highest accuracies were achieved for days to flowering and plant height, suggesting that these traits are suitable for use in training population selection. Optimizing the size and composition of the training population holds promise for successful application of GS in faba bean.
Empowering smallholder olive growers in northwest Tunisia through an agroecological business model
(Poster, 2024-09-13) Majri, Rihab; Dhraief, Mohamed Zied; Souissi, Asma; Ouerghemmi, Hassen; Dhehibi, Boubaker; Oueslati, Meriem; Frija, Aymen; M. Oumer, Ali; Fendri, Mahdi; Larbi, Ajmi
Olive cultivation is the most important agroecosystem in Tunisia. This agroecosystem is facing tremendous challenges, including climate change, loss of biodiversity, environmental pollution and resource degradation, as well as increasing price volatility with harmful implications for farmers’ incomes, livelihoods, and rural development. Agroecology is considered actually as the mainstream model for transforming agriculture toward more sustainable and resilient agri-food systems within the given economic and political context
Transdisciplinary research approaches for crop science research: theory, practice, and implications for research design
(Poster) Amoak, Daniel; Najjar, Dina; Belcher, Brian
Current challenges in agri-food systems, such as climate change, population growth, ecosystem degradation, and increasing demand for healthy and diverse diets, cut across geographical, cultural, and disciplinary boundaries. Successfully meeting these challenges will require research approaches that draw on a broad base of scientific and practical knowledge and expertise to develop and implement innovations in crop varieties, agronomy, markets and policies. Success needs to be measured in gains from multiple traits, including climate resilience (drought or heat tolerance), nutritional value, value to women farmers or the marginalized, and market traits valued by a range of consumers, as well as the necessary attention to productivity and income-generation (De Grandis & Efstathiou, 2016; FAO, 2023). The systematic exclusion of women and other minority voices may be partly explained by their limited representation in agri-food systems governance (Amoak et al., 2022), as well as programs bereft of research designs that embrace a plurality of views. This field has also been criticized for the lack of coherence when it comes to defining problems due to differing perspectives from stakeholders which undermines projected gains of breed programs (Brandt et al., 2013). In the last decade, advancements within the CGIAR and beyond, including tools and frameworks from the Excellence in Breeding (EiB) Platform and the Gender and Breeding Initiative (GBI), have worked to improve market intelligence, breeding programs, seed systems, and the safeguarding of genetic resources. However, there is still scope for further innovation in research processes in terms of how breeding objectives are decided, how stakeholders’ perspectives are incorporated, how teams are organized and function, how knowledge gets translated into action, and how success is defined and measured.
Towards a Multi-Stakeholder Approach to Barley Breeding in Ethiopia: Integrating Gender-Specific Preferences
(Poster) Najjar, Dina; Tsige Abebe, Meseret; Ouesalti, Dorsaf; Zeleke, Muluken; M. Oumer, Ali; Sanchez-Garcia, Miguel; Frija, Aymen; Wamatu, Jane
Barley is a key staple crop in Ethiopia, crucial for food security, malt production, and livestock feed. Smallholder farmers rely heavily on traditional landraces, making them particularly vulnerable to climate change and yield variability (Mohammed et al., 2016; Wada et al., 2022). This study aims to inform trait prioritization for the delivery of high yielding barley genotypes with tolerance to biotic and abiotic stresses, while integrating gender-specific preferences in the breeding process to enhance adoption rates and ensure food security. Women play a pivotal role in agriculture, yet their preferences in seed traits are often overlooked, especially in the Global South (Puskur et al., 2021). This gap leads to the development of crops that do not adequately address the needs of all farmers, particularly in terms of resilience, nutritional quality, and labor requirements (Weltzien et al., 2019; Badstue et al., 2022). The focus of this research is to explore gender-based preferences for seed traits and their implications for agricultural productivity and food security. We attend to the question of what role does a multi-stakeholder approach plays in identifying and incorporating trait preferences for barley varieties, including food and feed traits, to enhance the adoption rates among smallholder farmers in Ethiopia? Our study highlights the importance of incorporating women’s preferences into breeding programs to improve adoption, and benefits, and ensure sustainable agricultural practices.
ICARDA’s Research on Rangeland Governance and Pastoral Development: Institutional Arrangements for Economic Development
(Poster, 2023-04-29) Frija, Aymen
ICARDA’s Research on Rangeland Governance and Pastoral Development: Institutional Arrangements for Economic Development
Harnessing Artificial Intelligence-Chat GPT (Generative Pretrained Transformer) to engage youths and women in climate-smart, sustainable livestock farming
(Poster, 2023-09-01) Ekule, Muluken; Wamatu, Jane
Harnessing Artificial Intelligence-Chat GPT (Generative Pretrained Transformer) to engage youths and women in climate-smart, sustainable livestock farming.
Field evaluation of bread and durum wheat varieties for Septoria Tritici Blotch resistance in Morocco
(Poster) Maafa, Ilyass; Bentata, Fatiha; Labhilili, Mustapha.; Kemal, Seid Ahmed; El Aissam, Aicha
Septoria tritici blotch (STB) caused by Zymoseptoria tritici, is one of the devastating foliar diseases on bread and durum wheat production in Morocco. It causes up to 50% yield losses where susceptible wheat varieties are grown under weather conditions conducive to STB development. Farmers integrate growing moderately resistant varieties with additional sprays with fungicides. There are reports of Z. tritici isolates resistant to quinone outside inhibitor (QoIs) : a widely used group of fungicides in wheat disease management (1 & 2). The continuous virulence evolution of Z. tritici populations leads to losses of resistance in popular wheat varieties. The objective of this study was to assess if there are changes in the resistance of Moroccan wheat varieties released between 1982-2003 to the current field pathogen populations
Potential of Volatile Organic Compounds in the management of insect pests and diseases of chickpea
(Poster) Makhlouf, Leila; Maafa, Ilyass; Boulamtat, Rachid; El-Fakhouri, Karim; Aasfar, Abderrahim; Kemal, Seid Ahmed; Meftah Kadmiri, Issam; El Bouhssini, Mustapha
Chickpea (Cicer arietinum) is the second legume crop cultivated in Morocco after the Faba bean, and presents economical and nutritional benefits. However, the crop productivity is low due to biotic factors and drought. Ascochyta blight (Didymella rabiei), Fusarium wilt (Fusarium oxysporum f.sp. Ciceris), and leaf miner (Liriomyza cicerina) are key production constraints in spring-planted chickpeas.
Genome-wide association study of elite spring bread wheat (triticum aestivum l.) genotypes under drought conditions across different locations
(Poster) Ed-Daoudy, Lamyae; Zakaria, EL Gataa; Sbabou, Laila; Tadesse, Wuletaw
Drought, is the main abiotic stressor that significantly reduces bread wheat's grain yield and related-traits. A genome-wide association study was conducted using the 10K wheat SNP markers for grain yield and related traits of 246 spring bread wheat genotypes from ICARDA to identify the genomic regions and marker-trait associations (MTAs) responsible for drought tolerance. Grain yield (GY), days to heading (DHE), days to maturity (DMA), plant height (PLH), and thousand kernel weight (TKW), were evaluated at Merchouch sta tion (Morocco); in the other hand only grain yield that was considered for the rest of the environments; Terbol (Lebanon), Kheferdan (Sudan), and ARC (Egypt), as well as Tassaout, and Sidi El Aidi (Morocco); spanning two years 2015-2016 and 2016-2017, as per variance analysis. Grain yield and related-traits showed a considerable variation among geno types. Moreover, GWAS using a mixed linear model (MLM), revealed 53 MTAs across the six environments on 14 chromosomes. With an average r 2 value of 0.26, Genome D has the highest linkage, followed by Genomes B and A with r2 values of 0.22 and 0.21, respectively. GY had the highest MTA rating (35), followed by TKW (9) and 3 for each of the other agronomic traits (DHE, DMA, PLH) at Merchouch station. “CAP8_c1393_327” was the most significant associated marker correlated with grain yield located on chromosome 3A across Sid El Aidi station. Additionally, the SNP markers “wsnp_Ra_c26091_35652620” displayed extremely significant and stable MTA for TKW on chromosome 5B at Merchouch station. The markers and candidate genes reported throughout this study have the potential to be used in marker-assisted selection to enhance wheat genotypes in terms of yield and resistance to drought limitations.
Breaking wheat-based monocropping system through scaling of diverse crops and varieties in the highlands of Ethiopia
(Poster) Kemal, Seid Ahmed; Bishaw, Zewdie; Aynewa, Yetsedaw; Mekonnen, Kindu; Asfaw, Addisu; Alene, Temesgen; Ebrahim, Mohammed; Dubale, Workneh; Gebreyes, Million; Thorne, Peter; Seifu, Haimanot
Bread wheat is the third important food crop in the highlands of Ethiopia. Monocropping and rust disease epidemics remain challenges to increase bread wheat productivity and production. One of the strategies used in the AFRICA RISING (2012-2022) project was re-introducing high-yielding food and malt barley, durum wheat, and food legumes into the bread wheat-based cropping system through participatory variety selection (Phase I) and, community seed production and scaling (Phase-II)
Evaluation and Association Mapping of Bread Wheat (Triticum aestivum) pre-breeding Lines for Reaction to Leaf Rust (Puccinia triticina)
(Poster) Amounane, Fatima; Backhaus, Anna Elisabeth; Moulakat, Adil; Al-Jaboobi, Muamar; Amri, Ahmed; Belquadi, Loubna; Kehel, Zakaria
Bread wheat was domesticated 8,000 years ago and spread over the world and became the staple food of major civilizations in Europe, Western Asia, and North Africa. Today, around 95% of the wheat grown in the world is hexaploid wheat, Triticum aestivum (2n= 42 chromosomes). In order to meet the food demand of a growing human population and address food security challenges, it is essential to enhance economically important traits of bread wheat. Genetic resources conserved in gene banks are often considered to be important gene pools for breeding programmes. However, they require additional work, such as thorough evaluation and preselection efforts, to discover their crucial value and meet breeders' objectives. Within this context, the objectives of our study were to 1) carry out an evaluation of 480 bread wheat prebreeding lines derived from interspecific crosses with different crop wild relative species for resistance to leaf rust and 2) identify associated markers using the GWAS approach. The 480 lines were evaluated for resistance to leaf rust at the seedling stage under controlled conditions using a mixture of three isolates in an augmented experimental design. The study revealed a high genetic component of leaf rust with a heritability of 0.8. Approximately 34% of the lines showed resistance or immunity to leaf rust, 22% exhibited moderate resistance, and 43.54% displayed moderate susceptibility to high susceptibility. The highest number of lines expressing an Immune and resistant type of disease reaction was recorded in lines crossed with Aegilops bicornis var. bicornis (62%) followed those issued from crosses with Aegilops ovata IGAECO96-21(14%). The GWAS analysis performed using 3897 DarTag markers, revealed four DarTag markers on 1D, 3A , 5A and 6D to be in significant linkage with the disease resistance. In conclusion, this study highlights the importance of crop wild relatives as a source of valuable genetic diversity resistance to leaf rust. The associated markers presented here can improve the efficiency of breeding new resistant bread wheat varieties.
Assessing Genotype by Environment Interaction in a Diverse Barley Panel for Enhanced Breeding Strategies in Morocco
(Poster) Moulakat, Adil; Kehel, Zakaria; Bouhlal, Outmane; Ibriz, Mohammed; Sanchez-Garcia, Miguel
Barley (Hordeum vulgare) is an important cereal crop cultivated over a wide range of environments and in diverse agro-ecologies in Morocco. Genotype by environment interaction (GxE) has important consequences in barley breeding. It complicates testing and selection of superior genotypes and reduces genetic progress in breeding programs. The use of a diversity panel is an important component in a breeding program to understand GxE, traits linkage and feed crossing-blocks with the necessary diversity.
Artificial Intelligence in Genebanks: Seed Multispectral Analysis for Germplasm Integrity and Targeted Breeding Traits
(Poster) Zaher, Oumaima; Choukri, Hasnae; Moulakat, Adil; Tsivelikas, Athanasios; Kehel, Zakaria
Artificial Intelligence in Genebanks: Seed Multispectral Analysis for Germplasm Integrity and Targeted Breeding Traits.
Participatory action research for changing gender norms and achieving women’s and youth’s empowerment in mixed barley-livestock systems in Ethiopia
(Poster) Najjar, Dina; Tsige, Meseret; M. Oumer, Ali; Frija, Aymen; Ekule, Muluken; Wamatu, Jane; Haile, Aynalem; Sanchez-Garcia, Miguel
Far less attention is given to the social domains of Sustainable Intensification (SI). However, to intensify agricultural production sustainably, technical solutions must be paired with the social, economic and political innovations that can support their adoption by smallholder farmers (Barrett et al. 2020; Cook et al. 2015; Kuyah et al. 2021). The need for better understanding of broader contextual issues to enable the realization of pathways forward to improve SI adoption is often reiterated as a gap in theoretical and applied assessment literature. We employ participatory action research that focuses on bundling of social and technical aspects with regards to sheep fattening and improved barley varieties. We focus on social networks and institutions that affect access to knowledge and key farming resources and take an intersectional approach to gender. We work with producers, private companies, consumers, processors (many of whom are landless women), breeders, sellers and traders to enable access to better varieties and breeds and more sustainable practices. We focus on collective action for enabling access to information, inputs, essential networks and overcoming harmful social norms.
Unveiling Drought-Resilient Pathways: Integrating High Throughput Phenotyping and Multivariate Modeling to Enhance Barley Adaptation to Climate Change
(Poster) Ouahid, Safae; Backhaus, Anna Elisabeth; Jimenez, José-Antonio; Visioni, Andrea; Sanchez-Garcia, Miguel
The increasing threat of climate change makes developing drought-resilient crops ever more important. Barley (Hordeum vulgare), is a highly drought-tolerant cereal and a key player in the future of farming. Moreover, the pivotal role of plant architecture, development patterns and roots in conferring drought tolerance to plants has been understudied, despite their potential importance for drought tolerance. In this context, we delve into the intricate interplay between barley plants and the environment – specially drought - with a distinct focus on leveraging multi-data integration and machine learning techniques to analyse high throughput phenotyping data from the field. By employing automated ground-based platforms, such as the Phenomobile equipped with multi-spectral, RGB cameras, LiDAR and the Physiotron – a lysimeter with a multi-sensor bridge – that provides controlled environmental conditions for in-depth study of roots, for monitoring responses to stress with unmatched precision, we can capture large data encompassing many critical phenotypic indicators at plot and field level. This large dataset is subjected to multivariate modeling to discover complex relationships between multiple traits and environmental factors. We concentrate on predicting complex traits such as root traits, biomass accumulation, yield, stress responses that are fundamental to barley's resilience under stress. Leveraging the power of machine learning with phenomics and genotypic data holds the promise of unraveling the complex relationships between genetic makeup and observable traits enabling us to understand the fundamental genetic drivers of various phenotypic characteristics By identifying hidden correlations and interdependencies, our models will enable the prediction of phenotypic traits of interest under different stress conditions, offering invaluable insights into barley’s drought resistance potential and performance. Our work will highlight the importance of data integration and machine learning to unlock the potential of agricultural research.
Development of bread wheat genotypes for multiple resistance to foliar diseases
(Poster) Al-Jaboobi, Muamar; Tadesse, Wuletaw; Louriki, Sara; Zakaria, EL Gataa; Kemal, Seid Ahmed
Global food security and sustainable wheat production are both constantly threatened by increased human population. Yellow rust (Puccinia striiformis f. sp. tritici) stem rust (P.graminis f. sp. tritici) and Septoria tritici blotch , ((Zymoseptoria tritici) are the major challenges for sustainable wheat production in different countries around the world. The three wheat rusts are the most damaging diseases in world and continue threatening global food security ( Bhavani et al. 2022). Genetic resistance is the key objective of the bread breeding program. Many varieties are released in many countries and losses of resistance

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