CGIAR Initiative on Accelerated Breeding
Permanent URI for this collectionhttps://hdl.handle.net/10568/117883
Part of the CGIAR Action Area on Genetic Innovation
Primary CGIAR impact area: Nutrition, health and food security
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Item Near-infrared spectroscopy and wet chemistry dataset for forage nutritional quality assessment in Urochloa humidicola(Data Paper, 2025-05-13) Camelo, Rodrigo Andres; Mazabe, Johanna; Espitia-Buitrago, Paula; Jauregui, Rosa Noemi; Cardoso, Juan AndresAssessing the nutritional quality traits of pastures is crucial for germplasm and breeding evaluations, enabling the selection of high-quality forages to enhance livestock productivity. However, traditional laboratory analytical methods are logistically demanding and costly, particularly in large-scale trials, underscoring the need for rapid, precise, and high-throughput evaluation methods. Near-Infrared Spectroscopy (NIRS) optimizes the estimation of forage nutritional quality parameters by developing chemometric models that predict these parameters with high accuracy and precision, based on the association between NIRS data and wet chemistry analyses. This dataset, collected over ten years by the Tropical Forages Program at the International Center for Tropical Agriculture (CIAT) in Colombia, comprises 1112 samples. It includes 995 measurements of Neutral Detergent Fiber (NDF), 996 of Acid Detergent Fiber (ADF), 995 of In Vitro Dry Matter (IVDMD), and 469 of Crude Protein (CP), all obtained through wet chemistry methodologies. Additionally, the 1112 samples contain absorbance data spanning 400 to 2498 nanometers (nm) in 2 nm intervals, generating 1050 spectral data points per sample. Finally, this dataset is a valuable resource for predicting forage nutritional quality beyond conventional parameters, incorporating plant reflectance attributes to enhance selection strategies for optimized forage selection.Item Phenylalanine ammonia-lyase 2 regulates secondary metabolism and confers manganese tolerance in Stylosanthes guianensis(Journal Article, 2025-01-06) Wang, Linjie; Li, Jifu; Liu, Liting; Dong, Rongshu; Liu, Guodao; Idupulapati, Rao; Chen, ZhijianItem Updating high-resolution image dataset for the automatic classification of phenological stage and identification of racemes in Urochloa spp. hybrids with expanded images and annotations(Data Paper, 2025-04-28) Arrechea-Castillo, Darwin Alexis; Espitia-Buitrago, Paula; Florian-Vargas, David; Estupinan, Ronald David; Velázquez-Hernández, Riquelmer; Ruiz-Hurtado, Andres Felipe; Hernandez, Luis Miguel; Jauregui, Rosa Noemi; Cardoso, Juan AndresThis dataset is an expanded version of a previously published collection of high-resolution RGB images of Urochloa spp. genotypes, initially designed to facilitate automated classification of phenological stages and raceme identification in forage breeding trials. The original dataset included 2400 images of 200 genotypes captured under controlled conditions, supporting the development of computer vision models for High-Throughput Phenotyping (HTP). In this updated release, 139 additional images and 24,983 new annotations have been added, bringing the dataset to a total of 2539 images and 47,323 raceme annotations. This version introduces increased diversity in image-capture conditions, with data collected from two geographic locations (Palmira, Colombia, and Ocozocoautla de Espinosa, Mexico) and a range of image-capture devices, including smartphones (e.g. Realme C53 and Oppo Reno 11), a Nikon D5600 camera, and a Phantom 4 Pro V2 drone. Images now vary in perspective (nadir, high-angle, and frontal) and capture distance (1–3 meters), enhancing the dataset applicability for robust Deep Learning (DL) models. Compared to the original dataset, raceme density per plant has nearly doubled in some samples, offering higher raceme overlap for advanced instance segmentation tasks. This expanded dataset supports deeper exploration of phenotypic variation in Urochloa spp. and offers greater potential for developing adaptable models in crop phenotyping.Item Citizen science informs demand-driven breeding of opportunity crops(Journal Article, 2025-05-13) Voss, Rachel C.; De Sousa, Kaue; N'Danikou, Sognigbé; Shango, Abdul; Aglinglo, Lys Amavi; Laporte, Marie-Angelique; Legba, Eric C.; Houdegbe, Aristide Carlos; Diarra, Danfing dit Youssouf; Dolo, Aminata; Sidibe, Amadou; Ouedraogo, Colette Ouidyam; Coulibaly, Harouna; Achigan-Dako, Enoch G.; Kileo, Aishi; Malulu, Dickson; Matumbo, Zamira; Dinssa, Fekadu; van Heerwaarden, Joost; Van Etten, Jacob; Riar, Amritbir; van Zonneveld, MaartenItem BrRacemeCounter: An AI-based desktop tool for counting racemes in Urochloa spp.(Journal Article, 2025-05-08) Arrechea-Castillo, Darwin Alexis; Espitia-Buitrago, Paula; Arboleda, Ronald David; Gallego-Muñoz, Ana Marcela; Moreno-Domínguez, Valeria; Gaviria-Valencia, Juan Manuel; Bravo, Valeria Andrea; Ruiz-Hurtado, Andres Felipe; Jauregui, Rosa Noemi; Cardoso, Juan AndresSeed yield prediction in forage plants involves the detection and counting of individual racemes that comprise an inflorescence. However, this task is labor-intensive to perform manually across large numbers of plants and overly complex for classical machine learning techniques due to challenges such as high raceme overlap, large variations in raceme numbers per image and spectral signature similarities between the racemes and the vegetative parts of the plant. To address these challenges, a deep learning-based desktop tool was implemented to count individual racemes in RGB images of Urochloa genotypes, showing different phenological stages and wide variation in number of racemes per plant.Item Shaping the future of bananas: advancing genetic trait regulation and breeding in the post-genomics era(Journal Article, 2025-02-12) Miao, Hongxia; Zhang, Jianbin; Zheng, Yunke; Jia, Caihong; Hu, Yulin; Wang, Jingyi; Zhang, Jing; Sun, Peiguang; Jin, Zhiqiang; Zhou, Yongfeng; Zheng, Sijun; Wang, Wei; Rouard, Mathieu; Xie, Jianghui; Liu, JuhuaItem CGIAR Research Initiative on Accelerated Breeding: Annual Technical Report 2024(Report, 2025-04-15) CGIAR Initiative on Accelerated BreedingItem Costing report: White/Cream Fleshed Product Profile. National Crops Resources Research Institute (NaCRRI)(Report, 2024-10) Yada, B.; Otema, M.; Chelangat, D.M.; Osaru, F.; Musana, P.; Atugonza, K.; Wembabazi, E.; Kisseka, F.; Alajo, A.; Namakula, J.; Aboyo, R.; Sunday, L.; Asiimwe, J.; Nusula, N.; Nakasujja, F.; Nakimera, G.; Alalo, M.D.; Wasswa, G.Item Costing of White Fleshed Sweetpotato pipeline by CIP in Mozambique(Report, 2024-10) Makunde, G.S.; Madroba, G.; Covele, G.; Langa, C.B.; Chichango, A.; Hélio, J.; Das, B.; Musundire, L.; Milic, D.; Odiyo, O.; Madahanna, S.; Mutiga, S.Item Costing of Orange Fleshed Sweetpotato pipeline by CIP in Mozambique(Report, 2024-10) Makunde, G.S.; Madroba, G.; Covele, G.; Langa, C.B.; Chichango, A.; Hélio, J.; Das, B.; Musundire, L.; Milic, D.; Odiyo, O.; Madahanna, S.; Mutiga, S.Item Post-composing ontology terms for effcient phenotyping in plant breeding(Journal Article, 2025) Menda, N.; Ellerbrock, B.J.; Simoes, C.C.; Karaikal, S.K.; Nyaga, C.; Flores-Gonzalez, M.; Tecle, I.Y.; Lyon, D.; Agbona, A.; Agre, A.P.; Peteti, P.; Akech, V.; Asiimwe, A.; Fauvelle, E.; Meghar, K.; Tran, T.; Dufour, D.; Cooper, L.; Laporte, M.A.; Arnaud, E.; Mueller, L.Ontologies are widely used in databases to standardize data, improving data quality, integration, and ease of comparison. Within ontologies tailored to diverse use cases, post-composing user-defined terms reconciles the demands for standardization on the one hand and flexibility on the other. In many instances of Breedbase, a digital ecosystem for plant breeding designed for genomic selection, the goal is to capture phenotypic data using highly curated and rigorous crop ontologies, while adapting to the specific requirements of plant breeders to record data quickly and efficiently. For example, post-composing enables users to tailor ontology terms to suit specific and granular use cases such as repeated measurements on different plant parts and special sample preparation techniques. To achieve this, we have implemented a post-composing tool based on orthogonal ontologies providing users with the ability to introduce additional levels of phenotyping granularity tailored to unique experimental designs. Post-composed terms are designed to be reused by all breeding programs within a Breedbase instance but are not exported to the crop reference ontologies. Breedbase users can post-compose terms across various categories, such as plant anatomy, treatments, temporal events, and breeding cycles, and, as a result, generate highly specific terms for more accurate phenotyping.Item Genome-wide association analysis of Septoria tritici blotch for adult plant resistance in elite bread wheat (Triticum aestivum L) genotypes(Journal Article) Kassie, Molla Mekonnen; Dejene, Tiegist; Desta, Ermias Abate; Tadesse, WuletawSeptoria tritici blotch (STB) is a predominant foliar disease of wheat, caused by the pathogen Zymoseptoria tritici. This disease can lead to substantial yield losses warranting control by using expensive fungicides. One effective method of STB control is the utilization of resistant wheat varieties. In this particular study, a panel comprising of 186 bread wheat genotypes was assessed for their adult plant resistance (APR) to STB. Field trials were conducted across five environments in Ethiopia during the 2022 and 2023 growing seasons under natural infestation conditions. The association panel was genotyped using 20K single nucleotide polymorphism (SNP) markers. To determine the relationship between genetic markers and STB resistance, a mixed linear model (MLM) analysis was performed using the statgen GWAS R software package. Heritability estimates for STB resistance ranged from 0.39 to 0.95, underscoring the genetic variability and the potential for selection. The study identified 52 marker-trait associations (MTAs) for STB resistance at maturity (SDSM) and 62 MTAs at heading (SDSH). Chromosome 5A contains a high concentration of MTAs that confer resistance to STB, hosting multiple significant MTAs, including four consistently associated markers (‘Kukri_c10033_724’, ‘RAC875_rep_c116420_103’, ‘TG0019’, and ‘RAC875_c30566_230’). Additionally, chromosomes 1B, 2B, 5B, and 7A were found to harbor important MTAs, contributing to resistance across various environments. Notably, two QTLs, qtSTB23 (5A) and qtSTB38 (7B), exhibited stability across multiple environments, making them robust candidates for breeding programs. Furthermore, novel resistance loci on chromosome 2A were discovered, offering new opportunities for enhancing resistance. Therefore, these findings provide an opportunity for improving STB resistance through gene stacking using marker-assisted selection (MAS).Item Expanding genomic prediction in plant breeding: harnessing big data, machine learning, and advanced software(Journal Article, 2025) Crossa, José; Martini, Johannes W.R.; Vitale, Paolo; Perez-Rodriguez, Paulino; Costa-Neto, Germano; Fritsche-Neto, Roberto; Runcie, Daniel E.; Cuevas, Jaime; Toledo, Fernando H.; Huihui Li; De Vita, Pasquale; Gerard, Guillermo S.; Dreisigacker, Susanne; Crespo-Herrera, Leonardo A.; Saint Pierre, Carolina; Bentley, Alison R.; Lillemo, Morten; Ortiz, Rodomiro; Montesinos-Lopez, Osval A.; Montesinos-López, AbelardoWith growing evidence that genomic selection (GS) improves genetic gains in plant breeding, it is timely to review the key factors that improve its efficiency. In this feature review, we focus on the statistical machine learning (ML) methods and software that are democratizing GS methodology. We outline the principles of genomic-enabled prediction and discuss how statistical ML tools enhance GS efficiency with big data. Additionally, we examine various statistical ML tools developed in recent years for predicting traits across continuous, binary, categorical, and count phenotypes. We highlight the unique advantages of deep learning (DL) models used in genomic prediction (GP). Finally, we review software developed to democratize the use of GP models and recent data management tools that support the adoption of GS methodology.Item Quantitative trait loci for phenology, yield, and phosphorus use efficiency in cowpea(Journal Article, 2025) Mohammed, S.B.; Ongom, P.O.; Belko, N.; Umar, M.L.; Munoz-Amatriain, M.; Huynh, B.; Togola, A.; Ishiyaku, M.F.; Boukar, O.Background/Objectives: Cowpea is an important legume crop in sub-Saharan Africa (SSA) and beyond. However, access to phosphorus (P), a critical element for plant growth and development, is a significant constraint in SSA. Thus, it is essential to have high P-use efficiency varieties to achieve increased yields in environments where little-to- no phosphate fertilizers are applied. Methods: In this study, crop phenology, yield, and grain P efficiency traits were assessed in two recombinant inbred line (RIL) populations across ten environments under high- and low-P soil conditions to identify traits’ response to different soil P levels and associated quantitative trait loci (QTLs). Single-environment (SEA) and multi-environment (MEA) QTL analyses were conducted for days to flowering (DTF), days to maturity (DTM), biomass yield (BYLD), grain yield (GYLD), grain P-use efficiency (gPUE) and grain P-uptake efficiency (gPUpE). Results: Phenotypic data indicated significant variation among the RILs, and inadequate soil P had a negative impact on flowering, maturity, and yield traits. A total of 40 QTLs were identified by SEA, with most explaining greater than 10% of the phenotypic variance, indicating that many major-effect QTLs contributed to the genetic component of these traits. Similarly, MEA identified 23 QTLs associated with DTF, DTM, GYLD, and gPUpE under high- and low-P environments. Thirty percent (12/40) of the QTLs identified by SEA were also found by MEA, and some of those were identified in more than one P environment, highlighting their potential in breeding programs targeting PUE. QTLs on chromosomes Vu03 and Vu08 exhibited consistent effects under both high- and low-P conditions. In addition, candidate genes underlying the QTL regions were identified. Conclusions: This study lays the foundation for molecular breeding for PUE and contributes to understanding the genetic basis of cowpea response in different soil P conditions. Some of the identified genomic loci, many being novel QTLs, could be deployed in marker-aided selection and fine mapping of candidate genes.Item High-throughput field screening of cassava brown streak disease resistance for efficient and cost-saving breeding selection(Journal Article, 2025) Sikirou, M.; Adetoro, N.A.; Sheat, S.; Musungayi, E.; Musungangan, R.; Pierre, M.; Fowobaje, K.R.; Dieng, I.; Bamba, Z.; Rabbi, I.Y.; Mushoriwa, H.; Winter, S.Cassava brown streak disease (CBSD) remains the most severe threat to cassava production in the Great Lakes region and Southern Africa. Screening for virus resistance by subjecting cassava to high virus pressure in the epidemic zone (hotspots) is a common but lengthy process because of unpredictable and erratic virus infections requiring multiple seasons for disease evaluation. This study investigated the feasibility of graft-infections to provide a highly controlled infection process that is robust and reproducible to select and eliminate susceptible cassava at the early stages and to predict the resistance of adapted and economically valuable varieties. To achieve this, a collection of cassava germplasm from the Democratic Republic of Congo and a different set of breeding trials comprising two seed nurseries and one preliminary yield trial were established. The cassava varieties OBAMA and NAROCASS 1 infected with CBSD were planted one month after establishment of the main trials in a 50 m2 plot to serve as the source of the infection and to provide scions to graft approximately 1 ha. Grafted plants were inspected for virus symptoms and additionally tested by RT-qPCR for sensitive detection of the viruses. The incidence and severity of CBSD and cassava mosaic disease (CMD) symptoms were scored at different stages of plant growth and fresh root yield determined at harvesting. The results from the field experiments proved that graft-infection with infected plants showed rapid symptom development in susceptible cassava plants allowing instant exclusion of those lines from the next breeding cycle. High heritability, with values ranging from 0.63 to 0.97, was further recorded for leaf and root symptoms, respectively. Indeed, only a few cassava progenies were selected while clones DSC260 and two species of M. glaziovii (Glaziovii20210005 and Glaziovii20210006) showed resistance to CBSD. Taken together, grafting scions from infected cassava is a highly efficient and cost-effective method to infect cassava with CBSD even under rugged field conditions. It replaces an erratic infection process with a controlled method to ensure precise screening and selection for virus resistance. The clones identified as resistant could serve as elite donors for introgression, facilitating the transfer of resistance to CBSD.Item Genetic parameter estimates and selection gain for multiple traits in white Guinea yam (Dioscorea rotundata) in Ghana(Journal Article, 2025) Darkwa, K.; Adjei, E.A.; Chamba, E.B.; Sayibu, A.; Amegbor, I.K.; Agyapong, F.A.; Sayibu, Z.; Sayibu, I.; Kangmennaang, M.; Issifu, M.; Agre, P.A.; Adebola, P.; Asfaw, A.Quantifying selection gains enables a more targeted assessment of breeding program effectiveness, highlighting opportunities for strategic improvement and optimized genetic advancement in white Guinea Yam. This study assessed genetic parameters and gain for key traits in a white Guinea yam (D. rotundata) breeding population. A total of 81 genotypes were evaluated for two seasons using a 9 × 9 lattice design with three replicates. Data was collected on yam mosaic virus disease severity, tuber yield and tuber dry content for genetic analysis. Broad sense heritability was generally high (> 60) for most of the traits. At the same time, the corresponding genetic advance as a percentage of the mean was exceptionally high (30.28–93.96%) for tuber yield, tuber flesh oxidation, average tuber weight and number of tubers per plant, suggesting additive genetic effects. A multi-trait selection index of the 5% highest performing genotypes revealed positive genetic gain for plant vigour, tuber length, and width, tuber weight per plant, average tuber weight and fresh tuber yield. The genetic gain was, however, negative for tuber dry matter content compared to the check varieties, necessitating a modification of the current breeding scheme such that post-harvest food quality is not sacrificed for tuber yield. Ranking of the breeding lines based on the multi-trait selection index identified four lines (TDr1700004_014, TDr1700004_113, TDr1700001_112 and TDr1700002_090) with high genetic merits for all the economic traits. These lines can be used as potential trait progenitors and evaluated further for possible release as new varieties. Our results decipher the genetic control and provide an overview of the performance of the breeding program for key traits in white Guinea yam.Item An alternative Semi-Autotropic Hydroponics (SAH) substrate for cassava rapid propagation: a first study case(Journal Article, 2024-12) Binzunga, M.M.; Kintche, K.; Sikirou, M.; Adetoro, N.; Dieng, I.; Angelique, K.; Mignouna, J.; Nyende, A.B.The expansion of Semi-Autotrophic Hydroponics technology to address the issue of multiplying and disseminating virus-free planting materials for vegetatively propagated crops is challenged by the utilization of imported substrate, namely, KlasmannTS3. In this study, we evaluated the growth parameters and cutting production of cassava genotypes during three subsequent plantlet production cycles using three single substrates, namely, KlasmannTS3 (K), vermiculite (V), and local peat (P), and three blended substrates. The blended substrates were a combination of 25% K and 75% P (K25P75), a combination of V and P at respective rates of 25% and 75% (V25P75), and respective rates of 10% and 90% (V10P90). All cuttings obtained in one plantlet production cycle were transplanted into the next. The multiplication rate of cutting from cycle 1 to 2 (R1) and cycle 2 to 3 (R2) was calculated as the ratios of the number of cuttings per the number of plantlets in each cycle. K and K25P75 led to similar R1 and R2, except with the genotype IBA961089A, where K25P75 led to a higher R1. Local peat and V solely showed similar cutting multiplication rates, and were lower than V25P75 and V10P90. Substrates with a higher cutting production also led to a higher plantlet height, leaf, and internode number. V and its combinations with local peat led to the densest plantlet root system. The performance of the substrates contrasted among the genotypes, but IBA961089A mostly outperformed the two other genotypes. We concluded that up to 75% of K and, to a lesser extent 75% of V, can be substituted by P without compromising cutting production. V and P should be combined instead of being used separately.Item Disina groundnut seed Hub: A game-changer for farmers in Bauchi State(Report, 2025) Mohammed, S.G.; Aliyu, Abdulmajid Abdussalam; Mohammed, Ismaila Y.; Puozaa, Doris KanvenaaItem Breaking barriers: How early maturing ground nut and pigeon pea varieties can transform farming communities(Report, 2025) Makweti, LutanguItem Private sector led multi-stakeholder platforms positively influence certified seed supply in Malawi(Journal Article, 2024-08-24) Gondwe, Wanangwa; Phiri, Alexander; Birachi, Eliud; Magreta, Ruth; Larochelle, Catherine; Machira, Kennedy; Mutua, Mercy; Rubyogo, Jean Claude; Nkhata, WilsonCommon bean yields in Malawi remain low, primarily due to the use of low-yielding, recycled local seeds by most smallholder farmers. The low uptake of certified bean seed is attributed to limited incentives from the private sector. This study hypothesizes that the sustainable adoption of market-preferred varieties can be achieved by synchronizing and linking seed production to the grain market through committed value chain actors in a private sector-led multi-stakeholder platform. This paper examines the role of private sector-led multi-stakeholder platforms in the supply of certified common bean seed in Malawi. The research draws on both qualitative and quantitative primary data collected through a semi-structured questionnaire and interviews with key informants. Data were analyzed using an Ordinary Least Squares (OLS) regression model. The results indicate that several variables representing membership in multi-stakeholder platforms (MSPs) significantly affect the supply of certified common bean seed. Participation in MSPs, contractual arrangements, market structure, extension services, and seed demonstrations positively influenced seed supply. The findings underscore the need for a well-coordinated multi-stakeholder platform to enhance the supply of certified common bean seed, supported by effective policies and incentives from policymakers.