Revisiting the ignored Ethiopian durum wheat (Triticum turgidum var. durum) landraces for genetic diversity exploitation in future wheat breeding programs

The majority of Ethiopian durum wheat are farmers’ varieties. Durum wheat varieties under production in Ethiopia are less productive due to the effect of climate change and marginalism of agricultural inputs. Recognizant to these, revisiting farmers varieties, ex-situ conserved, could be among the best options to adapt these changes. This study has thoroughly characterized a set of 49 durum wheat varieties to assess the level of phenotypic diversity through multivariate approaches for traits of importance. The study was aimed at estimating the extent of genetic diversity among the genotypes and to identify traits maximally contributing to the observed phenotypic variations. The statistical analyses have confirmed that the genotypes have shown very large (p<0.001) variations for most traits considered, except for number of effective tillers. The estimated broad – sense heritability (h2) has ranged from 20% for grain yield to 78% for spike length. The genotypes were grouped into six clusters with significant inter-cluster distances (χ2=15.51, p<0.05). The clustering revealed that the landraces are genetically far from the improved varieties. Genotypes consisted in a particular cluster are superior for a trait or more compared to the other clusters. For instance, genotypes in the first cluster are superior for grain and biomass yields. Early maturing and second high yielding genotypes were consisted in the fifth cluster. The genotype – by – traits biplot analysis has explained 82% of the total variation where 65.5% was explained by PC1, indicating that most of the observed variation is inherited. It can be concluded that the landraces are quite divergent from the improved varieties and the within landraces diversity was also high indicating that they represent important gene pool for important traits. Hence, revisiting landraces, which are Ex-situ conserved, and their exploitation in durum wheat breeding programs for grain yield improvement, earliness and other traits of importance is crucial

Research site selection for SI-FMS initiative at Basona Worena woreda

Ethiopia is among the five implementors of this initiative and the implementing team composed of individuals from various CG centres based in Addis Ababa, Ethiopia has made visited to the agreed project sites in Ethiopia on 30 August 2022. In north Shewa, it was agreed that Basona Worena will be the implementing site of this initiative activities. On this day, SI – MFS initiative implementing team composed of researchers from Alliance of Bioversity International and CIAT, ICARDA and ILRI has travelled to Debre Birhan area to select research site for integrated research efforts and technology aggregations. The objective of the site selection was to implement research interventions and improve the land, crop, and livestock productivity through sustainable intensification of the mixed farming system (SI-FMS) initiative. The team has discussed with Basona Worena Woreda of Agriculture and livestock offices to identify the specific project implementation kebele. After the purpose of the initiative was discussed site selection criteria was set to select the implementation kebele

Productivity of mixtures and evolutionary populations of wheat, barley, beans and rice

Mixtures of different varieties of barley (Hordeum vulgare), wheat (Triticum ssp.) are grown by farmers in Ethiopia, Iran, Jordan, as a means of diversifying production and/or coping with difficult or uncertain growing conditions. Similarly, mixtures of different varieties of beans (Phaseolus vulgaris) were grown by farmers in Bhutan, Nepal and Uganda, with mixtures of Rice (Oryza sativa) were also grown by Bhutan and Nepal farmers. The mixture of all crops in all countries were grown for three consecutive years under IFAD – EPB project. Varietal diversity can improve farmers’ productivity, capabilities to manage pests and diseases and allows farmers to select suitable cultivars in response to varied or uncertain climatic conditions. Moreover, varietal diversification can improve the nutritional security of smallholder farmers

Data-driven decentralized breeding increases prediction accuracy in a challenging crop production environment

Crop breeding must embrace the broad diversity of smallholder agricultural systems to ensure food security to the hundreds of millions of people living in challenging production environments. This need can be addressed by combining genomics, farmers’ knowledge, and environmental analysis into a data-driven decentralized approach (3D-breeding). We tested this idea as a proof-of-concept by comparing a durum wheat (Triticum durum Desf.) decentralized trial distributed as incomplete blocks in 1,165 farmer-managed fields across the Ethiopian highlands with a benchmark representing genomic prediction applied to conventional breeding. We found that 3D-breeding could double the prediction accuracy of the benchmark. 3D-breeding could identify genotypes with enhanced local adaptation providing superior productive performance across seasons. We propose this decentralized approach to leverage the diversity in farmer fields and complement conventional plant breeding to enhance local adaptation in challenging crop production environments.publishedVersio

Improving Grain Micronutrient Content of Durum Wheat (Triticum turgidum var. durum) through Agronomic Biofortification to Alleviate the Hidden Hunger

Improvement of durum wheat grain quality through agronomic biofortification becomes a priority research area and an effective route to combat malnutrition. An experiment was conducted to evaluate the effect of micronutrient application to different varieties of durum wheat and seeding rate on final harvest grain quality under different growing locations. The treatments were arranged in split-split plot design where the varieties were assigned in the main plot, micronutrients into the subplots, and seeding rate into the sub-subplots. Each variety was sown at four levels of seeding rates and treated with ZnSO₄ and FeSO4 applied foliarly, both at a rate of 25 Kg ha−1 during flowering. Micronutrients were applied in the form of ZnSO₄ 7H2O and FeSO₄ 7H2O. The study confirmed that application of 25 Kg ha−1 ZnSO₄-containing fertilizer has increased mineral content from 33.04 mg Kg−1 to 56.73 mg kg−1. The tested durum wheat varieties significantly differ in their capacity to accumulate grain Zn and Fe concentrations. Higher amount of Zn (20 mg kg−1) and Fe (10 mg kg−1) were accumulated by the landrace 208304 than by Asassa, an improved commercial variety. Increasing seeding rate from 100–175 Kg ha−1 has reduced grain Zn and Fe concentrations. Grain mineral concentration was significantly lower at the Mekelle location than at the Melfa location. It can be concluded that foliar application of ZnSO₄ and FeSO4 to the landrace, acc.208304, combined with 125 Kg seeds ha−1 can produce better Zn and Fe denser durum wheat grain. This will help to combat the hidden hunger, especially in resource poor countries, where fortified foods are limited in access and unaffordable by small-scale farmers

Diversity and traditional use knowledge of medicinal plants among communities in the South and South-Eastern zones of the Tigray Region, Ethiopia

In the present study, the diversity of medicinal plants (MPs) and associated traditional knowledge of rural community herbalists to treat human and animals’ diseases were assessed in two districts in the Tigray Region, Ethiopia. Study participants were randomly selected for survey and focus group discussions, while key informant traditional healers were identified through snowball/chain-referral sampling. The informant consensus factor (FIC) by ailment category and fidelity level (FL) for some MPs were determined. About 97 MP species were identified. Leaves, roots, and seeds are the parts predominantly used for phytomedication preparation to treat 30 human and 5 animal diseases. Diseases, such as epilepsy, arthritis, otitis media, and fever, are treated with a combination of 2–4 MPs. The FIC value ranged from 0.29–1.00, with most human diseases showing an FIC value of above 0.7. The FL value for the MPs ranged from 53–100%, with plants used to treat more than one disease tending to have lower FL values. Higher values of FIC and FL indicate high levels of traditional knowledge used to identify and administer medicinal preparations. Despite the frequent use of MPs, the four-cell analysis showed that most of them risk extinction due anthropogenic and climate factors. We recommend botanical gardens as a solution to sustainable conservation, study, education and a source for these declining MP species

First experiences with a novel farmer citizen science approach : crowdsourcing participatory variety selection through on-farm triadic comparisons of technologies (tricot)

Rapid climatic and socio-economic changes challenge current agricultural R&D capacity. The necessary quantum leap in knowledge generation should build on the innovation capacity of farmers themselves. A novel citizen science methodology, triadic comparisons of technologies or tricot, was implemented in pilot studies in India, East Africa, and Central America. The methodology involves distributing a pool of agricultural technologies in different combinations of three to individual farmers who observe these technologies under farm conditions and compare their performance. Since the combinations of three technologies overlap, statistical methods can piece together the overall performance ranking of the complete pool of technologies. The tricot approach affords wide scaling, as the distribution of trial packages and instruction sessions is relatively easy to execute, farmers do not need to be organized in collaborative groups, and feedback is easy to collect, even by phone. The tricot approach provides interpretable, meaningful results and was widely accepted by farmers. The methodology underwent improvement in data input formats. A number of methodological issues remain: integrating environmental analysis, capturing gender-specific differences, stimulating farmers' motivation, and supporting implementation with an integrated digital platform. Future studies should apply the tricot approach to a wider range of technologies, quantify its potential contribution to climate adaptation, and embed the approach in appropriate institutions and business models, empowering participants and democratizing science.</p

Data-driven decentralized breeding increases prediction accuracy in a challenging crop production environment

Crop breeding must embrace the broad diversity of smallholder agricultural systems to ensure food security to the hundreds of millions of people living in challenging production environments. This need can be addressed by combining genomics, farmers’ knowledge, and environmental analysis into a data-driven decentralized approach (3D-breeding). We tested this idea as a proof-of-concept by comparing a durum wheat (Triticum durum Desf.) decentralized trial distributed as incomplete blocks in 1,165 farmer-managed fields across the Ethiopian highlands with a benchmark representing genomic prediction applied to conventional breeding. We found that 3D-breeding could double the prediction accuracy of the benchmark. 3D-breeding could identify genotypes with enhanced local adaptation providing superior productive performance across seasons. We propose this decentralized approach to leverage the diversity in farmer fields and complement conventional plant breeding to enhance local adaptation in challenging crop production environments

FIRST EXPERIENCES WITH A NOVEL FARMER CITIZEN SCIENCE APPROACH: CROWDSOURCING PARTICIPATORY VARIETY SELECTION THROUGH ON-FARM TRIADIC COMPARISONS OF TECHNOLOGIES (TRICOT)

SUMMARYRapid climatic and socio-economic changes challenge current agricultural R&amp;D capacity. The necessary quantum leap in knowledge generation should build on the innovation capacity of farmers themselves. A novel citizen science methodology, triadic comparisons of technologies or tricot, was implemented in pilot studies in India, East Africa, and Central America. The methodology involves distributing a pool of agricultural technologies in different combinations of three to individual farmers who observe these technologies under farm conditions and compare their performance. Since the combinations of three technologies overlap, statistical methods can piece together the overall performance ranking of the complete pool of technologies. The tricot approach affords wide scaling, as the distribution of trial packages and instruction sessions is relatively easy to execute, farmers do not need to be organized in collaborative groups, and feedback is easy to collect, even by phone. The tricot approach provides interpretable, meaningful results and was widely accepted by farmers. The methodology underwent improvement in data input formats. A number of methodological issues remain: integrating environmental analysis, capturing gender-specific differences, stimulating farmers' motivation, and supporting implementation with an integrated digital platform. Future studies should apply the tricot approach to a wider range of technologies, quantify its potential contribution to climate adaptation, and embed the approach in appropriate institutions and business models, empowering participants and democratizing science