Crowdsourcing seed-based innovations to improve diversity, nutrition and crop productivity

Crowdsourcing is a method of enlisting a group of people to work toward a common objective or solve a pressing issue, notably to ensure the sustainable expansion of agricultural activities. By using crowdsourcing, it is feasible to select the finest suggestions made by a large number of responders as opposed to depending simply on the credentials and experience of one individual. By seeking ideas and solutions from a broad group of individuals, crowdsourcing is superior to internal thought processes in many ways. This technique for variety selection improves seed systems by enhancing variety recommendations, enhancing on-farm testing, engaging and empowering farmers, aiding in the diversification of seed systems, supporting the scaling up of on-farm agricultural research, allowing women to make their own variety selections, supplying business opportunities for farmers, women, and young people, and helping researchers learn farmers' variety preferences. The primary techniques for putting crowdsourcing into practice include component identification, identifying farmers who are receiving various mixtures of varieties, seed preparation, site selection and planting, cultivation, measurements and observations, and proper harvesting

Epidemiological factors of septoria tritici blotch (Zymoseptoria tritici) in durum wheat (Triticum turgidum) in the highlands of Wollo, Ethiopia

Septoria tritici blotch (STB) (Zymoseptoria tritici) is a major disease of durum wheat, an economic crop grown in the highlands of Wollo in Ethiopia. To determine the status of this disease, we conducted surveys in five districts of Wollo (Meket, Woreilu, Wadila, Jama, and Dessie Zuria) during the 2015 cropping season. We visited 75 farm plots to determine the prevalence, incidence, and severity of STB. STB prevalence varied among locations, genotypes, planting dates, growth stages, previous crops, plant population, weed population, and soil types. Similarly, disease intensity also varied along all independent variables. The level of incidence was high in all the visited districts, and the level severity ranged from 9.9 to 59.3% while the incidence varied from 50 to 100%. The mean differences in incidence and severity within the districts’ variable classes, altitude, varieties, growth stage, plant population, planting date, previous crop, weed population, and soil type were high. The independent variables, districts, altitude, varieties, growth stage, plant population, planting date, previous crops, weed population, and soil type, were significantly associated with high incidence and severity of STB as single predictor in the logistic regression model. A reduced multiple variable model was fitted using districts, altitude, varieties, growth stage, plant population, planting date, previous crop, weed population, and soil type as independent variables. High incidence (> 50%) and severity (> 25%) had a high probability of association to all independent variables, except previous crop. Low disease incidence (≤ 50%) and low disease severity (≤ 25%) had high probability of association to the previous crop. Environmental variables, cultivation practice, and responses were important for the development of STB. Therefore, these factors must be considered in designing strategies for the effective management of STB

“Seeds for Needs” experience to improve diversity, nutrition and crop productivity

The agricultural industry in Ethiopia is dominated by smallholder farming and rain-fed food production systems that are struggling with dwindling diversity and expanding mono- cropping. In order to address diversity, food security, and nutrition, sustainable agricultural production systems must place a greater emphasis on the efficient protection and management of biodiversity and ecosystem services. Growing multiple crops in a region is referred to as crop diversification. It can be achieved by introducing new crop species or varieties, as well as by altering the current cropping system. Typically, it might refer to incorporating extra crops into an already-existing rotation. Our seeds for needs experience will play an important role in enabling agriculture to improve crop productivity, nutrition and crop diversity productivity. Together with Ethiopian and international partners, Bioversity International has been conducting a crowdsourcing methodology and crop improvement strategy under the name "seeds for needs" since 2010 in order to comprehend and study the potential of these varieties in underserved areas and to improve the resilience of the communities where these varieties are grown. The main objective was to provide variation so that farmers could adjust to climate change. The Seeds for Needs Initiative, which leverages the genetic diversity already present to discover traits for adaptation to climate change, has been successfully implemented by Bioversity International. With the help of farmers, particularly women farmers, Seeds for Needs uses a participatory approach to choose a set of crops and varieties that will be further tested under their farming conditions using a crowdsourcing technique. The registration of two varieties in the Tigray region, development of more than 6000 recombinant inbreed lines and their adoption by smallholder farmers in Tigray, Amhara, and Oromia, and a number of scientific paper publications that highlight the most important traits of these varieties—including their high grain and biomass yield in marginal environments, resistance to diseases, and adaptability to climatic conditions that change from year to year—are among the most significant outcomes of these studie

Discussion with representative participants from Meket district on SI-MFS initiative activities implementation

Sixteen participants (M=15; F=1) have represented the community in this discussion. The objective of the discussion was to introduce the concepts of Si-MFS initiative to the participants and discuss on possible areas of intervention under this initiative. Furthermore, the role of WTL to link crowdsourcing winner varieties of durum wheat and faba bean to the surrounding farmers. Besides, the project team has discussed with Meket woreda administration and office of Agriculture about the initiative, main agricultural sector problems and designed possible alleviation solutions

Pre-implementation capacity building training on SI-MFS initiative

Building capacity of key implementing stakeholders is a prerequisite for successful implementation of projects. We have caried capacity building training on several topics under the framework of Sustainable Intensification of Mixed Farming Systems (SI-MFS) initiative. Briefing on SI-MFs, crowdsourcing platform for accelerated varietal evaluation and selection, and potential of local landraces for breeding and yield improvement for sustainable development were given for a total of 39 participants from 9 district agricultural officers, 18 kebele level extension workers and 12 selected model farmers from norther, central and southern parts of the country. This training workshop has also provided opportunity to strengthen collaboration among different actors of the project within the same district as well as across country. Furthermore, participants from the different corners of the country have shared experience and gained common understanding of the initiative to be implemented in their respective areas

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

Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers’ traditional knowledge

In the smallholder, low-input farming systems widespread in sub-Saharan Africa, farmers select and propagate crop varieties based on their traditional knowledge and experience. A data-driven integration of their knowledge into breeding pipelines may support the sustainable intensification of local farming. Here, we combine genomics with participatory research to tap into traditional knowledge in smallholder farming systems, using durum wheat (Triticum durum Desf.) in Ethiopia as a case study. We developed and genotyped a large multiparental population, called the Ethiopian NAM (EtNAM), that recombines an elite international breeding line with Ethiopian traditional varieties maintained by local farmers. A total of 1,200 EtNAM lines were evaluated for agronomic performance and farmers’ appreciation in three locations in Ethiopia, finding that women and men farmers could skillfully identify the worth of wheat genotypes and their potential for local adaptation. We then trained a genomic selection (GS) model using farmer appreciation scores and found that its prediction accuracy over grain yield (GY) was higher than that of a benchmark GS model trained on GY. Finally, we used forward genetics approaches to identify marker–trait associations for agronomic traits and farmer appreciation scores. We produced genetic maps for individual EtNAM families and used them to support the characterization of genomic loci of breeding relevance with pleiotropic effects on phenology, yield, and farmer preference. Our data show that farmers’ traditional knowledge can be integrated in genomics-driven breeding to support the selection of best allelic combinations for local adaptation