RESUMO
Seed systems research is central to achieving the United Nations Sustainable Development Goals. Improved varieties with promise for ending hunger, improving nutrition, and increasing livelihood security may be released, but how do they reach and benefit different types of farmers? Without widespread adoption the genetic gains achieved with improved crop varieties can never be actualized. Progress has been made toward demand responsive breeding, however the draft CGIAR 2030 Research and Innovation Strategy fails to recognize the complexity of seed systems and thus presents a narrow vision for the future of seed systems research. This points to the lack of evidence-based dialogue between seed systems researchers and breeders. This perspective paper presents findings from an interdisciplinary group of more than 50 CGIAR scientists who used a suite of seed systems tools to identify four knowledge gaps and associated insights from work on the seed systems for vegetatively propagated crops (VPCs), focusing on bananas (especially cooking bananas and plantains), cassava, potato, sweetpotato, and yam. We discuss the implications for thinking about and intervening in seed systems using a combined biophysical and socioeconomic perspective and how this can contribute to increased varietal adoption and benefits to farmers. The tools merit wider use, not only for the seed systems of VPCs, but for the seed of crops facing similar adoption challenges. We argue for deeper collaboration between seed systems researchers, breeders and national seed system stakeholders to address these and other knowledge gaps and generate the evidence and innovations needed to break through the 40% adoption ceiling for modern varieties, and ensure good quality seed once the new varieties have been adopted. Without this, the achievements of breeders may remain stuck in the seed delivery pipeline.
RESUMO
Virome analysis via high-throughput sequencing (HTS) allows rapid and massive virus identification and diagnoses, expanding our focus from individual samples to the ecological distribution of viruses in agroecological landscapes. Decreases in sequencing costs combined with technological advances, such as automation and robotics, allow for efficient processing and analysis of numerous samples in plant disease clinics, tissue culture laboratories, and breeding programs. There are many opportunities for translating virome analysis to support plant health. For example, virome analysis can be employed in the development of biosecurity strategies and policies, including the implementation of virome risk assessments to support regulation and reduce the movement of infected plant material. A challenge is to identify which new viruses discovered through HTS require regulation and which can be allowed to move in germplasm and trade. On-farm management strategies can incorporate information from high-throughput surveillance, monitoring for new and known viruses across scales, to rapidly identify important agricultural viruses and understand their abundance and spread. Virome indexing programs can be used to generate clean germplasm and seed, crucial for the maintenance of seed system production and health, particularly in vegetatively propagated crops such as roots, tubers, and bananas. Virome analysis in breeding programs can provide insight into virus expression levels by generating relative abundance data, aiding in breeding cultivars resistant, or at least tolerant, to viruses. The integration of network analysis and machine learning techniques can facilitate designing and implementing management strategies, using novel forms of information to provide a scalable, replicable, and practical approach to developing management strategies for viromes. In the long run, these management strategies will be designed by generating sequence databases and building on the foundation of pre-existing knowledge about virus taxonomy, distribution, and host range. In conclusion, virome analysis will support the early adoption and implementation of integrated control strategies, impacting global markets, reducing the risk of introducing novel viruses, and limiting virus spread. The effective translation of virome analysis depends on capacity building to make benefits available globally.
RESUMO
Cassava mosaic disease, one of the ten most economically important crop viral diseases in the world, was first reported in Southeast Asia from a single plantation in Cambodia in 2015. To determine the presence and incidence of Sri Lankan cassava mosaic virus (SLCMV) one year after first detection, a total of 6,480 samples from 419 fields were systematically collected from cassava production areas across Cambodia (3,840 samples; 240 fields) and Vietnam (2,640samples; 179 fields) in the 2016 cropping season. Using PCR-based diagnostics, we identified 49 SLCMV-infected plants from nine fields, representing 2% of the total number of fields sampled. Infected fields were geographically restricted to two provinces of Eastern Cambodia, while no infection was detected from any of the other sampled sites in either country. Symptom expression patterns in infected plants suggested that SLCMV may have been transmitted both through infected planting materials, and by Bemisia tabaci, the known whitefly vector of SLCMV. In addition, 14% of virus infected plants did not express typical symptoms of cassava mosaic disease on their leaves, highlighting that molecular-based validation is needed to confirm the presence of SLCMV in the field. None of the owners of the SLCMV-infected fields indicated acquired planting materials from the plantation in Ratanakiri where SLCMV was first reported. The surveillance baseline data generated for both countries is discussed in light of future options to control and manage cassava mosaic disease.