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Cassava breeding and agronomy in Asia: 50 years of history and future directions

期刊

BREEDING SCIENCE
卷 70, 期 2, 页码 145-166

出版社

JAPANESE SOC BREEDING
DOI: 10.1270/jsbbs.18180

关键词

Asia; cassava; conventional breeding; agronomy; new breeding techniques; data-driven agriculture; CMD

资金

  1. Nippon Foundation
  2. CGIAR Research Program on Roots, Tubers and Banana (RTB)
  3. Australian Centre for International Agricultural Research (ACIAR)
  4. Ministry of Foreign Affairs (MOFA) of Japan
  5. Japan International Cooperation Agency (JICA)
  6. Japan Science and Technology Agency (JST) through the Science and Technology Research Partnership for Sustainable Development (SATREPS) program
  7. Japan Society for the Promotion of Science (JSPS)
  8. United States National Science Foundation (NSF)

向作者/读者索取更多资源

In Asia, cassava (Manihot esculenta) is cultivated by more than 8 million farmers, driving the rural economy of many countries. The International Center for Tropical Agriculture (CIAT), in partnership with national agricultural research institutes (NARIS), instigated breeding and agronomic research in Asia, 1983. The breeding program has successfully released high-yielding cultivars resulting in an average yield increase from 13.0 t ha(-1) in 1996 to 21.3 t ha(-1) in 2016, with significant economic benefits. Following the success in increasing yields, cassava breeding has turned its focus to higher-value traits, such as waxy cassava, to reach new market niches. More recently, building resistance to invasive pests and diseases has become a top priority due to the emergent threat of cassava mosaic disease (CMD). The agronomic research involves driving profitability with advanced technologies focusing on better agronomic management practices thereby maintaining sustainable production systems. Remote sensing technologies are being tested for trait discovery and large-scale field evaluation of cassava. In summary, cassava breeding in Asia is driven by a combination of food and market demand with technological innovations to increase the productivity. Further, exploration in the potential of data-driven agriculture is needed to empower researchers and producers for sustainable advancement.

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