Dataset Information

Diversity of global rice markets and the science required for consumer-targeted rice breeding.

ABSTRACT: With the ever-increasing global demand for high quality rice in both local production regions and with Western consumers, we have a strong desire to understand better the importance of the different traits that make up the quality of the rice grain and obtain a full picture of rice quality demographics. Rice is by no means a 'one size fits all' crop. Regional preferences are not only striking, they drive the market and hence are of major economic importance in any rice breeding / improvement strategy. In this analysis, we have engaged local experts across the world to perform a full assessment of all the major rice quality trait characteristics and importantly, to determine how these are combined in the most preferred varieties for each of their regions. Physical as well as biochemical characteristics have been monitored and this has resulted in the identification of no less than 18 quality trait combinations. This complexity immediately reveals the extent of the specificity of consumer preference. Nevertheless, further assessment of these combinations at the variety level reveals that several groups still comprise varieties which consumers can readily identify as being different. This emphasises the shortcomings in the current tools we have available to assess rice quality and raises the issue of how we might correct for this in the future. Only with additional tools and research will we be able to define directed strategies for rice breeding which are able to combine important agronomic features with the demands of local consumers for specific quality attributes and hence, design new, improved crop varieties which will be awarded success in the global market.

SUBMITTER: Calingacion M

PROVIDER: S-EPMC3893639 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Publications

Diversity of global rice markets and the science required for consumer-targeted rice breeding.

Calingacion Mariafe M Laborte Alice A Nelson Andrew A Resurreccion Adoracion A Concepcion Jeanaflor Crystal JC Daygon Venea Dara VD Mumm Roland R Reinke Russell R Dipti Sharifa S Bassinello Priscila Zaczuk PZ Manful John J Sophany Sakhan S Lara Karla Cordero KC Bao Jinsong J Xie Lihong L Loaiza Katerine K El-hissewy Ahmad A Gayin Joseph J Sharma Neerja N Rajeswari Sivakami S Manonmani Swaminathan S Rani N Shobha NS Kota Suneetha S Indrasari Siti Dewi SD Habibi Fatemeh F Hosseini Maryam M Tavasoli Fatemeh F Suzuki Keitaro K Umemoto Takayuki T Boualaphanh Chanthkone C Lee Huei Hong HH Hung Yiu Pang YP Ramli Asfaliza A Aung Pa Pa PP Ahmad Rauf R Wattoo Javed Iqbal JI Bandonill Evelyn E Romero Marissa M Brites Carla Moita CM Hafeel Roshni R Lur Huu-Sheng HS Cheaupun Kunya K Jongdee Supanee S Blanco Pedro P Bryant Rolfe R Thi Lang Nguyen N Hall Robert D RD Fitzgerald Melissa M

PloS one 20140114 1

With the ever-increasing global demand for high quality rice in both local production regions and with Western consumers, we have a strong desire to understand better the importance of the different traits that make up the quality of the rice grain and obtain a full picture of rice quality demographics. Rice is by no means a 'one size fits all' crop. Regional preferences are not only striking, they drive the market and hence are of major economic importance in any rice breeding / improvement str ...[more]

PMID: 24454799

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Project description:BackgroundDespite the critical role rice breeders play to ensure food security, there is a lack of information regarding their current socio-economic characteristics, constraints and attitudes towards technology adoption. Some key concepts like budget, experience, local ecosystems, level of education and even main breeding method have hardly been surveyed in the past. This not only clouds any policy making regarding scientists in national agricultural research programmes, it also makes it difficult to assess the needs and problems local rice breeders face around the world.MethodsA global online survey was conducted reaching 189 rice breeders from 51 rice-growing countries around the world. The questionnaire was structured according to an adoption framework we proposed from the literature. We specifically investigated their attitudes to adopting an alternative breeding method called rapid generation advance (RGA) (also known as single seed descent). To provide some historical perspective, we compare our results with those reported by Hargrove (Rice breeders in Asia: a ten-country survey of their backgrounds, attitudes, and use of genetic materials, 1978), the only published survey on rice breeders.ResultsOverall, rice breeders are highly educated and have a long experience with their main breeding method. However, a gender gap with respect to education seems to persist. Large variation in resources (staff, land and budget) was observed with a small number of resource-rich institutes and a large number of resource-poor institutes. Most rice breeders are focused on breeding for irrigated conditions. Most breeders have a relatively high degree of risk taking and time preference towards shorter breeding cycles. The majority of breeders are aware of RGA and its benefits with more than half having observed RGA in practice. Finally, breeders are confident in the RGA technique and estimate its resource savings to be substantial.ConclusionsBreeders' willingness to adopt RGA was remarkably high. Surprisingly, adoption of RGA remains low (4% as main method). This may suggest that the benefits of using the RGA method still need to be further demonstrated in rice breeding. Our results could be useful to develop targeted extension material or interventions for implementing new technologies, which could be useful to high-level agricultural managers, international research centres and aid agencies.

Dataset Information

Diversity of global rice markets and the science required for consumer-targeted rice breeding.

Publications

Diversity of global rice markets and the science required for consumer-targeted rice breeding.

Similar Datasets

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