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      Diversity of Global Rice Markets and the Science Required for Consumer-Targeted Rice Breeding

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          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.

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          Most cited references14

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          Not just a grain of rice: the quest for quality.

          A better understanding of the factors that contribute to the overall grain quality of rice (Oryza sativa) will lay the foundation for developing new breeding and selection strategies for combining high quality, with high yield. This is necessary to meet the growing global demand for high quality rice while offering producing countries additional opportunities for generating higher export revenues. Several recent developments in genetics, genomics, metabolomics and phenomics are enhancing our understanding of the pathways that determine several quality traits. New research strategies, as well as access to the draft of the rice genome, will not only advance our understanding of the molecular mechanisms that lead to quality rice but will also pave the way for efficient and targeted grain improvement.
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            Rare allele of OsPPKL1 associated with grain length causes extra-large grain and a significant yield increase in rice.

            Grain size and shape are important components determining rice grain yield, and they are controlled by quantitative trait loci (QTLs). Here, we report the cloning and functional characterization of a major grain length QTL, qGL3, which encodes a putative protein phosphatase with Kelch-like repeat domain (OsPPKL1). We found a rare allele qgl3 that leads to a long grain phenotype by an aspartate-to-glutamate transition in a conserved AVLDT motif of the second Kelch domain in OsPPKL1. The rice genome has other two OsPPKL1 homologs, OsPPKL2 and OsPPKL3. Transgenic studies showed that OsPPKL1 and OsPPKL3 function as negative regulators of grain length, whereas OsPPKL2 as a positive regulator. The Kelch domains are essential for the OsPPKL1 biological function. Field trials showed that the application of the qgl3 allele could significantly increase grain yield in both inbred and hybrid rice varieties, due to its favorable effect on grain length, filling, and weight.
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              MSClust: a tool for unsupervised mass spectra extraction of chromatography-mass spectrometry ion-wise aligned data

              Mass peak alignment (ion-wise alignment) has recently become a popular method for unsupervised data analysis in untargeted metabolic profiling. Here we present MSClust—a software tool for analysis GC–MS and LC–MS datasets derived from untargeted profiling. MSClust performs data reduction using unsupervised clustering and extraction of putative metabolite mass spectra from ion-wise chromatographic alignment data. The algorithm is based on the subtractive fuzzy clustering method that allows unsupervised determination of a number of metabolites in a data set and can deal with uncertain memberships of mass peaks in overlapping mass spectra. This approach is based purely on the actual information present in the data and does not require any prior metabolite knowledge. MSClust can be applied for both GC–MS and LC–MS alignment data sets. Electronic supplementary material The online version of this article (doi:10.1007/s11306-011-0368-2) contains supplementary material, which is available to authorized users.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                14 January 2014
                : 9
                : 1
                : e85106
                Affiliations
                [1 ]International Rice Research Institute, Los Baños, Laguna, Philippines
                [2 ]Laboratory of Plant Physiology, Wageningen University, Wageningen, The Netherlands
                [3 ]International Network for Quality Rice
                [4 ]Plant Research International, Wageningen, The Netherlands
                [5 ]Centre for BioSystems Genomics, Wageningen, The Netherlands
                [6 ]Yanco Agricultural Institute, NSW Department of Industry and Investment, PMB, Yanco, New South Wales, Australia
                [7 ]Grain Quality and Nutrition Division, Bangladesh Rice Research Institute (BRRI), Gazipur, Bangladesh
                [8 ]EMBRAPA Rice and Beans, Santo Antonio de Goiás, GO, Brazil
                [9 ]Africa Rice Center (AfricaRice), Cotonou, Republic of Benin
                [10 ]Cambodian Agricultural Research and Development Institute, Phnom Penh, Cambodia
                [11 ]Mejoramiento Genetico de Arroz INIA CRI Quilamapu, Vicente Mendez, Chile
                [12 ]Institute of Nuclear Agricultural Sciences, Zhejiang University, Hua Jiachi Campus, Hangzhou, China
                [13 ]China National Rice Research Institute, Hangzhou, China
                [14 ]Laboratorio de Calidad FLAR-CIAT, CIAT, Cali-Palmira, Colombia
                [15 ]Rice Research Section, Field Crops Research Institute, A.R.C., Rice Research & Training Center, Sakha, Kafr El-Shiekh, Egypt
                [16 ]CSIR-Food Research Institute, Accra, Ghana
                [17 ]Rice Section, Department of Plant Breeding and Genetics, Punjab Agricultural University Ludhiana, Ludhiana, India
                [18 ]Department of Rice, Centre for Plant Breeding and Genetics, Tamil Nadu Agricultural University Coimbatore, Tamil Nadu, India
                [19 ]Crop Improvement Section, Directorate of Rice Research, Rajendra Nagar, Hyderabad, AP, India
                [20 ]Indonesian Center for Rice Research (ICRR) BB Padi, Sukamandi, Subang Jawa Barat, Indonesia
                [21 ]Rice Research Institute of Iran (RRII), Rasht, I.R. Iran
                [22 ]NARO Institute of Crop Science, 2-1-18 Kannondai, Tsukuba, Ibaraki, Japan
                [23 ]NARO Hokkaido Agricultural Research Centre, Toyohira, Sapporo, Hokkaido, Japan
                [24 ]Rice and Cash Crop Research Institute, NAFRI, Vientiane, Lao PDR
                [25 ]Faculty of Agriculture and Food Science, Universiti Putra Malaysia, Bintulu Sarawak, Malaysia
                [26 ]Pusat Penyelidikan Padi dan Tanaman Industri, MARDI Seberang Perai Beg Berkunci, Seberang Perai Pulau Penang, Malaysia
                [27 ]Plant Biotechnology Center, Myanmar Agriculture Service, Ministry of Agriculture and Irrigation, Yangon, Myanmar
                [28 ]Rice Programme, National Agricultural Research Centre, Islamabad, Pakistan
                [29 ]National Institute for Biotechnology and Genetic Engineering, Faislabad, Pakistan
                [30 ]Rice Chemistry and Food Science Division, Philippine Rice Research Institute, Maligaya, Science City of Muñoz, Nueva Ecija, Philippines
                [31 ]Instituto Nacional de Investigacao Agraria e Veterinaria, Quinta do Marques, Oeiras, Portugal
                [32 ]Rice Research Station, Department of Agriculture, Ambalantota, Sri Lanka
                [33 ]Department of Agronomy, National Taiwan University, Taiwan
                [34 ]Pathumthani Rice Research Centre, Bureau of Rice Research and Development, Thailand
                [35 ]Khon Kaen Rice Research Center, Khon Kaen, Thailand
                [36 ]Rice Research Program, National Agricultural Research Institute, INIA Treinta y Tres, Treinta y Tres, CP, Uruguay
                [37 ]USDA-ARS, Dale Bumpers National Rice Research Center, Stuttgart, Arkansas, United States of America
                [38 ]Genetic & Plant Breeding Division, Cuulong Delta Rice Research Inst., Can Tho, Viet Nam
                National Rice Research Center, United States of Ameirca
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: MF MC. Performed the experiments: All. Analyzed the data: MC MF AL AN. Contributed reagents/materials/analysis tools: AL AN VD JC MF AR. Wrote the paper: MF MC RH RR TU.

                [¤a]

                Current address: International Rice Research Institute, National Institute of Crop Science, Gwonsun-gu, Suwon, Republic of Korea,

                [¤b]

                Current address: School of Agriculture and Food Science, University of Queensland, St Lucia, Queensland, Australia

                Article
                PONE-D-13-28069
                10.1371/journal.pone.0085106
                3893639
                b3935afc-5718-409c-83ab-8200bb4797cd
                Copyright @ 2014

                This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.

                History
                : 8 July 2013
                : 22 November 2013
                Page count
                Pages: 12
                Funding
                This work was supported by International Network for Quality Rice (INQR), International Rice Research Institute (IRRI), Wageningen University Research (WUR), and the Monsanto Beachell Borlaug Scholarship Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Agriculture
                Agricultural Production
                Crops
                Cereals
                Rice
                Crop Management
                Biology
                Biochemistry
                Biotechnology
                Chemistry
                Analytical Chemistry
                Science Policy
                Research Funding
                Technology Development
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                Economics
                Industrial Organization
                Structure of Markets
                Agricultural Economics
                Macroeconomics

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