Genetic Assessment of a Mini‐core Developed from the USDA Rice Genebank

Agrama, H. A.; Wang, Yan; Lee, Fleet; Fjellstrom, Robert G.; Chen, Ming‐Hsuan; Jia, Melissa H.; McClung, Anna M.

doi:10.2135/cropsci2008.06.0551er

Cited by 13 publications

(25 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…As a result, this core subset has been evaluated for agronomic descriptors (Yan et al, 2005a), kernel dimension traits that impact milling yield and market class (Yan et al, 2005b), resistance to physiological disease 'straighthead' and fungal disease 'sheath blight' (Rhizoctonia solani) and 'blast' (Magnaporthe oryzae) (Agrama et al, 2009), and DNA markers associated with cooking quality and blast resistance (McClung et al, 2004Fjellstrom et al, 2006).…”

Section: The Rcs Improves Genetic Characterization Of Germplasm Collementioning

confidence: 99%

“…Seventy-two (71 SSR and an indel) molecular markers, covering the entire rice genome, approximately with an average of one marker per 30 cM, were used to genotype the 1,794 accessions. PCR amplification of the markers followed the procedure that was described by Agrama et al (2009). DNA samples were separated on an ABI Prism 3730 DNA analyzer according to the manufacturer's instructions (Applied Biosystems, Foster City, CA, USA).…”

Section: Genotyping and Statistical Analysismentioning

confidence: 99%

“…Development of core collections is an effective tool to extensively characterize large germplasm collections, and the utilization of a mini-core sub-sampling strategy further increases the effectiveness of genetic diversity analysis at detailed phenotype and molecular levels (Agrama et al, 2009). Using the advanced M strategy, Kim et al (2007) presented PowerCore software that possesses the power to represent all the alleles identified by molecular markers and classes of the phenotypic observations in the development of core collections.…”

Section: Usda Rice Mini-core Collectionmentioning

confidence: 99%

“…Sampling the core collection was performed by the PowerCore software with an effort to maximize both the number of observed alleles at SSR loci and the number of phenotypic trait classes using the advanced M (maximization) strategy implemented through a modified heuristic algorithm (Agrama et al, 2009). The phenotypic traits were automatically classified into different categories or classes by the PowerCore program based on Sturges' rule = 1 + Log 2 (n), where n is the number of observed accessions (Kim et al, 2007).…”

Section: Sampling Strategy and Representation Analysismentioning

confidence: 99%

“…Demonstrated both phenotypically and genotypically, the USDA rice mini-core collection of 217 entries is a good representative of the core of 1,794 entries as well as the entire rice global genebank of more than 18,000 accessions in the US (Yan et al, 2007;Agrama et al, 2009). The vast genetic diversity means the richness of valuable genes that could be extracted for cultivar improvement (Li et al, 2010).…”

Section: Use the Usda Rice Mini-core Collection For Mining Valuable Gmentioning

confidence: 99%

See 4 more Smart Citations

Genetic Characterization of Global Rice Germplasm for Sustainable Agriculture

Wang¹

2012

Food Production - Approaches, Challenges and Tasks

Self Cite

View full text Add to dashboard Cite

Section: The Rcs Improves Genetic Characterization Of Germplasm Collementioning

confidence: 99%

Section: Genotyping and Statistical Analysismentioning

confidence: 99%

Section: Usda Rice Mini-core Collectionmentioning

confidence: 99%

Section: Sampling Strategy and Representation Analysismentioning

confidence: 99%

Section: Use the Usda Rice Mini-core Collection For Mining Valuable Gmentioning

confidence: 99%

See 3 more Smart Citations

Genetic Characterization of Global Rice Germplasm for Sustainable Agriculture

Wang¹

2012

Food Production - Approaches, Challenges and Tasks

Self Cite

View full text Add to dashboard Cite

Predicting single kernel and bulk milled rice alkali spreading value and gelatinization temperature class using NIR spectroscopy

et al. 2022

View full text Add to dashboard Cite

Background and Objectives The alkali spreading value (ASV) of rice is a widely measured quality parameter and accepted indicator of gelatinization temperature (GT) class. However, the alkali test, developed in 1958, is labor intensive and subjective. Better methods to measure ASV and GT, for single kernel and bulk rice would provide an important tool to determine the effects of individual kernels on end‐use quality and rice with desired cooking qualities. An instrument developed by the USDA‐ARS and a commercially available near infrared (NIR) instrument were evaluated for determining ASV and classification of intermediate and low GT levels for single kernel and bulk milled rice, respectively. Findings Quantitative prediction of ASV scores (2–7) demonstrated the potential of NIR spectroscopy for screening with a standard error of prediction for validation samples ranging from 0.91 to 1.39 for the single kernel NIR instrument, and from 0.97 to 1.19 for the commercial instrument. GT categorization into intermediate and low values, using ASV scores, showed 82.4% and 85.0% correct classification using 1 and 30‐single kernel average calibration models, respectively. GT was correctly classified (93.6%–84.4%) using a commercial NIR instrument. Conclusion NIR spectroscopy has potential for rough screening of ASV and for two‐category GT rice classification. Significance and Novelty Considering that NIR spectroscopy has been proven to be applicable for other quality parameters, such as rice starch content and quality, protein content, and milling degree, the addition of calibrations for ASV as a predictor of GT class will be highly beneficial while not requiring additional resources. The rapid and nondestructive classification of individual kernels may also enable physical segregation of individual kernels for use by rice researchers and/or industry for additional studies on kernels with specific quality parameters and for determining the extent of variant kernels in a milled rice lot that could affect end use quality. Future studies on the use of NIR spectroscopy for brown rice should be evaluated so that quality could be assessed, while maintaining seed viability, and then used in field studies.

show abstract

Phylogenetic origin and dispersal pattern of Taiwan weedy rice

Gealy

Jia

et al. 2019

Pest Management Science

View full text Add to dashboard Cite

BACKGROUND Knowledge of the genetic diversity and spatial structure of Taiwan weedy red rice (WRR) populations, which adapted in a transplanting system, will facilitate the design of effective methods to control this weed by tracing its origins and dispersal patterns in a given region. RESULTS Taiwan WRR is genetically most similar to Taiwan indica cultivars and landraces according to genetic distance. The inbreeding coefficient of the Taiwan WRR population is greater than 0.8, which is similar to the inbred cultivars. The ancestry coefficients map suggests a dispersal pattern of long‐distance and seed‐mediated contamination across Taiwan, often from warmer, earlier‐planted regions to cooler, later‐planted regions. Parentage analysis of Taiwan WRR revealed that mostly early indica landraces and indica cultivars were present in the genetic pool; in rare cases temperate japonica was present. Based on the above results, the phylogenetic origin of most Taiwan weedy rice appears to be from hybrid progenies of old cultivated red rice accessions crossed with ‘DGWG’. The inbreeding coefficient trend of the six TWR clusters suggests a temporal shift from ‘old’ indica landraces with red bran (high inbreeding coefficient) to modern indica varieties (low inbreeding coefficient). CONCLUSION Although there were sustained efforts to remove these old red rice accessions from paddy fields before 1945, some farmers continued to use low purity seed. This practice, along with volunteer cultivation of these old varieties in the second cropping season, apparently has facilitated the long‐distance, seed‐mediated contamination of rice seed, and the increase in weedy rice seed in paddy soil. © 2019 Society of Chemical Industry

show abstract

Genetic Assessment of a Mini‐core Developed from the USDA Rice Genebank

Cited by 13 publications

References 0 publications

Genetic Characterization of Global Rice Germplasm for Sustainable Agriculture

Genetic Characterization of Global Rice Germplasm for Sustainable Agriculture

Predicting single kernel and bulk milled rice alkali spreading value and gelatinization temperature class using NIR spectroscopy

Phylogenetic origin and dispersal pattern of Taiwan weedy rice

Contact Info

Product

Resources

About