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Dive into the research topics where Ailan Zeng is active.

Publication


Featured researches published by Ailan Zeng.


Journal of Crop Improvement | 2018

Field evaluation and break-even analysis of specialty soybeans for biodiesel and meal protein production

Bryan Stobaugh; Pengyin Chen; Luciano M. Jaureguy; Liliana Florez-Palacios; Moldir Orazaly; Ailan Zeng

ABSTRACT The economic value of a soybean [Glycine max (L.) Merr.] crop depends on yield and quality. The objectives of this study were to evaluate soybean lines for protein and oil content and to examine the break-even (BE) analysis of these traits combined with yield. Forty lines of maturity group (MG) IV or V were grown at four Arkansas locations for two years. Yield, protein, and oil content of each line were determined and compared to the check average for a BE comparison of the total economic value of the line. Results showed six profitable lines (


Journal of Crop Improvement | 2018

Confirmation of SSR Markers and QTL for Seed Calcium Content and Hardness of Soybean

Moldir Orazaly; Pengyin Chen; Bo Zhang; Liliana Florez-Palacios; Ailan Zeng

8.40 to


Crop Science | 2016

A Simple Greenhouse Method for Screening Salt Tolerance in Soybean

Fernando Ledesma; Cindy Lopez; Diana Ortiz; Pengyin Chen; Kenneth L. Korth; Tetsuaki Ishibashi; Ailan Zeng; Moldir Orazaly; Liliana Florez-Palacios

54.96 per metric ton based on yield) in 2008 and six profitable lines (


Molecular Breeding | 2015

Identification and mapping of stable QTL for protein content in soybean seeds

J. Wang; Pengyin Chen; Dechun Wang; Grover Shannon; Ailan Zeng; Moldir Orazaly; Chengjun Wu

0.49 to


Molecular Breeding | 2017

Genome-wide association study (GWAS) of salt tolerance in worldwide soybean germplasm lines

Ailan Zeng; Pengyin Chen; Kenneth L. Korth; Floyd Hancock; Andy Pereira; Kristofor R. Brye; Chengjun Wu; Ainong Shi

61.19 per metric ton based on yield) in 2009. Overall, in both MG, high-protein lines needed to yield more to be profitable, whereas high-oil lines had competitive yield, protein and oil content; R00-764 (MG IV), R05-71 (MG V), and R02-6185F (MG V) were competitive without added premiums.


Plant Breeding | 2015

Agronomic performance and genetic progress of selected historical soybean varieties in the southern USA

Justin Rogers; Pengyin Chen; Ainong Shi; Bo Zhang; Andrew Scaboo; S. Faye Smith; Ailan Zeng

ABSTRACT Seed calcium content and hardness constitute determining characteristics of soybean [Glycine max (L.) Merr.] texture affecting soyfood quality. Molecular markers linked to these traits will accelerate breeding of soybeans for the soyfood market through the use of marker-assisted selection (MAS). Confirmation of linked markers and validation of quantitative trait loci (QTL), prior to their application through MAS, are the keys. The objectives of this study were to confirm previously reported QTL for calcium content and seed hardness and investigate the relationship between these traits. Evaluation of seven recombinant inbred line (RIL) populations with different genetic backgrounds, grown in two Arkansas locations for 2 years, showed inconsistent correlations between these traits. In general, a positive correlation was found in most of the populations and correlation was significant in six populations. Combined data showed a positive correlation between calcium content and seed hardness (r = 0.23 – 0.49). Furthermore, previously reported QTL for calcium content and/or hardness were evaluated in six different sub-populations and stable markers across environments were identified for potential use in MAS. Based on our results, markers Satt267 and Sat_345 on chromosome 1, Sat_288 on chromosome 7, Sat_228, Satt341, and Sat_392 on chromosome 8, Satt547 on chromosome 16, and Satt002 on chromosome 17, are reliable for calcium content selection; whereas, Satt267, Satt680, Satt341, and Sct_010 on chromosomes 1, 7, 8, and 19, respectively, can be used for selection for seed hardness. Findings of this research will facilitate MAS for seed calcium content and hardness in breeding programs aimed at improving food-grade soybeans.


Crop Science | 2015

Identification of quantitative trait loci for oil content in soybean seed.

Jiao Wang; Pengyin Chen; Dechun Wang; Grover Shannon; Ainong Shi; Ailan Zeng; Moldir Orazaly


Crop Science | 2015

Identification and Confirmation of Quantitative Trait Loci Associated with Soybean Seed Hardness

Moldir Orazaly; Pengyin Chen; Ailan Zeng; Bo Zhang


American Journal of Plant Sciences | 2017

Effect of Flood Stress on Soybean Seed Germination in the Field

Chengjun Wu; Pengyin Chen; Wade Hummer; Ailan Zeng; Mariola Klepadlo


Crop Science | 2014

Quantitative Trait Loci Mapping for Seed Calcium Content of Soybean

Moldir Orazaly; Pengyin Chen; Bo Zhang; Ailan Zeng

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Chengjun Wu

University of Arkansas

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Dechun Wang

Michigan State University

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Ainong Shi

University of Arkansas

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Wade Hummer

University of Arkansas

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