@article{amankwaah_williamson_reynolds_ibrahem_pecota_zhang_olukolu_truong_carey_felde_et al._2023, title={Development of NIRS calibration curves for sugars in baked sweetpotato}, volume={7}, ISSN={["1097-0010"]}, DOI={10.1002/jsfa.12800}, abstractNote={AbstractBackgroundVariability in sugar content between raw and cooked sweetpotato storage roots impact nutritional and dietary importance with implications for consumer preference. High‐throughput phenotyping is required to breed varieties that satisfy consumer preferences.ResultsNear‐infrared reflectance spectroscopy (NIRS) calibration curves were developed for analysing sugars in baked storage roots using 147 genotypes from a population segregating for sugar content and other traits. The NIRS prediction curves had high coefficients of determination in calibration (R2c) of 0.96 (glucose), 0.93 (fructose), 0.96 (sucrose), and 0.96 (maltose). The corresponding coefficients of determination for cross‐validation (R2cv) were 0.92 (glucose), 0.89 (fructose), 0.96 (sucrose) and 0.93 (maltose) and were similar to the R2c for all sugars measured. The ratios of the standard deviation of the reference set to the standard error of cross‐validation were greater than three for all sugars. These results confirm the applicability of the NIRS curves in efficiently determining sugar content in baked sweetpotato storage roots. External validation was performed on an additional 70 genotypes. Coefficients of determination (r2) were 0.88 (glucose), 0.88 (fructose), 0.86 (sucrose) and 0.49 (maltose). The results were comparable to those found for the calibration and cross‐validation in fructose, glucose, and sucrose, but were moderate for maltose due to the low variability of maltose content in the population.ConclusionsNIRS can be used for screening sugar content in baked sweetpotato storage roots in breeding programs and can be used to assist with the development of improved sweetpotato varieties that better meet consumer preferences. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.}, journal={JOURNAL OF THE SCIENCE OF FOOD AND AGRICULTURE}, author={Amankwaah, Victor A. and Williamson, Sharon and Reynolds, Rong and Ibrahem, Ragy and Pecota, Kenneth V. and Zhang, Xiaofei and Olukolu, Bode A. and Truong, Van-Den and Carey, Edward and Felde, Thomas Zum and et al.}, year={2023}, month={Jul} }
 @article{bajgain_zhang_turner_curland_heim_dill-macky_ishimaru_anderson_2019, title={Characterization of Genetic Resistance to Fusarium Head Blight and Bacterial Leaf Streak in Intermediate Wheatgrass (Thinopyrum intermedium)}, volume={9}, ISSN={["2073-4395"]}, DOI={10.3390/agronomy9080429}, abstractNote={Intermediate wheatgrass (IWG, Thinopyrum intermedium, (Host) Barkworth & D.R. Dewey subsp. intermedium, 2n = 6x = 42) is a novel perennial crop currently undergoing domestication efforts. It offers remarkable ecosystem services and yields higher relative to other perennial grain crops. While IWG is mostly resistant to Fusarium head blight (FHB), identifying genomic regions associated with resistance will help protect the crop from potential disease epidemics. An IWG biparental population of 108 individuals was developed by crossing parents differing in their response to FHB and bacterial leaf streak (BLS). The population was screened for disease reaction over three years using isolates collected from IWG plants in St. Paul, Minnesota, USA. Linkage maps representing the 21 IWG chromosomes were constructed from 4622 Single Nucleotide Polymorphism (SNP) markers, with one SNP at every 0.74 cM. Interval mapping identified 15 quantitative trait loci (QTL) associated with FHB resistance and 11 with BLS resistance. Models with two or three QTL combinations reduced FHB disease severity by up to 15%, and BLS by up to 17%. When markers associated with FHB resistance were used as cofactors in genomic selection models, trait predictive ability improved by 24–125%. These genomic regions and genetic markers associated with FHB and BLS resistance can also be used to safeguard annual cereal grains through gene introgression and selective breeding.}, number={8}, journal={AGRONOMY-BASEL}, author={Bajgain, Prabin and Zhang, Xiaofei and Turner, M. Kathryn and Curland, Rebecca D. and Heim, Brett and Dill-Macky, Ruth and Ishimaru, Carol A. and Anderson, James A.}, year={2019}, month={Aug} }
 @article{larson_dehaan_poland_zhang_dorn_kantarski_anderson_schmutz_grimwood_jenkins_et al._2019, title={Genome mapping of quantitative trait loci (QTL) controlling domestication traits of intermediate wheatgrass (Thinopyrum intermedium)}, volume={132}, ISSN={["1432-2242"]}, DOI={10.1007/s00122-019-03357-6}, abstractNote={Allohexaploid (2n = 6x = 42) intermediate wheatgrass (Thinopyrum intermedium), abbreviated IWG, is an outcrossing perennial grass belonging to the tertiary gene pool of wheat. Perenniality would be valuable option for grain production, but attempts to introgress this complex trait from wheat-Thinopyrum hybrids have not been commercially successful. Efforts to breed IWG itself as a dual-purpose forage and grain crop have demonstrated useful progress and applications, but grain yields are significantly less than wheat. Therefore, genetic and physical maps have been developed to accelerate domestication of IWG. Herein, these maps were used to identify quantitative trait loci (QTLs) and candidate genes associated with IWG grain production traits in a family of 266 full-sib progenies derived from two heterozygous parents, M26 and M35. Transgressive segregation was observed for 17 traits related to seed size, shattering, threshing, inflorescence capacity, fertility, stem size, and flowering time. A total of 111 QTLs were detected in 36 different regions using 3826 genotype-by-sequence markers in 21 linkage groups. The most prominent QTL had a LOD score of 15 with synergistic effects of 29% and 22% over the family means for seed retention and percentage of naked seeds, respectively. Many QTLs aligned with one or more IWG gene models corresponding to 42 possible domestication orthogenes including the wheat Q and RHT genes. A cluster of seed-size and fertility QTLs showed possible alignment to a putative Z self-incompatibility gene, which could have detrimental grain-yield effects when genetic variability is low. These findings elucidate pathways and possible hurdles in the domestication of IWG.}, number={8}, journal={THEORETICAL AND APPLIED GENETICS}, author={Larson, Steve and DeHaan, Lee and Poland, Jesse and Zhang, Xiaofei and Dorn, Kevin and Kantarski, Traci and Anderson, James and Schmutz, Jeremy and Grimwood, Jane and Jenkins, Jerry and et al.}, year={2019}, month={Aug}, pages={2325–2351} }
 @article{bajgain_zhang_anderson_2019, title={Genome-Wide Association Study of Yield Component Traits in Intermediate Wheatgrass and Implications in Genomic Selection and Breeding}, volume={9}, ISSN={["2160-1836"]}, DOI={10.1534/g3.119.400073}, abstractNote={Abstract
               Intermediate wheatgrass (Thinopyrum intermedium, IWG) is a perennial grain crop with high biomass and grain yield, long seeds, and resistance to pests and diseases. It also reduces soil erosion, nitrate and mineral leaching into underground water tables, and sequesters carbon in its roots. The domestication timeline of IWG as a grain crop spans only 3 decades, hence it lags annual grain crops in yield and seed characteristics. One approach to improve its agronomic traits is by using molecular markers to uncover marker-trait associations. In this study, we performed association mapping on IWG breeding germplasm from the third recurrent selection cycle at the University of Minnesota. The IWG population was phenotyped in St Paul, MN in 2017 and 2018, and in Crookston, MN in 2018 for grain yield, seed length, width and weight, spike length and weight, and number of spikelets per spike. Strong positive correlations were observed among most trait pairs, with correlations as high as 0.76. Genotyping using high throughput sequencing identified 8,899 high-quality genome-wide SNPs which were combined with phenotypic data in association mapping to discover regions associated with the yield component traits. We detected 154 genetic loci associated with these traits of which 19 were shared between at least two traits. Prediction of breeding values using significant loci as fixed effects in genomic selection model improved predictive abilities by up to 14%. Genetic mapping of agronomic traits followed by using genomic selection to predict breeding values can assist breeders in selecting superior genotypes to accelerate IWG domestication.}, number={8}, journal={G3-GENES GENOMES GENETICS}, author={Bajgain, Prabin and Zhang, Xiaofei and Anderson, James A.}, year={2019}, month={Aug}, pages={2429–2439} }