Data from: Genetic dissection of protein content in cowpea using custom-made NIRS equations and GWAS as a model for nutritional breeding and undergraduate research training
Data files
Apr 01, 2026 version files 17.92 KB
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Cowpea_Specfic_Data.csv
6.62 KB
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Legume_Hay_Data.csv
6.62 KB
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README.md
2.79 KB
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wet_chem_blues.csv
1.89 KB
Abstract
The manuscript titled "Genetic Dissection of Protein Content in Cowpea Using Custom-made NIRS equations and GWAS as a Model for Nutritional Breeding and Undergraduate Research Training" examines the genetic basis of grain protein content in cowpea (black-eye pea), a key crop for food and nutrition security. The authors evaluated 287 diverse cowpea accessions using a species-specific near-infrared spectroscopy model with high accuracy to estimate protein levels.
This dataset supports the manuscript that investigates the genetic basis of seed protein content in cowpea (Vigna unguiculata L. Walp) using genome-wide association studies (GWAS)
and near-infrared reflectance spectroscopy (NIRS).
A total of 287 cowpea accessions were evaluated, including 281 from the University of California Riverside (UCR) Minicore Collection and six locally grown U.S. cultivars. Field experiments were conducted in 2021 at the University of Florida Plant Science Research and Education Unit (PSREU), Citra, FL, using a row-column design with two replications.
Wet chemistry analysis provided reference values for NIRS calibration. A cowpea-specific NIRS model (R = 0.86, r = 0.92)
was developed and compared with the commercial Legume Hay (LH)equation for estimating crude protein (CP). The CP estimates from both calibrations were then used for GWAS to identify loci associated with protein content.
Contact: estebanrios@ufl.edu with questions about the dataset.
Data Files Included
Legume_Hay_Data.csv
Crude protein BLUEs for cowpea cowpea accessions obtained using the commercial Legume Hay (LH) NIRS calibration model.
Cowpea_Specific_Data.csv
Crude protein estimates for cowpea accessions were generated using a cowpea-specific PLSR NIRS calibration, developed from wet chemistry reference data.
These values were used for the final GWAS and downstream analyses.
Wet_Chemistry_Data.csv
Wet chemistry data
BLUEs of crude protein content obtained from wet chemistry referenced data used for developing and validating the cowpea-specific NIRS calibration model.
Data Columns (for all files)
Taxa: The name of the cowpea accession (from the UCR Minicore Collection or U.S. cultivar).
CP: Crude protein content (%) estimated either from the Legume Hay or Cowpea-specific NIRS calibration equation.
Experimental Notes
Field design: Row-column layout with two replicates at PSREU, Citra, FL.
Wet chemistry: Performed using aluminum block digestion and AutoAnalyzer colorimetry.
NIRS: Performed with Foss DS2500 using ground seeds; calibration models developed with PLSR in R (pls package) .
Heritability and GWAS analyses were conducted using ASReml and GAPIT v3, respectively.
The study was part of the USDA-NIFA REEU Program Circularity and Digitalization Skills for Sustainable Food Systems, integrating undergraduate research training.
For reference, the phenotypic datasets are presented here,e and the genomic data can be found in https://doi.org/10.1002/leg3.95.