Economic and chemometric studies to supplement food-grade soybean variety development in the Mid-Atlantic region


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Virginia Tech


Sustainability of the soybean industry relies on the growth of new industries and the continued improvement of seeds for utilization. Grower adoption and growth of the edamame industry has been slow in part due to insufficient information on its potential profitability and marketability. As such, the first and second objectives of this thesis aimed at 1) determining production costs of hand-harvested fresh edamame enterprise and 2) exploring consumer willingness-to-pay (WTP) for fresh, local, organic, and "on-the-stalk" marketed edamame. Sucrose, raffinose, and stachyose sugars hold tremendous implications for utilization of soybean seeds in livestock, soyfood, and probiotics industries. Current sugar phenotyping methods using high-performance liquid chromatography (HPLC) are costly and inefficient. Therefore, the third objective of this study was to develop calibrations to predict sugar content using near-infrared reflectance spectroscopy (NIRS). Results showed that labor accounted for 72% of production costs for edamame pods, which largely limits its profit potential. Mean WTP for fresh and local edamame exceeded their frozen and non-local counterparts by 94 and 88 cents, respectively. In addition, mean WTP for organic edamame exceeded non-GMO edamame by 33 cents. Pro-environmental attitudes appeared to be a consistent driver of WTP these three attributes. Meanwhile, a 40-cent discount for "on-the-stalk" edamame compared to pods indicates convenience may also be a factor in edamame marketability. Calibration development for sucrose and stachyose was successful, with R2cal, R2cv, RMSEC, and RMSECV of 0.901, 0.869, 0.516, and 0.596, and 0.911, 0.891, 0.361, and 0.405, respectively. Alternative methods should be investigated for quantification of raffinose.



edamame, vegetable soybean, production feasibility, willingness-to-pay, near-infrared reflectance spectroscopy (NIRS), soybean sugar profiling