Near-Infrared Reflectance Spectroscopy Calibration for Trypsin Inhibitor in Soybean Seed and Meal

Elizabeth B. Fletcher, M. Luciana Rosso, Troy Walker, Haibo Huang, Gota Morota and Bo Zhang ()
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Elizabeth B. Fletcher: School of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University Blacksburg, Blacksburg, VA 24061, USA
M. Luciana Rosso: School of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University Blacksburg, Blacksburg, VA 24061, USA
Troy Walker: Department of Food Science and Technology, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
Haibo Huang: Department of Food Science and Technology, Virginia Polytechnic Institute and State University, Blacksburg, VA 24061, USA
Gota Morota: Department of Agricultural and Environmental Biology, University of Tokyo, Tokyo 113-8657, Japan
Bo Zhang: School of Plant and Environmental Sciences, Virginia Polytechnic Institute and State University Blacksburg, Blacksburg, VA 24061, USA

Agriculture, 2025, vol. 15, issue 10, 1-12

Abstract: Trypsin inhibitors (TI) are naturally occurring antinutritional factors found in soybean seeds [ Glycine max. (L.)] that decrease the growth rate of livestock, causing malnutrition and digestion troubles. The current accurate method to quantify TI levels in soybean seeds or meals is by high-performance liquid chromatography (HPLC); however, it is time-consuming, creating bottlenecks in industrial processing. Establishing a near-infrared reflectance spectroscopy (NIR) model for estimating TI in seeds and meals would provide a more efficient and cost-effective method for breeding programs and feed producers. In this study, 300 soybean lines, both seeds and meals, were analyzed for TI content using HPLC, and calibration models were created based on spectral data collected from a Perten DA 7250 NIR instrument. The resulting models demonstrated robust validation, achieving accuracy rates of 97% for seed total TI, 97% for seed Kunitz TI, and 89% for meal total TI. The findings of this study are significant as no NIR calibration models had previously been developed for TI estimation in soybean seed and meal. These models can be used by breeding programs to efficiently assess their lines and by industry to quickly evaluate their soybean meal quality.

Keywords: soybean; trypsin inhibitor; NIR calibration (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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