Artificial intelligence-driven near-infrared spectrophotometry model for rapid quantification of anti-nutritional factors in soybean (Glycine max.)

Abstract Anti-nutritional factors can impact soybean nutrient bioavailability when consumed by monogastric animals. However, conventional methods available for quantifying anti-nutritional factors such as phytate and trypsin inhibitors in feeds are laboratory-intensive, time-consuming, expensive, an...

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Main Authors: Norberto Jose Palange, Tonny Obua, Julius Pyton Sserumaga, Enoch Wembabazi, Mildred Ochwo-Ssemakula, Ephraim Nuwamanya, Isaac Onziga Dramadri, Moses Matovu, Richard Edema, Phinehas Tukamuhabwa
Format: Article
Language:English
Published: Springer 2025-06-01
Series:Discover Applied Sciences
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Online Access:https://doi.org/10.1007/s42452-025-07235-3
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