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 |
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| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-06-01
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| Series: | Discover Applied Sciences |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/s42452-025-07235-3 |
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