Nondestructive Prediction of Eggshell Thickness Using NIR Spectroscopy and Machine Learning with Explainable AI

ACS Food Science & Technology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 22, 2025

Language: Английский

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Non-destructive detection of pre-incubated chicken egg fertility using hyperspectral imaging and machine learning

Smart Agricultural Technology, Journal Year: 2025, Volume and Issue: unknown, P. 100857 - 100857

Published: Feb. 1, 2025

Language: Английский

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Determination of brown egg fertility by multi-directional visible/near-infrared spectroscopy and machine learning

The Journal of Applied Poultry Research, Journal Year: 2025, Volume and Issue: unknown, P. 100534 - 100534

Published: March 1, 2025

Language: Английский

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Non-destructive pre-incubation sex determination in chicken eggs using hyperspectral imaging and machine learning

Food Control, Journal Year: 2025, Volume and Issue: unknown, P. 111233 - 111233

Published: Feb. 1, 2025

Language: Английский

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A sensitive and rapid visual method of chicken sexing based on LAMP-CRISPR/Cas12a system

British Poultry Science, Journal Year: 2025, Volume and Issue: unknown, P. 1 - 8

Published: March 12, 2025

1. Accurate sex identification of one-day-old chicks is crucial in layer poultry production. Establishing an early sexing method during the chicken embryonic period essential for animal welfare. However, PCR-based has limitations terms specialised equipment and time-consuming.2. This study presents a rapid, simple fluorescent visual technique based on Loop-mediated isothermal amplification (LAMP)-clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 12a (Cas12a). It targets Z chromosome gene DMRT1 W chromosome-specific fragment EE0.6 using designed primers sgRNA. The LAMP amplicon cleaved by Cas12a, producing product detectable portable light apparatus.3. high sensitivity, capable detecting as few two copies per microlitre template 20 template. significant potential distinguishing embryo gender very development.

Language: Английский

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Non‐destructive measurement of eggshell strength using NIR spectroscopy and explainable artificial intelligence

Journal of the Science of Food and Agriculture, Journal Year: 2025, Volume and Issue: unknown

Published: April 17, 2025

Abstract Background Eggshell strength is crucial for ensuring high‐quality eggs, reducing breakage during handling, and meeting consumer expectations freshness integrity. Conventional methods of eggshell measurement are often destructive, time‐consuming unsuitable large‐scale applications. This study evaluated the potential near‐infrared (NIR) spectroscopy combined with explainable artificial intelligence (AI) as a rapid, non‐destructive method determining strength. Various multivariate analysis techniques were explored to enhance prediction accuracy, including spectral pre‐processing variable selection methods. Results Principal component partial least squares discriminant effectively classified eggs based on threshold shell 30 N. Regression models, regression, random forest (RF), light gradient boosting machine K‐nearest neighbors, evaluated. Using only 14 selected variables, RF model achieved very good performance 0.83, root mean square error 1.49 N ratio deviation 2.44. The Shapley additive explanation approach provided insights into contributions, enhancing model's interpretability. Conclusion demonstrated that NIR spectroscopy, integrated AI, robust, environmentally sustainable prediction. innovative holds significant optimizing resource utilization quality control in egg industry. © 2025 Author(s). Journal Science Food Agriculture published by John Wiley & Sons Ltd behalf Society Chemical Industry.

Language: Английский

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Egg characteristics assessment as an enabler for in-ovo sexing technology: A review

Biosystems Engineering, Journal Year: 2024, Volume and Issue: 249, P. 41 - 57

Published: Dec. 2, 2024

Language: Английский

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