Hyperspectral imaging and explainable deep-learning for non-destructive quality prediction of sweetpotato DOI Creative Commons
Md. Toukir Ahmed, Arthur Villordon, Mohammed Kamruzzaman

и другие.

Postharvest Biology and Technology, Год журнала: 2024, Номер 222, С. 113379 - 113379

Опубликована: Дек. 25, 2024

Язык: Английский

A comprehensive review of deep learning-based hyperspectral image reconstruction for agri-food quality appraisal DOI Creative Commons
Md. Toukir Ahmed, Ocean Monjur, Alin Khaliduzzaman

и другие.

Artificial Intelligence Review, Год журнала: 2025, Номер 58(4)

Опубликована: Янв. 25, 2025

Язык: Английский

Процитировано

4
Nondestructive Prediction of Eggshell Thickness Using NIR Spectroscopy and Machine Learning with Explainable AI DOI
Md Wadud Ahmed,

S. Sharar Alam,

Alin Khaliduzzaman

и другие.

ACS Food Science & Technology, Год журнала: 2025, Номер unknown

Опубликована: Янв. 22, 2025

Язык: Английский

Процитировано

3
Influence of particle size on NIR spectroscopic characterization of sorghum biomass for the biofuel industry DOI Creative Commons
Md Wadud Ahmed, Carlos Esquerre, Kristen K. Eilts

и другие.

Results in Chemistry, Год журнала: 2025, Номер 13, С. 102016 - 102016

Опубликована: Янв. 1, 2025

Язык: Английский

Процитировано

1
An overview of recent advancements in hyperspectral imaging in the egg and hatchery industry DOI Creative Commons
Md Wadud Ahmed, Alin Khaliduzzaman, J.L. Emmert

и другие.

Computers and Electronics in Agriculture, Год журнала: 2024, Номер 230, С. 109847 - 109847

Опубликована: Дек. 18, 2024

Язык: Английский

Процитировано

5
Non-destructive pre-incubation sex determination in chicken eggs using hyperspectral imaging and machine learning DOI Creative Commons
Md Wadud Ahmed,

Asher Sprigler,

J.L. Emmert

и другие.

Food Control, Год журнала: 2025, Номер unknown, С. 111233 - 111233

Опубликована: Фев. 1, 2025

Язык: Английский

Процитировано

0
A systematic review of explainable artificial intelligence for spectroscopic agricultural quality assessment DOI Creative Commons
Md. Toukir Ahmed,

Md Wadud Ahmed,

Mohammed Kamruzzaman

и другие.

Computers and Electronics in Agriculture, Год журнала: 2025, Номер 235, С. 110354 - 110354

Опубликована: Апрель 4, 2025

Язык: Английский

Процитировано

0
Non‐destructive measurement of eggshell strength using NIR spectroscopy and explainable artificial intelligence DOI Creative Commons

Md Wadud Ahmed,

S. Sharar Alam,

Alin Khaliduzzaman

и другие.

Journal of the Science of Food and Agriculture, Год журнала: 2025, Номер unknown

Опубликована: Апрель 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.

Язык: Английский

Процитировано

0
Hyperspectral imaging and explainable deep-learning for non-destructive quality prediction of sweetpotato DOI Creative Commons
Md. Toukir Ahmed, Arthur Villordon, Mohammed Kamruzzaman

и другие.

Postharvest Biology and Technology, Год журнала: 2024, Номер 222, С. 113379 - 113379

Опубликована: Дек. 25, 2024

Язык: Английский

Процитировано

2