AI-Papers

Faculty AI Research Papers

AI-Related Research Papers (Authored by AI@AU Faculty)

Big data analytics in food industry: a stateof-the-art literature review

Aftab Siddique, Ashish Gupta, Jason T. Sawyer, Tung-Shi Huang & Amit Morey

Abstract: Access to safe, healthy, and adequate food is fundamental for the expanding world population. The food sector faces increasing issues in maintaining food safety, quality, and supply due to escalating population demands and evolving consumer tastes. Confronting these difficulties necessitates innovative, cost-effective, and sustainable solutions to enhance the efficiency of food production, distribution, and safety monitoring systems1. Integrating Big Data Analytics (BDA) has ... continue reading

Development of Predictive Classification Models and Extraction of Signature Wavelengths for the Identification of Spoilage in Chicken Breast Fillets During Storage Using Near Infrared Spectroscopy

Aftab Siddique, Charles B. Herron, Bet Wu, Katherine S. S. Melendrez, Luis J. G. Sabillon, Laura J. Garner Mary Durstock, Alvaro Sanz‑Saez, Amit Morey

Abstract: Technologies for rapid identification and prediction of food spoilage can be crucial in minimizing food waste and losses, although their efficiency requires further improvement. This study aimed to pinpoint specific near-infrared (NIR) wavelengths that could indicate spoilage in raw chicken breast fillets. In this study, commercial tray-packs of boneless, skinless chicken breast fillets stored in a walk-in cooler ... continue reading

Rapid detection of poultry meat quality using S-band to KU-band radio-frequency waves combined with machine learning—A proof of concept 

Aftab Siddique, Ashish Gupta, Jason Sawyer, Laura J. Garner, Amit Morey

Abstract: Rapid changes in consumer preferences for high-quality animal-based protein have driven the poultry industry to identify non-invasive, in-line processing technologies for rapid detection of muscle meat quality defects. At production plants, technologies like radio-frequency waves (RF waves) can identify and separate myopathy-conditioned meat, reducing misclassification errors due to human fatigue and inexperience. Previous studies have shown that advanced diagnostic tools combined with complex data analytics, such as support vector machines (SVMs) and backpropagation neural networks (BPNNs), can classify chicken breast myopathies post-deboning. This study demonstrates ... continue reading

Effect of Age, Deboning Time of Carcass, and Different Cooking Conditions on the Woody Breast Myopathies in Chicken: A Meta-Analysis

Aftab Siddique, Micah T. Black, Bet W. Alvarado, Laura Garner, Tung-Shi Huang, Ashish Gupta, Alan E. Wilson, Jason T. Sawyer, Amit Morey

Abstract: This meta-analysis review undertakes a comprehensive examination of various approaches for identifying myopathic fillets and meticulously evaluates the effects of bird age, deboning time, and different cooking and storage conditions on woody breast (WB) myopathic conditions in broiler deboned fillets. The data, meticulously collected from 20 articles based on predefined inclusion criteria sourced from various databases and online resources, reveal significant insights. For instance, the analysis uncovers that deboning time significantly affects Meullenet-Owens Razor Shear (MORS), Blunt Meullenet-Owens Razor Shear (BMORS), and descriptive analysis ... continue reading 

Classification and Feature Extraction Using Supervised and Unsupervised Machine Learning Approach for Broiler Woody Breast Myopathy Detection

Aftab Siddique, Charles B. Herron, Jaroslav Valenta, Laura J. Garner, Ashish Gupta, Jason T. Sawyer, Amit Morey

Abstract: Bioelectrical impedance analysis (BIA) was established to quantify diverse cellular characteristics. This technique has been widely used in various species, such as fish, poultry, and humans for compositional analysis. This technology was limited to offline quality assurance/detection of woody breast (WB); however, inline technology that can be retrofitted on the conveyor belt would be more helpful to processors. Freshly deboned (n = 80) chicken breast fillets ... continue reading

Building “First Expire, First Out” models to predict food losses at retail due to cold chain disruption in the last mile

Charles B. Herron, Laura J. Garner, Aftab Siddique, Tung-Shi Huang, Jesse C. Campbell, Shashank Rao, Amit Morey

Abstract: Current less-than-truckload (LTL) shipping practices allow for temperature abuse (TA) in the last segment (last mile) of the food supply chain. When this TA is combined with “First In, First Out” product rotation methods, it could lead to food spoilage and food waste; therefore, data-based decision models are needed to aid retail managers. An experiment was designed using pallets (4 layers/pallet × 5 boxes/layer) of commercially produced boneless chicken breast filet trays. The pallets were exposed to 24 h of simulated ... continue reading

Testing the capability of generative artificial intelligence for parent and caregiver information seeking

YaeBin Kim, Silvia L. Vilches, Sidney Shapiro, Anne Clarkson

Abstract: This study explored the quality of generative artificial intelligence (AI) responses to common parenting questions across diverse sources of digitally available information ... continue reading

Partnering with Reach Out and Read to understand families' experiences with books and their babies

Kimberly M. Rogers, Cynthia A. Frosch, Silvia L. Vilches, Sheila R. Sjolseth

Preparing Early Childhood Educators/Interventionists: Scoping Review Insights Into the Characteristics of Rural Practice

Silvia L. Vilches, Maria J. Pighini, Mary J.Stewart, Verena Rossa-Roccor, Beth McDaniel