AIMC Topic: Cattle

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Weighted gene co-expression network analysis identifies functional modules related to bovine respiratory disease.

PloS one
Bovine respiratory disease (BRD) is a multifactorial disease of dairy and beef cattle that involves complex interactions with the host immune system. In the current study, a comprehensive meta-analysis was performed using a P-value combination approa...

The SERS method based on the COF-ag substrate, combined with machine learning, is used for the detection of tetracycline and oxytetracycline in milk.

Food chemistry
Tetracycline antibiotics, valued for potent antibacterial effects, are widely used in livestock but raise concerns over unsafe residues in milk. In this study, a surface-enhanced Raman spectroscopy (SERS) method based on an amino-functionalized coval...

Improving bovine disease detection through multilabel classification.

Scientific reports
R1.C1: The dairy industry is a cornerstone of global food production and economic development; yet, its productivity is frequently hindered by common bovine health issues, including lameness, mastitis, metritis, and foot-and-mouth disease. These cond...

Maternal administration of octanoate, a medium-chain fatty acid, improves feed efficiency of Japanese black calves through influencing gut bacteriome structure.

Scientific reports
Maternal-offspring gut bacteriomes are closely linked to each other; however, the effects of the maternal diet have not been fully elucidated. This study aimed to determine the effect of administration of octanoate, a medium-chain fatty acid as a phy...

Field-oriented assessment of bovine tuberculosis in Tunisian cattle: IDR, PCR and serological test prediction based on AI approaches.

World journal of microbiology & biotechnology
Bovine tuberculosis (bTB), caused by Mycobacterium bovis (M. bovis), remains a major zoonotic and economically burdensome disease worldwide. In Tunisia, where bTB has remained present for many years, Efforts to eliminate the disease have been slowed ...

Leveraging pre-trained computer vision models for accurate classification of meat freshness.

Food chemistry
Increasing concerns about food quality and safety have led to research into ways to assess meat freshness. Advances in deep learning, particularly image classification, enable up new possibilities for fast and non-destructive methods of evaluating me...

Dynamic forecasting of beef freshness using multi-step time series analysis of electronic nose signals.

Biosensors & bioelectronics
The preservation of microbial quality in meat products represents a fundamental challenge in contemporary food supply chain management due to the highly perishable nature of these commodities. Although modern testing techniques, particularly electron...

Machine learning based on pangenome-wide association studies reveals the impact of host source on the zoonotic potential of closely related bacterial pathogens.

Communications biology
Variations in host species significantly impact bacterial growth traits and antibiotic resistance, making it essential to consider host origin when evaluating the zoonotic potential of pathogens. This study focuses on multiple Brucella species, which...

Integrated deep eutectic solvent with amorphous metal-organic framework for highly sensitive electrochemical determination of dicofol in milk and water.

Food chemistry
High-throughput screening of deep eutectic solvents (DESs) was performed using artificial intelligence/quantum mechanical models. Ni-amorphous metal-organic frameworks (aMOFs) was synthesized through amine-DES aqueous solution. The target-specific DE...

Prediction of blown pack in vacuum-packaged beef based on microbiome profiles and supervised machine learning.

International journal of food microbiology
The preservation of vacuum-packaged beef products is essential for maintaining shelf life. However, the occurrence of blown pack phenomenon, characterized by the expansion of packaging due to gas production by spoilage microorganisms, is still a chal...