AIMC Topic: Chickens

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Flexible Porous ACH/Ag Surface-Enhanced Raman Scattering Platform for Sensitive Detection and Machine-Learning-Assisted Classification of Multiple Pathogenic Bacteria.

Analytical chemistry
Pathogenic bacteria pose serious threats to public health and environmental safety. Conventional colony counting, a standard method for bacterial detection, is time-consuming and unsuitable for rapid on-site detection. In this work, a flexible ACH/Ag...

Rapid analysis of chinese blanched chicken (Mahuang, Tuer, and Huangyou) based on volatile compounds and machine learning.

Food chemistry
To promote the intelligent development of the poultry industry, this study systematically analyzed volatile organic compounds (VOCs) in three Chinese Blanched Chicken (CBC) breeds (Mahuang, Tuer, and Huangyou) using gas chromatography-ion mobility sp...

Global genomic survey of Kentucky: discovery of a chromosomeborne and the emergence of ST314, an MDR clone mediated by the IncR plasmid.

Emerging microbes & infections
Antimicrobial resistance (AMR) in enterica serotype Kentucky ( Kentucky) is a global challenge, with increasing resistance to cephalosporins, ciprofloxacin, and carbapenems significantly limiting treatment strategies, yet its worldwide dissemination...

Research on egg yolk color detection based on near infrared spectroscopy and machine vision.

Analytical methods : advancing methods and applications
Yolk color is a key indicator of egg quality, as customers prefer eggs with intensely yellow yolks, which also signal nutrient richness. At present, the commonly used method for yolk color detection is to open the eggs and evaluate the yolk color usi...

A multi-task deep learning model based on transformer for simultaneously evaluating the TVB-N and TVC contents of chicken breasts using two different hyperspectral imaging.

Food chemistry
Accurate assessment of freshness is crucial for ensuring quality and safety in the chicken meat industry. This study developed a Multi-task Interleaved Group Transformer Model (MIGTM) integrating dual hyperspectral imaging (HSI) data to simultaneousl...

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...

Toroidal indentation for measuring cell and tissue mechanical anisotropy.

Acta biomaterialia
Indentation-based mechanical tests are advantageous for measuring tissue and cell stiffness due to their simplicity and ability to probe samples non-destructively. Most commonly, spherical or pyramidal probes are used, and Hertzian analysis is applie...

Integrative transcriptomics and metabolomics reveal neuroendocrine-lipid crosstalk and adenosine signaling in broiler under heat stress.

BMC genomics
BACKGROUND: Heat stress (HS) is a significant challenge in poultry, negatively impacting feed efficiency and survival. These adaptive responses could lead to disrupted lipid metabolism, impaired immunity, and neural damage. We hypothesized that the n...

Nondestructive freshness recognition of chicken breast meat based on deep learning.

Scientific reports
Identifying chicken breast freshness is an important component of poultry food safety. Traditional methods for chicken breast freshness recognition suffer from issues such as high cost, difficulty in recognition, and low efficiency. In this study, th...

MFSnet: a multi-scale feature screening network for chicken counting in dense environments.

British poultry science
1. Machine-vision-based chicken counting is a highly efficient approach. Nonetheless, in scenarios with high breeding densities, chickens in the captured images frequently overlap with one another. This research addressed the challenge of accurately ...