AIMC Topic: Chickens

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Automated detection of broiler vocalizations a machine learning approach for broiler chicken vocalization monitoring.

Poultry science
The poultry industry relies on highly efficient production systems. For sustainable food production, where maintaining broiler welfare is crucial, it is essential to have robust data collection systems and automated methods for assessing broiler heal...

Sustainable gelatin extraction from poultry skin-head-feet blend: An ultrasound-assisted approach.

Poultry science
The study investigated gelatin extraction from chicken skin-head-feet (SHF) blend using conventional and ultrasound-assisted methods with food-grade acetic and citric acids. Ultrasound pretreatment was introduced as an intervention in the extraction ...

Automatic analysis of high, medium, and low activities of broilers with heat stress operations via image processing and machine learning.

Poultry science
Heat stress is a major welfare problem in the poultry industry, altering broilers' activity levels. Advancements in image processing and machine learning provide opportunities to automatically quantify and analyze broiler activity. This study aimed t...

Initializing a Public Repository for Hosting Benchmark Datasets to Facilitate Machine Learning Model Development in Food Safety.

Journal of food protection
While there is clear potential for artificial intelligence (AI) and machine learning (ML) models to help improve food safety, the development and deployment of these models in the food safety domain are by and large lacking. The absence of publicly a...

Classification of chicken Eimeria species through deep transfer learning models: A comparative study on model efficacy.

Veterinary parasitology
Eimeria is a protozoan parasite that causes coccidiosis in various animal species, especially in chickens, resulting in infections characterized by intestinal damage, hemorrhagic diarrhea, lethargy, and high mortality rates in the absence of effectiv...

Edge intelligence for poultry welfare: Utilizing tiny machine learning neural network processors for vocalization analysis.

PloS one
The health of poultry flock is crucial in sustainable farming. Recent advances in machine learning and speech analysis have opened up opportunities for real-time monitoring of the behavior and health of flock. However, there has been little research ...

Physalis Calyx seu Fructus relieves chicken intestinal damage to heat via improving the antioxidant ability.

Frontiers in immunology
Heat-stress-induced oxidative and inflammatory responses were important factors contributing to chicken intestinal damage. The purpose of this study was based on the antioxidant and anti-inflammatory activities of Physalis Calyx seu Fructus (Jin Deng...

Rapid detection of microplastics in chicken feed based on near infrared spectroscopy and machine learning algorithm.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The main objective of this study was to evaluate the potential of near infrared (NIR) spectroscopy and machine learning in detecting microplastics (MPs) in chicken feed. The application of machine learning techniques in building optimal classificatio...

Gene ontology defines pre-post- hatch energy dynamics in the complexus muscle of broiler chickens.

BMC genomics
BACKGROUND: Chicken embryos emerge from their shell by the piercing movement of the hatching muscle. Although considered a key player during hatching, with activity that imposes a substantial metabolic demand, data are still limited. The study provid...

Parallel development of object recognition in newborn chicks and deep neural networks.

PLoS computational biology
How do newborns learn to see? We propose that visual systems are space-time fitters, meaning visual development can be understood as a blind fitting process (akin to evolution) in which visual systems gradually adapt to the spatiotemporal data distri...