AIMC Topic: Farms

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On-farm 3D images of beef cattle for the prediction of carcass classification traits and cold carcass weight.

Animal : an international journal of animal bioscience
For beef cattle, subjective methods tend to be used on-farm for assessing readiness for slaughter. This means that the target classification grades cannot be accurately estimated, leading to over- and under-finished animals being sent to slaughter. T...

Machine learning for predictive mapping of exceedance probabilities for potentially toxic elements in Czech farmland.

Journal of environmental management
For efficient decision-making and optimal land management trajectories, information on soil properties in relation to safety guidelines should be processed from point inventories to surface predictive maps. For large-scale predictive mapping, very fe...

A drop dispenser for simplifying on-farm detection of foodborne pathogens.

PloS one
Nucleic-acid biosensors have emerged as useful tools for on-farm detection of foodborne pathogens on fresh produce. Such tools are specifically designed to be user-friendly so that a producer can operate them with minimal training and in a few simple...

A Systematic Review and Meta-Analysis of the Efficacy of Biosecurity in Disease Prevention and Control in Livestock Farms in Africa.

Transboundary and emerging diseases
In Africa, livestock production plays a crucial role for sustainable food security and economic growth. However, the development of this sector has been delayed by livestock diseases, one of the main constraints, which can cause important production ...

Inversion model of soil salinity in alfalfa covered farmland based on sensitive variable selection and machine learning algorithms.

PeerJ
PURPOSE: Timely and accurate monitoring of soil salinity content (SSC) is essential for precise irrigation management of large-scale farmland. Uncrewed aerial vehicle (UAV) low-altitude remote sensing with high spatial and temporal resolution provide...

GooseDetect: A Fully Annotated Dataset for Lion-head Goose Detection in Smart Farms.

Scientific data
Large datasets are required to develop Artificial Intelligence (AI) models in AI powered smart farming for reducing farmers' routine workload, this paper contributes the first large lion-head goose dataset GooseDetect, which consists of 2,660 images ...

Assessing the risk of E. coli contamination from manure application in Chinese farmland by integrating machine learning and Phydrus.

Environmental pollution (Barking, Essex : 1987)
This study aims to present a comprehensive study on the risks associated with the residual presence and transport of Escherichia coli (E. coli) in soil following the application of livestock manure in Chinese farmlands by integrating machine learning...

Transforming Poultry Farming: A Pyramid Vision Transformer Approach for Accurate Chicken Counting in Smart Farm Environments.

Sensors (Basel, Switzerland)
Smart farm environments, equipped with cutting-edge technology, require proficient techniques for managing poultry. This research investigates automated chicken counting, an essential part of optimizing livestock conditions. By integrating artificial...

DairyCoPilot-Automated data compilation and analysis tools for DairyComp data assets.

PloS one
Modern dairy farm management requires meaningful data and careful analysis to maximize profitability, cow health, and welfare. Current data platforms, such as DairyComp, lack robust integrated data analysis tools. Producers and consultants need dedic...

Improvement of pasture biomass modelling using high-resolution satellite imagery and machine learning.

Journal of environmental management
Robust quantification of vegetative biomass using satellite imagery using one or more forms of machine learning (ML) has hitherto been hindered by the extent and quality of training data. Here, we showcase how ML predictive demonstrably improves when...