ArticleScientific reports2025
Prediction and evaluation of environmental quality for nursing sow buildings via multisource sensor information fusion.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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1 citing paper in PubMed.
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4 authors.
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Abstract
Environmental quality in nursing sow buildings has been a crucial determinant of the health and growth performance of piglets in large-scale pig production systems. Given that the environment within sow buildings comprises numerous interrelated factors, predicting and evaluating environmental comfort presents significant challenges. Consequently, accurate assessment of environmental quality and timely regulation of environmental conditions are essential, particularly for optimising breeding efficiency under minimal environmental stress. An analytical method was proposed using multivariate data fusion. The data repair, Grubbs criterion and a batch estimation adaptive weighted calculation method were employed to fuse the multiple sensor data, so as to eliminate abnormal values and redundant data. The Random Forest (RF) model was selected for the feature selection. There were six feature factors that were closely related to environmental quality, including temperature, relative humidity, concentrations of NH3, CO2,H
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