ArticleJDS communications2025
Application of multivariate techniques for estimating herd feed efficiency using chemical and near-infrared calibration models in dairy cattle.
Article in JDS communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Feed efficiency (FE) is an indicator of overall farm nutritional efficiency, helping farmers to identify any critical points in nutritional management. Particularly, FE is a measure of the ability of animals to convert feed into milk and it can be influenced by genetic, health, management, and nutritional factors. Higher FE allows results in reduced feed and maintenance costs and contributes to improved economic and environmental efficiency of dairy farms. This study aimed to develop and compare 2 predictive models for estimating FE in dairy cattle using data derived from the TMR: one based on its chemical composition and the other on near-infrared (NIR) spectral data. A total of 144 TMR samples were collected from farms in Po Valley from 2021 to 2024 and analyzed with an Fourier-transform NIR spectrometer. The spectral data were processed with chemometric techniques, including least absolute shrinkage and selection operator regression, in order to build a predictive model of FE. The model based on chemical composition showed strong calibration performance (R
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.