Evidence map›Paper›PMID 39624331›Full record

ArticleHeliyon2024

Near-infrared spectroscopy for analysing livestock diet quality: A systematic review.

Md Ekramul Hossain, Muhammad Ashad Kabir, Lihong Zheng, David L Swain, Shawn McGrath, Jonathan Medway

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Increasing Cattle Herd Size or Density in CAnimals : an open access journal from MDPI · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Md Ekramul HossainSchool of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, NSW 2795, Australia.
Muhammad Ashad KabirSchool of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, NSW 2795, Australia.
Lihong ZhengSchool of Computing, Mathematics and Engineering, Charles Sturt University, Bathurst, NSW 2795, Australia.
David L SwainTerraCipher Pty. Ltd., Alton Downs, QLD 4702, Australia.
Shawn McGrathGulbali Institute for Agriculture, Water and Environment, Charles Sturt University, Wagga Wagga, NSW, 2678, Australia.
Jonathan MedwayGulbali Institute for Agriculture, Water and Environment, Charles Sturt University, Wagga Wagga, NSW, 2678, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Near-infrared spectroscopy (NIRS) is a non-invasive and fast technology that has been increasingly used to analyse livestock diet quality. The objective of this study was to conduct a systematic review of the literature to examine the utilisation of NIRS technology for analysing livestock diet quality, with a focus on identifying trends, methodologies, and challenges in recent research. We conducted a systematic search of the literature on five electronic databases and retrieved 718 studies that have been published on the subject. Fifty-four studies were subsequently selected and investigated in depth. These studies were categorised into two groups, namely benchtop and portable, based on the types of NIRS devices utilised, with a majority employing the reflectance spectra mode. Our analysis found that standard normal variate (SNV), detrend (DT), and multiplicative scatter correction (MSC) are the most commonly used spectral data processing methods. The findings indicate that NIRS technology can provide accurate and reliable measurements of key livestock diet quality parameters such as crude protein, fibre, and moisture content. Additionally, we discuss the challenges associated with NIRS technology and provide recommendations for future research directions to further advance the use of NIRS technology in the livestock industry.

Indexed as

Diet qualityFecalForageGrain feedLivestockNear-infrared spectroscopyRegression model

Identifiers

PMID39624331
PMCPMC11609248

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.