Evidence map›Paper›PMID 33572673›Full record

ReviewAnimals : an open access journal from MDPI2021

Challenges and Tendencies of Automatic Milking Systems (AMS): A 20-Years Systematic Review of Literature and Patents.

Alessia Cogato, Marta Brščić, Hao Guo, Francesco Marinello, Andrea Pezzuolo

Abstract readReview
In one paragraph

Review in Animals : an open access journal from MDPI, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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

5 authors.

Alessia CogatoDepartment of Land, Environmental, Agriculture and Forestry, University of Padova, 35020 Legnaro (PD), Italy.ORCID 0000-0001-8354-7324
Marta BrščićDepartment of Animal Medicine, Production and Health, University of Padova, 35020 Legnaro (PD), Italy.ORCID 0000-0001-8366-5961
Hao GuoCollege of Land Science and Technology, China Agricultural University, Beijing 100083, China.ORCID 0000-0001-9317-4015
Francesco MarinelloDepartment of Land, Environmental, Agriculture and Forestry, University of Padova, 35020 Legnaro (PD), Italy.ORCID 0000-0002-3283-5665
Andrea PezzuoloDepartment of Land, Environmental, Agriculture and Forestry, University of Padova, 35020 Legnaro (PD), Italy.ORCID 0000-0002-9955-9896

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over the last two decades, the dairy industry has adopted the use of Automatic Milking Systems (AMS). AMS have the potential to increase the effectiveness of the milking process and sustain animal welfare. This study assessed the state of the art of research activities on AMS through a systematic review of scientific and industrial research. The papers and patents of the last 20 years (2000-2019) were analysed to assess the research tendencies. The words appearing in title, abstract and keywords of a total of 802 documents were processed with the text mining tool. Four clusters were identified (Components, Technology, Process and Animal). For each cluster, the words frequency analysis enabled us to identify the research tendencies and gaps. The results showed that focuses of the scientific and industrial research areas complementary, with scientific papers mainly dealing with topics related to animal and process, and patents giving priority to technology and components. Both scientific and industrial research converged on some crucial objectives, such as animal welfare, process sustainability and technological development. Despite the increasing interest in animal welfare, this review highlighted that further progress is needed to meet the consumers' demand. Moreover, milk yield is still regarded as more valuable compared to milk quality. Therefore, additional effort is necessary on the latter. At the process level, some gaps have been found related to cleaning operations, necessary to improve milk quality and animal health. The use of farm data and their incorporation on herd decision support systems (DSS) appeared optimal. The results presented in this review may be used as an overall assessment useful to address future research.

Indexed as

automationdairy farmingmilkingprecision livestock farmingrobotic milking

Identifiers

PMID33572673
PMCPMC7912558

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.