S. McParland

3.6k total citations · 1 hit paper
69 papers, 2.6k citations indexed

About

S. McParland is a scholar working on Genetics, Agronomy and Crop Science and Animal Science and Zoology. According to data from OpenAlex, S. McParland has authored 69 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 54 papers in Genetics, 51 papers in Agronomy and Crop Science and 21 papers in Animal Science and Zoology. Recurrent topics in S. McParland's work include Genetic and phenotypic traits in livestock (52 papers), Ruminant Nutrition and Digestive Physiology (23 papers) and Reproductive Physiology in Livestock (23 papers). S. McParland is often cited by papers focused on Genetic and phenotypic traits in livestock (52 papers), Ruminant Nutrition and Digestive Physiology (23 papers) and Reproductive Physiology in Livestock (23 papers). S. McParland collaborates with scholars based in Ireland, Belgium and Italy. S. McParland's co-authors include D.P. Berry, Deirdre C. Purfield, Daniel G. Bradley, Hélène Soyeurt, E. Wall, M.P. Coffey, Nicolas Gengler, Frédéric Dehareng, E. Wall and Pierre Dardenne and has published in prestigious journals such as PLoS ONE, Trends in Food Science & Technology and Journal of Dairy Science.

In The Last Decade

S. McParland

68 papers receiving 2.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Runs of homozygosity and population history in cattle

2012 415 citations Deirdre C. Purfield, D.P. Berry et al. profile →

Peers

Countries citing papers authored by S. McParland

Since Specialization

Citations

This map shows the geographic impact of S. McParland's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by S. McParland with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites S. McParland more than expected).

Fields of papers citing papers by S. McParland

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by S. McParland. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by S. McParland. The network helps show where S. McParland may publish in the future.

Co-authorship network of co-authors of S. McParland

This figure shows the co-authorship network connecting the top 25 collaborators of S. McParland. A scholar is included among the top collaborators of S. McParland based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with S. McParland. S. McParland is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

#	Work	Indexed citations
1	Estimation of body condition score change in dairy cows in a seasonal calving pasture-based system using routinely available milk mid-infrared spectra and machine learning techniques 2023 ·Journal of Dairy Science ·(unknown), Isobel Claire Gormley, D.P. Berry, S. McParland	10
2	Cow-level factors associated with nitrogen utilization in grazing dairy cows using a cross-sectional analysis of a large database 2023 ·Journal of Dairy Science ·E. Tavernier, Isobel Claire Gormley, Luc Delaby, S. McParland, M. O’Donovan, D.P. Berry	9
3	Evaluation of test-day milk somatic cell count to predict intramammary infection in late lactation grazing dairy cows 2023 ·Journal of Dairy Science ·(unknown), (unknown), P. Dillon, S. McParland, Seán Arkins, Kathleen O’Sullivan, James Flynn, J. Murphy, (unknown)	5
4	Predicting cow milk quality traits from routinely available milk spectra using statistical machine learning methods 2021 ·Journal of Dairy Science ·(unknown), Isobel Claire Gormley, D.P. Berry, Thomas Brendan Murphy, (unknown), (unknown), S. McParland	58
5	A comparison of 4 different machine learning algorithms to predict lactoferrin content in bovine milk from mid-infrared spectra 2020 ·Journal of Dairy Science ·Hélène Soyeurt, Clément Grelet, S. McParland, (unknown), M.P. Coffey, (unknown), (unknown), Frédéric Dehareng, Nicolas Gengler	37
6	Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysis 2019 ·Journal of Dairy Science ·(unknown), S. McParland, E. Kennedy, T.M. Boland, (unknown), (unknown), N. Galvin, B. McCarthy, F. Buckley	35
7	Milk production of Holstein-Friesian cows of divergent Economic Breeding Index evaluated under seasonal pasture-based management 2019 ·Journal of Dairy Science ·Michael O’Sullivan, B. Horan, K.M. Pierce, S. McParland, Kathleen O’Sullivan, F. Buckley	48
8	Effect of using internal teat sealant with or without antibiotic therapy at dry-off on subsequent somatic cell count and milk production 2019 ·Journal of Dairy Science ·S. McParland, P. Dillon, James Flynn, Nick Ryan, Seán Arkins, (unknown)	39
9	Genetic and nongenetic factors associated with milk color in dairy cows 2017 ·Journal of Dairy Science ·(unknown), S. McParland, Giulio Visentin, D.P. Berry, (unknown), Massimo De Marchi	26
10	Genetics of alternative definitions of feed efficiency in grazing lactating dairy cows 2017 ·Journal of Dairy Science ·(unknown), N. López‐Villalobos, S. McParland, E. Lewis, E. Kennedy, M. O’Donovan, J.L. Burke, D.P. Berry	35
11	Inference of population structure of purebred dairy and beef cattle using high-density genotype data 2016 ·animal ·Margaret Kelleher, D.P. Berry, John F. Kearney, S. McParland, F. Buckley, Deirdre C. Purfield	31
12	Hot topic: Innovative lactation-stage-dependent prediction of methane emissions from milk mid-infrared spectra 2015 ·Journal of Dairy Science ·Amélie Vanlierde, Marie-Laure Vanrobays, Frédéric Dehareng, Éric Froidmont, Hélène Soyeurt, S. McParland, (unknown), M.H. Deighton, Florian Grandl, Michael Kreuzer, Birgit Gredler, Pierre Dardenne, Nicolas Gengler	75
13	Mid-Infrared Spectroscopy to Predict Feed Intake and Efficiency in Lactating Dairy Cows 2014 ·S. McParland	1
14	Genetic parameters for methane emissions predicted from milk mid-infrared spectra in dairy cows 2013 ·Journal of Dairy Science ·(unknown), Marie-Laure Vanrobays, Amélie Vanlierde, Frédéric Dehareng, Éric Froidmont, Pierre Dardenne, E. Lewis, F. Buckley, (unknown), S. McParland, Nicolas Gengler, Hélène Soyeurt	6
15	Genetics of body energy status of Holstein cows predicted by mid-infrared spectrometry 2013 ·Journal of Dairy Science ·Catherine Bastin, D.P. Berry, Nicolas Gengler, S. McParland	1
16	Genome-wide association study for milk fatty acid composition using cow versus bull data 2012 ·Socio-Environmental Systems Modeling ·Catherine Bastin, Nicolas Gengler, Hélène Soyeurt, S. McParland, E. Wall, M.P.L. Calus	1
17	Lessons Learned in Pooling Data for Reference Populations 2011 ·Socio-Environmental Systems Modeling ·E. Wall, M.P. Coffey, R.F. Veerkamp, S. McParland, Georgios Banos	1
18	Genetic Evaluations for Energy Balance A Real Possibility 2011 ·Bulletin - International Bull Evaluation Service/Interbull bulletin ·S. McParland, Georgios Banos, M. O’Donovan, M.P. Coffey, B. McCarthy, H B O'Neill, E. Wall, D.P. Berry	4
19	Mid-infrared prediction of bovine milk fatty acids across multiple breeds, production systems, and countries 2011 ·Journal of Dairy Science ·Hélène Soyeurt, Frédéric Dehareng, Nicolas Gengler, S. McParland, E. Wall, D.P. Berry, M.P. Coffey, Pierre Dardenne	247
20	Inbreeding trends in purebred Irish beef cattle. 2006 ·Proceedings of the 8th World Congress on Genetics Applied to Livestock Production, Belo Horizonte, Minas Gerais, Brazil, 13-18 August, 2006 ·S. McParland, John F. Kearney, M. Rath, D.P. Berry	1

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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