S. McParland

Teagasc - The Irish Agriculture and Food Development Authority — Ireland

Biochemistry, Genetics and Molecular Biology · Life Sciences

31h-index3.5kcitations99works0.02yr avg
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Research Topics

Genetic and phenotypic traits in livestock(61), Reproductive Physiology in Livestock(26), Ruminant Nutrition and Digestive Physiology(25), Milk Quality and Mastitis in Dairy Cows(21), Effects of Environmental Stressors on Livestock(21)

Publications99 total

Transferability across countries of equations developed using milk mid-infrared spectroscopy to estimate daily body condition score change in dairy cows
Journal of Dairy Science·2024Open Access
Predicting methane emissions of individual grazing dairy cows from spectral analyses of their milk samples
Journal of Dairy Science·2023· 13 citedOpen Access
Cow-level factors associated with nitrogen utilization in grazing dairy cows using a cross-sectional analysis of a large database
Journal of Dairy Science·2023· 13 citedOpen Access
Evaluation of test-day milk somatic cell count to predict intramammary infection in late lactation grazing dairy cows
Journal of Dairy Science·2023· 6 citedOpen Access
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
Journal of Dairy Science·2023· 14 citedOpen Access
125. Milk spectra selection for equations development to predict milk technological traits
2022
67. Genetic variation exists in nitrogen use efficiency for lactating cows in grass-grazed dairy systems
2022
Breeding for improved protein fractions and free amino acids concentration in bovine milk
Journal of Animal Breeding and Genetics·2022· 3 citedOpen Access
The development of effective ruminant breeding programmes in Ireland from science to practice
Irish Journal of Agricultural and Food Research·2022· 12 citedOpen Access
Internal teat sealants alone or in combination with antibiotics at dry-off – the effect on udder health in dairy cows in five commercial herds
animal·2022· 23 citedOpen Access
Irish research response to dairy quality in an era of change
Irish Journal of Agricultural and Food Research·2022· 2 citedOpen Access
Selecting Milk Spectra to Develop Equations to Predict Milk Technological Traits
Foods·2021Open Access
Analysis of milk solids production and mid-lactation bodyweight to evaluate cow production efficiency on commercial dairy farms
Livestock Science·2021· 8 citedOpen Access
Predicting cow milk quality traits from routinely available milk spectra using statistical machine learning methods
Journal of Dairy Science·2021· 88 citedOpen Access
161 Predicting milk quality traits in dairy cows from routinely available milk spectra using machine learning methods
Animal - science proceedings·2021
Health-related outcomes of genetic polymorphism of bovine β-casein variants: A systematic review of randomised controlled trials
Trends in Food Science & Technology·2021· 53 cited
Improving robustness and accuracy of predicted daily methane emissions of dairy cows using milk mid‐infrared spectra
Journal of the Science of Food and Agriculture·2020· 27 citedOpen Access
A comparison of 4 different machine learning algorithms to predict lactoferrin content in bovine milk from mid-infrared spectra
Journal of Dairy Science·2020· 49 citedOpen Access
Prediction of 24-hour milk yield and composition in dairy cows from a single part-day yield and sample
Irish Journal of Agricultural and Food Research·2019· 9 citedOpen Access
Predicting the dry matter intake of grazing dairy cows using infrared reflectance spectroscopy analysis
Journal of Dairy Science·2019· 55 citedOpen Access
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Frequent Co-authors

D.P. Berry(37), Hélène Soyeurt(8), Massimo De Marchi(8), Nicolas Gengler(7), A. McDermott(7), Giulio Visentin(7), Frédéric Dehareng(6), E. Wall(6), E. Kennedy(6), M.P. Coffey(5), E. Lewis(5), Pierre Dardenne(4), B. McCarthy(4), N. López‐Villalobos(4), Deirdre C. Purfield(3), E. Lewis(3), M. O’Donovan(3), Mark A. Fenelon(3), Amélie Vanlierde(3), Éric Froidmont(3)