What is she best known for?
The fields of study she is best known for:
- Statistics
- Agriculture
- Genetics
Hélène Soyeurt mostly deals with Fatty acid, Animal science, Partial least squares regression, Dairy cattle and Food science.
Hélène Soyeurt has included themes like Breed and Herd in her Fatty acid study.
Her studies in Animal science integrate themes in fields like Sugar beet and Lactation.
Her research integrates issues of Energy, Energy balance and Mass spectrometry in her study of Partial least squares regression.
Her Dairy cattle research integrates issues from Mid infrared spectrometry and Heritability.
Her Food science study incorporates themes from Repeatability and Biotechnology.
Her most cited work include:
- Estimating Fatty Acid Content in Cow Milk using Mid-Infrared Spectrometry (202 citations)
- Mid-infrared prediction of bovine milk fatty acids across multiple breeds, production systems, and countries. (178 citations)
- Variation in Fatty Acid Contents of Milk and Milk Fat Within and Across Breeds (128 citations)
What are the main themes of her work throughout her whole career to date?
Her main research concerns Animal science, Dairy cattle, Mid infrared, Food science and Fatty acid.
The various areas that Hélène Soyeurt examines in her Animal science study include Lactation, Parity and Heritability.
Her work carried out in the field of Lactation brings together such families of science as Internal medicine and Endocrinology.
In Dairy cattle, Hélène Soyeurt works on issues like Biotechnology, which are connected to Animal breeding.
Her Fatty acid research is multidisciplinary, relying on both Bovine milk and Mid infrared spectrometry.
Hélène Soyeurt has researched Mid infrared spectrometry in several fields, including Chromatography and Cow milk.
She most often published in these fields:
- Animal science (41.46%)
- Dairy cattle (25.61%)
- Mid infrared (18.70%)
What were the highlights of her more recent work (between 2017-2021)?
- Animal science (41.46%)
- Dairy cattle (25.61%)
- Mid infrared (18.70%)
In recent papers she was focusing on the following fields of study:
Her primary areas of investigation include Animal science, Dairy cattle, Mid infrared, Statistics and Business.
Her biological study spans a wide range of topics, including Lactose, Lactation, Body weight, Methane and Test day.
Hélène Soyeurt applies her multidisciplinary studies on Lactation and Bran in her research.
Mammary gland and Phenotype are fields of study that overlap with her Dairy cattle research.
Her Statistics study integrates concerns from other disciplines, such as External validation, Herd and Residual.
Her Standard error research is multidisciplinary, incorporating elements of Breed and Ice calving.
Between 2017 and 2021, her most popular works were:
- Short communication: Development of an equation for estimating methane emissions of dairy cows from milk Fourier transform mid-infrared spectra by using reference data obtained exclusively from respiration chambers (20 citations)
- Diagnosing the pregnancy status of dairy cows: How useful is milk mid-infrared spectroscopy? (11 citations)
- Relationships between Pb, As, Cr, and Cd in individual cows’ milk and milk composition and heavy metal contents in water, silage, and soil (11 citations)
In her most recent research, the most cited papers focused on:
- Statistics
- Agriculture
- Genetics
Hélène Soyeurt mainly investigates Animal science, Lactation, Weaning, Statistics and Partial least squares regression.
Her work deals with themes such as Inductively coupled plasma mass spectrometry, Lactose and Fatty acid, which intersect with Animal science.
Her Lactation study combines topics in areas such as Feeding behavior, Rumen, Methane, Hay and Carbon dioxide.
Her Weaning study combines topics from a wide range of disciplines, such as Andrology, Inulin, Gestation and Period.
Her Statistics research includes themes of Herd and Residual.
Her studies deal with areas such as Stability and Econometrics as well as Partial least squares regression.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
