What is he best known for?
The fields of study he is best known for:
- Internal medicine
- Animal science
- Biochemistry
M. L. Galyean mostly deals with Animal science, Beef cattle, Feedlot, Dry matter and Feedlot cattle.
His research in Animal science intersects with topics in Internal medicine, Feces and Forage.
His Forage research includes elements of Rangeland, Incubation, Propionate, Digestion and Fodder.
M. L. Galyean has researched Beef cattle in several fields, including Weight gain, Immune system and Agricultural science.
His Feedlot study combines topics in areas such as Environmental protection, Marbled meat, Veterinary medicine, Randomized block design and Crossbreed.
His work carried out in the field of Dry matter brings together such families of science as Dairy cattle, Sorghum, Net energy and Feed conversion ratio.
His most cited work include:
- Board-invited review: recent advances in management of highly stressed, newly received feedlot cattle. (343 citations)
- Interaction of cattle health/immunity and nutrition. (208 citations)
- Nutritional recommendations of feedlot consulting nutritionists: the 2007 Texas Tech University survey. (199 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Animal science, Beef cattle, Feedlot, Agronomy and Food science.
M. L. Galyean combines subjects such as Digestion, Forage and Internal medicine with his study of Animal science.
His studies in Digestion integrate themes in fields like Rumen, Latin square and Starch.
His Forage research is multidisciplinary, incorporating elements of Organic matter, Feces and Grazing.
M. L. Galyean works mostly in the field of Beef cattle, limiting it down to topics relating to Nutrient and, in certain cases, Biotechnology, as a part of the same area of interest.
His Feedlot study integrates concerns from other disciplines, such as Veterinary medicine, Cattle feeding, Animal feed and Marbled meat.
He most often published in these fields:
- Animal science (61.38%)
- Beef cattle (34.15%)
- Feedlot (28.46%)
What were the highlights of his more recent work (between 2011-2021)?
- Beef cattle (34.15%)
- Animal science (61.38%)
- Nutrient (7.72%)
In recent papers he was focusing on the following fields of study:
M. L. Galyean focuses on Beef cattle, Animal science, Nutrient, Food science and Biotechnology.
His Beef cattle study combines topics from a wide range of disciplines, such as Rumen, Yeast extract, Dietary supplementation and Animal feed.
His Animal science research is multidisciplinary, incorporating perspectives in Forage, Moringa and Simple linear regression.
His Food science research incorporates themes from Randomized block design and Feedlot.
The Feedlot study combines topics in areas such as Dietary fiber, Cattle feeding and Distillers grains.
His research integrates issues of Hay and Marbled meat in his study of Starch.
Between 2011 and 2021, his most popular works were:
- Nutritional recommendations of feedlot consulting nutritionists: The 2015 New Mexico State and Texas Tech University survey (102 citations)
- Effect of feeding diets with processed Moringa oleifera meal as protein source in lactating Anglo-Nubian goats (43 citations)
- Influence of wet distillers grains diets on beef cattle fecal bacterial community structure. (37 citations)
In his most recent research, the most cited papers focused on:
- Internal medicine
- Biochemistry
- Enzyme
M. L. Galyean focuses on Animal science, Beef cattle, Dry matter, Nutrient and Food science.
He performs multidisciplinary study in Animal science and Linear equation in his work.
The various areas that M. L. Galyean examines in his Beef cattle study include Feedlot, Distillers grains, Regression, Mean squared error and Net energy.
His Feedlot study incorporates themes from Dietary fiber and Medical education.
The concepts of his Dry matter study are interwoven with issues in Feedlot cattle, Lasalocid, Substrate and Predictive value.
Many of his research projects under Food science are closely connected to Individual data and Independent data with Individual data and Independent data, tying the diverse disciplines of science together.
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