BBSRC Portfolio Analyser
Investigator / Supervisor details
Name
Professor Martin Green
Current Institution
University of Nottingham
Current Department
School of Veterinary Medicine and Sci
Institution website
http://www.nott.ac.uk
Previous Institutions
Current Awards
Reference
Title
Award Role
Value £
Type
BB/S016341/1
Investigating the impact of farmer behaviour and farmer-led control of infectious disease outbreaks in livestock
Principal Investigator
371,745
Research Grant
BB/W020408/1
Predicting and enhancing lifetime resilience in dairy cattle
Principal Investigator
200,820
Research Grant
BB/W020459/1
Optimisation Of On-farm Technologies To Predict Health And Resilience In Dairy Calves
Co-investigator
196,653
Research Grant
BB/X017303/1
Genetic and management solutions for lameness-associated endemic diseases in dairy cattle
Co-investigator
177,051
Research Grant
BB/X017362/1
A UK platform for the control of Bovine Viral Diarrhoea:Application of a novel disease simulation model to guide programme development & policy design
Co-investigator
526,224
Research Grant
BB/X017435/1
Digital Platform For Sustainable Health: A Step Change In Reducing Endemic Disease In Dairy Cattle
Co-investigator
709,016
Research Grant
Completed Awards
Reference
Title
Award Role
Value £
Type
00/V2/S/06484
The role of minor pathogens in protecting the bovine udder
Student
37,132
Studentships
BB/I015493/1
A Bayesian decision-theoretic framework to evaluate and optimize decision making for mastitis control in the UK Mastitis Control Scheme.
Principal Investigator
91,932
Training Grants
BB/L00416X/1
Are microbiomes important to mammary gland health in dairy cows?
Principal Investigator
53,547
Research Grant
BB/M005119/1
13TSB_ACT: Evaluation of MALDI-TOF-MS to differentiate sub species of the pathogen S uberis to provide an improved approach to mastitis control
Principal Investigator
120,566
Research Grant
BB/R021538/1
ISCF WAVE 1 AGRI TECH: Early Detection of Lameness in Dairy Cows through Multi-format Data Synthesis
Principal Investigator
191,465
Research Grant
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