Cooper, Mark

Modelling Crop Improvement in a G×E×M Framework via Gene–Trait–Phenotype Relationships

Messina, C., Hammer, G., Dong, Z., Podlich, D., & Cooper, M. (2009) · Crop Physiology

Genetics and Plant BreedingGenetic and phenotypic traits in livestock

Cited by 121

Tackling G × E × M interactions to close on-farm yield-gaps: creating novel pathways for crop improvement by predicting contributions of genetics and management to crop productivity

Cooper, M., Voss-Fels, K. P., Messina, C. D., Tang, T., & Hammer, G. L. (2021) · Theoretical and Applied Genetics

Genetics and Plant BreedingAgricultural Productivity and Crop Improvement

Cited by 119

A selection strategy to accommodate genotype-by-environment interaction for grain yield of wheat: managed-environments for selection among genotypes

Cooper, M., Woodruff, D. R., Eisemann, R. L., Brennan, P. S., & DeLacy, I. H. (1995) · Theoretical and Applied Genetics

Genetics and Plant BreedingWheat and Barley Genetics and Pathology

Cited by 110

Biological reality and parsimony in crop models—why we need both in crop improvement!

Hammer, G., Messina, C., Wu, A., & Cooper, M. (2019) · in silico Plants

Genetics and Plant BreedingGenetic and phenotypic traits in livestock

Cited by 108

Gene-to-phenotype models and complex trait genetics

Cooper, M., Podlich, D. W., & Smith, O. S. (2005) · Australian Journal of Agricultural Research

Genetic and phenotypic traits in livestockGenetic Mapping and Diversity in Plants and Animals

Cited by 104

Using crop simulation to generate genotype by environment interaction effects for sorghum in water-limited environments

Chapman, S. C., Cooper, M., & Hammer, G. L. (2002) · Australian Journal of Agricultural Research

Genetics and Plant BreedingAgricultural Productivity and Crop Improvement

Cited by 103

Evaluation of experimental designs and spatial analyses in wheat breeding trials

Qiao, C. G., Basford, K. E., DeLacy, I. H., & Cooper, M. (2000) · Theoretical and Applied Genetics

Genetics and Plant BreedingOptimal Experimental Design Methods

Cited by 91

Computer simulation of a selection strategy to accommodate genotype environment interactions in a wheat recurrent selection programme

Podlich, D. W., Cooper, M., Basford, K. E., & Geiger, H. H. (1999) · Plant Breeding

Genetics and Plant BreedingGenetic and phenotypic traits in livestock

Cited by 79

Predicting phenotypes from genetic, environment, management, and historical data using CNNs

Washburn, J. D., Cimen, E., Ramstein, G., Reeves, T., O’Briant, P., McLean, G., Cooper, M., Hammer, G., & Buckler, E. S. (2021) · Theoretical and Applied Genetics

Smart Agriculture and AIGenetic and phenotypic traits in livestock

Cited by 57

Predicting Genotype × Environment × Management (G × E × M) Interactions for the Design of Crop Improvement Strategies: Integrating Breeder, Agronomist, and Farmer Perspectives

Cooper, M., Messina, C. D., Tang, T., Gho, C., Powell, O. M., Podlich, D. W., Technow, F., & Hammer, G. L. (2022) · Plant Breeding Reviews

Genetics and Plant BreedingCrop Yield and Soil Fertility

Cited by 56

Back to the future: Implications of genetic complexity for hybrid breeding strategies

Technow, F., Podlich, D., & Cooper, M. (2020) · G3 Genes Genomes Genetics

Genetic and phenotypic traits in livestockGenetics and Plant Breeding

Cited by 36

Crop science: A foundation for advancing predictive agriculture

Messina, C. D., Cooper, M., Reynolds, M., & Hammer, G. L. (2020) · Crop Science

Smart Agriculture and AIClimate change impacts on agriculture

Cited by 35