| Application of machine learning algorithms in plant breeding: predicting yield from hyperspectral reflectance in soybean M Yoosefzadeh-Najafabadi, HJ Earl, D Tulpan, J Sulik, M Eskandari Frontiers in plant science 11, 624273, 2021 | 172 | 2021 |
| Genetic control of soybean seed oil: II. QTL and genes that increase oil concentration without decreasing protein or with increased seed yield M Eskandari, ER Cober, I Rajcan Theoretical and Applied Genetics 126, 1677-1687, 2013 | 121 | 2013 |
| Genetic control of soybean seed oil: I. QTL and genes associated with seed oil concentration in RIL populations derived from crossing moderately high-oil parents M Eskandari, ER Cober, I Rajcan Theoretical and Applied Genetics 126, 483-495, 2013 | 81 | 2013 |
| Using hybrid artificial intelligence and evolutionary optimization algorithms for estimating soybean yield and fresh biomass using hyperspectral vegetation indices M Yoosefzadeh-Najafabadi, D Tulpan, M Eskandari Remote Sensing 13 (13), 2555, 2021 | 60 | 2021 |
| Application of machine learning and genetic optimization algorithms for modeling and optimizing soybean yield using its component traits M Yoosefzadeh-Najafabadi, D Tulpan, M Eskandari Plos one 16 (4), e0250665, 2021 | 54 | 2021 |
| Genome-wide association studies of soybean yield-related hyperspectral reflectance bands using machine learning-mediated data integration methods M Yoosefzadeh-Najafabadi, S Torabi, D Tulpan, I Rajcan, M Eskandari Frontiers in plant science 12, 777028, 2021 | 38 | 2021 |
| Machine learning-assisted approaches in modernized plant breeding programs M Yoosefzadeh Najafabadi, M Hesami, M Eskandari Genes 14 (4), 777, 2023 | 37 | 2023 |
| Machine-learning-based genome-wide association studies for uncovering QTL underlying soybean yield and its components M Yoosefzadeh-Najafabadi, M Eskandari, S Torabi, D Torkamaneh, ... International Journal of Molecular Sciences 23 (10), 5538, 2022 | 35 | 2022 |
| Genome-wide genetic diversity is maintained through decades of soybean breeding in Canada RW Bruce, D Torkamaneh, C Grainger, F Belzile, M Eskandari, I Rajcan Theoretical and Applied Genetics 132, 3089-3100, 2019 | 29 | 2019 |
| Genetic and environmental effects on fatty acid composition in soybeans with potential use in the automotive industry J Hemingway, M Eskandari, I Rajcan Crop Science 55 (2), 658-668, 2015 | 27 | 2015 |
| Using the candidate gene approach for detecting genes underlying seed oil concentration and yield in soybean M Eskandari, ER Cober, I Rajcan Theoretical and applied genetics 126, 1839-1850, 2013 | 24 | 2013 |
| Effects of type I Diacylglycerol O-acyltransferase (DGAT1) genes on soybean (Glycine max L.) seed composition S Torabi, A Sukumaran, S Dhaubhadel, SE Johnson, P LaFayette, ... Scientific reports 11 (1), 2556, 2021 | 23 | 2021 |
| Genotypic main effect and genotype-by-environment interaction effect on seed protein concentration and yield in food-grade soybeans (Glycine max (L.) Merrill) R Whaley, M Eskandari Euphytica 215 (2), 33, 2019 | 22 | 2019 |
| Trends in soybean trait improvement over generations of selective breeding RW Bruce, CM Grainger, A Ficht, M Eskandari, I Rajcan Crop Science 59 (5), 1870-1879, 2019 | 21 | 2019 |
| Optimizing genomic selection in soybean: An important improvement in agricultural genomics M Yoosefzadeh-Najafabadi, I Rajcan, M Eskandari Heliyon 8 (11), 2022 | 20 | 2022 |
| Genome-wide association identifies several QTLs controlling cysteine and methionine content in soybean seed including some promising candidate genes S Malle, M Eskandari, M Morrison, F Belzile Scientific reports 10 (1), 21812, 2020 | 19 | 2020 |
| Genome-wide association study statistical models: A review M Yoosefzadeh-Najafabadi, M Eskandari, F Belzile, D Torkamaneh Genome-Wide Association Studies, 43-62, 2022 | 18 | 2022 |
| Genomic regions associated with important seed quality traits in food-grade soybeans RM Whiting, S Torabi, L Lukens, M Eskandari BMC Plant Biology 20, 1-14, 2020 | 18 | 2020 |
| Genotype, environment, and genotype by environment interaction for seed isoflavone concentration in soybean grown in soybean cyst nematode infested and non-infested environments A Carter, I Rajcan, L Woodrow, A Navabi, M Eskandari Field Crops Research 216, 189-196, 2018 | 17 | 2018 |
| Using advanced proximal sensing and genotyping tools combined with bigdata analysis methods to improve soybean yield M Yoosefzadeh Najafabadi University of Guelph, 2021 | 16 | 2021 |
Mohsen Yoosefzadeh NajafabadiAssistant ProfessorVerified email at uoguelph.ca
