| African soil properties and nutrients mapped at 30 m spatial resolution using two-scale ensemble machine learning T Hengl, MAE Miller, J Križan, KD Shepherd, A Sila, M Kilibarda, ... Scientific reports 11 (1), 6130, 2021 | 173 | 2021 |
| The effect of different organic fertilizers on yield and soil and crop nutrient concentrations CL Thomas, GE Acquah, AP Whitmore, SP McGrath, SM Haefele Agronomy 9 (12), 776, 2019 | 114 | 2019 |
| Near infrared spectroscopy calibration for wood chemistry: which chemometric technique is best for prediction and interpretation? BK Via, C Zhou, G Acquah, W Jiang, L Eckhardt Sensors 14 (8), 13532-13547, 2014 | 57 | 2014 |
| Continental-scale controls on soil organic carbon across sub-Saharan Africa SF von Fromm, AM Hoyt, M Lange, GE Acquah, E Aynekulu, AA Berhe, ... Soil 7 (1), 305-332, 2021 | 55 | 2021 |
| Rapid quantitative analysis of forest biomass using fourier transform infrared spectroscopy and partial least squares regression GE Acquah, BK Via, OO Fasina, LG Eckhardt Journal of Analytical Methods in Chemistry 2016 (1), 1839598, 2016 | 52 | 2016 |
| Chemometric modeling of thermogravimetric data for the compositional analysis of forest biomass GE Acquah, BK Via, OO Fasina, S Adhikari, N Billor, LG Eckhardt PloS one 12 (3), e0172999, 2017 | 36 | 2017 |
| Non-destructive prediction of the properties of forest biomass for chemical and bioenergy applications using near infrared spectroscopy GE Acquah, BK Via, OO Fasina, LG Eckhardt Journal of Near Infrared Spectroscopy 23 (2), 93-102, 2015 | 33 | 2015 |
| Identifying plant part composition of forest logging residue using infrared spectral data and linear discriminant analysis GE Acquah, BK Via, N Billor, OO Fasina, LG Eckhardt Sensors 16 (9), 1375, 2016 | 30 | 2016 |
| Heterogeneity of forest harvest residue from eastern Ontario biomass harvests GE Acquah, S Krigstin, S Wetzel, P Cooper, D Cormier Forest Products Journal 66 (3-4), 164-175, 2016 | 16 | 2016 |
| Estimating the basic density and mechanical properties of elite loblolly pine families with near infrared spectroscopy GE Acquah, C Essien, BK Via, N Billor, LG Eckhardt Forest Science 64 (2), 149-158, 2018 | 14 | 2018 |
| Comprehensive nutrient analysis in agricultural organic amendments through non-destructive assays using machine learning EK Towett, LB Drake, GE Acquah, SM Haefele, SP McGrath, ... Plos one 15 (12), e0242821, 2020 | 13 | 2020 |
| High throughput screening of elite loblolly pine families for chemical and bioenergy traits with near infrared spectroscopy GE Acquah, BK Via, T Gallagher, N Billor, OO Fasina, LG Eckhardt Forests 9 (7), 418, 2018 | 12 | 2018 |
| Spectral variable selection for estimation of soil organic carbon content using mid‐infrared spectroscopy J Wang, T Liu, J Zhang, H Yuan, GE Acquah European Journal of Soil Science 73 (4), e13267, 2022 | 11 | 2022 |
| Combining variable selection and multiple linear regression for soil organic matter and Total nitrogen estimation by DRIFT-MIR spectroscopy H Li, J Wang, J Zhang, T Liu, GE Acquah, H Yuan Agronomy 12 (3), 638, 2022 | 10 | 2022 |
| Portable X-ray fluorescence (pXRF) calibration for analysis of nutrient concentrations and trace element contaminants in fertilisers GE Acquah, J Hernandez-Allica, CL Thomas, SJ Dunham, EK Towett, ... Plos one 17 (1), e0262460, 2022 | 9 | 2022 |
| Effect of genetic sources on anatomical, morphological, and mechanical properties of 14-year-old genetically improved loblolly pine families from two sites in the southern … C Essien, BK Via, G Acquah, T Gallagher, T McDonald, L Eckhardt Journal of Forestry Research 29, 1519-1531, 2018 | 9 | 2018 |
| African soil properties and nutrients mapped at 30m spatial resolution using two-scale ensemble machine learning, Sci. Rep., 11, 6130 T Hengl, MAE Miller, J Križan, KD Shepherd, A Sila, M Kilibarda, ... | 8 | 2021 |
| Characterization of forest harvest residue from the Great Lakes-St Lawrence forests of south-eastern Ontario GE Acquah MSc Thesis, University of Toronto. 2010. https://tspace. library. utoronto …, 2010 | 5 | 2010 |
| Screening Pinus taeda (loblolly pine) families for physical and mechanical properties using vibrational spectroscopy GE Acquah, BK Via, LG Eckhardt Proceedings of the 18th biennial southern silvicultural research conference …, 2016 | 4 | 2016 |
| Chemometric Modeling of the Structural Integrity, Chemistry and Bioenergy Potential of Elite Loblolly Pine Families and Forest Biomass GE Acquah Auburn University, 2016 | 1 | 2016 |
