| The application of multiple linear regression and artificial neural network models for yield prediction of very early potato cultivars before harvest M Piekutowska, G Niedbała, T Piskier, T Lenartowicz, K Pilarski, ... Agronomy 11 (5), 885, 2021 | 106 | 2021 |
| Selection of independent variables for crop yield prediction using artificial neural network models with remote sensing data P Hara, M Piekutowska, G Niedbała Land 10 (6), 609, 2021 | 95 | 2021 |
| A comprehensive review about the molecular structure of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2): Insights into natural products against COVID-19 EM Saied, YA El-Maradny, AA Osman, AMG Darwish, HH Abo Nahas, ... Pharmaceutics 13 (11), 1759, 2021 | 63 | 2021 |
| Seed priming boost adaptation in pea plants under drought stress SA Arafa, KA Attia, G Niedbała, M Piekutowska, S Alamery, K Abdelaal, ... Plants 10 (10), 2201, 2021 | 52 | 2021 |
| Roles of exogenous α-lipoic acid and cysteine in mitigation of drought stress and restoration of grain quality in wheat A Elkelish, MM El-Mogy, G Niedbała, M Piekutowska, MAM Atia, ... Plants 10 (11), 2318, 2021 | 43 | 2021 |
| Application of artificial neural networks for yield modeling of winter rapeseed based on combined quantitative and qualitative data G Niedbała, M Piekutowska, J Weres, R Korzeniewicz, K Witaszek, ... Agronomy 9 (12), 781, 2019 | 43 | 2019 |
| Multicriteria prediction and simulation of winter wheat yield using extended qualitative and quantitative data based on artificial neural networks G Niedbała, K Nowakowski, J Rudowicz-Nawrocka, M Piekutowska, ... Applied Sciences 9 (14), 2773, 2019 | 34 | 2019 |
| Genetic Characterization and Agronomic Evaluation of Drought Tolerance in Ten Egyptian Wheat (Triticum aestivum L.) Cultivars MA Emam, AM Abd EL-Mageed, G Niedbała, SA Sabrey, AS Fouad, ... Agronomy 12 (5), 1217, 2022 | 20 | 2022 |
| Genetic diversity and population structure in bread wheat germplasm from Türkiye using iPBS-retrotransposons-based markers K Haliloğlu, A Türkoğlu, A Öztürk, G Niedbała, M Niazian, ... Agronomy 13 (1), 255, 2023 | 18 | 2023 |
| Diversity of toxigenic fungi in livestock and poultry feedstuffs E Khalifa, MT Mohesien, MI Mossa, M Piekutowska, AM Alsuhaibani, ... International Journal of Environmental Research and Public Health 19 (12), 7250, 2022 | 17 | 2022 |
| Application of Artificial Neural Networks Sensitivity Analysis for the Pre-Identification of Highly Significant Factors Influencing the Yield and Digestibility of Grassland … G Niedbała, B Wróbel, M Piekutowska, W Zielewicz, ... Agronomy 12 (5), 1133, 2022 | 16 | 2022 |
| Insights into the Bioprospecting of the Endophytic Fungi of the Medicinal Plant Palicourea rigida Kunth (Rubiaceae): Detailed Biological Activities IR Dos Santos, AM Abdel-Azeem, MT Mohesien, M Piekutowska, ... Journal of Fungi 7 (9), 689, 2021 | 16 | 2021 |
| Application of Artificial Neural Network Sensitivity Analysis to Identify Key Determinants of Harvesting Date and Yield of Soybean (Glycine max [L.] Merrill) Cultivar … G Niedbała, D Kurasiak-Popowska, M Piekutowska, T Wojciechowski, ... Agriculture 12 (6), 754, 2022 | 15 | 2022 |
| Analysis of the possibility of obtaining thermal energy from combustion of selected cereal straw species M Herkowiak, M Adamski, Z Dworecki, B Waliszewska, K Pilarski, ... Journal of Research and Applications in Agricultural Engineering 63 (4), 68-72, 2018 | 15 | 2018 |
| Degree of biomass conversion in the integrated production of bioethanol and biogas K Pilarski, AA Pilarska, P Boniecki, G Niedbała, K Witaszek, ... Energies 14 (22), 7763, 2021 | 14 | 2021 |
| Prediction of Pea (Pisum sativum L.) Seeds Yield Using Artificial Neural Networks P Hara, M Piekutowska, G Niedbała Agriculture 13 (3), 661, 2023 | 13 | 2023 |
| Paszkiewicz-Jasi nska, A.; Wojciechowski, T.; Niazian, M. Application of Artificial Neural Networks Sensitivity Analysis for the Pre-Identification of Highly Significant … G Niedbała, B Wróbel, M Piekutowska, W Zielewicz s Note: MDPI stays neutral with regard to jurisdictional claims in published …, 2022 | 12 | 2022 |
| Prediction of Protein Content in Pea (Pisum sativum L.) Seeds Using Artificial Neural Networks P Hara, M Piekutowska, G Niedbała Agriculture 13 (1), 29, 2022 | 11 | 2022 |
| Modeling Callus Induction and Regeneration in Hypocotyl Explant of Fodder Pea (Pisum sativum var. arvense L.) Using Machine Learning Algorithm Method A Türkoğlu, P Bolouri, K Haliloğlu, B Eren, F Demirel, Mİ Işık, ... Agronomy 13 (11), 2835, 2023 | 10 | 2023 |
| New Trends and Challenges in Precision and Digital Agriculture G Niedbała, M Piekutowska, P Hara Agronomy 13 (8), 2136, 2023 | 10 | 2023 |
