| Phenomic data-facilitated rust and senescence prediction in maize using machine learning algorithms AJ DeSalvio, A Adak, SC Murray, SC Wilde, T Isakeit Scientific reports 12 (1), 7571, 2022 | 11 | 2022 |
| Temporal field phenomics allows discovery of nature AND nurture, so can we saturate the phenome? SC Murray, A Adak, A Desalvio, H Lane Authorea Preprints, 2022 | 5 | 2022 |
| Field based high throughput phenotyping enables the discovery of loci linked to senescence and grain filling period A Adak, AJ Desalvio, SC Murray | 2 | 2022 |
| Field-based high-throughput phenotyping enhances phenomic and genomic predictions for grain yield and plant height across years in maize A Adak, AJ DeSalvio, MA Arik, SC Murray G3: Genes, Genomes, Genetics, jkae092, 2024 | 1 | 2024 |
| Cotton Chronology: Convolutional Neural Network Enables Single-Plant Senescence Scoring with Temporal Drone Images AJ DeSalvio, MA Arik, SC Murray, O García-Ramos, SM DeSalvio, ... | 1 | 2024 |
| High temporal resolution unoccupied aerial systems phenotyping provides unique information between flight dates JD Washburn, A Adak, AJ DeSalvio, MA Arik, SC Murray The Plant Phenome Journal 7 (1), e20113, 2024 | | 2024 |
| Convolutional Neural Network Classification of Maize Senescence C Kettler, SC Murray, A DeSalvio, A Adak, N de Leon ASA, CSSA, SSSA International Annual Meeting, 2024 | | 2024 |
| Functional Analysis of Variance on Time-Series Vegetation Indices of Five Unique Maize Genotypes C Kettler, SC Murray, A DeSalvio ASA, CSSA, SSSA International Annual Meeting, 2024 | | 2024 |
| Near‐infrared reflectance spectroscopy phenomic prediction can perform similarly to genomic prediction of maize agronomic traits across environments AJ DeSalvio, A Adak, SC Murray, D Jarquín, ND Winans, D Crozier, ... The Plant Genome, e20454, 2024 | | 2024 |
| Temporal Image Sandwiches Enable Link between Functional Data Analysis and Deep Learning for Single-Plant Cotton Senescence AJ DeSalvio, A Adak, MA Arik, NR Shepard, SM DeSalvio, SC Murray, ... bioRxiv, 2024.06. 30.601428, 2024 | | 2024 |
| Deep Learning-Based High-Throughput Phenotyping Of Maize (Zea mays L.) Tasseling From Uas Imagery Across Environments NR Shepard, AJ DeSalvio, M Arik, A Adak, SC Murray, JI Varela, ... bioRxiv, 2024.06. 24.600506, 2024 | | 2024 |
| Facilitating community unoccupied aerial systems (UAS, drone) knowledge, communication, and data processing across agriculture A Porter, SC Murray, M Bhandari, JLL Scott, M Arik, AJ DeSalvio, A Adak Authorea Preprints, 2023 | | 2023 |
| Phenomic and Genomic Prediction of Maize Agronomic Traits By NIRS and GBS Data across and within Environments. A DeSalvio ASA, CSSA, SSSA International Annual Meeting, 2023 | | 2023 |
| Near Infrared Reflectance Spectroscopy Phenomic and Genomic Prediction of Maize Agronomic and Composition Traits Across Environments AJ DeSalvio, A Adak, SC Murray, D Jarquín, ND Winans, D Crozier, ... bioRxiv, 2023.08. 21.554202, 2023 | | 2023 |
| Phenomic Data and Machine Learning Facilitate Rust and Senescence Predictions in Maize While Uncovering Relationship between Grain Filling and Yield A DeSalvio, A Adak, SC Murray, S Wilde, T Isakeit ASA, CSSA, SSSA International Annual Meeting, 2022 | | 2022 |
Seth C. MurrayProfessor & Butler Chair, Dept. Soil and Crop Sciences, Texas A&M University在 tamu.edu 的电子邮件经过验证
Seth C. MurrayProfessor & Butler Chair, Dept. Soil and Crop Sciences, Texas A&M University在 tamu.edu 的电子邮件经过验证
Alper Adak在 tamu.edu 的电子邮件经过验证