Felix B. Fritschi
Felix B. Fritschi
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Cited by
Soybean yield prediction from UAV using multimodal data fusion and deep learning
M Maimaitijiang, V Sagan, P Sidike, S Hartling, F Esposito, FB Fritschi
Remote sensing of environment 237, 111599, 2020
Global warming, climate change, and environmental pollution: recipe for a multifactorial stress combination disaster
SI Zandalinas, FB Fritschi, R Mittler
Trends in Plant Science 26 (6), 588-599, 2021
Unmanned Aerial System (UAS)-based phenotyping of soybean using multi-sensor data fusion and extreme learning machine
M Maimaitijiang, A Ghulam, P Sidike, S Hartling, M Maimaitiyiming, ...
ISPRS Journal of Photogrammetry and Remote Sensing 134, 43-58, 2017
Meta‐analysis of drought and heat stress combination impact on crop yield and yield components
I Cohen, SI Zandalinas, C Huck, FB Fritschi, R Mittler
Physiologia Plantarum 171 (1), 66-76, 2021
UAV-based high resolution thermal imaging for vegetation monitoring, and plant phenotyping using ICI 8640 P, FLIR Vue Pro R 640, and thermomap cameras
V Sagan, M Maimaitijiang, P Sidike, K Eblimit, KT Peterson, S Hartling, ...
Remote Sensing 11 (3), 330, 2019
Jasmonic acid is required for plant acclimation to a combination of high light and heat stress
D Balfagón, S Sengupta, A Gómez-Cadenas, FB Fritschi, RK Azad, ...
Plant Physiology 181 (4), 1668-1682, 2019
Soybean leaf nitrogen, chlorophyll content, and chlorophyll a/b ratio
FB Fritschi, JD Ray
Photosynthetica 45, 92-98, 2007
Crop monitoring using satellite/UAV data fusion and machine learning
M Maimaitijiang, V Sagan, P Sidike, AM Daloye, H Erkbol, FB Fritschi
Remote Sensing 12 (9), 1357, 2020
Vegetation index weighted canopy volume model (CVMVI) for soybean biomass estimation from unmanned aerial system-based RGB imagery
M Maimaitijiang, V Sagan, P Sidike, M Maimaitiyiming, S Hartling, ...
ISPRS Journal of Photogrammetry and Remote Sensing 151, 27-41, 2019
The impact of multifactorial stress combination on plant growth and survival
SI Zandalinas, S Sengupta, FB Fritschi, RK Azad, R Nechushtai, R Mittler
New Phytologist 230 (3), 1034-1048, 2021
Response of irrigated Acala and Pima cotton to nitrogen fertilization: Growth, dry matter partitioning, and yield
FB Fritschi, BA Roberts, RL Travis, DW Rains, RB Hutmacher
Agronomy Journal 95 (1), 133-146, 2003
Genomic mechanisms of climate adaptation in polyploid bioenergy switchgrass
JT Lovell, AH MacQueen, S Mamidi, J Bonnette, J Jenkins, JD Napier, ...
Nature 590 (7846), 438-444, 2021
Vinobot and vinoculer: Two robotic platforms for high-throughput field phenotyping
A Shafiekhani, S Kadam, FB Fritschi, GN DeSouza
Sensors 17 (1), 214, 2017
Genome-wide association study (GWAS) of carbon isotope ratio (δ13C) in diverse soybean [Glycine max (L.) Merr.] genotypes
AP Dhanapal, JD Ray, SK Singh, V Hoyos-Villegas, JR Smith, LC Purcell, ...
Theoretical and Applied Genetics 128, 73-91, 2015
Signal transduction networks during stress combination
SI Zandalinas, FB Fritschi, R Mittler
Journal of Experimental Botany 71 (5), 1734-1741, 2020
Influence of large amounts of nitrogen on nonirrigated and irrigated soybean
JD Ray, LG Heatherly, FB Fritschi
Crop Science 46 (1), 52-60, 2006
Impact of heat stress during seed development on soybean seed metabolome
KK Chebrolu, FB Fritschi, S Ye, HB Krishnan, JR Smith, JD Gillman
Metabolomics 12, 1-14, 2016
dPEN: Deep Progressively Expanded Network for mapping heterogeneous agricultural landscape using WorldView-3 satellite imagery
P Sidike, V Sagan, M Maimaitijiang, M Maimaitiyiming, N Shakoor, ...
Remote sensing of environment 221, 756-772, 2019
Soybean maturity group choices for early and late plantings in the Midsouth
M Salmeron, EE Gbur, FM Bourland, NW Buehring, L Earnest, FB Fritschi, ...
Agronomy Journal 106 (5), 1893-1901, 2014
Field-scale crop yield prediction using multi-temporal WorldView-3 and PlanetScope satellite data and deep learning
V Sagan, M Maimaitijiang, S Bhadra, M Maimaitiyiming, DR Brown, ...
ISPRS journal of photogrammetry and remote sensing 174, 265-281, 2021
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