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Field-based phenomics for plant genetics research
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Remote Sensing in Entomology
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GROUNDBASED REMOTE SENSING OF WATER AND NITROGEN STRESS
inferredcites →https://doi.org/10.13031/2013.15626openalex-snapshot
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inferredcites →https://doi.org/10.2134/agronj1986.00021962007800030020xopenalex-snapshot
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inferredcites →https://doi.org/10.2134/agronj2001.1327openalex-snapshot
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inferredcites →https://doi.org/10.2134/agronj2001.931125xopenalex-snapshot
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inferredcites →https://doi.org/10.2134/agronj2004.0093openalex-snapshot
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inferredcites →https://doi.org/10.2135/cropsci2005.0211openalex-snapshot
Spectral Reflectance to Estimate Genetic Variation for In‐Season Biomass, Leaf Chlorophyll, and Canopy Temperature in Wheat
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inferredcites →https://doi.org/10.2136/sssaj2003.1439openalex-snapshot
In‐Season Nitrogen Status Sensing in Irrigated Cotton
inferredcites →https://doi.org/10.3389/fpls.2011.00034openalex-snapshot
The iPlant Collaborative: Cyberinfrastructure for Plant Biology
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AUTONOMOUS UNMANNED HELICOPTER SYSTEM FOR REMOTE SENSING MISSIONS IN UNKNOWN ENVIRONMENTS
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Rice Breeding and Genomics Approaches for Improving Water and Nitrogen Use Efficiency
inferred← citeshttps://doi.org/10.1007/978-981-15-8249-3_6openalex-snapshot
Physiology of Growth, Development and Yield
inferred← citeshttps://doi.org/10.1007/978-981-16-2922-8_16openalex-snapshot
Omics Technology for Plant Stress Management
inferred← citeshttps://doi.org/10.1007/978-981-19-3800-9_11openalex-snapshot
OMICS Tools and Techniques for Study of Defense Mechanism in Plants
inferred← citeshttps://doi.org/10.1007/978-981-95-0583-8_9openalex-snapshot
Post-genomic Era in Crop Breeding
inferred← citeshttps://doi.org/10.1007/978-981-95-5218-4_1openalex-snapshot
Field-Based High-Throughput Plant Phenotyping of Selected Horticultural Crops
inferred← citeshttps://doi.org/10.1007/978-981-96-3890-1_2openalex-snapshot
Molecular Strategies for Confronting Abiotic Stress Tolerance in Tomatoes
inferred← citeshttps://doi.org/10.1007/978-981-97-4347-6_15openalex-snapshot
New Breeding Trends in Sorghum
inferred← citeshttps://doi.org/10.1007/s00122-013-2066-0openalex-snapshot
Next-generation phenotyping: requirements and strategies for enhancing our understanding of genotype–phenotype relationships and its relevance to crop improvement
inferred← citeshttps://doi.org/10.1007/s00122-013-2229-zopenalex-snapshot
Joint linkage QTL analyses for partial resistance to Phytophthora sojae in soybean using six nested inbred populations with heterogeneous conditions
inferred← citeshttps://doi.org/10.1007/s00122-016-2772-5openalex-snapshot
Bandwagons I, too, have known
inferred← citeshttps://doi.org/10.1007/s00122-020-03651-8openalex-snapshot
Integration of genotypic, hyperspectral, and phenotypic data to improve biomass yield prediction in hybrid rye
inferred← citeshttps://doi.org/10.1007/s00122-020-03726-6openalex-snapshot
A novel way to validate UAS-based high-throughput phenotyping protocols using in silico experiments for plant breeding purposes
inferred← citeshttps://doi.org/10.1007/s00122-021-03779-1openalex-snapshot
Early prediction of biomass in hybrid rye based on hyperspectral data surpasses genomic predictability in less-related breeding material
inferred← citeshttps://doi.org/10.1007/s00122-021-03795-1openalex-snapshot
Breeding for drought and heat tolerance in wheat
inferred← citeshttps://doi.org/10.1007/s00122-021-03997-7openalex-snapshot
The performance of phenomic selection depends on the genetic architecture of the target trait
inferred← citeshttps://doi.org/10.1007/s00138-015-0728-4openalex-snapshot
An opinion on imaging challenges in phenotyping field crops
inferred← citeshttps://doi.org/10.1007/s00138-016-0756-8openalex-snapshot
A patch-based approach to 3D plant shoot phenotyping
inferred← citeshttps://doi.org/10.1007/s10661-019-7730-7openalex-snapshot
Forest biomass estimation using remote sensing and field inventory: a case study of Tripura, India
inferred← citeshttps://doi.org/10.1007/s10681-020-02742-3openalex-snapshot
Novel insights of maize structural feature in China
inferred← citeshttps://doi.org/10.1007/s10722-020-00885-9openalex-snapshot
Phenotypic characterization of Stauntonia obovatifoliola Hayata subsp. urophylla germplasm: a potential new fruit crop
inferred← citeshttps://doi.org/10.1007/s10722-024-02226-6openalex-snapshot
Morphological and phylogenetic insights into Berberis species: a tool for species identification and conservation
inferred← citeshttps://doi.org/10.1007/s11032-024-01449-wopenalex-snapshot
Multispectral-derived genotypic similarities from budget cameras allow grain yield prediction and genomic selection augmentation in single and multi-environment scenarios in spring wheat
inferred← citeshttps://doi.org/10.1007/s11119-017-9501-1openalex-snapshot
Predicting cover crop biomass by lightweight UAS-based RGB and NIR photography: an applied photogrammetric approach
inferred← citeshttps://doi.org/10.1007/s11119-018-9601-6openalex-snapshot
Design and field evaluation of a ground robot for high-throughput phenotyping of energy sorghum
inferred← citeshttps://doi.org/10.1007/s11119-023-10028-6openalex-snapshot
Developing an efficiency and energy-saving nitrogen management strategy for winter wheat based on the UAV multispectral imagery and machine learning algorithm
inferred← citeshttps://doi.org/10.1007/s11119-026-10464-0openalex-snapshot
The effect of train-test data splitting ratio on yield prediction from multispectral UAV imagery: effective reduction of training ratio with algorithm selection for single- and multi-date models
inferred← citeshttps://doi.org/10.1007/s11427-017-9056-0openalex-snapshot
Crop 3D—a LiDAR based platform for 3D high-throughput crop phenotyping
inferred← citeshttps://doi.org/10.1007/s11427-020-1910-1openalex-snapshot
Plant multiscale networks: charting plant connectivity by multi-level analysis and imaging techniques
inferred← citeshttps://doi.org/10.1007/s11738-013-1239-4openalex-snapshot
Plant polyamines in abiotic stress responses
inferred← citeshttps://doi.org/10.1007/s11738-015-1844-5openalex-snapshot
Physiological requirements for wheat ideotypes in response to drought threat
inferred← citeshttps://doi.org/10.1007/s12230-012-9291-yopenalex-snapshot
Adaptation of Potato to Water Shortage: Irrigation Management and Enhancement of Tolerance to Drought and Salinity
inferred← citeshttps://doi.org/10.1007/s12524-024-02076-wopenalex-snapshot
Field-scale Estimation of Phenotypic Parameters for Jute and Allied Fibre Crops: An Unmanned Aerial Vehicle Remote Sensing Approach
inferred← citeshttps://doi.org/10.1007/s13253-020-00396-1openalex-snapshot
Adjusting for Spatial Effects in Genomic Prediction
inferred← citeshttps://doi.org/10.1007/s40502-018-0416-2openalex-snapshot
Physiological, genetic and molecular basis of drought resilience in sorghum [Sorghum bicolor (L.) Moench]
inferred← citeshttps://doi.org/10.1007/s40502-024-00840-1openalex-snapshot
Machine learning based approach for wheat plant senescence quantification
inferred← citeshttps://doi.org/10.1007/s42976-025-00748-yopenalex-snapshot
Haploids (n) possess significantly compromised morphological, physiological and biochemical attributes over diploid (2n) plants in maize
inferred← citeshttps://doi.org/10.1007/s43657-020-00007-6openalex-snapshot
High-Throughput Phenotyping: A Platform to Accelerate Crop Improvement
inferred← citeshttps://doi.org/10.1007/s44372-026-00696-9openalex-snapshot
A review of AI-driven phenomics, genomics, and predictive breeding in wheat
inferred← citeshttps://doi.org/10.1016/b978-0-08-102163-7.00011-9openalex-snapshot
Modern Field Phenotyping Opens New Avenues for Selection
inferred← citeshttps://doi.org/10.1016/b978-0-08-102163-7.00013-2openalex-snapshot
Genomic Selection in Wheat
inferred← citeshttps://doi.org/10.1016/b978-0-12-417104-6.00014-5openalex-snapshot
Model-assisted phenotyping and ideotype design
inferred← citeshttps://doi.org/10.1016/b978-0-12-417104-6.00015-7openalex-snapshot
Crop phenotyping for physiological breeding in grain crops: A case study for maize
inferred← citeshttps://doi.org/10.1016/b978-0-12-823048-0.00018-6openalex-snapshot
Categories of various plant biostimulants – mode of application and shelf-life
inferred← citeshttps://doi.org/10.1016/b978-0-323-85449-8.00003-8openalex-snapshot
High-throughput phenotyping: the latest research tool for sustainable crop production under global climate change scenarios
inferred← citeshttps://doi.org/10.1016/b978-0-323-85797-0.00002-1openalex-snapshot
Conventional, genomics, and post-genomics era of pulses breeding: Current status and future prospects
inferred← citeshttps://doi.org/10.1016/b978-0-323-89905-5.00015-xopenalex-snapshot
Omics advances in tea research
inferred← citeshttps://doi.org/10.1016/b978-0-443-13220-9.00041-xopenalex-snapshot
Remote Sensing in Agriculture
inferred← citeshttps://doi.org/10.1016/b978-0-443-27465-7.00004-2openalex-snapshot
Scope of conventional knowledge and deep learning approaches for the identification of plant diseases
inferred← citeshttps://doi.org/10.1016/bs.agron.2018.02.004openalex-snapshot
Water–Nitrogen Colimitation in Grain Crops
inferred← citeshttps://doi.org/10.1016/bs.agron.2023.05.004openalex-snapshot
Remote and proximal sensing: How far has it come to help plant breeders?
inferred← citeshttps://doi.org/10.1016/j.aasci.2018.02.002openalex-snapshot
Next generation crop improvement program: Progress and prospect in tea ( Camellia sinensis (L.) O. Kuntze)
inferred← citeshttps://doi.org/10.1016/j.agwat.2015.05.003openalex-snapshot
The combined use of vegetation indices and stable isotopes to predict durum wheat grain yield under contrasting water conditions
inferred← citeshttps://doi.org/10.1016/j.agwat.2020.106304openalex-snapshot
Design and assessment of new artificial reference surfaces for real time monitoring of crop water stress index in maize
inferred← citeshttps://doi.org/10.1016/j.atech.2025.101641openalex-snapshot
Flexible spatial-frequency feature fusion for UAV-based semantic segmentation in rice phenotyping
inferred← citeshttps://doi.org/10.1016/j.atech.2026.102553openalex-snapshot
PVSCNet: Point-voxel dual-grained feature fusion and spatial constraints for 3D plant organ segmentation
inferred← citeshttps://doi.org/10.1016/j.biosystemseng.2013.08.007openalex-snapshot
Feasibility study on the use of attenuated total reflectance infrared spectroscopy as high throughput screening tool to phenotype single barley seeds (Hordeum vulgare L.)
inferred← citeshttps://doi.org/10.1016/j.biosystemseng.2016.04.010openalex-snapshot
Field phenotyping system for the assessment of potato late blight resistance using RGB imagery from an unmanned aerial vehicle
inferred← citeshttps://doi.org/10.1016/j.biotechadv.2013.09.008openalex-snapshot
Can a late bloomer become an early bird? Tools for flowering time adjustment
inferred← citeshttps://doi.org/10.1016/j.cels.2016.06.001openalex-snapshot
Dynamic Environmental Photosynthetic Imaging Reveals Emergent Phenotypes
inferred← citeshttps://doi.org/10.1016/j.cois.2015.03.002openalex-snapshot
Applying high-throughput phenotyping to plant–insect interactions: picturing more resistant crops
inferred← citeshttps://doi.org/10.1016/j.compag.2014.11.015openalex-snapshot
Determination of oil content in whole corn (Zea mays L.) seeds by means of near infrared reflectance spectroscopy
inferred← citeshttps://doi.org/10.1016/j.compag.2015.09.005openalex-snapshot
Proximal hyperspectral sensing and data analysis approaches for field-based plant phenomics
inferred← citeshttps://doi.org/10.1016/j.compag.2015.10.011openalex-snapshot
LiDAR: An important tool for next-generation phenotyping technology of high potential for plant phenomics?
inferred← citeshttps://doi.org/10.1016/j.compag.2016.01.017openalex-snapshot
Development of a field-based high-throughput mobile phenotyping platform
inferred← citeshttps://doi.org/10.1016/j.compag.2016.08.021openalex-snapshot
A multi-sensor system for high throughput field phenotyping in soybean and wheat breeding
inferred← citeshttps://doi.org/10.1016/j.compag.2016.09.017openalex-snapshot
High throughput phenotyping of cotton plant height using depth images under field conditions
inferred← citeshttps://doi.org/10.1016/j.compag.2017.02.024openalex-snapshot
Hyperspectral data mining to identify relevant canopy spectral features for estimating durum wheat growth, nitrogen status, and grain yield
inferred← citeshttps://doi.org/10.1016/j.compag.2018.10.036openalex-snapshot
Tensor-based classification and segmentation of three-dimensional point clouds for organ-level plant phenotyping and growth analysis
inferred← citeshttps://doi.org/10.1016/j.compag.2019.03.009openalex-snapshot
NU-Spidercam: A large-scale, cable-driven, integrated sensing and robotic system for advanced phenotyping, remote sensing, and agronomic research
inferred← citeshttps://doi.org/10.1016/j.compag.2019.05.043openalex-snapshot
Automated morphological traits extraction for sorghum plants via 3D point cloud data analysis
inferred← citeshttps://doi.org/10.1016/j.compag.2019.104854openalex-snapshot
In vivo human-like robotic phenotyping of leaf traits in maize and sorghum in greenhouse
inferred← citeshttps://doi.org/10.1016/j.compag.2020.105237openalex-snapshot
Development and evaluation of a self-propelled electric platform for high-throughput field phenotyping in wheat breeding trials
inferred← citeshttps://doi.org/10.1016/j.compag.2020.105703openalex-snapshot
Deep learning-based automatic detection of productive tillers in rice
inferred← citeshttps://doi.org/10.1016/j.compag.2022.107235openalex-snapshot
Predicting grain yield and protein content of winter wheat at different growth stages by hyperspectral data integrated with growth monitor index
inferred← citeshttps://doi.org/10.1016/j.compag.2023.108078openalex-snapshot
Advantages and limitations of using near infrared spectroscopy in plant phenomics applications
inferred← citeshttps://doi.org/10.1016/j.compag.2024.108628openalex-snapshot
Cotton Verticillium wilt monitoring based on UAV multispectral-visible multi-source feature fusion
inferred← citeshttps://doi.org/10.1016/j.compag.2024.109795openalex-snapshot
Non-destructive monitoring of tea plant growth through UAV spectral imagery and meteorological data using machine learning and parameter optimization algorithms
inferred← citeshttps://doi.org/10.1016/j.crope.2022.03.009openalex-snapshot
Casting light on the architecture of crop yield
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Image-based plant phenotyping with incremental learning and active contours
inferred← citeshttps://doi.org/10.1016/j.ecoinf.2021.101524openalex-snapshot
A method of calculating phenotypic traits for soybean canopies based on three-dimensional point cloud
inferred← citeshttps://doi.org/10.1016/j.eja.2013.08.009openalex-snapshot
High-throughput phenotyping early plant vigour of winter wheat
inferred← citeshttps://doi.org/10.1016/j.eja.2015.07.004openalex-snapshot
Low-altitude, high-resolution aerial imaging systems for row and field crop phenotyping: A review
inferred← citeshttps://doi.org/10.1016/j.eja.2016.04.013openalex-snapshot
Data fusion of spectral, thermal and canopy height parameters for improved yield prediction of drought stressed spring barley
inferred← citeshttps://doi.org/10.1016/j.eja.2017.07.005openalex-snapshot
Mid-season prediction of grain yield and protein content of spring barley cultivars using high-throughput spectral sensing
inferred← citeshttps://doi.org/10.1016/j.eja.2020.126104openalex-snapshot
Is canopy temperature suitable for high throughput field phenotyping of drought resistance of winter rye in temperate climate?
inferred← citeshttps://doi.org/10.1016/j.eja.2021.126378openalex-snapshot
Estimating economic benefit of sugar beet based on three-dimensional computer vision: a case study in Inner Mongolia, China
inferred← citeshttps://doi.org/10.1016/j.eja.2023.126751openalex-snapshot
Aerial and ground-based phenotyping of an alfalfa diversity panel to assess adaptation to a prolonged drought period in a Mediterranean environment of central Chile
inferred← citeshttps://doi.org/10.1016/j.envpol.2026.128415openalex-snapshot
Next generation risk assessment and new approach methodologies for sustainable management of heavy metal contaminated environments: A critical review
inferred← citeshttps://doi.org/10.1016/j.fcr.2013.09.006openalex-snapshot
Evaluation of active and passive sensor systems in the field to phenotype maize hybrids with high-throughput
inferred← citeshttps://doi.org/10.1016/j.fcr.2013.10.001openalex-snapshot
The phenotype and the components of phenotypic variance of crop traits
inferred← citeshttps://doi.org/10.1016/j.fcr.2017.12.004openalex-snapshot
Evaluating canopy spectral reflectance vegetation indices to estimate nitrogen use traits in hard winter wheat
inferred← citeshttps://doi.org/10.1016/j.fcr.2021.108260openalex-snapshot
Comparative prediction accuracy of hyperspectral bands for different soybean crop variables: From leaf area to seed composition
inferred← citeshttps://doi.org/10.1016/j.fcr.2022.108781openalex-snapshot
Phenotyping early-vigour in oat cover crops to assess plant-trait effects across environments
inferred← citeshttps://doi.org/10.1016/j.ifacol.2016.10.045openalex-snapshot
3D Robotic System Development for High-throughput Crop Phenotyping
inferred← citeshttps://doi.org/10.1016/j.ifacol.2016.10.052openalex-snapshot
Field Phenotyping Robot Design and Validation for the Crop Breeding
inferred← citeshttps://doi.org/10.1016/j.indcrop.2018.04.050openalex-snapshot
Phenotypic characterization of Elaeagnus angustifolia using multivariate analysis
inferred← citeshttps://doi.org/10.1016/j.indcrop.2019.111943openalex-snapshot
Selection of crown type provides a potential to improve the content of isorhamnetin in Ginkgo biloba
inferred← citeshttps://doi.org/10.1016/j.infrared.2024.105326openalex-snapshot
Classification of soybean groups for grain yield and industrial traits using Vnir-Swir spectroscopy
inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2017.01.010openalex-snapshot
Estimating rice yield related traits and quantitative trait loci analysis under different nitrogen treatments using a simple tower-based field phenotyping system with modified single-lens reflex cameras
inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2019.01.023openalex-snapshot
Simulation of satellite reflectance data using high-frequency ground based hyperspectral canopy measurements for in-season estimation of grain yield and grain nitrogen status in winter wheat
inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2021.01.014openalex-snapshot
UAV-Thermal imaging and agglomerative hierarchical clustering techniques to evaluate and rank physiological performance of wheat genotypes on sodic soil
inferred← citeshttps://doi.org/10.1016/j.isprsjprs.2024.03.010openalex-snapshot
Plant-Denoising-Net (PDN): A plant point cloud denoising network based on density gradient field learning
inferred← citeshttps://doi.org/10.1016/j.jbiotec.2020.11.010openalex-snapshot
Harnessing High-throughput Phenotyping and Genotyping for Enhanced Drought Tolerance in Crop Plants
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Omics approaches in effective selection and generation of potential plants for phytoremediation of heavy metal from contaminated resources
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A review of the journey of field crop phenotyping: From trait stamp collections and fancy robots to phenomics-informed crop performance predictions
inferred← citeshttps://doi.org/10.1016/j.lwt.2013.11.019openalex-snapshot
Evaluation of the use of attenuated total reflectance mid infrared spectroscopy to determine fatty acids in intact seeds of barley (Hordeum vulgare)
inferred← citeshttps://doi.org/10.1016/j.molp.2015.06.005openalex-snapshot
A Versatile Phenotyping System and Analytics Platform Reveals Diverse Temporal Responses to Water Availability in Setaria
inferred← citeshttps://doi.org/10.1016/j.ohx.2018.e00025openalex-snapshot
Professor: A motorized field-based phenotyping cart
inferred← citeshttps://doi.org/10.1016/j.pbi.2015.02.006openalex-snapshot
Lights, camera, action: high-throughput plant phenotyping is ready for a close-up
inferred← citeshttps://doi.org/10.1016/j.pbi.2015.05.002openalex-snapshot
Measurement of plant growth in view of an integrative analysis of regulatory networks
inferred← citeshttps://doi.org/10.1016/j.plantsci.2017.05.003openalex-snapshot
High-biomass C 4 grasses—Filling the yield gap
inferred← citeshttps://doi.org/10.1016/j.plantsci.2018.05.008openalex-snapshot
Quantitative and comparative analysis of whole-plant performance for functional physiological traits phenotyping: New tools to support pre-breeding and plant stress physiology studies
inferred← citeshttps://doi.org/10.1016/j.plantsci.2018.06.017openalex-snapshot
Review: High-throughput phenotyping to enhance the use of crop genetic resources
inferred← citeshttps://doi.org/10.1016/j.plantsci.2019.110396openalex-snapshot
Breeder friendly phenotyping
inferred← citeshttps://doi.org/10.1016/j.plaphe.2025.100014openalex-snapshot
Design and implementation of a high-throughput field phenotyping robot for acquiring multisensor data in wheat
inferred← citeshttps://doi.org/10.1016/j.plaphe.2025.100089openalex-snapshot
Predictive modeling, pattern recognition, and spatiotemporal representations of plant growth in simulated and controlled environments: A comprehensive review
inferred← citeshttps://doi.org/10.1016/j.plaphy.2021.02.030openalex-snapshot
Metabolome profiling reveals impact of water limitation on grain filling in contrasting rice genotypes
inferred← citeshttps://doi.org/10.1016/j.rsase.2021.100583openalex-snapshot
UAV-thermal imaging: A technological breakthrough for monitoring and quantifying crop abiotic stress to help sustain productivity on sodic soils – A case review on wheat
inferred← citeshttps://doi.org/10.1016/j.rse.2016.10.005openalex-snapshot
Development of methods to improve soybean yield estimation and predict plant maturity with an unmanned aerial vehicle based platform
inferred← citeshttps://doi.org/10.1016/j.rse.2019.111402openalex-snapshot
Remote sensing for agricultural applications: A meta-review
inferred← citeshttps://doi.org/10.1016/j.rse.2021.112797openalex-snapshot
High-throughput field phenotyping of soybean: Spotting an ideotype
inferred← citeshttps://doi.org/10.1016/j.scienta.2018.10.060openalex-snapshot
Effectiveness of recurrent selection in Akebia trifoliata (Lardizabalaceae) breeding
inferred← citeshttps://doi.org/10.1016/j.scienta.2022.111013openalex-snapshot
Unravelling the responses of different apple varieties to water constraints by continuous field thermal monitoring
inferred← citeshttps://doi.org/10.1016/j.softx.2024.101928openalex-snapshot
vegspec: A compilation of spectral vegetation indices and transformations in Python
inferred← citeshttps://doi.org/10.1016/j.stress.2024.100386openalex-snapshot
High-throughput phenotyping for terminal drought stress in chickpea (Cicer arietinum L.)
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