ReviewPlants (Basel, Switzerland)2022
Utilization of Spectral Indices for High-Throughput Phenotyping.
Review in Plants (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
17 citing papers in PubMed, 56 citations in OpenAlex.
- Phenomics-assisted sparse testing for potato breeding.Scientific reports · 2026Article
- Methodology for Selecting Stable UAV-Based Vegetation Indices for Prediction of Agronomic Variables in Maize Using a Multispectral Sensor.Plants (Basel, Switzerland) · 2026Article
- A shade-hyposensitive tomato line shows altered auxin homeostasis and higher fruit yield under high-density field conditions.The New phytologist · 2025Article
- Advancing Crop Resilience Through High-Throughput Phenotyping for Crop Improvement in the Face of Climate Change.Plants (Basel, Switzerland) · 2025Review
- Targeted integrating hyperspectral and metabolomic data with spectral indices and metabolite content models for efficient salt-tolerant phenotype discrimination inPlant phenomics (Washington, D.C.) · 2025Article
- EcoBOT: an AI/ML enabled automated phenotyping capability for model plants.Frontiers in plant science · 2025Article
- Automatic optimization of regions of interest in hyperspectral images for detecting vegetative indices in soybeans.Frontiers in plant science · 2025Article
- Early-life exposure to residential greenness and risk of asthma in a U.S. bronchiolitis cohort.Allergy · 2024Article
- Leveraging genomics and temporal high-throughput phenotyping to enhance association mapping and yield prediction in sesame.The plant genome · 2024Article
- Effect of LED Lights on Secondary Metabolites and Antioxidant Activities in Red Pakchoi Baby Leaves.ACS omega · 2024Article
- High-Throughput Analysis of Leaf Chlorophyll Content in Aquaponically Grown Lettuce Using Hyperspectral Reflectance and RGB Images.Plants (Basel, Switzerland) · 2024Article
- Optimal-Band Analysis for Chlorophyll Quantification in Rice Leaves Using a Custom Hyperspectral Imaging System.Plants (Basel, Switzerland) · 2024Article
- Article
- A Model for the Determination of Potato Tuber Mass by the Measurement of Carbon Dioxide Concentration.Plants (Basel, Switzerland) · 2023Article
- Multi-Omics Pipeline and Omics-Integration Approach to Decipher Plant's Abiotic Stress Tolerance Responses.Genes · 2023Review
- Rapid Identification of Main Vegetation Types in the Lingkong Mountain Nature Reserve Based on Multi-Temporal Modified Vegetation Indices.Sensors (Basel, Switzerland) · 2023Article
- The era of cultivating smart rice with high light efficiency and heat tolerance has come of age.Frontiers in plant science · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 2 countries.
Funding
Abstract
The conventional plant breeding evaluation of large sets of plant phenotypes with precision and speed is very challenging. Thus, consistent, automated, multifaceted, and high-throughput phenotyping (HTP) technologies are becoming increasingly significant as tools to aid conventional breeding programs to develop genetically improved crops. With rapid technological advancement, various vegetation indices (VIs) have been developed. These VI-based imaging approaches, linked with artificial intelligence and a variety of remote sensing applications, provide high-throughput evaluations, particularly in the field of precision agriculture. VIs can be used to analyze and predict different quantitative and qualitative aspects of vegetation. Here, we provide an overview of the various VIs used in agricultural research, focusing on those that are often employed for crop or vegetation evaluation, because that has a linear relationship to crop output, which is frequently utilized in crop chlorophyll, health, moisture, and production predictions. In addition, the following aspects are here described: the importance of VIs in crop research and precision agriculture, their utilization in HTP, recent photogrammetry technology, mapping, and geographic information system software integrated with unmanned aerial vehicles and its key features. Finally, we discuss the challenges and future perspectives of HTP technologies and propose approaches for the development of new tools to assess plants' agronomic traits and data-driven HTP resolutions for precision breeding.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.