ReviewFrontiers in plant science2022
Applications of a Hyperspectral Imaging System Used to Estimate Wheat Grain Protein: A Review.
Review in Frontiers in plant science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 48 citations in OpenAlex.
- Estimation of Wheat Grain Protein Content at Multiple Growth Stages Based on Space-Air-Ground Collaborative Observation Data.Plants (Basel, Switzerland) · 2026Article
- Predicting wheat yield and grain quality with UAV multispectral imagery and deep learning.Frontiers in plant science · 2026Article
- Modeling grain biochemical composition traits of commercial sorghum hybrids under diverse management practices.Frontiers in plant science · 2026Article
- Identification of HybridBiosensors · 2025Article
- A Handheld Multispectral Device for Assessing Leaf Nitrogen Concentrations in Maize.Sensors (Basel, Switzerland) · 2025Article
- Winter wheat yield prediction using UAV-based multivariate time series data and variate-independent tokenization.Plant phenomics (Washington, D.C.) · 2025Article
- Micronutrient Biofortification in Wheat: QTLs, Candidate Genes and Molecular Mechanism.International journal of molecular sciences · 2025Review
- The 500-meter long-term winter wheat grain protein content dataset for China from multi-source data.Scientific data · 2024Article
- A model for inversion of hyperspectral characteristics of phosphate content in mural plaster based on fractional-order differential algorithm.Scientific reports · 2024Article
- Nitrogen monitoring and inversion algorithms of fruit trees based on spectral remote sensing: a deep review.Frontiers in plant science · 2024Review
- Challenges facing sustainable protein production: Opportunities for cereals.Plant communications · 2023Review
- Reviving grain quality in wheat through non-destructive phenotyping techniques like hyperspectral imaging.Food and energy security · 2023Review
- Ensuring Explainability and Dimensionality Reduction in a Multidimensional HSI World for Early XAI-Diagnostics of Plant Stress.Entropy (Basel, Switzerland) · 2023Article
- Hyperspectral remote sensing for tobacco quality estimation, yield prediction, and stress detection: A review of applications and methods.Frontiers in plant science · 2023Review
- Dynamic monitoring of maize grain quality based on remote sensing data.Frontiers in plant science · 2023Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Recent research advances in wheat have focused not only on increasing grain yields, but also on establishing higher grain quality. Wheat quality is primarily determined by the grain protein content (GPC) and composition, and both of these are affected by nitrogen (N) levels in the plant as it develops during the growing season. Hyperspectral remote sensing is gradually becoming recognized as an economical alternative to traditional destructive field sampling methods and laboratory testing as a means of determining the N status within wheat. Currently, hyperspectral vegetation indices (VIs) and linear nonparametric regression are the primary tools for monitoring the N status of wheat. Machine learning algorithms have been increasingly applied to model the nonlinear relationship between spectral data and wheat N status. This study is a comprehensive review of available N-related hyperspectral VIs and aims to inform the selection of VIs under field conditions. The combination of feature mining and machine learning algorithms is discussed as an application of hyperspectral imaging systems. We discuss the major challenges and future directions for evaluating and assessing wheat N status. Finally, we suggest that the underlying mechanism of protein formation in wheat grains as determined by using hyperspectral imaging systems needs to be further investigated. This overview provides theoretical and technical support to promote applications of hyperspectral imaging systems in wheat N status assessments; in addition, it can be applied to help monitor and evaluate food and nutrition security.
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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.