A study on high-throughput estimation of corn phenotype based on multi-sensor and integrated learning of unmanned aerial vehicles

Plant Phenomics | High-throughput estimation of corn phenotype based on multi-sensor and ensemble learning of drones

Recently, Plant Phenomics published a research paper

Based on field experiments on maize breeding, UAV digital and multispectral images of four growth stages of maize were obtained

Figure 1 Feature variable extraction process based on UAV multi-sensor data

Figure 2 Estimated heat map of plant height in the study area

Figure 3 is based on the validation set results of each phenotypic estimate and measured value of the BMA model

The digital agriculture research team of China Agricultural University mainly focuses on genotype/phenotype research on plant function-structure-environment interaction at multi-source scale, including systematic simulation and digital twin of plant function-structure-environment interaction, plant (three-dimensional) phenotype research and application research and development, multi-source sensor fusion and digital agriculture application, artificial intelligence and its agricultural algorithm application

https://doi.

Repeated Multiview Imaging for Estimating Seedling Tiller Counts of Wheat Genotypes Using Drones

https://doi.

Plant Phenomics | Multi-view imaging techniques of drones were used to estimate the tiller count of wheat seedlings

Canopy Roughness: A New Phenotypic Trait to Estimate Aboveground Biomass from Unmanned Aerial System

https://doi.

Plant Phenomics | Canopy roughness: A new phenotypic trait used by drone aerial surveys to estimate aboveground biomass

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About Plant Phenomics

Plant Phenomics is an English-language academic journal co-founded by Nanjing Agricultural University and the American Association for the Advancement of Science (AAAS), which was officially released
in January 2019.
In the form of open access, it publishes original research papers, reviews, datasets and perspectives
with breakthrough scientific research progress in the interdisciplinary hot field of plant phenomics.
The specific scope covers the latest techniques of high-throughput phenotypic analysis, phenotypic analysis research based on image analysis and machine learning, new algorithms for extracting phenotypic information, new applications of phenotypic omics in crop cultivation, plant breeding and agricultural practice, molecular biology, plant physiology, statistics, crop models and other omics studies combined with plant phenotypes, plant biology related to phenotypic omics, etc
.
The journal has been included in
databases such as DOAJ, Scopus, PMC, EI and SCIE.
Clarivate JCR2021 impact factor of 6.
961, located in agronomy, plant science, remote sensing area 1
.
Agronomy, Plant Science, Chinese Academy of Sciences, Remote Sensing, And Biology (TOP Journal
).
In 2020, it was selected as a new journal project with a high starting point for the Excellence Action Plan of China's Scientific and Technological Journals
.

Note: This paper is organized by the editorial department of Plant Phenomics
.

Chinese content is for reference only, and all content is subject
to the original English version.

Invited authors: Shu Meiyan, Ma Yuntao

Editor: Huimin Wang (Intern)

Review: Kong Min, Wang Ping