ArticlePlant phenomics (Washington, D.C.)2025
Design and implementation of a high-throughput field phenotyping robot for acquiring multisensor data in wheat.
Article in Plant phenomics (Washington, D.C.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- Embedding of ripening topology into one-stage detection for tomato cluster phenotyping.Journal of Zhejiang University. Science. B · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Ensuring food security has become a global challenge owing to climate change and population growth. High-throughput phenotyping can effectively drive crop genetic enhancement, which can potentially solve food crisis. Phenotyping robot is an essential part of crop ground phenotyping information monitoring, although there are challenges such as the inability to adjust the fixed track width, poor load capacity of the detection robotic arm, and inability to fuse information in real-time. This study reports a phenotyping robot with a gantry-style chassis featuring an adjustable wheeltrack (1400-1600 mm) to adapt to different row spacing arrangements and reduced damage, and function effectively in both dry field and paddy field environments. A six-degree-of-freedom sensor gimbal with high payload capacity is also developed to enable precise height (1016-2096 mm) and angle adjustments. Additionally, this study introduces an enhanced method for data acquisition from multiple imaging sensors through registration and fusion using Zhang's calibration and feature point extraction algorithm, calculating a homography matrix for high-throughput data collection at fixed positions and heights. The experimental validation results demonstrate that the RMSE of the registration algorithm does not exceed 3 pixels. The gimbal data strongly correlated with that of a handheld instrument data (r
Indexed as
Identifiers
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.