The DOI matches its Crossref record; 129 of the 129 references it cites were found in a registry or an index.
High-throughput phenotyping: Breaking through the bottleneck in future crop breeding
Open accessAbstract
With the rapid development of genetic analysis techniques and crop population size, phenotyping has become the bottleneck restricting crop breeding. Breaking through this bottleneck will require phenomics, defined as the accurate, high-throughput acquisition and analysis of multi-dimensional phenotypes during crop growth at organism-wide levels, ranging from cells to organs, individual plants, plots, and fields. Here we offer an overview of crop phenomics research from technological and platform viewpoints at various scales, including microscopic, ground-based, and aerial phenotyping and phenotypic data analysis. We describe recent applications of high-throughput phenotyping platforms for abiotic/biotic stress and yield assessment. Finally, we discuss current challenges and offer perspectives on future phenomics research.
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Cites
Phenomics – technologies to relieve the phenotyping bottleneck
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A Robust Deep-Learning-Based Detector for Real-Time Tomato Plant Diseases and Pests Recognition
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A Review of Imaging Techniques for Plant Phenotyping
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Soybean yield prediction from UAV using multimodal data fusion and deep learning
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Self-citationCrop Yield Prediction Using Deep Neural Networks
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Metadata
- Authors
- Song, P., Wang, J., Guo, X., Yang, W., & Zhao, C.
- Venue
- The Crop Journal
- Publisher
- Elsevier BV
- Published
- 2021-06
- Volume
- 9
- Issue
- 3
- Pages
- 633-645
- ISSN
- 2095-5421 (ISSN-L)
- 2214-5141
- OpenAlex
- W3159378418
- Cited by
- 269
- References
- 129
- FWCI
- 20.75
- Type
- journal article
- Language
- en
- Open access
- gold
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- Song, P., Wang, J., Guo, X., Yang, W., & Zhao, C. (2021). High-throughput phenotyping: Breaking through the bottleneck in future crop breeding. The Crop Journal. https://doi.org/10.1016/j.cj.2021.03.015
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