Scope
Plant phenotyping is widely known as the basis of plant phenomics, which is the bridge as well as a bottleneck for studying the interactions between genomics and the environment. Recently, time-series phenotyping is gaining more and more attention due to its potential in revealing key trait differences in critical growth periods as well as a way to access more functional traits. Meanwhile, proximal sensing and image analysis have brought a renaissance in plant phenotyping. It is possible to combine multi-source proximal sensing techniques, such as RGB, light detection and ranging (LiDAR), multi/hyperspectral, solar-induced fluorescence (SIF), and thermal sensors, to better describe plant growth and development. Image analysis, especially computer vision and data-driven deep learning methods, can make phenotyping more objective, accurate, and efficient than traditional field measurement. Therefore, combining advanced proximal sensing and image analysis will provide a comprehensive study of time-series plant phenotyping.
Given the above context, this special issue invites submissions broadly contributing to time-series plant phenotyping. Specific topics of interest include:
- Data fusion of multi-source proximal sensing imagery to provide consistent spatial and temporal support.
- Methods in time-series phenotyping including object detection, tracking, trait extraction, etc.
- Application of time-series imagery to plant breeding, cultivation, and management.
Articles must be original research, not published elsewhere. All articles will go through a rigorous peer-review process as per the journal standard. Review articles around the topics are also encouraged.
Guest Editors
Shichao Jin, Nanjing Agricultural University
Yanjun Su, Institute of Botany, Chinese Academy of Sciences
Changying Li, University of Georgia
Qinghua Guo, Peking University
Submission Instructions
Please indicate in your cover letter that your submission is intended for consideration for the special issue, Advances in Proximal Sensing and Image Analysis for Time-Series Phenotyping. For inquiries, please contact Dr. Shichao Jin ([email protected]).
Submission Deadline: June 30, 2023
Table of Contents
Enhancing the photosynthetic rate is one of the effective ways to increase rice yield, given that photosynthesis is the basis of crop productivity. At the leaf level, crops’ photosynthetic rate is mainly determined by photosynthetic functional traits ...
The field phenotyping platforms that can obtain high-throughput and time-series phenotypes of plant populations at the 3-dimensional level are crucial for plant breeding and management. However, it is difficult to align the point cloud data and extract ...
Accurate and high-throughput plant phenotyping is important for accelerating crop breeding. Spectral imaging that can acquire both spectral and spatial information of plants related to structural, biochemical, and physiological traits becomes one of the ...
Proximal remote sensing offers a powerful tool for high-throughput phenotyping of plants for assessing stress response. Bean plants, an important legume for human consumption, are often grown in regions with limited rainfall and irrigation and are ...
Verticillium wilt is one of the most critical cotton diseases, which is widely distributed in cotton-producing countries. However, the conventional method of verticillium wilt investigation is still manual, which has the disadvantages of subjectivity and ...
High-throughput estimation of phenotypic traits from UAV (unmanned aerial vehicle) images is helpful to improve the screening efficiency of breeding maize. Accurately estimating phenotyping traits of breeding maize at plot scale helps to promote gene ...
Canopy photosynthesis is the sum of photosynthesis of all above-ground photosynthetic tissues. Quantitative roles of nonfoliar tissues in canopy photosynthesis remain elusive due to methodology limitations. Here, we develop the first complete canopy ...
Forested environments feature a highly complex radiation regime, and solar radiation is hindered from penetrating into the forest by the 3D canopy structure; hence, canopy shortwave radiation varies spatiotemporally, seasonally, and meteorologically, ...
Phenotyping of plant growth improves the understanding of complex genetic traits and eventually expedites the development of modern breeding and intelligent agriculture. In phenotyping, segmentation of 3D point clouds of plant organs such as leaves and ...
Wheat yield and grain protein content (GPC) are two main optimization targets for breeding and cultivation. Remote sensing provides nondestructive and early predictions of yield and GPC, respectively. However, whether it is possible to simultaneously ...