GRABSEEDS: extraction of plant organ traits through image analysis
Haibao Tang,
Wenqian Kong,
Pheonah Nabukalu,
Johnathan S. Lomas,
Michel Moser,
Jisen Zhang,
Mengwei Jiang,
Xingtan Zhang,
Andrew H. Paterson,
Won Cheol Yim
Affiliations
Haibao Tang
Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Haixia Institute of Science and Technology and College of Life Sciences, Fujian Agriculture and Forestry University
Wenqian Kong
Plant Genome Mapping Laboratory, University of Georgia
Pheonah Nabukalu
The Land Institute
Johnathan S. Lomas
Department of Biochemistry and Molecular Biology, University of Nevada
Michel Moser
Institute of Plant Sciences, University of Bern
Jisen Zhang
State Key Lab for Conservation and Utilization of Subtropical Agro-Biological Resources, Guangxi Key Lab for Sugarcane Biology, Guangxi University
Mengwei Jiang
National Key Laboratory for Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences
Xingtan Zhang
National Key Laboratory for Tropical Crop Breeding, Shenzhen Branch, Guangdong Laboratory for Lingnan Modern Agriculture, Genome Analysis Laboratory of the Ministry of Agriculture, Agricultural Genomics Institute at Shenzhen, Chinese Academy of Agricultural Sciences
Andrew H. Paterson
Plant Genome Mapping Laboratory, University of Georgia
Won Cheol Yim
Department of Biochemistry and Molecular Biology, University of Nevada
Abstract Background Phenotyping of plant traits presents a significant bottleneck in Quantitative Trait Loci (QTL) mapping and genome-wide association studies (GWAS). Computerized phenotyping using digital images promises rapid, robust, and reproducible measurements of dimension, shape, and color traits of plant organs, including grain, leaf, and floral traits. Results We introduce GRABSEEDS, which is specifically tailored to extract a comprehensive set of features from plant images based on state-of-the-art computer vision and deep learning methods. This command-line enabled tool, which is adept at managing varying light conditions, background disturbances, and overlapping objects, uses digital images to measure plant organ characteristics accurately and efficiently. GRABSEED has advanced features including label recognition and color correction in a batch setting. Conclusion GRABSEEDS streamlines the plant phenotyping process and is effective in a variety of seed, floral and leaf trait studies for association with agronomic traits and stress conditions. Source code and documentations for GRABSEEDS are available at: https://github.com/tanghaibao/jcvi/wiki/GRABSEEDS .
