The development of RGB (red, green, blue) sensors has opened the way for plant phenotyping. This is relevant because plant phenotyping allows us to visualize the product of the interaction between the plant ontogeny, anatomy, physiology, and biochemistry. Better yet, this can be achieved at any stage of plant development, i.e., from seedling to maturity. Here, we describe the use of phenotyping, based on the stay-green trait, of common bean (Phaseolus vulgaris L.) plant, as a model, stressed by water deficit, to elucidate the result of that interaction. Description is based on interpretation of RGB digital images acquired using a phenomic platform and a specific software. These images allow us to obtain a data group related to the color parameters that quantify the changes and alterations in each plant growth and development.
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http://dx.doi.org/10.1007/978-1-0716-2537-8_1 | DOI Listing |
Plant Commun
December 2024
Rice Research Institute, Fujian Academy of Agricultural Sciences, Fuzhou 350019, China; State Key Laboratory of Ecological Pest Control for Fujian and Taiwan' Crops/Key Laboratory of Germplasm Innovation and Molecular Breeding of Hybrid Rice in South China/Fujian Engineering Laboratory of Crop Molecular Breeding/Fujian Key Laboratory of Rice Molecular Breeding/Fuzhou Branch, National Center of Rice Improvement of China/National Engineering Laboratory of Rice/South Base of National Key Laboratory of Hybrid Rice of China, Fuzhou 350003, China; College of Agriculture, Fujian Agriculture and Forestry University, Fuzhou 350002, China. Electronic address:
Leaf angle is a major agronomic trait that determines plant architecture, which directly affects rice planting density, photosynthetic efficiency, and yield. The plant phytohormones brassinosteroids (BRs) and the MAPK signaling cascade are known to play crucial roles in regulating the leaf angle, but the underlying molecular mechanisms are not fully understood. Here, we report a rice WRKY family transcription factor gene, OsWRKY72, which positively regulates leaf angle by affecting lamina joint development and BR signaling.
View Article and Find Full Text PDFBMC Plant Biol
December 2024
Hami-melon Research Center, Xinjiang Academy of Agricultural Sciences, Urumqi, Xinjiang, 830091, China.
Fruit diameter is one of important agronomy traits that has greatly impacts fruit yield and commercial value in cucumber (Cucumis sativus L.). Hence, we preliminary mapping of fruit diameter was conducted to refine its genetic locus.
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December 2024
Laboratorio de Biotecnología y Estudios Ambientales, Departamento de Ciencias y Tecnología Vegetal, Escuela de Ciencias y Tecnologías, Universidad de Concepción, Campus Los Ángeles, 4440000, Concepción, Chile.
Colobanthus quitensis is known for enduring extreme conditions, such as high salinity in Antarctica, making it an excellent model for studying environmental stress. In plant families, variations in seed color heteromorphism have been linked to various germination under stress conditions. Preliminary laboratory observations indicated that dark brown seeds of C.
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December 2024
Shanghai Center for Plant Stress Biology, CAS Center for Excellence in Molecular Plant Sciences, Chinese Academy of Sciences, Shanghai, 200032, China.
Gene targeting (GT) is a powerful tool for manipulating endogenous genomic sequences as intended. However, its efficiency is rather low, especially in seed plants. Numerous attempts have been made to improve the efficiency of GT via the CRISPR/Cas systems in plants, but these have not been sufficiently effective to be used routinely by everyone.
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December 2024
National Key Laboratory of Crop Genetic Improvement, National Center of Plant Gene Research, Huazhong Agricultural University, Wuhan, 430070, P. R. China.
Point cloud analysis is a crucial task in computer vision. Despite significant advances over the past decade, the developments in agricultural domain have faced challenges due to a scarcity of datasets. To facilitate 3D point cloud research in agriculture community, we introduce Crops3D, the diverse real-world dataset derived from authentic agricultural scenarios.
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