Efficient Noninvasive FHB Estimation using RGB Images from a Novel Multiyear, Multirater Dataset [0.03%]
基于新型多年度、多评价者的数据集使用RGB图像有效非侵入估计FHB病情指数
Dominik Rößle,Lukas Prey,Ludwig Ramgraber et al.
Dominik Rößle et al.
Fusarium head blight (FHB) is one of the most prevalent wheat diseases, causing substantial yield losses and health risks. Efficient phenotyping of FHB is crucial for accelerating resistance breeding, but currently used methods are time-con...
A Combined Genomics and Phenomics Approach is Needed to Boost Breeding in Sugarcane [0.03%]
甘蔗育种需要结合基因组学和表型组学的综合方法
Ting Luo,Xiaoyan Liu,Prakash Lakshmanan
Ting Luo
Can Distributed Ledgers Help to Overcome the Need of Labeled Data for Agricultural Machine Learning Tasks? [0.03%]
分布式分类账技术能否帮助克服农业机器学习任务中对标注数据的需求？
Stefan Paulus,Benjamin Leiding
Stefan Paulus
Application of Improved UNet and EnglightenGAN for Segmentation and Reconstruction of In Situ Roots [0.03%]
改进的UNet和EnglightenGAN在根系原位分割与重建中的应用研究
Qiushi Yu,Jingqi Wang,Hui Tang et al.
Qiushi Yu et al.
The root is an important organ for crops to absorb water and nutrients. Complete and accurate acquisition of root phenotype information is important in root phenomics research. The in situ root research method can obtain root images without...
Wearable Sensor: An Emerging Data Collection Tool for Plant Phenotyping [0.03%]
植物表型分析新兴的数据采集工具：可穿戴传感器技术及其应用展望
Cheng Zhang,Jingjing Kong,Daosheng Wu et al.
Cheng Zhang et al.
The advancement of plant phenomics by using optical imaging-based phenotyping techniques has markedly improved breeding and crop management. However, there remains a challenge in increasing the spatial resolution and accuracy due to their n...
Knowledge Distillation Facilitates the Lightweight and Efficient Plant Diseases Detection Model [0.03%]
知识蒸馏促进轻量高效的植物病害检测模型
Qianding Huang,Xingcai Wu,Qi Wang et al.
Qianding Huang et al.
Plant disease diagnosis in time can inhibit the spread of the disease and prevent a large-scale drop in production, which benefits food production. Object detection-based plant disease diagnosis methods have attracted widespread attention d...
Classification of Plant Endogenous States Using Machine Learning-Derived Agricultural Indices [0.03%]
基于机器学习农业指数的植物内源状态分类模型
Sally Shuxian Koh,Kapil Dev,Javier Jingheng Tan et al.
Sally Shuxian Koh et al.
Leaf color patterns vary depending on leaf age, pathogen infection, and environmental and nutritional stresses; thus, they are widely used to diagnose plant health statuses in agricultural fields. The visible-near infrared-shortwave infrare...
Multispectral Phenotyping and Genetic Analyses of Spring Appearance in Greening Plant, Phedimus spp [0.03%]
光谱表型分析和遗传分析在景天类植物春季发芽中的应用
Taeko Koji,Hiroyoshi Iwata,Motoyuki Ishimori et al.
Taeko Koji et al.
The change in appearance during the seasonal transitions in ornamental greening plants is an important characteristic. In particular, the early onset of green leaf color is a desirable trait for a cultivar. In this study, we established a m...
Combining High-Resolution Imaging, Deep Learning, and Dynamic Modeling to Separate Disease and Senescence in Wheat Canopies [0.03%]
结合高分辨率成像、深度学习和动态建模分离小麦冠层中的疾病和衰老
Jonas Anderegg,Radek Zenkl,Achim Walter et al.
Jonas Anderegg et al.
Maintenance of sufficiently healthy green leaf area after anthesis is key to ensuring an adequate assimilate supply for grain filling. Tightly regulated age-related physiological senescence and various biotic and abiotic stressors drive ove...
Analyzing Nitrogen Effects on Rice Panicle Development by Panicle Detection and Time-Series Tracking [0.03%]
基于水稻穗检测与时间序列跟踪的氮素影响研究
Qinyang Zhou,Wei Guo,Na Chen et al.
Qinyang Zhou et al.
Detailed observation of the phenotypic changes in rice panicle substantially helps us to understand the yield formation. In recent studies, phenotyping of rice panicles during the heading-flowering stage still lacks comprehensive analysis, ...