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Plant Phenomics |《植物表型组学》2021-2022年文章导读
发表时间:2023-03-31 08:38:21点击:865
来源:植物表型组学
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2021-2022年Plant Phenomics文章导读
全文链接:https://spj.science.org/doi/10.34133/plantphenomics.0007
微信导读:Plant Phenomics | 基于无人机多光谱图像和SRGAN的大白菜单株表型测定研究
全文链接:https://spj.science.org/doi/10.34133/plantphenomics.0002
微信导读:Plant Phenomics | 两个大田高粱品种根系性状对磷肥响应的变异性和可塑性研究
SE-COTR: A Novel Fruit Segmentation Model for Green Apples Application in Complex Orchard
全文链接:https://spj.science.org/doi/10.34133/plantphenomics.0005
微信导读:Plant Phenomics | SE-COTR:针对复杂果园中绿色苹果的果实分割模型
SegVeg: Segmenting RGB Images into Green and Senescent Vegetation by Combining Deep and Shallow Methods
全文链接:https://spj.science.org/doi/10.34133/2022/9803570
微信导读:Plant Phenomics | SegVeg通过深度和浅层方法的结合将RGB图像分割成绿色和衰老植被
Assessing the Storage Root Development of Cassava with a New Analysis Tool
全文链接:https://spj.science.org/doi/10.34133/2022/9767820
微信导读:Plant Phenomics | 评估木薯贮藏根系发育新的分析工具
Deep Learning for Strawberry Canopy Delineation and Biomass Prediction from High-Resolution Images
全文链接:https://spj.science.org/doi/10.34133/2022/9850486
基于高分辨率图像的草莓冠层描绘和生物量预测的深度学习
BFP Net: Balanced Feature Pyramid Network for Small Apple Detection in Complex Orchard Environment
全文链接:https://spj.science.org/doi/10.34133/2022/9892464
微信导读:Plant Phenomics | 基于可平衡特征金字塔网络的小苹果检测模型
EasyDAM_V2: Efficient Data Labeling Method for Multishape, Cross-Species Fruit Detection
全文链接:https://spj.science.org/doi/10.34133/2022/9761674
微信导读:Plant Phenomics | EasyDAM_V2,零数据标注实现果实识别模型构建
Application of UAV Multisensor Data and Ensemble Approach for High-Throughput Estimation of Maize Phenotyping Traits
全文链接:https://spj.science.org/doi/10.34133/2022/9802585
微信导读:Plant Phenomics | 基于无人机多传感器和集成学习的玉米表型高通量估算
Spectral Preprocessing Combined with Deep Transfer Learning to Evaluate Chlorophyll Content in Cotton Leaves
全文链接:https://spj.science.org/doi/10.34133/2022/9813841
微信导读:Plant Phenomics | 光谱预处理与深度转移学习相结合的叶片叶绿素含量评估
End-to-End Fusion of Hyperspectral and Chlorophyll Fluorescence Imaging to Identify Rice Stresses
全文链接:https://spj.science.org/doi/10.34133/2022/9851096
高光谱和叶绿素荧光成像的端到端融合识别水稻胁迫
3dCAP-Wheat: An Open-Source Comprehensive Computational Framework Precisely Quantifies Wheat Foliar, Nonfoliar, and Canopy Photosynthesis
全文链接:https://spj.science.org/doi/10.34133/2022/9758148
微信导读:Plant Phenomics | 基于整合叶片与非叶片组织光合作用的三维冠层模型精确刻画小麦群体光合
Shortwave Radiation Calculation for Forest Plots Using Airborne LiDAR Data and Computer Graphics
全文链接:https://spj.science.org/doi/10.34133/2022/9856739
微信导读:Plant Phenomics | 基于机载LiDAR数据和计算机图形学的林分短波辐射计算
Unsupervised Plot-Scale LAI Phenotyping via UAV-Based Imaging, Modelling, and Machine Learning
全文链接:https://spj.science.org/doi/10.34133/2022/9768253
微信导读:Plant Phenomics | 基于无人机成像实现对田间小麦叶面积指数的快速精准估计
A Review of High-Throughput Field Phenotyping Systems: Focusing on Ground Robots
全文链接:https://spj.science.org/doi/10.34133/2022/9760269
高通量田间表型系统综述:重点关注地面机器人
Moxa Wool in Different Purities and Different Growing Years Measured by Terahertz Spectroscopy
全文链接:https://spj.science.org/doi/10.34133/2022/9815143
微信导读:Plant Phenomics | 太赫兹光谱技术可以精确区分艾绒纯度和生长年限
Development and Validation of a Deep Learning Based Automated Minirhizotron Image Analysis Pipeline
全文链接:https://spj.science.org/doi/10.34133/2022/9758532
微信导读:Plant Phenomics | 基于深度学习的微根管图像自动化分析方法
PSegNet: Simultaneous Semantic and Instance Segmentation for Point Clouds of Plants
全文链接:https://spj.science.org/doi/10.34133/2022/9787643
微信导读:Plant Phenomics | PSegNet:针对多品种作物点云的器官同步语义分割与实例分割深度学习网络
Robust High-Throughput Phenotyping with Deep Segmentation Enabled by a Web-Based Annotator
全文链接:https://spj.science.org/doi/10.34133/2022/9893639
基于网络标注器的深度分割技术支持的鲁棒高通量表型分析
Evaluation of Postharvest Senescence of Broccoli via Hyperspectral Imaging
全文链接:https://spj.science.org/doi/10.34133/2022/9761095
通过高光谱成像评价西兰花采后衰老
Enabling Breeding Selection for Biomass in Slash Pine Using UAV-Based Imaging
全文链接:https://spj.science.org/doi/10.34133/2022/9783785
微信导读:Plant Phenomics | 无人机成像技术助力湿地松生物量遗传选择育种
Estimating Photosynthetic Attributes from High-Throughput Canopy Hyperspectral Sensing in Sorghum
全文链接:https://spj.science.org/doi/10.34133/2022/9768502
微信导读:Plant Phenomics | 利用高通量冠层高光谱遥感预测高粱的光合参数
Objective Phenotyping of Root System Architecture Using Image Augmentation and Machine Learning in Alfalfa (Medicago sativa L.)
全文链接:https://spj.science.org/doi/10.34133/2022/9879610
微信导读:Plant Phenomics | 基于图像增强和机器学习的苜蓿根系表型研究
Prediction of the Maturity of Greenhouse Grapes Based on Imaging Technology
全文链接:https://spj.science.org/doi/10.34133/2022/9753427
微信导读:Plant Phenomics | 基于表型图像信息与反向神经网络预测温室葡萄成熟度
Simultaneous Prediction of Wheat Yield and Grain Protein Content Using Multitask Deep Learning from Time-Series Proximal Sensing
全文链接:https://spj.science.org/doi/10.34133/2022/9757948
微信导读:Plant Phenomics | 基于近端多源时序数据和多任务深度学习同步预测小麦产量和品质性状
How Useful Is Image-Based Active Learning for Plant Organ Segmentation?
全文链接:https://spj.science.org/doi/10.34133/2022/9795275
基于图像的主动学习对植物器官分割有多大用处?
Dynamic Color Transform Networks for Wheat Head Detection
全文链接:https://spj.science.org/doi/10.34133/2022/9818452
微信导读:Plant Phenomics | 华中科技大学曹治国教授提出用于麦穗检测的动态颜色变换网络
Wheat Ear Segmentation Based on a Multisensor System and Superpixel Classification
全文链接:https://spj.science.org/doi/10.34133/2022/9841985
微信导读:Plant Phenomics | 基于多传感器系统和超像素分类的麦穗图像分割
Spectrometric Prediction of Nitrogen Content in Different Tissues of Slash Pine Trees
全文链接:https://spj.science.org/doi/10.34133/2022/9892728
微信导读:Plant Phenomics | 氮肥都去哪儿了?湿地松不同部位氮元素含量差异及其光谱预测方法
Panicle-3D: Efficient Phenotyping Tool for Precise Semantic Segmentation of Rice Panicle Point Cloud
全文链接:https://spj.science.org/doi/10.34133/2021/9838929
微信导读:Plant Phenomics | Panicle-3D:水稻穗点云精确语义分割的高效表型工具
Automatic Microplot Localization Using UAV Images and a Hierarchical Image-Based Optimization Method
全文链接:https://spj.science.org/doi/10.34133/2021/9764514
使用无人机图像的自动微图定位和基于分层图像的优化方法
A Double Swath Configuration for Improving Throughput and Accuracy of Trait Estimate from UAV Images
全文链接:https://spj.science.org/doi/10.34133/2021/9892647
微信导读:Plant Phenomics | “双眼”胜于“单眼”:精准农业的创新战略
Complementary Phenotyping of Maize Root System Architecture by Root Pulling Force and X-Ray Imaging
全文链接:https://spj.science.org/doi/10.34133/2021/9859254
微信导读:Plant Phenomics | 基于根提拉力和X射线成像的玉米根系结构表型研究
GANana: Unsupervised Domain Adaptation for Volumetric Regression of Fruit
全文链接:https://spj.science.org/doi/10.34133/2021/9874597
微信导读:Plant Phenomics | GANana:用于水果三维重建的无监督域自适应体积回归算法
Detecting Sorghum Plant and Head Features from Multispectral UAV Imagery
全文链接:https://spj.science.org/doi/10.34133/2021/9874650
从多光谱无人机图像中检测高粱植株和穗的特征
Global Wheat Head Detection 2021: An Improved Dataset for Benchmarking Wheat Head Detection Methods
全文链接:https://spj.science.org/doi/10.34133/2021/9846158
微信导读:Plant Phenomics | GWHD_2021:改进后的全球麦穗检测数据集
Exploring Seasonal and Circadian Rhythms in Structural Traits of Field Maize from LiDAR Time Series
全文链接:https://spj.science.org/doi/10.34133/2021/9895241
微信导读:Plant Phenomics | 作物是否会睡觉?时间序列激光雷达量化玉米生育期和昼夜节律表型
Field Phenomics: Will It Enable Crop Improvement?
全文链接:https://spj.science.org/doi/10.34133/2021/9871989
田间表型组学:它能促进作物改良吗?
Estimates of Maize Plant Density from UAV RGB Images Using Faster-RCNN Detection Model: Impact of the Spatial Resolution
全文链接:https://spj.science.org/doi/10.34133/2021/9824843
使用 Faster-RCNN 检测模型从无人机 RGB 图像估计玉米植株密度:空间分辨率的影响
Classification of Soybean Pubescence from Multispectral Aerial Imagery
全文链接:https://spj.science.org/doi/10.34133/2021/9806201
微信导读:Plant Phenomics | 基于多光谱航拍图像对大豆茸毛进行分类
KAT4IA: KK-Means Assisted Training for Image Analysis of Field-Grown Plant Phenotypes
全文链接:https://spj.science.org/doi/10.34133/2021/9805489
KAT4IA:用于田间植物表型图像分析的 K-Means 辅助训练
Using Machine Learning to Develop a Fully Automated Soybean Nodule Acquisition Pipeline (SNAP)
全文链接:https://spj.science.org/doi/10.34133/2021/9834746
微信导读:Plant Phenomics | SNAP:基于机器学习的全自动大豆根瘤提取算法
High-Throughput Corn Image Segmentation and Trait Extraction Using Chlorophyll Fluorescence Images
全文链接:https://spj.science.org/doi/10.34133/2021/9792582
微信导读:Plant Phenomics | 基于叶绿素荧光图像的高通量玉米图像分割和性状提取
Qualification of Soybean Responses to Flooding Stress Using UAV-Based Imagery and Deep Learning
全文链接:https://spj.science.org/doi/10.34133/2021/9892570
微信导读:Plant Phenomics | 基于无人机图像和深度学习鉴定大豆对水涝胁迫的响应
Deep Multiview Image Fusion for Soybean Yield Estimation in Breeding Applications
全文链接:https://spj.science.org/doi/10.34133/2021/9846470
微信导读:Plant Phenomics | 深度融合多角度图像以预估育种应用中的大豆产量
UAS-Based Plant Phenotyping for Research and Breeding Applications
全文链接:https://spj.science.org/doi/10.34133/2021/9840192
微信导读:Plant Phenomics 综述 | 基于无人驾驶航空器系统的植物表型分析
Impact of Varying Light and Dew on Ground Cover Estimates from Active NDVI, RGB, and LiDAR
全文链接:https://spj.science.org/doi/10.34133/2021/9842178
微信导读:Plant Phenomics | 在不同光线和露水情况下评估用传感器估算冠层覆盖度的可靠性
Enhanced Field-Based Detection of Potato Blight in Complex Backgrounds Using Deep Learning
全文链接:https://spj.science.org/doi/10.34133/2021/9835724
使用深度学习在复杂背景下增强基于田间马铃薯枯萎病检测
Automatic Fruit Morphology Phenome and Genetic Analysis: An Application in the Octoploid Strawberry
全文链接:https://spj.science.org/doi/10.34133/2021/9812910
微信导读:Plant Phenomics | 对八倍体草莓形态的自动化表型和遗传分析
The Application of UAV-Based Hyperspectral Imaging to Estimate Crop Traits in Maize Inbred Lines
全文链接:https://spj.science.org/doi/10.34133/2021/9890745
微信导读:Plant Phenomics | 无人机高光谱影像在玉米自交系作物性状估算中的应用
An Integrated Method for Tracking and Monitoring Stomata Dynamics from Microscope Videos
全文链接:https://spj.science.org/doi/10.34133/2021/9835961
微信导读:Plant Phenomics | 南京农大提出了一种从显微镜视频中跟踪和监测气孔动态的集成方法
Robust Surface Reconstruction of Plant Leaves from 3D Point Clouds
全文链接:https://spj.science.org/doi/10.34133/2021/3184185
微信导读:Plant Phenomics | 基于植物叶片三维点云的稳健表面重建
Classification of Rice Yield Using UAV-Based Hyperspectral Imagery and Lodging Feature
全文链接:https://spj.science.org/doi/10.34133/2021/9765952
微信导读:Plant Phenomics | 结合无人机高光谱图像和倒伏特征构建水稻产量类别检测模型
Detection of the Progression of Anthesis in Field-Grown Maize Tassels: A Case Study
全文链接:https://spj.science.org/doi/10.34133/2021/4238701
微信导读:Plant Phenomics | 田间条件下检测玉米雄穗的开花进程
A Comparative Analysis of Quantitative Metrics of Root Architecture
全文链接:https://spj.science.org/doi/10.34133/2021/6953197
微信导读:Plant Phenomics | 对根系结构量化指标的比较分析
Semiautomated 3D Root Segmentation and Evaluation Based on X-Ray CT Imagery
全文链接:https://spj.science.org/doi/10.34133/2021/8747930
微信导读:Plant Phenomics | 基于X射线CT图像的半自动3D根系分割与评价方法
Photosynthetic Phenomics of Field- and Greenhouse-Grown Amaranths vs. Sensory and Species Delimits
全文链接:https://spj.science.org/doi/10.34133/2021/2539380
微信导读:Plant Phenomics | 对大田和温室栽培苋菜的光合表型、感官和品种界限的分析
Phenotyping Tomato Root Developmental Plasticity in Response to Salinity in Soil Rhizotrons
全文链接:https://spj.science.org/doi/10.34133/2021/2760532
微信导读:Plant Phenomics | 表型分析番茄根系发育可塑性对土壤盐分胁迫的响应
Terahertz Spectroscopy for Accurate Identification of Panax quinquefolium Basing on Nonconjugated 24(R)-Pseudoginsenoside F11
全文链接:https://spj.science.org/doi/10.34133/2021/6793457
微信导读:Plant Phenomics | 上海理工大学庄松林院士团队开发了一种基于西洋参标志物F11的无损快速分析方法
《植物表型组学》(Plant Phenomics)是由南京农业大学和美国科学促进会(AAAS)合作创办的英文学术期刊,于2019年1月正式上线发行。采用开放获取形式,刊载植物表型组学交叉学科热点领域具有突破性科研进展的原创性研究论文、综述、数据集和观点。具体范围涵盖高通量表型分析的最新技术,基于图像分析和机器学习的表型分析研究,提取表型信息的新算法,作物栽培、植物育种和农业实践中的表型组学新应用,与植物表型相结合的分子生物学、植物生理学、统计学、作物模型和其他组学研究,表型组学相关的植物生物学等。期刊已被DOAJ、Scopus、PMC、EI和SCIE等数据库收录。科睿唯安JCR2021影响因子为6.961,位于农艺学、植物科学、遥感一区。中科院农艺学、植物科学一区,遥感二区,生物大类一区(TOP期刊)。2020年入选中国科技期刊卓越行动计划高起点新刊项目。
说明:本文由《植物表型组学》编辑部负责组稿。
审核:孔敏、王平