Estimating Photosynthetic Attributes from High-Throughput Canopy Hyperspectral Sensing in Sorghum [0.03%]
基于高通量冠层高光谱遥感估算谷物的光合作用性质属性参数值
Xiaoyu Zhi,Sean Reynolds Massey-Reed,Alex Wu et al.
Xiaoyu Zhi et al.
Sorghum, a genetically diverse C4 cereal, is an ideal model to study natural variation in photosynthetic capacity. Specific leaf nitrogen (SLN) and leaf mass per leaf area (LMA), as well as, maximal rates of Rubisco carboxylation (V cmax), ...
Objective Phenotyping of Root System Architecture Using Image Augmentation and Machine Learning in Alfalfa (Medicago sativa L.) [0.03%]
基于图像增强和机器学习的多年生豆科植物根系表型的客观研究
Zhanyou Xu,Larry M York,Anand Seethepalli et al.
Zhanyou Xu et al.
Active breeding programs specifically for root system architecture (RSA) phenotypes remain rare; however, breeding for branch and taproot types in the perennial crop alfalfa is ongoing. Phenotyping in this and other crops for active RSA bre...
Prediction of the Maturity of Greenhouse Grapes Based on Imaging Technology [0.03%]
基于影像技术的温室葡萄成熟度预测模型研究
Xinguang Wei,Linlin Wu,Dong Ge et al.
Xinguang Wei et al.
To predict grape maturity in solar greenhouses, a plant phenotype-monitoring platform (Phenofix, France) was used to obtain RGB images of grapes from expansion to maturity. Horizontal and longitudinal diameters, compactness, soluble solid c...
Simultaneous Prediction of Wheat Yield and Grain Protein Content Using Multitask Deep Learning from Time-Series Proximal Sensing [0.03%]
基于时序邻近传感器的多任务深度学习同时预测小麦产量和籽粒蛋白含量
Zhuangzhuang Sun,Qing Li,Shichao Jin et al.
Zhuangzhuang Sun et al.
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 simu...
How Useful Is Image-Based Active Learning for Plant Organ Segmentation? [0.03%]
基于图像的主动学习在植物器官分割中有多大作用？
Shivangana Rawat,Akshay L Chandra,Sai Vikas Desai et al.
Shivangana Rawat et al.
Training deep learning models typically requires a huge amount of labeled data which is expensive to acquire, especially in dense prediction tasks such as semantic segmentation. Moreover, plant phenotyping datasets pose additional challenge...
Chengxin Liu,Kewei Wang,Hao Lu et al.
Chengxin Liu et al.
Wheat head detection can measure wheat traits such as head density and head characteristics. Standard wheat breeding largely relies on manual observation to detect wheat heads, yielding a tedious and inefficient procedure. The emergence of ...
Wheat Ear Segmentation Based on a Multisensor System and Superpixel Classification [0.03%]
基于多传感器系统的基于超像素分类的小麦穗段分割
Alexis Carlier,Sébastien Dandrifosse,Benjamin Dumont et al.
Alexis Carlier et al.
The automatic segmentation of ears in wheat canopy images is an important step to measure ear density or extract relevant plant traits separately for the different organs. Recent deep learning algorithms appear as promising tools to accurat...
Corrigendum to "Automatic Fruit Morphology Phenome and Genetic Analysis: An Application in the Octoploid Strawberry" [0.03%]
关于“自动水果形态组学和遗传分析：八倍体草莓的应用”的勘误注释
Laura M Zingaretti,Amparo Monfort,Miguel Pérez-Enciso
Laura M Zingaretti
[This corrects the article DOI: 10.34133/2021/9812910.]. Copyright © 2022 Laura M. Zingaretti et al.
Published Erratum
Plant phenomics (Washington, D.C.). 2022 Jan 20:2022:9873618. DOI:10.34133/2022/9873618 2022
Spectrometric Prediction of Nitrogen Content in Different Tissues of Slash Pine Trees [0.03%]
slash pine不同组织含氮量的光谱预测模型
Yanjie Li,Honggang Sun,Federico Tomasetto et al.
Yanjie Li et al.
The internal cycling of nitrogen (N) storage and consumption in trees is an important physiological mechanism associated with tree growth. Here, we examined the capability of near-infrared spectroscopy (NIR) to quantify the N concentration ...
Panicle-3D: Efficient Phenotyping Tool for Precise Semantic Segmentation of Rice Panicle Point Cloud [0.03%]
Panicle-3D：高效的大米穗点云精准语义分割表型工具
Liang Gong,Xiaofeng Du,Kai Zhu et al.
Liang Gong et al.
The automated measurement of crop phenotypic parameters is of great significance to the quantitative study of crop growth. The segmentation and classification of crop point cloud help to realize the automation of crop phenotypic parameter m...