GSP-AI: An AI-Powered Platform for Identifying Key Growth Stages and the Vegetative-to-Reproductive Transition in Wheat Using Trilateral Drone Imagery and Meteorological Data [0.03%]
基于无人机和气象数据的AI平台：用于识别小麦生长关键阶段及营养生长向生殖生长转变的GSP-AI系统
Liyan Shen,Guohui Ding,Robert Jackson et al.
Liyan Shen et al.
Wheat (Triticum aestivum) is one of the most important staple crops worldwide. To ensure its global supply, the timing and duration of its growth cycle needs to be closely monitored in the field so that necessary crop management activities ...
MLG-YOLO: A Model for Real-Time Accurate Detection and Localization of Winter Jujube in Complex Structured Orchard Environments [0.03%]
一种冬枣果园复杂环境下的实时精确实例检测与定位模型MLG-YOLO
Chenhao Yu,Xiaoyi Shi,Wenkai Luo et al.
Chenhao Yu et al.
Our research focuses on winter jujube trees and is conducted in a greenhouse environment in a structured orchard to effectively control various growth conditions. The development of a robotic system for winter jujube harvesting is crucial f...
Fruit Water Stress Index of Apple Measured by Means of Temperature-Annotated 3D Point Cloud [0.03%]
基于温度标注三维点云的苹果树果实水分胁迫指标研究
Nikos Tsoulias,Arash Khosravi,Werner B Herppich et al.
Nikos Tsoulias et al.
In applied ecophysiological studies related to global warming and water scarcity, the water status of fruit is of increasing importance in the context of fresh food production. In the present work, a fruit water stress index (FWSI) is intro...
AFM-YOLOv8s: An Accurate, Fast, and Highly Robust Model for Detection of Sporangia of Plasmopara viticola with Various Morphological Variants [0.03%]
一种准确、快速且高度鲁棒的病原卵菌葡萄腔孢属孢子囊检测模型AFM-YOLOv8s
Changqing Yan,Zeyun Liang,Ling Yin et al.
Changqing Yan et al.
Monitoring spores is crucial for predicting and preventing fungal- or oomycete-induced diseases like grapevine downy mildew. However, manual spore or sporangium detection using microscopes is time-consuming and labor-intensive, often result...
Phenotyping Alfalfa (Medicago sativa L.) Root Structure Architecture via Integrating Confident Machine Learning with ResNet-18 [0.03%]
基于集成可信机器学习与ResNet-18表型技术鉴定紫花苜蓿根系结构特征
Brandon J Weihs,Zhou Tang,Zezhong Tian et al.
Brandon J Weihs et al.
Background: Root system architecture (RSA) is of growing interest in implementing plant improvements with belowground root traits. Modern computing technology applied to images offers new pathways forward to plant trait improvements and sel...
Auto-LIA: The Automated Vision-Based Leaf Inclination Angle Measurement System Improves Monitoring of Plant Physiology [0.03%]
自动叶片角度测量系统提升植物生理监测效力
Sijun Jiang,Xingcai Wu,Qi Wang et al.
Sijun Jiang et al.
Plant sensors are commonly used in agricultural production, landscaping, and other fields to monitor plant growth and environmental parameters. As an important basic parameter in plant monitoring, leaf inclination angle (LIA) not only influ...
Evaluating Neural Radiance Fields for 3D Plant Geometry Reconstruction in Field Conditions [0.03%]
基于神经辐射场的植物几何重建技术在野外条件下的评估研究
Muhammad Arbab Arshad,Talukder Jubery,James Afful et al.
Muhammad Arbab Arshad et al.
We evaluate different Neural Radiance Field (NeRF) techniques for the 3D reconstruction of plants in varied environments, from indoor settings to outdoor fields. Traditional methods usually fail to capture the complex geometric details of p...
High-Throughput Phenotyping of Soybean Biomass: Conventional Trait Estimation and Novel Latent Feature Extraction Using UAV Remote Sensing and Deep Learning Models [0.03%]
基于无人机遥感和深度学习模型的高通量大豆生物量表型分析：传统性状估计与新型潜在特征提取
Mashiro Okada,Clément Barras,Yusuke Toda et al.
Mashiro Okada et al.
High-throughput phenotyping serves as a framework to reduce chronological costs and accelerate breeding cycles. In this study, we developed models to estimate the phenotypes of biomass-related traits in soybean (Glycine max) using unmanned ...
What to Choose for Estimating Leaf Water Status-Spectral Reflectance or In vivo Chlorophyll Fluorescence? [0.03%]
选择叶水状态估算方法——光谱反射率还是原位叶绿素荧光？
Martina Špundová,Zuzana Kučerová,Vladimíra Nožková et al.
Martina Špundová et al.
In the context of global climate change and the increasing need to study plant response to drought, there is a demand for easily, rapidly, and remotely measurable parameters that sensitively reflect leaf water status. Parameters with this p...
MTSC-Net: A Semi-Supervised Counting Network for Estimating the Number of Slash pine New Shoots [0.03%]
半监督计数网络在刀桩新芽数量估计中的应用
Zhaoxu Zhang,Yanjie Li,Yue Cao et al.
Zhaoxu Zhang et al.
The new shoot density of slash pine serves as a vital indicator for assessing its growth and photosynthetic capacity, while the number of new shoots offers an intuitive reflection of this density. With deep learning methods becoming increas...