Automated 3D Segmentation of Plant Organs via the Plant-MAE: A Self-Supervised Learning Framework [0.03%]
基于Plant-MAE的植物器官自动化三维分割：自监督学习框架
Kai Xie,Chenxi Cui,Xue Jiang et al.
Kai Xie et al.
Reliable and automated three-dimensional segmentation of plant organs is essential for extracting phenotypic traits at the organ level. However, existing methods for plant organ segmentation predominantly rely on fully supervised learning, ...
Shuo Zhou,Qixin Sun,Ning Zhang et al.
Shuo Zhou et al.
Noninvasive analysis of pod phenotypic traits under field conditions is crucial for soybean breeding research. However, previous pod phenotyping studies focused on postharvest materials or were limited to indoor scenarios, failing to genera...
Boosting leaf trait estimation from reflectance spectra by elucidating the transferability of PLSR models [0.03%]
揭示PLSR模型的可转移性以增强从反射光谱估计叶片性状的能力
Jiatong Wang,Xiaoqiang Liu,Xiaotian Qi et al.
Jiatong Wang et al.
Leaf spectroscopy, combined with partial least squares regression (PLSR), is recognized as an efficient and precise tool for measuring plant leaf traits. However, the feasibility of developing a generalizable model remains unclear, primaril...
A scalable and efficient UAV-based pipeline and deep learning framework for phenotyping sorghum panicle morphology from point clouds [0.03%]
一种可扩展高效的基于无人机的管道和深度学习框架 从点云中表型高丹草穗形态学
Chrisbin James,Shekhar S Chandra,Scott C Chapman
Chrisbin James
Sorghum canopy architecture in field trials is determined by various phenotypic traits, such plant and panicle count, leaf density and angle and panicle morphology, and canopy height. These traits together affect light capture and biomass p...
Design and implementation of a high-throughput field phenotyping robot for acquiring multisensor data in wheat [0.03%]
一种用于小麦多传感器数据采集的高通量田间表型机器人设计与实现
Miao Su,Dong Zhou,Yaze Yun et al.
Miao Su et al.
Ensuring food security has become a global challenge owing to climate change and population growth. High-throughput phenotyping can effectively drive crop genetic enhancement, which can potentially solve food crisis. Phenotyping robot is an...
High-Throughput Field Phenotyping Using Unmanned Aerial Vehicles (UAVs) for Rapid Estimation of Photosynthetic Traits [0.03%]
基于无人驾驶飞机（UAV）的高通量田间表型技术在快速估计光合特性中的应用
Jingshan Lu,Qimo Qi,Gangjun Zheng et al.
Jingshan Lu et al.
Efficient measurement of photosynthetic traits, such as the maximum carboxylation rate of Rubisco (Vcmax) and electron transport rate (Jmax), is essential for advancing research and breeding aimed at enhancing crop productivity. Traditional...
FreezeNet: A Lightweight Model for Enhancing Freeze Tolerance Assessment and Genetic Analysis in Wheat [0.03%]
冻敏感性评估和遗传分析的轻量级模型FreezeNet在小麦中的构建及应用研究
Fujun Sun,Mou Yin,Shusong Zheng et al.
Fujun Sun et al.
Freeze injury during the seedling stage significantly impacts wheat growth and yield, making the development of freeze-tolerant varieties crucial for ensuring stable yields. To identify key genetic factors for wheat freeze tolerance, an acc...
Location-guided lesions representation learning via image generation for assessing plant leaf diseases severity [0.03%]
基于图像生成的定位指导病征表型学习用于评估植物叶部病害病情分级
Ya Yu,Xingcai Wu,Peijia Yu et al.
Ya Yu et al.
Accurate assessment of plant leaf disease severity is crucial for implementing precision pesticide application, which in turn significantly enhances crop yields. Previous methods primarily rely on global perceptual learning, often leading t...
PhenoGazer: A high-throughput phenotyping system to track plant stress responses using hyperspectral reflectance, nighttime chlorophyll fluorescence and RGB imaging in controlled environments [0.03%]
基于高光谱反射、夜间叶绿素荧光和RGB成像的控制环境下植物逆境响应表型组学分析系统
Muhammad Adeel Hassan,Christine Yao-Yun Chang
Muhammad Adeel Hassan
High throughput phenotyping for crop monitoring at both leaf and canopy scales is essential for understanding plant responses to various stresses. PhenoGazer, a high-throughput phenotyping system, enhances crop monitoring in controlled envi...
RGB imaging and computer vision-based approaches for identifying spike number loci for wheat [0.03%]
基于RGB成像和计算机视觉的 wheat 小穗识别方法及应用研究
Lei Li,Muhammad Adeel Hassan,Duoxia Wang et al.
Lei Li et al.
The spike number (SN) is an important trait that significantly impacts grain yield in wheat. Manual counting of SN is time-consuming, hindering large-scale breeding efforts. Hence, there is an urgent need to develop efficient and accurate m...