Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Light Acquisition02:16

Light Acquisition

8.6K
In order to produce glucose, plants need to capture sufficient light energy. Many modern plants have evolved leaves specialized for light acquisition. Leaves can be only millimeters in width or tens of meters wide, depending on the environment. Due to competition for sunlight, evolution has driven the evolution of increasingly larger leaves and taller plants, to avoid shading by their neighbors with contaminant elaboration of root architecture and mechanisms to transport water and nutrients.
8.6K
Key Elements for Plant Nutrition02:35

Key Elements for Plant Nutrition

21.4K
Like all living organisms, plants require organic and inorganic nutrients to survive, reproduce, grow and maintain homeostasis. To identify nutrients that are essential for plant functioning, researchers have leveraged a technique called hydroponics. In hydroponic culture systems, plants are grown—without soil—in water-based solutions containing nutrients. At least 17 nutrients have been identified as essential elements required by plants. Plants acquire these elements from the...
21.4K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

A custom preservation solution extends the ex vivo availability of living heart valves for transplantation.

JTCVS open·2025
Same author

Line-YOLO: An Efficient Detection Algorithm for Power Line Angle.

Sensors (Basel, Switzerland)·2025
Same author

Public preferences and willingness to pay for environmental benefits of straw return: Empirical evidence from Northeast China.

Journal of environmental management·2024
Same author

Ecotourism and sustainable development: a scientometric review of global research trends.

Environment, development and sustainability·2022
Same author

Boron nitride-nanosheet enhanced cellulose nanofiber aerogel with excellent thermal management properties.

Carbohydrate polymers·2020
Same author

Oral Supplements of Combined <i>Bacillus licheniformis</i> Zhengchangsheng® and Xylooligosaccharides Improve High-Fat Diet-Induced Obesity and Modulate the Gut Microbiota in Rats.

BioMed research international·2020
Same journal

LSL-YOLO11n: a YOLO11n-based model for maize leaf disease detection in complex field environments.

Frontiers in plant science·2026
Same journal

Patterns of plastid gene evolution: identifying candidate genes for plastid-nuclear incompatibility across the Campanulaceae.

Frontiers in plant science·2026
Same journal

Assembly and comparative analysis of the complete mitochondrial genome of <i>Holmskioldia sanguinea</i>.

Frontiers in plant science·2026
Same journal

Genotypic resilience and fruit quality responses of tomato (<i>Solanum lycopersicum</i> L.) in progressive salinity stress across diverse cultivation conditions.

Frontiers in plant science·2026
Same journal

Growth history revealed by tree rings provides clues for the conservation of an endangered subtropical tree species.

Frontiers in plant science·2026
Same journal

Climate change reshapes habitat suitability of ancient tea trees in Yunnan: insights from an optimized MaxEnt model.

Frontiers in plant science·2026
查看所有相关文章

相关实验视频

Updated: Sep 12, 2025

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.6K

动态门增强的深度学习模型与多源远程传感协同作用,以优化小麦产量估计.

Jian Li1,2, Junrui Kang1,2, Jian Lu2,3

  • 1College of Information Technology, Jilin Agricultural University, Changchun, China.

Frontiers in plant science
|August 5, 2025
PubMed
概括
此摘要是机器生成的。

一个新的专家空间时间融合混合 (STF-MoE) 模型使用遥感和环境数据准确估计小麦产量. 这种深度学习方法提供了可靠的收获前预测,改善了作物管理策略.

关键词:
在 MoE 模块中.深度学习是一种深度学习.多源远程传感多源远程传感变压器的变压器是一个变压器.小麦产量估计小麦产量估计

更多相关视频

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
11:49

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images

Published on: February 2, 2019

9.4K
Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain
07:10

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Published on: March 13, 2020

10.2K

相关实验视频

Last Updated: Sep 12, 2025

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation
08:47

Author Spotlight: UAV Remote Sensing for Efficient Invasive Plant Biomass Estimation

Published on: February 9, 2024

1.6K
Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images
11:49

Cereal Crop Ear Counting in Field Conditions Using Zenithal RGB Images

Published on: February 2, 2019

9.4K
Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain
07:10

Untargeted Liquid Chromatography-Mass Spectrometry-Based Metabolomics Analysis of Wheat Grain

Published on: March 13, 2020

10.2K

科学领域:

  • 农业科学 农业科学
  • 遥感 遥感 遥感 遥感
  • 深度学习 (Deep Learning) 是一种深度学习.

背景情况:

  • 准确的小麦产量估计对于全球粮食安全和有效的农业管理至关重要.
  • 传统的方法经常与作物生长和环境因素的时空复杂性作斗争.

研究的目的:

  • 引入和评估专家空间时间融合混合 (STF-MoE) 模型,以精确估计小麦产量.
  • 为了提高预测准确性,利用多源遥感和环境数据.

主要方法:

  • 开发了一个基于LSTM-Transformer的深度学习框架,STF-MoE.
  • 整合了一个异质的专家组合 (MoE) 与一个自适应的门网.
  • 合并的遥感数据 (NIRv,Fpar) 和环境变量 (相对湿度,DEM) 用于产量预测.

主要成果:

  • 在最近的产量估计中获得了高精度 (R2 = 0.827,RMSE = 547.7 kg/ha).
  • 在历史数据和极端气候事件中表现出强的性能,表现优于基线模型.
  • 确定了相对湿度和DEM作为影响产量的关键因素,并启用了在收获前1-2个月的预估.

结论:

  • STF-MoE模型通过动态门和专家专业化有效地解决了时空数据的复杂性.
  • 该模型为预收割小麦产量估计提供了一个可扩展的解决方案,尽管极端产量地区存在挑战.
  • 未来的研究将专注于优化计算效率和整合更高分辨率的数据.