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相关概念视频

Gene-Environment Interactions01:20

Gene-Environment Interactions

1.1K
Gene expression is a dynamic process that is significantly influenced by environmental factors. This interaction underlies the complex nature of biological development and the phenotypic differences observed among individuals, even among those with identical genetic makeups. Factors such as radiation, temperature, behavior, nutrition, and stress play pivotal roles in determining how genes are expressed. The concept of the reaction range is central to understanding this interaction. It posits...
1.1K
Background and Environment Affect Phenotype02:27

Background and Environment Affect Phenotype

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Although the genetic makeup of an organism plays a major role in determining the phenotype, there are also several environmental factors, such as temperature, oxygen availability, presence of mutagens, that can alter an organism’s phenotype.
An example of how genetic background affects phenotype can be seen in horses. The Extension gene in horses is responsible for their coat color. A wild-type gene (EE) produces black pigment in the coat, while a mutant gene (ee) produces red pigment. A...
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Light Acquisition02:16

Light Acquisition

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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.
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Multiple Regression01:25

Multiple Regression

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Multiple regression assesses a linear relationship between one response or dependent variable and two or more independent variables. It has many practical applications.
Farmers can use multiple regression to determine the crop yield based on more than one factor, such as water availability, fertilizer, soil properties, etc. Here, the crop yield is the response or dependent variable as it depends on the other independent variables. The analysis requires the construction of a scatter plot...
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Plant Breeding and Biotechnology01:59

Plant Breeding and Biotechnology

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Crop cultivation has a long history in human civilization, with records showing the cultivation of cereal plants beginning at around 8000 BC. This early plant breeding was developed primarily to provide a steady supply of food.
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相关实验视频

Updated: Jan 12, 2026

A Telemetric, Gravimetric Platform for Real-Time Physiological Phenotyping of Plant–Environment Interactions
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在普通豆多环境试验中增强基于环境学的预测.

Gabriel M Blasques1, Luiz A S Dias1, Mauricio S Araújo2

  • 1Department of Agronomy, Federal University of Viçosa, Viçosa, Minas Gerais, Brazil.

Scientific reports
|October 31, 2025
PubMed
概括

这项研究改进了使用机器学习进行更好的基因型预测的GIS-FA方法. 改进的方法提高了在各种环境中预测工厂性能的准确性.

关键词:
这是一种因子分析学.根据GIS-FA方法进行分析.基因型与环境的相互作用.多环境试验多环境试验品种建议 品种建议

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High-Throughput, In-Field Screening of Photosynthetic Efficiency in Crop Plants Using an Autonomous Robot
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Plant Promoter Analysis: Identification and Characterization of Root Nodule Specific Promoter in the Common Bean
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Plant Promoter Analysis: Identification and Characterization of Root Nodule Specific Promoter in the Common Bean

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相关实验视频

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科学领域:

  • 植物育种 植物育种
  • 遗传学 是一个遗传学.
  • 农业科学 农业科学

背景情况:

  • 环境学方法将环境数据整合到预测模型中.
  • 地理信息系统因素分析 (GIS-FA) 方法改善了新环境中的基因型预测.
  • 改进GIS-FA可以提高环境特征和预测准确度.

研究的目的:

  • 通过随机森林空间互叠和优化空间采样来改进GIS-FA方法.
  • 加强环境数据的插值和表征,以便更好地预测基因型.
  • 在巴西各地的普通豆试验中评估改进的GIS-FA框架.

主要方法:

  • 实现环境数据的随机森林空间插值.
  • 优化了空间抽样,以排除非农业地区.
  • 将增强的GIS-FA框架应用于普通豆试验 (59个基因型,23个环境).

主要成果:

  • 经验最佳线性无偏预测 (eBLUPs) 的准确度从0.46提高到0.53 (15.2%的改善).
  • 在未经测试的环境中实现可靠的基因型性能预测.
  • 通过使用高分辨率主题地图,在整个圣保罗促进了基因型建议.

结论:

  • 精细的GIS-FA方法显著提高了基因型预测的准确性和可靠性.
  • 整合机器学习插值和空间优化增强了GIS-FA的潜力.
  • 这种方法支持植物育种中环境知情的选择策略.