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相关概念视频

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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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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Trihybrid Crosses

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Trihybrid Crosses
Some of Mendel’s crosses examined three pairs of contrasting characteristics. Such a cross is called a trihybrid cross. A trihybrid cross is a combination of three individual monohybrid crosses. For example, plant height (tall vs. short), seed shape (round vs. wrinkled), and seed color (yellow vs. green).
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Overview
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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.
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Plant Tissue Culture

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Plant tissue culture is widely used in both primary and applied science. Applications range from plant development studies to functional gene studies, crop improvement, commercial micropropagation, virus elimination, and conservation of rare species.
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相关实验视频

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Author Spotlight: Streamlining Rice Breeding with CRISPR/Cas for Obtaining Optimal Phenotypic and Agronomic Traits
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通过使用多环境试验育种数据优化基因型特定参数来评估麻瓜作物生长模型.

Pamelas M Okoma1, Siraj Ismail Kayondo2, Ismail Y Rabbi2

  • 1Plant Breeding and Genetics Section, School of Integrative Plant Science, College of Agriculture and Life Sciences, Cornell University, Ithaca, NY, United States.

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概括

为尼日利亚麻种植的作物生长模型 (CGM) 校准改善了产量预测. 该模型显示了偏差,低估了干燥条件下的产量,高估了潮湿条件下的产量.

关键词:
尼日利亚 尼日利亚 尼日利亚校准校准的时间麻豆 - 麻豆是一种麻豆.农作物生长模型的作物生长模型一般概率不确定性估计估计.

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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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科学领域:

  • 农业科学 农业科学
  • 植物育种 植物育种
  • 计算生物学 计算生物学

背景情况:

  • 大麻 (Manihot esculenta) 对于撒哈拉以南非洲的粮食安全至关重要.
  • 农作物生长模型 (CGM) 通过预测各种环境和未来气候的表现来帮助繁殖.

研究的目的:

  • 评估大规模CGM校准在麻育种计划中的可行性.
  • 在CROPGRO-MANIHOT-Cassava模型中识别系统偏差.

主要方法:

  • 参数化了CROPGRO-MANIHOT-Cassava模型,使用了尼日利亚八个地点 (2017-2020) 的67个克隆的数据.
  • 采用试错调整和一般概率不确定性估计 (GLUE) 方法进行校准.
  • 使用皮尔森相关性,根平均平方误差 (RMSE) 和d统计评估模型性能.

主要成果:

  • 在校准后,相关性从 -0.03 改善到 +0.08,RMSE 从 21 t ha-1 减少到 5 t ha-1,d 从 0.23 增加到 0.44.
  • 该模型低估了干燥,炎热环境中的根产量.
  • 该模型高估了在潮湿,凉爽环境中的根产量.

结论:

  • CGM校准可以整合到常规麻豆育种数据分析中.
  • 有机会对CROPGRO-MANIHOT-Cassava模型进行改进,以提高预测准确度.