通过基因型和环境特征解,从情节级卫星图像提高产量预测
Anirudha A Powadi1, Talukder Z Jubery2, Michael Tross3
1Department of Electrical and Computer Engineering, Iowa State University, Ames, IA, United States.
Frontiers in plant science
|October 16, 2025
概括
使用一种新的深度学习方法 - - 复合自编码器 (CAE) 来改进准确的作物产量预测,将植物遗传学和环境因素从卫星图像中分离出来,从而增强精确农业.
科学领域:
- 农业科学 农业科学
- 计算机科学 计算机科学
- 遗传学 是一个遗传学.
背景情况:
- 准确的产量预测对于作物管理和资源分配至关重要.
- 目前的方法依赖于卫星植被指数 (VI) 和机器学习 (ML) 模型,如PCA和AE.
- 图片规模的产量预测在解开基因型和环境相互作用方面面临挑战.
研究的目的:
- 通过使用组合自动编码器 (CAE) 在地块规模上增强收获前产量预测.
- 改进从高分辨率卫星图像中分离基因型 (G) 和环境 (E) 特征.
- 为了更好地纳入基因型对环境 (GxE) 相互作用,以便更准确地预测产量.
主要方法:
- 利用了来自美国五个玉米带地区84种杂交玉米品种复制图片的4000张卫星图像的数据集.
- 应用了深度学习方法,组成自编码器 (CAE),以从图片级卫星数据中解脱G和E特征.
- 对传统的自动编码器 (AEs) 和植被指数 (VIs) 进行CAE性能评估,用于产量预测.
主要成果:
- 与传统的AE相比,CAE的早期收益率预测得到了提高,高达10%.
- 在各种增长阶段,CAE在收益率预测准确度方面表现比VI高9%.
- 在环境因素聚类方面,CAE获得了0.919的高轮得分,证明了有效的分离.
- 在预测未见的环境和基因型的产量方面,CAE表现出卓越的表现,这表明它具有很强的概括性.
结论:
- 组合自编码器 (CAE) 通过有效地解开基因型和环境影响,在图片规模的产量预测方面取得了重大进展.
- 该CAE模型能够更准确地预测早期收益率,并更好地建模GxE相互作用.
- 这种方法支持精准农业的知情决策,并加速了植物育种计划.
相关概念视频
02:27Background and Environment Affect Phenotype
7.4K
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...
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...
7.4K
02:16Light Acquisition
9.4K
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.
9.4K
01:25Multiple Regression
3.7K
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...
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...
3.7K