产量潜力的高分辨率全球地图,对有针对性的作物生产改进具有当地相关性
Fernando Aramburu-Merlos1,2, Marloes P van Loon3, Martin K van Ittersum3
1Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE, USA.
Nature food
|July 29, 2024
概括
这项研究利用机器学习绘制了玉米,小麦和大米的全球作物产量潜力. 这些高分辨率地图揭示了全球增加粮食生产的尚未开发的机会.
科学领域:
- 农业科学 农业科学
- 机器学习应用 机器学习应用
- 全球粮食安全 全球粮食安全
背景情况:
- 提高作物生产对于全球粮食供应至关重要.
- 目前用于评估收益率潜力的方法存在局限性.
- 识别尚未开发的生产机会需要准确的数据.
研究的目的:
- 创建玉米,小麦和大米产量潜力的高分辨率全球地图.
- 为了提供一个可靠的参考,用于对比农民的产量.
- 确定有显著产量增长潜力的地区.
主要方法:
- 整合了一个农业学上强大的自下而上的方法.
- 利用了机器学习算法.
- 产生的高分辨率 (大约. 1公里2) 的全球地图.
主要成果:
- 为关键作物开发了准确的全球产量潜在地图.
- 建立了当前农民产量的基准.
- 突出地区具有大幅度的产量改善潜力.
结论:
- 生成的地图对于指导粮食可用性干预措施至关重要.
- 这种方法确定了在全球范围内增加作物产量的重大机会.
- 准确的产量潜力测绘支持可持续的农业发展.
相关概念视频
02:16Light Acquisition
8.4K
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.
8.4K
01:59Plant Breeding and Biotechnology
18.9K
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.
18.9K
01:25Multiple Regression
3.0K
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...
3.0K