在有机种植下描述各种玉米品种:来自VIT Vellore的表型,产量和树冠数据
Sandhya Prakash1, Sujatha R2, Venkataramana B3
1Research Scholar, Data Science, Vellore Institute of Technology, Vellore, Tamil Nadu, India.
Data in brief
|March 7, 2025
概括
这项研究提出了一套新的玉米数据集,用于作物改进. 它包括八种玉米品种的表型,产量,树冠温度和叶绿素数据,有助于开发适应气候变化的基因型.
科学领域:
- 农业科学 农业科学
- 植物育种 植物育种
- 农业学是一种农业学.
背景情况:
- 玉米是全球重要的粮食来源和工业原料.
- 开发适应气候的玉米基因型对于持续的生产力至关重要.
- 评估品种表现是有效作物开发的关键.
研究的目的:
- 提供玉米表型和产量属性的综合数据集.
- 促进未来的玉米育种和改良研究.
- 支持开发用于作物分析的深度学习模型.
主要方法:
- 有机种植八种玉米品种 (四种IIMR,四种本地).
- 实验设计:随机块设计与四个复制.
- 数据收集:来自160种植物的表型特征,产量,树冠温度 (CT) 和叶绿素 (Ch) 读数.
主要成果:
- 创建了一个包含植物性特征,产量特征,树冠温度和叶绿素读数的数据集.
- 在场随机块设计 (FRBD) 中使用差异分析 (ANOVA) 的分析确定了显著的基因型差异.
- 收集的数据为玉米品种的比较分析提供了基础.
结论:
- 该数据集对于未来的玉米育种和作物改进研究具有价值.
- 它可以用于开发先进的预测模型,包括深度学习应用程序.
- 该资源支持开发更适应不同环境条件的玉米品种.
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