在木果 (Feronia limonia L.) 中进行形态特征分析和基于机器学习的产量建模
Vikas Yadav1, Daya Shankar Mishra2, Jagadish Rane3
1ICAR-Central Horticultural Experiment Station, Gujarat, 389340, Vejalpur, Panchmahals, India.
BMC plant biology
|December 28, 2025
概括
木果产量是由树形状,花朵和果皮特征的组合决定的. 选择具有紧的树冠和理想的水果特征的基因型可以提高生产力和果园效率.
科学领域:
- 园艺园艺 园艺园艺
- 植物育种 植物育种
- 农业科学 农业科学
背景情况:
- 木果是印度次大陆的一个未充分利用但重要的果树.
- 它作为一种适应气候变化的作物的潜力很高,但产量决定因素尚未得到充分理解.
- 这项研究解决了木果产量变化的知识差距.
研究的目的:
- 量化树冠建筑,花和水果特征的形态描述符如何解释木果的产量变化.
- 开发一个数据驱动的框架来识别影响生产力的特征组合.
- 为意识形态选择和精确果园设计提供见解.
主要方法:
- 利用多变量统计和可解释的机器学习模型 (随机森林+SHAP).
- 分析了62种木果基因型的形态变异性.
- 综合主要组件分析 (PCA),相关性分析和层次聚类.
主要成果:
- 在基因型之间观察到显著的形态变异性.
- 随机森林模型实现了高预测性能 (R2 = 0.84).
- 产量的关键预测因素包括树的形状,开放的花的颜色和纸的颜色;紧的树冠和优越的繁殖特征导致了更高的产量.
结论:
- 木制果的产量是由一组集成的建筑和生殖特征所决定的.
- 具有紧的树冠和首选的纸特征的基因型有望实现高生产率.
- 可解释的机器学习工具为基于特征的育种和气候智能果园设计提供了强大的框架.
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