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一个层次模型,用天气数据和芽动态来预测基维果的开花时间

Jingjing Zhang¹, Maryam Alavi¹, Lindy Guo¹

¹The New Zealand Institute for Plant and Food Research Limited, Private Bag 92169, Auckland 1142, New Zealand.

Plants (Basel, Switzerland)

|August 29, 2024

概括

预测果的开花时间对于果园管理至关重要. 这项研究开发了一种使用芽和生长度日 (GDD) 准确预测开花的模型,有助于害虫控制和授粉.

科学领域:

园艺园艺园艺园艺
植物现象学植物现象学
农业气象农业气象学

背景情况:

准确预测果的开花时间对于有效的果园管理至关重要,包括害虫控制和授粉.
目前的方法可能缺乏精度,需要改进的预测工具.

研究的目的:

开发和评估一个预测模型,预测果的开花时间.
整合气候数据和现象学观测,以提高预测准确度.

主要方法:

利用来自"海沃德"和"Zesy002"果研究的历史数据 (2007-2022年).
分析了芽和开花时间,与累积热量总和 (增长度日,GDD) 和冷却单位 (CU) 相比.
使用气象站数据开发和验证回归模型.

主要成果:

确定了一个层次模型结构,其中芽时的GDD积累是开花时间的关键预测因素.
该模型在使用综合气候和现象学数据预测开花时间方面表现出有效性.
2020-2022年的验证数据证实了该模型的预测能力.

结论:

将气候数据与芽等现象学事件相结合,显著提高了果开花时间的可预测性.
开发的模型是优化基维果园管理实践的宝贵工具.
这种方法支持对疾病控制,害虫管理和授粉的及时干预.

关键词:

布德布雷克 (Budbreak) 是一个关于芽的故事.气候变化气候变化气候变化花开的时候,花开的时候.果种植品种是果的种植品种.果园管理果园管理植物现象学植物现象学预测建模预测建模热量要求热量要求

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