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在水培温室中预测番茄的水消耗:光拦截模型的贡献

Konstantinos Florakis^1,2, Samis Trevezas¹, Véronique Letort²

¹Department of Mathematics, National and Kapodistrian University of Athens, Athens, Greece.

Frontiers in plant science

|December 13, 2023

概括

水培温室种植需要精确的灌. 这项研究引入了使用气象数据和作物生长原理的新模型,以预测用水量,改善资源管理.

科学领域:

农业工程农业工程
植物生理学植物生理学
环境科学环境科学

背景情况:

水培温室种植提供了高效的资源使用和全年生长.
精确的灌管理对于最佳产量和节水至关重要.
数据驱动的水消耗预测模型面临着有限数据集的挑战.

研究的目的:

开发可靠的模型来预测水培温室日常用水量.
探索作物模型概念的整合,以提高预测准确度,特别是在有限的数据.
使用易于获得的气象数据和水消耗记录.

主要方法:

开发了两种策略:一种是使用绿色实验室模型与重新估计的参数,另一种是提出基于输入能源的随机细分 (SSiE) 的新方法.
模型使用最大概率方法进行调整.
使用每日吸水量数据,对番茄 (狂喜) 进行了概念验证.

主要成果:

该研究展示了一种方法来估计植物中拦截光线的动态模式.
这种估计有助于预测水消耗.
开发的SSiE模型显示了从常规温室测量中有效提取作物信息的潜力.

结论:

新的SSiE模型为改善水培温室灌管理提供了一个有希望的方法.
这些模型可以增强水资源经济和作物产量预测.
为了更广泛的应用,建议进行进一步的开发和测试.

关键词:

酒 - 兰伯特定律绿色实验室的模型 MLE MLE MLE MLE MLE MLE MLE MLE MLE MLE MLE MLE MLE MLE MLE MLE MLE MLE 随机分类输入的细分能源能量温室的温室效应是什么温室效应是什么截获光线的拦截方式水的消耗水的消耗.

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Light Acquisition

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