Utilising artificial intelligence for cultivating decorative plants.

IF 3.4 3区生物学 Q1 Agricultural and Biological Sciences

Botanical Studies Pub Date : 2024-12-19 DOI:10.1186/s40529-024-00445-9

Nurdana Salybekova, Gani Issayev, Aikerim Serzhanova, Valery Mikhailov

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引用次数: 0

Abstract

Background: The research aims to assess the effectiveness of artificial intelligence models in predicting the risk level in tulip greenhouses using different varieties. The study was conducted in 2022 in the Almaty region, Panfilov village.

Results: Two groups of 10 greenhouses each (area 200 m2) were compared: the control group used standard monitoring methods, while the experimental group employed AI-based monitoring. We applied ANOVA, regression analysis, Bootstrap, and correlation analysis to evaluate the impact of factors on the risk level. The results demonstrate a statistically significant reduction in the risk level in the experimental group, where artificial intelligence models were employed, especially the recurrent neural network "Expert-Pro." A comparison of different tulip varieties revealed differences in their susceptibility to risks. The results provide an opportunity for more effective risk management in greenhouse cultivation.

Conclusions: The high accuracy and sensitivity exhibited by the "Expert-Pro" model underscore its potential to enhance the productivity and resilience of crops. The research findings justify the theoretical significance of applying artificial intelligence in agriculture and its practical applicability for improving risk management efficiency in greenhouse cultivation conditions.

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利用人工智能培育装饰性植物。

背景：本研究旨在评估人工智能模型在不同品种郁金香大棚风险水平预测中的有效性。该研究于2022年在阿拉木图地区的潘菲洛夫村进行。结果：对比两组，每组10个温室（面积200 m2），对照组采用标准监测方法，试验组采用人工智能监测方法。我们采用方差分析、回归分析、Bootstrap和相关分析来评估各因素对风险水平的影响。结果显示，在使用人工智能模型，特别是循环神经网络“Expert-Pro”的实验组中，风险水平在统计上显着降低。不同郁金香品种的比较揭示了它们对风险的易感性的差异。研究结果为更有效地进行温室栽培风险管理提供了契机。结论：“Expert-Pro”模型具有较高的准确性和敏感性，具有提高作物生产力和抗灾能力的潜力。研究结果验证了人工智能应用于农业的理论意义及其在提高温室栽培条件下风险管理效率方面的实际适用性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Botanical Studies 生物-植物科学

CiteScore

5.50

自引率

2.90%

发文量

审稿时长

2.4 months

期刊介绍： Botanical Studies is an open access journal that encompasses all aspects of botany, including but not limited to taxonomy, morphology, development, genetics, evolution, reproduction, systematics, and biodiversity of all plant groups, algae, and fungi. The journal is affiliated with the Institute of Plant and Microbial Biology, Academia Sinica, Taiwan.