用于预测发芽的三角区模型 (TAM):加强热液时间模型应用的方法

IF 5.4 Q1 PLANT SCIENCES
Mostafa Oveisi , Hassan Alizadeh , Sassan A. Lorestani , Aboozar Esmaili , Nasrin Sadeghnejad , Ramin Piri , Jose L. Gonzalez-Andujar , Heinz Müller-Schärer
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TAM is characterized by its depiction of triangles, considering insightful parameters such as the distance of germination temperature (<em>T</em>) to the base (<em>T</em><sub><em>b</em></sub>), optimal (<em>T</em><sub><em>o</em></sub>), and ceiling (<em>T</em><sub><em>c</em></sub>) temperatures, the range of <em>T</em><sub><em>c</em></sub> – <em>T</em><sub><em>o</em></sub>, <em>T</em><sub><em>o</em></sub> – <em>T</em><sub><em>b</em></sub>, and the germination water potential (<em>Ψ</em>), i.e. mean base water potential (<em>Ψ</em><sub><em>b(g)</em></sub>), along with potential <em>g</em> that may occur with <em>T</em> and <em>Ψ</em> combinations within <em>T</em><sub><em>c</em></sub> – <em>T</em><sub><em>b</em></sub> when <em>Ψ &gt; Ψ</em><sub><em>b(g)</em></sub>. 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引用次数: 0

摘要

对水热时间模型假设的全面研究揭示了可提高模型性能的领域。我们引入了三角形面积模型(TAM),该模型利用直角三角形的面积来计算水热时间,从而预测种群发芽率(g)。三角形面积模型的特点是对三角形的描述,并考虑了一些有洞察力的参数,如发芽温度(T)到基底温度(Tb)、最佳温度(To)和最高温度(Tc)的距离,Tc - To、To - Tb 的范围,以及发芽水势(Ψ),即平均基底水势(Ψ)。即平均基本水势 (Ψb(g)),以及 Tc - Tb 范围内 T 和 Ψ 组合可能出现的水势 g(当 Ψ > Ψb(g)时)。将 TAM 应用于 Ambrosia psilostachya L.、Cynanchum acutum L. 和 Bidens pilosa L. 的发芽数据,A. psilostachya 和 C. acutum 的 RMSE 为 0.03,B. pilosa 为 0.05。此外,TAM 对相应物种的 R2 分别为 0.96、0.97 和 0.98。通过比较不同的 T 和 Ψ,TAM 明显优于早期的模型。TAM 确定了 A. psilostachya、C. acutum 和 B. pilosa 的 Tb 为 0.19、14.57 和 5.76 °C;To 为 25.1、39.9 和 29.8 °C;Tc 为 46.7、53 和 41 °C。它还估计 A. psilostachya 的 Ψb(g) 为-1.48,C. acutum 为-0.98,B. pilosa 为-0.97。TAM方法加深了我们对影响这三种外来入侵物种的植物生存、定殖和栖息地扩展的温度-水分过程的理解。此外,它还可以更广泛地应用于估算不同生长阶段的温度-湿度和 HTT,从而提高植物物候发展的预测准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Triangle area model (TAM) for predicting germination: An approach to enhance hydrothermal time model applications

A thorough examination of assumptions in hydrothermal time models revealed areas for enhancing model performance. We introduce the Triangle Area Model (TAM), which uses the area of right-angled triangles to calculate hydrothermal time for predicting population germination fractions (g). TAM is characterized by its depiction of triangles, considering insightful parameters such as the distance of germination temperature (T) to the base (Tb), optimal (To), and ceiling (Tc) temperatures, the range of TcTo, ToTb, and the germination water potential (Ψ), i.e. mean base water potential (Ψb(g)), along with potential g that may occur with T and Ψ combinations within TcTb when Ψ > Ψb(g). Applied to germination data from Ambrosia psilostachya L., Cynanchum acutum L., and Bidens pilosa L., TAM achieves an RMSE of 0.03 for A. psilostachya and C. acutum, and 0.05 for B. pilosa. Moreover, TAM demonstrates an R2 of 0.96, 0.97, and 0.98 for the respective species. TAM significantly outperforms earlier models through a comparison with varying T and Ψ. TAM determined Tb for A. psilostachya, C. acutum, and B. pilosa as 0.19, 14.57, and 5.76 °C; To as 25.1, 39.9, and 29.8 °C; and Tc as 46.7, 53, and 41°C, for the respective species. It also estimates Ψb(g) as -1.48 for A. psilostachya, -0.98 for C. acutum, and -0.97 for B. pilosa. The TAM approach deepens our understanding of temperature-moisture processes influencing plant survival, colonization, and habitat expansion for these three invasive alien species. Furthermore, it can be more widely applied for estimating TT and HTT across different growth stages, enhancing the prediction accuracy of plant phenological development.

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来源期刊
Current Plant Biology
Current Plant Biology Agricultural and Biological Sciences-Plant Science
CiteScore
10.90
自引率
1.90%
发文量
32
审稿时长
50 days
期刊介绍: Current Plant Biology aims to acknowledge and encourage interdisciplinary research in fundamental plant sciences with scope to address crop improvement, biodiversity, nutrition and human health. It publishes review articles, original research papers, method papers and short articles in plant research fields, such as systems biology, cell biology, genetics, epigenetics, mathematical modeling, signal transduction, plant-microbe interactions, synthetic biology, developmental biology, biochemistry, molecular biology, physiology, biotechnologies, bioinformatics and plant genomic resources.
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