ArticlePlants (Basel, Switzerland)2022
The Modified Brière Equation and Its Applications.
Article in Plants (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- A flexible model for thermal performance curves.Ecology · 2026Article
- Modeling the Effects of Temperature and Resource Quality on the Outcome of Competition Between Aedes aegypti and Aedes albopictus and the Resulting Risk of Vector-Borne Disease.Bulletin of mathematical biology · 2025Article
- Effect of temperature on in vitro germination and growth of Colletotrichum fioriniae, a new emerging pathogen of olive fruits.Environmental microbiology reports · 2024Article
- Comparison of four performance models in quantifying the inequality of leaf and fruit size distribution.Ecology and evolution · 2024Article
- Plant Morphology and Function, Geometric Morphometrics, and Modelling: Decoding the Mathematical Secrets of Plants.Plants (Basel, Switzerland) · 2023Article
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3 authors.
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Abstract
The Brière equation (BE) is widely used to describe the effect of temperature on the development rate of insects, and it can produce both symmetrical and asymmetrical bell-shaped curves. Because of its elasticity in curve fitting, the integrated form of BE has been recommended for use as a sigmoid growth equation to describe the increase in plant biomass with time. However, the start time of growth predicted by the sigmoid growth equation based on the BE is not completely comparable to empirical crop growth data. In the present study, we modified the BE by adding an additional parameter to further increase its elasticity for data fitting. We termed this new equation the modified Brière equation (MBE). Data for the actual height and biomass of 15 species of plants (with two cultivars for one species) were fit with the sigmoid growth equations based on both the BE and MBE assuming that the growth start time was zero for both. The goodness of fit of the BE and MBE sigmoid growth equations were compared based on their root-mean-square errors and the corresponding absolute percentage error between them when fit to these data. For most species, we found that the MBE sigmoid growth equation achieved a better goodness of fit than the BE sigmoid growth equation. This work provides a useful tool for quantifying the ontogenetic or population growth of plants.
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