Predicting height growth in bean plants using non-linear and polynomial models

Frühauf, Ariana Campos; Silva, Edilson Marcelino; Fernandes, Tales Jesus; Muniz, Joel Augusto

doi:10.18406/2316-1817v13n320211625

Cited by 4 publications

(2 citation statements)

References 16 publications

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“…Para verificar os pressupostos dos modelos de regressão foram feitos os testes: Shapiro-Wilk, para verificar o pressuposto de normalidade dos erros; Breusch-Pagan, para verificar a hipótese de que os erros são homocedásticos e o teste de Durbin-Watson, para verificar a independência dos erros. Quando o teste de Durbin-Watson rejeitou a hipótese nula de que os erros experimentais foram independentes, os erros do modelo foram considerados da seguinte maneira: u i = ϕ 1 u i-1 + ε i , em que ϕ 1 é o parâmetro de autocorrelação de primeira ordem AR(1) e ε i é o ruído branco (FRUHAUF, et al, 2022;JANE, et al, 2020b;MORETTIN;TOLOI, 2006) ii. Desvio-padrão residual, DPR: iii.…”

Section: Methodsunclassified

Comparison of nonlinear models for the description of carbon mineralization in degraded pasture soil and in soils with plant cover

Vilela

Silva

Frühauf

et al. 2022

R. Agrogeoambiental

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Tree planting is an important way to restore degraded areas, however, the quality of the plant residue added to the soil influences the organic matter decomposition rate and, consequently, carbon availability. Carbon mineralization curves over time make it possible to understand the decomposition of organic residues and improve soil management. Nonlinear regression models have been used to describe the dynamics of carbon mineralization over time, as they summarize the information contained in the data in just a few parameters with practical interpretations. Thus, this study aimed at evaluating the nonlinear models Cabrera, Juma and Stanford & Smith to describe the soil carbon mineralization in the following plantations: Secondary forest, Acacia auriculiformis, Mimosa caesalpiniifolia and Pasture, obtained from the first to the twentieth week. All the computational part involved in the adjustments and analyses was performed using the R statistical software. The most suitable regression model was selected for the description of soil carbon mineralization for each vegetation cover based on the following criteria: adjusted coefficient of determination (R2adj), residual standard deviation (RSD) and Akaike information criterion (AIC). For Acacia, the Cabrera model was indicated as the best to describe this treatment. For Forest and Pasture, the Juma model had the best fit, and the Stanford & Smith model best described the Mimosa treatment.

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Section: Methodsunclassified

Comparison of nonlinear models for the description of carbon mineralization in degraded pasture soil and in soils with plant cover

Vilela

Silva

Frühauf

et al. 2022

R. Agrogeoambiental

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“…The Logistics equation of time to plant height increment was fitted with DPS data processing system for seedling growth curve. Here, the growth curves correlate the seedling height to the cultivated time according to Logistics equation, Y = K/(1 + e a−bt ) [45], and the components of the equation are as follows:…”

Section: Data Statistics and Analysismentioning

confidence: 99%

Endogenous Phytohormone and Transcriptome Analysis Provided Insights into Seedling Height Growth of Pinus yunnanensis

Lu,

Wang,

Yang

et al. 2024

Forests

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Plant height plays a crucial role in both the structure and quality of plants. Pinus yunnanensis is a distinctive species of the forest found in Southwest China, where the height of the plants significantly influences both yield performance and plant architecture. Although the phenotypes of P. yunnanensis seedlings with different plant heights were quite different at their seedling stage, the molecular mechanisms controlling the seedling differentiation remain poorly understood. This study is aimed to investigate the underlying mechanisms of P. yunnanensis seedling differentiation using phenotypic, transcriptomic, and endogenous phytohormone analyses. The P. yunnanensis seedlings were categorized into three grades, i.e., Grades A, B, and C, by mean ± 1/2 standard deviation method (H ± 1/2σ), and the seedling height and ground diameter were measured. We conducted the measurements of endogenous hormone levels in the young shoot apexes of seedlings at different grades during the fast-growth period (March). The DEGs were identified through transcriptome sequencing and analyzed by qRT-PCR validation. Significant differences were observed in the content and ratio of endogenous phytohormones among various grades of P. yunnanensis seedlings (p < 0.05). The ABA content in Grade A was prominently more than that in Grades B and C, and the order of the content of auxins was Grade B > C > A. Furthermore, when compared to Grade A, the ratios of auxins/CTKs, auxins/ABA, CTKs/ABA, and (auxins + CTKs)/ABA exhibited significant increases in Grades B and C. Moreover, GO functional annotation analysis indicated the more pronounced enrichment of DEGs in molecular functions. KEGG metabolic pathway analysis revealed notable differences in enrichment pathways between the pairwise comparisons. The “plant hormone signal transduction” pathway exhibited enrichment in the two groups, followed by “plant–pathogen interaction” pathway in the organism system that was enriched in the three groups. In addition, the results for endogenous phytohormone metabolism pathways indicate a significant up-regulation in the expression of AUX1, while AHP and PP2C exhibited significant down-regulation. To sum up, we aimed at investigating the underlying mechanisms of P. yunnanensis seedling differentiation using phenotypic, transcriptomic, and endogenous phytohormone analyses. The results suggested that individual phytohormones have a limited capacity to regulate gene expression, and seedling differentiation results from the combined regulation of multiple hormones. In addition, several candidate genes associated with phytohormone biosynthesis and signal transduction pathways were identified, including AUX1, GH3, AHP, B-ARR, PP2C, etc., which provided candidate genes for the following hormone-related gene overexpression and knockout experiments. These findings provide insights into the molecular genetic control of seedling height growth of P. yunnanensis.

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Uso dos modelos von Bertalanffy e Logístico na descrição do acúmulo de massa seca das plantas daninhas Amaranthus retroflexus e Amaranthus hybridus

Azarias,

Gonzaga,

Machado

et al. 2023

Rev. Foco

Self Cite

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As plantas daninhas são motivo de preocupação aos agricultores, pois infestam áreas agrícolas e podem causar grandes prejuízos, por demandarem gastos com métodos de controle, além de poderem prejudicar a produção. Estudar o crescimento desse tipo de planta permite o conhecimento em relação seu comportamento no ambiente em que se desenvolve e pode auxiliar no desenvolvimento de formas adequadas e sustentáveis de manejo. Neste sentido os modelos não lineares Logístico e von Bertalanffy foram ajustados, por meio do software R, para as variáveis massa seca nos ramos e massa seca total das espécies Amaranthus retroflexus e Amaranthus hybridus, as avaliações foram aos 20, 30, 40, 50, 60, 70, 80, 90 dias após a semeadura. Avaliou-se qual é o melhor modelo para descrever o crescimento das espécies. Os dois modelos se ajustaram adequadamente aos dados, porém de acordo com os avaliadores de qualidade utilizados, o modelo Logístico apresentou-se melhor para as duas espécies. Para a massa seca nos ramos os parâmetros dos modelos não diferiram. Em relação a massa seca total a espécie A. retroflexus apresentou ponto de inflexão anterior. A espécie A. hybridus apresentou maior acúmulo de massa seca total.

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Predicting height growth in bean plants using non-linear and polynomial models

Cited by 4 publications

References 16 publications

Comparison of nonlinear models for the description of carbon mineralization in degraded pasture soil and in soils with plant cover

Comparison of nonlinear models for the description of carbon mineralization in degraded pasture soil and in soils with plant cover

Endogenous Phytohormone and Transcriptome Analysis Provided Insights into Seedling Height Growth of Pinus yunnanensis

Uso dos modelos von Bertalanffy e Logístico na descrição do acúmulo de massa seca das plantas daninhas Amaranthus retroflexus e Amaranthus hybridus

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