MODELOS MATEMÁTICOS PARA DESCRIBIR CRECIMIENTOS DOBLE SIGMOIDEOS EN FRUTOS DE UN NECTARIN TARDIO (c.v. Sun Grand)

Álvarez, Adriana; Boche, Simon

doi:10.4206/agrosur.1999.v27n1-03

Cited by 12 publications

(5 citation statements)

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“…The emergence, physiological maturity and senescence phases are clearly observed in Fig 4 for irrigation treatments and planting date. These results are similar to those obtained in other studies, which shows that this type of adjustment is a good descriptor of the growth evolution of a plant [ 52 , 53 , 54 , 55 ].…”

Section: Discussionsupporting

confidence: 91%

“…The method used to estimate the dry matter accumulation or aerial biomass as functions of time and chia phenology is based on fitting the biomass accumulation data (BIOM) using a double logistic function [ 51 , 52 , 53 , 54 ]in the growth cycle. This method is very useful when one needs to represent the complete crop cycle quantitatively from emergence to senescence.…”

Section: Methodsmentioning

confidence: 99%

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Effect of sowing date and water availability on growth of plants of chia (Salvia hispanica L) established in Chile

Silva¹,

Arriagada²,

Campos-Saez³

et al. 2018

PLoS ONE

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From 2010 to 2014 two trials were performed to assess the effect of sowing date (SD1, SD2) and irrigation treatments (IT1, IT2) on the growth of chia in central Chile, measuring leaf area (LA) and dry matter (DM) as primary parameters and relative growth rate (RGR), net assimilation rate (NAR), leaf weight ratio (LWR), crop growth rate (CGR) and specific leaf weight (SLW) as secondary parameters. Both LA and DM reached maximum values between 640 and 1150 accumulated degree days (ADD). However, LA and DM were 25% greater for sowing dates than for available water. Flowering date was also not affected by sowing date or water availability; plants flowered at 1140 and 942 ADD in SD1 and SD2 respectively, and at 499 ADD in the water availability trial. Sowing date had a significant effect on RGR 0.15 g g-1 d-1 for SD1 and 0.12 g g-1 d-1 for SD2 at 410 ADD. Greater water availability increased RGR by 60% compared to stressed plants, however NAR was similar between sowing dates with a tendency to greater values in SD2 plants; maximum values were recorded at 514 ADD in IT1 and IT2, with a tendency toward higher values in IT1. Thus, the primary growth variables LA, DM and flowering are genetically determined. However, the derived growth variables RGR, LWR, NAR, CGR and SLW were affected by sowing date and water availability, with significant differences at p≤ 0.05. The results showed that the sowing date and water availability influence significantly the growth parameters. The physiological component (NAR) show a strong influence on the growth rate of the chia (RGR), above the morphological component (SLW and LAR).

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Section: Discussionsupporting

confidence: 91%

Section: Methodsmentioning

confidence: 99%

Effect of sowing date and water availability on growth of plants of chia (Salvia hispanica L) established in Chile

Silva¹,

Arriagada²,

Campos-Saez³

et al. 2018

PLoS ONE

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“…This behavior makes the biometric measurements of fruits to present the shape of a double "S" over time, with characteristics of a curve with two sigmoids (COOMBE, 1976;FERNANDES et al, 2017). Double sigmoid models have been satisfactorily used in growth studies (ALVAREZ and BOCHE, 1999;GOMES et al, 2008;CUNHA JUNIOR et al, 2007;BEBBINGTON el al., 2009;FAMIANE et al, 2012;BRUCKNER et al, 2012;MARTINEZ et al, 2017;FERNANDES et al, 2017;SILVA et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Description of blackberry fruit growth by nonlinear regression models

et al. 2020

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Blackberry is a small fruit with several properties beneficial to human health and its cultivation is an alternative for small producers due to its fast and high financial return. Studying the growth of fruits over time is extremely important to understand their development, helping in the most appropriate crop management, avoiding post-harvest losses, which is one of the aggravating factors of blackberry cultivation, being a short shelf life fruit. Thus, growth curves are highlighted in this type of study and modeling through statistical models helps understanding how such growth occurs. Data from this study were obtained from an experiment conducted at the Federal University of Lavras in 2015. The aim of this study was to adjust nonlinear, double Logistic and double Gompertz models to describe the diameter growth of four blackberry cultivars (‘Brazos’, ‘Choctaw’, ‘Guarani’ and ‘Tupy’). Estimations of parameters were obtained using the least squares method and the Gauss-Newton algorithm, with the “nls” and “glns” functions of the R statistical software. The comparison of adjustments was made by the Akaike information criterion (AICc), residual standard deviation (RSD) and adjusted determination coefficient (R2 aj). The models satisfactorily described data, choosing the Logistic double model for ‘Brazos’ and ‘Guarani’ cultivars and the double Gompertz model for ‘Tupy’ and ‘Choctaw’ cultivars.

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“…For this reason, the use of sigmoidal curves with more than one inflection point is a good approach. A typical example of this behaviour is observed in the growth of various fruit species, such as stone fruits (Álvarez and Boché [21]). Cairns et al [22] used double-sigmoidal models to study fatigue profiles in mouse muscles, while Amorim et al [23] detected this type of behaviour in the different phases in which the fungus Ustilago Scitaminea Sydow infects the sugarcane and produces its characteristic smut.…”

Section: Introductionmentioning

confidence: 91%

A Note on Estimation of Multi-Sigmoidal Gompertz Functions with Random Noise

2019

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The behaviour of many dynamic real phenomena shows different phases, with each one following a sigmoidal type pattern. This requires studying sigmoidal curves with more than one inflection point. In this work, a diffusion process is introduced whose mean function is a curve of this type, concretely a transformation of the well-known Gompertz model after introducing in its expression a polynomial term. The maximum likelihood estimation of the parameters of the model is studied, and various criteria are provided for the selection of the degree of the polynomial when real situations are addressed. Finally, some simulated examples are presented.

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MODELOS MATEMÁTICOS PARA DESCRIBIR CRECIMIENTOS DOBLE SIGMOIDEOS EN FRUTOS DE UN NECTARIN TARDIO (c.v. Sun Grand)

Cited by 12 publications

References 0 publications

Effect of sowing date and water availability on growth of plants of chia (Salvia hispanica L) established in Chile

Effect of sowing date and water availability on growth of plants of chia (Salvia hispanica L) established in Chile

Description of blackberry fruit growth by nonlinear regression models

A Note on Estimation of Multi-Sigmoidal Gompertz Functions with Random Noise

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