Nonlinear regression for description of strawberry <i>(Fragaria x ananassa)</i> production

Diel, Maria Inês; Sari, Bruno Giacomini; Krysczun, Dionatan Ketzer; Olivoto, Tiago; Pinheiro, Marcos Vinícius Marques; Meira, Daniela; Schmidt, Denise; Lúcio, Alessandro Dal’Col

doi:10.1080/14620316.2018.1472045

Cited by 20 publications

(22 citation statements)

References 23 publications

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“…The parameters β 2 and β 3 that indicated the precocity and rate of fruit production (DIEL et al, 2019;SARI et al, 2018), are similar regardless of the cultivar chosen and growing season. In experiments that determine precocity, it is usually measured by counting days after the transplant until the beginning of the harvest.…”

Section: Discussionmentioning

confidence: 93%

“…The reproductive period of the biquinho pepper fruits, described by the Logistic model, could be well characterized, because the parameters allowed biological interpretation, and the critical points of the model provide the trend of the production along the crop cycle (MISCHAN et al, 2011); which, for example, indicated precocity and rate of fruit production (DIEL et al, 2019;SARI et al, 2018;. In addition, nonlinear growth models such as logistic are flexible enough to explain the variable performance of plants (PAINE et al, 2012) over the cycle.…”

Section: Discussionmentioning

confidence: 99%

“…The logistic model was selected a priori since it presents lower intrinsic and parametric nonlinearity values when compared with other nonlinear growth models. In addition, the logistic model was selected in other researches with multipleharvested crops (LÚCIO et al, 2015;DIEL et al, 2019;SARI et al, 2018). The logistic model for the cultivars in the E1 and E2 seasons was specified as…”

Section: Statistical Analyzesmentioning

confidence: 99%

“…For multiple-harvest crops, logistic regression models can efficiently describe fruit production which is the appropriate for crops such as Capsicum annuum, Cucurbita pepo, Solanum melongena, Phaseolus vulgaris and Fragaria ananassa (DIEL et al, 2019;LUCIO et al, 2016;LÚCIO;NUNES;REGO, 2015;SARI, et al, 2018;. For Fragaria ananassa, DIEL et al (2019) modeled the fruit production as a function of STa (accumulated thermal sum) for the logistic, Gompertz and von Bertalanffy models in different parameterizations and concluded that the Logisitic model described fruit production best while the models of Gompertz and von Bertalanffy overestimate the parameter that represent the production.…”

Section: Introductionmentioning

confidence: 99%

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Production of biquinho pepper in different growing seasons characterized by the logistic model and its critical points

Diel

Lúcio

Valera³

et al. 2020

Cienc. Rural

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The objective of this study was to characterize the production of biquinho pepper through the interpretation of parameter estimates from the logistic model and its critical points obtained by the partial derivatives of the function, and to indicate the best cultivar and growing season for subtropical climate sites. For this, a 2x3 factorial experiment was conducted with two cultivars of biquinho pepper (BRS Moema and Airetama biquinho) in three growing seasons (E1: October 2015, E2: November 2015, E3: January 2016). The logistic non-linear model for fruit mass was specified as a function of the accumulated thermal sum, and the critical points were calculated through the partial derivatives of the model, in order to characterize the productive performance of the crop by the biological interpretation of the estimates of the three set parameters. In E3, temperatures close to 0 ºC during the experiment were lethal to the plants, and a linear regression model was used in this case. The production of the cultivars in E1 and E2 were well characterized by the estimated logistic models, and the most productive cultivar was Airetama biquinho in all evaluated seasons. This cultivar also presented higher concentration of production. The two cultivars did not differ significantly with regards to productive precocity. For E3, it was not possible to interpret the parameters in the same way as for E1 and E2, since the use of the linear model did not allow the same interpretations performed for the nonlinear model, reaffirming its applicability horticultural crops of multiple harvests.

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Section: Discussionmentioning

confidence: 93%

Section: Discussionmentioning

confidence: 99%

Section: Statistical Analyzesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Production of biquinho pepper in different growing seasons characterized by the logistic model and its critical points

Diel

Lúcio

Valera³

et al. 2020

Cienc. Rural

Self Cite

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“…However, some reparametrizations confuse readers, making the use of nonlinear regression more complicated. According to Cordeiro et al (2009) and Diel et al (2019), the model is not always expressed in an appropriate parametric form, which facilitates the convergence of iterative processes used to obtain the estimates of its parameters, being necessary to seek a more appropriate parameterization.…”

Section: Introductionmentioning

confidence: 99%

Parameterizations of the Von Bertalanffy Model for Description of Growth Curves

et al. 2020

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The growth curves of animals, in general, have an “S” shape, also known as sigmoidal curves. This type of curve is well fitted by nonlinear regression models, including von Bertalanffy’s model, which has been widely applied in several areas, being presented in literature through different parameterizations, which in practice, can complicate its understanding, affect nonlinearity measures and inferences about parameters. To quantify the nonlinearity present in a Bates and Watts model, a geometric concept of curvature has been used. The aim of this work was to analytically develop three parameterizations of the von Bertalanffy’s nonlinear model referring to its nonlinearity, implications for inferences and to establish relationships between parameters in the different ways of expressing the models. These parameterizations were adjusted to the growth data of sheep. For each parameterization, the intrinsic and parametric curvature measurements described by Bates and Watts were calculated. The parameterization choice affects nonlinearity measures, consequently, influences the reliability and inferences about estimated parameters. The forms most used in literature showed the greatest deviations from linearity, showing the importance of analyzing these measures in any growth curve study. Parameterization should be used in which the b estimate represents the abscissa of the inflection point, as it presents minor linearity deviations and direct biological interpretation for all parameters.

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Prediction of strawberry yield based on receptacle detection and Bayesian inference

Yoon¹,

Jo²,

Kim³

et al. 2023

Heliyon

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Nonlinear regression for description of strawberry (Fragaria x ananassa) production

Cited by 20 publications

References 23 publications

Production of biquinho pepper in different growing seasons characterized by the logistic model and its critical points

Production of biquinho pepper in different growing seasons characterized by the logistic model and its critical points

Parameterizations of the Von Bertalanffy Model for Description of Growth Curves

Prediction of strawberry yield based on receptacle detection and Bayesian inference

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