Chanter model: nonlinear modeling of the fruit growth of cocoa

Silva, Pollyane Vieira da; Savian, Taciana Villela

doi:10.1590/0103-8478cr20190409

Cited by 4 publications

(5 citation statements)

References 9 publications

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“…Furthermore, the HPD intervals for the φ parameter do not include zero (Table 2 and Table 3), emphasizing that the autocorrelation is significant in all studied scenarios. As highlighted by Silva et al (2021), incorporating residual dependence may not necessarily improve the quality of the fit, but it is more consistent, since the assumption of independence is not satisfied in longitudinal data modeling.…”

Section: Resultsmentioning

confidence: 99%

“…Due to the economic importance of coffee for Brazil, one of the main focuses of research in the agricultural sector refers to the development of coffee tree. A relevant variable to be considered in such research is the plant height, because in addition to being representative of vegetative development, it is also correlated with productivity (ASSIS et al, 2014;PEREIRA et al, 2016;SILVA et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

“…Diante desse contexto, o objetivo deste trabalho foi apresentar a modelagem não linear bayesiana do crescimento em altura de plantas do cafeeiro, irrigadas e não irrigadas (NI), considerando a autocorrelação residual e os modelos não lineares Logístico, Brody, von researcher to describe growth over time and obtain information of practical interest, such as the maximum height at adult stage and the speed of growth. They are important to characterize the development of plants (PEREIRA et al, 2014;REIS et al, 2014;FERNANDES et al, 2017;SARI et al, 2018;SILVA & SAVIAN, 2019;JANE et al, 2020;SILVA et al, 2021;MENDES et al, 2021).…”

Section: Introductionunclassified

“…To model the growth curve, it should be considered that the growth data taken over time may show residual autocorrelation (PEREIRA et al, 2016;JANE et al, 2020;SILVA et al, 2021). However, in several applied researches, it appears that this characteristic is not incorporated in the modeling, and may compromise the results and inferences (MUNIZ et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

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Bayesian modeling of the coffee tree growth curve

et al. 2022

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When modeling growth curves, it should be considered that longitudinal data may show residual autocorrelation, and, if this characteristic is not considered, the results and inferences may be compromised. The Bayesian approach, which considers priori information about studied phenomenon has been shown to be efficient in estimating parameters. However, as it is generally not possible to obtain marginal distributions analytically, it is necessary to use some method, such as the weighted resampling method, to generate samples of these distributions and thus obtain an approximation. Among the advantages of this method, stand out the generation of independent samples and the fact that it is not necessary to evaluate convergence. In this context, the objective of this work research was: to present the Bayesian nonlinear modeling of the coffee tree height growth, irrigated and non-irrigated (NI), considering the residual autocorrelation and the nonlinear Logistic, Brody, von Bertalanffy and Richard models. Among the results, it was found that, for NI plants, the Deviance Information Criterion (DIC) and the Criterion of density Predictive Ordered (CPO), indicated that, among the evaluated models, the Logistic model is the one that best describes the height growth of the coffee tree over time. For irrigated plants, these same criteria indicated the Brody model. Thus, the growth of the non-irrigated and irrigated coffee tree followed different growth patterns, the height of the non-irrigated coffee tree showed sigmoidal growth with maximum growth rate at 726 days after planting and the irrigated coffee tree starts its development with high growth rates that gradually decrease over time.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionunclassified

Section: Introductionmentioning

confidence: 99%

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Bayesian modeling of the coffee tree growth curve

et al. 2022

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“…The logistic model, and the double logistic and hybrid models such as chanter (logistic + Gompertz), have been used for modeling fruit growth in cacao 3 and various productive systems such as kiwi, coffee, and cashew. 11,[18][19][20] The cacao fruit development has been characterized by an early exponential growth, followed by a linear phase, and stabilizing in the ripening state. The fruit variables measured over time confirmed this behavior in the evaluated clones and facilitated the biological interpretation of the parameters obtained by the different models.…”

Section: Discussionmentioning

confidence: 99%

Growth, respiration and physicochemical changes during the maturation of cacao fruits

et al. 2021

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BACKGROUND: Cacao is important for the economy of many countries in the humid tropics. Its quality is affected when fruits are not collected at the optimal harvest point. The aim of this study was to obtain maturity indices for producers to facilitate the timely harvest and improve the development of fermentation and the sensorial quality of cacao. The growth and respiration processes, and the physicochemical changes during the maturation of three cacao genotypes were determined. Physiological follow-ups measuring fruit length and diameter were performed from 30 days after anthesis to fruit deterioration in the tree. RESULTS: Growth equations were obtained, establishing four maturity stages based on days after anthesis, and fruit length and diameter. Nineteen descriptors were used for the characterization, and through Pearson's correlation and principal component analysis (PCA), five descriptors were identified as representative of the maturity stages of the cacao fruit. PCA results and respiration measurements established that stage 3 presented the highest substrate availability for obtaining good fermentation and quality cacao. This stage showed values between 124 and 197 days after anthesis with lengths between 167.7 and 249.73 mm, and diameters between 64.4 and 95.8 mm, according to the locality. CONCLUSION: Three growth phases of the cacao fruits were established considering days after anthesis. Both the edaphoclimatic conditions and the cacao genotype characteristics influenced this determination. Stage 3 of fruit maturation shows the best physicochemical conditions for good fermentation.

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Nonlinear models. An approach to model irrigated and non-irrigated common bean (Phaseolus vulgaris L.) growth

Pohlmann

Lopes

Lago

et al. 2021

Int J Innov Educ Res

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Common beans reduce their development and productivity when facing soil water deficit. Comprehension about growth response under this condition can be a tool for cultivar selection and escape from scarcity periods. Therefore, the objective was to characterize bean growth in different water conditions using logistic and chanter models. Two experiments (crop season= EI and fallow season = EII) were carried out in Santa Maria, RS, Brazil in a bifactorial scheme (cultivars: Triunfo, Garapiá, FC104; water condition: irrigated, not irrigated) in a completely randomized design. Fortnightly evaluations of height, number of nodes, stem diameter, root length, aerial part, roots, and nodules dry matter were carried out. The data were adjusted according to the accumulated thermal sum by the logistic and chanter models. From the results, it is noted that there was a dissimilar performance between water conditions, cultivars, and experiments. The best adjustment occurred for stem diameter, node number, and aerial part dry matter. Between models, the logistic is the most suitable to describe common bean growth.

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Chanter model: nonlinear modeling of the fruit growth of cocoa

Cited by 4 publications

References 9 publications

Bayesian modeling of the coffee tree growth curve

Bayesian modeling of the coffee tree growth curve

Growth, respiration and physicochemical changes during the maturation of cacao fruits

Nonlinear models. An approach to model irrigated and non-irrigated common bean (Phaseolus vulgaris L.) growth

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