Nonlinear models in the study of the cedar diametric growth in a seasonally dry tropical forest

In 2020, the Brazilian commercial cattle herd was the largest in the world, representing 14.3% of the worldwide herd, with201.7 million heads. Although this activity yields significant profits, contributing to the economic and social development ofBrazil, it has been the target of concerns, mainly due to the large production of waste/effluents associated to bovine leatherprocessing. In this scenario, mineralization is important because nutrients essential for plant growth are released duringthe process of organic waste decomposition, and the dynamics of carbon release can be described by nonlinear regressionmodels. Thus, this study aimed to model the mineralization of organic carbon in the soil for 6, 12, 24, and 36 megagramsdoses per hectare (Mg ha−1) of tannery sludge using the Stanford & Smith, Cabrera, and Juma nonlinear models. Very clayeysoil samples were used: eutroferric red nitosol (NVef). Mineralized carbon was measured in 21 observations over time untilthe 105th day of incubation. Parameters were estimated using the least squares method. Adjustments were compared usingthe corrected Akaike information criterion (AICc) and the adjusted coefficient of determination (R2aj) as selection criteria. The Cabrera model had the best adjustments for doses 6, 12, and 24 Mg ha−1 and Juma for dose 36 Mg ha−1, based on the selection criteria used. Although the Stanford & Smith model is the most widely used in the literature to model soil carbon dynamics, its use was not the most appropriate for any of the doses evaluated in this study. The higher the dose of tannerysludge, the greater the amount of potentially mineralizable carbon.

Section: Resultsmentioning

confidence: 99%

Nonlinear modeling of carbon dynamics in soil treated with tannery sludge

Leoncio da Silva,

Silva,

Campos Frühauf

et al. 2023

“…Thus, to better understand decomposition dynamics and employ appropriate soil management, other models must be evaluated in this process. Gompertz model is an alternative for describing decomposition as it considers the abscissa of the inflection point at the beginning of the process (SILVA et al, 2021a;JANE et al, 2020a;FRÜHAUF et al, 2020;PRADO et al, 2020;SARI et al, 2018;RIBEIRO et al, 2018;MICHAN and PINHO, 2014).…”

Section: Introductionmentioning

confidence: 99%

Sigmoid models in the description of CO₂ evolved from legumes in the soil

Silva,

Campos Frühauf,

Menezes da Silva

et al. 2023

The decomposition of legumes in the soil over time can be described by nonlinear sigmoid models. Thus, this study aimedto describe and to compare the fit of the nonlinear sigmoid models, Logistic and Gompertz, to the CO2 mineralization of fourlegume species over time in the soil, and indicate the most suitable model. Furthermore, it is also proposed to evaluate the CO2mineralization of legumes from two different edaphoclimatic conditions when added to the soil under controlled temperatureand humidity conditions. The following legume species used in green manure were evaluated: Arachis pintoi (forage peanut),Calopogonium mucunoides (calopo), Stylosanthes guianensis (Caribbean stylo), and Stizolobium aterrimum (mucuna). Arandomized block design with four replications was used. The soils from both areas are classified as Red-Yellow Latosol andhave a clayey texture. The mineralized carbon was measured at 48, 96, 144, 192, 240, 312, 384, and 480 hours fromthe beginning of incubation. Legumes in different locations had the same amount of potentially mineralizable carbon, andmicroorganisms had the same adaptation time to reach the maximum decomposition rate. The maximum decompositionrate occurs at the beginning of mineralization, and therefore the Gompertz model was more suitable than the Logistic modelin describing the decomposition of the four legumes in the soil.

“…Several researchers have used non-linear models with satisfactory results for the adjustment of plant species growth curves. Frühauf et al (2020) fitted the Logistic, Gompertz, von Bertalanffy and Brody models for the diameter growth of cedar (Cedrela fissilis); these same models were used by Jane et al (2020) to describe the height and diameter of sugarcane variety RB92579; Prado et al (2020) modeled Predicting height growth in bean plants using non-linear and polynomial models Ariana Campos Frühauf 1, Edilson Marcelino Silva 2, Tales Jesus Fernandes 3, Joel Augusto Muniz 4 the growth of green dwarf coconut fruit with the Logistic and Gompertz models; and Silva et al (2020a) described the growth of blackberry fruit by the double Logistic and double Gompertz models. Martins Filho et al (2008) evaluated the growth of common bean cultivars using nonlinear models and Bayesian inference.…”

Section: Introductionmentioning

confidence: 99%

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

Frühauf

Silva

Fernandes

et al. 2022

Brazil has stood out worldwide as one of the main producers and consumers of beans, which makes their cultivation important for the economic and social development of the country. As the bean plant has a short growth cycle, its modeling is essential for optimizing management plans for this crop. This modeling can be performed by linear and non-linear models, but the latter have stood out for providing more information to the researcher, mainly due to the practical interpretation of their parameters. In this sense, in the R statistical software, the third-degree linear polynomial model and the Logistic and Gompertz non-linear models were adjusted to height data, in centimeters, in relation to time, in days after emergence, totaling 11 observations. As criteria to assess the quality of the fit, the adjusted coefficient of determination, the corrected Akaike information criterion and the residual standard deviation were used. The logistic model best fitted the data.