Nonlinear models for describing lettuce growth in autumn-winter

Abstract

<jats:p>ABSTRACT: The objectives of this study were to fit the Gompertz and Logistic models for the fresh and dry matter of leaves and the fresh and dry matter of shoots of three lettuce cultivars and indicate the best model to describe their growth in autumn-winter. The lettuce cultivars Gloriosa, Pira Verde, and Stella were evaluated in the autumn-winter of 2016 and 2017, in soilless in a protected environment. After transplantation, the fresh and dry matter of leaves and shoots were weighed every seven days. These dependent variables were fit using the accumulated thermal sum. The parameters of the Gompertz and Logistic models were estimated, the assumptions of the models were verified, the indicators of fit quality and critical points were calculated and the parametric and intrinsic curvature measures quantified. The Logistic and Gompertz models presented a satisfactory adjustment for the fresh and dry matter of leaves and the fresh and dry matter of shoots, for the lettuce cultivars Gloriosa, Pira Verde and Stella, in autumn-winter. The Logistic model best describes the growth of the lettuce cultivars.</jats:p>

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

“…These results indicate that the models showed different behavior between the experiments and within each variable. Similar results have also been stated for tomato genotypes (Sari et al, 2019) and lettuce (Carini et al, 2020).Analyzing the response variables within each experiment, it was possible to observe that the logistic model presented a greater number of parameters, differing between cultivars and between WC in the two experiments. In this model, parameter c was the one that most differed between cultivars in the two experiments.…”

“…For example, for the cultivar Triunfo (irrigated) in the EI, both overestimated the value of the asymptote for H, in the logistic, there was an overestimation of 16.17 cm and in the chanter around 15.23 cm. In an experiment with lettuce, Carini et al (2020) found that the Gompertz model overestimated the values of the variables, dissimilar to the logistic.…”

“…For tomatoes, the weight and number of fruits per plant were studied (Sari et al, 2019). In lettuce, leaves, and shoots fresh and dry matter were adjusted (Carini et al, 2020). From the aforementioned research, it can be observed that the adjustment of growth curves for variables related to the plant stem, such as stem diameter and a number of nodes, and root variables, have not been studied.…”

“…In general, the response variables that demonstrated the best fit (Tables 2, 3, 4, and 5) and the lowest error (Table 1) were: MSD, NN, and APDM, and should preferably be used to evaluate bean growth. The estimates parameters (a, b, c, d) of each cultivar vs WC were compared between each experiment (Tables 2, 3, 4 and 5) using the overlapping confidence intervals (CI) criteria, used by Deprá et al (2016) and Carini et al (2020). It was considered that when one of the estimates was within the CI of the other, the effect was not significant.…”

“…Significance frequently occurred for parameter b, whereas in the logistic model, parameters b, c, d was more frequently significant (Tables 2 and 3), indicating that the chanter model shows a modest difference between the combinations. In a study with lettuce, Carini et al (2020) perceived that the Gompertz model showed less difference between some cultivars than the logistic one and observed the need to determine specific models by character and cultivar. The models showed the same behavior for most variables.…”