Avaliação de modelos não lineares na descrição do acúmulo de macronutrientes em plantas de chicória

Abstract

Chicory is among the main leafy greens including lettuce, cabbage, arugula and kale. It is con- sumed in the form of a salad or sautéed, constituting a food indicated in meals for providing nutrients and vitamins. In the study of the growth and development of vegetables, it is inte- resting to follow the content and mobilization of macronutrients over time to understand the dynamics involved and the need for fertilization, seeking efficient responses from the plants. The accumulation of nutrients in plants over time, in general, has a sigmoidal character that can be described by non-linear models. The objective of this work was to evaluate the use of the Logistic and Gompertz models in the study of the accumulation of macronutrients (Nitrogen, Potassium, Phosphorus, Calcium, Magnesium, Sulphur), in mg/plant, as a function of the age of the plant, in days, in the matter dry season of "Crespa" and "AF-218" cultivars, grown with or without covering with polypropylene fabric. Data were obtained from an experiment where the accumulated macronutrient content was recorded at the ages of 7, 14, 21, 28, 35 and 42 days after transplants. The models were adjusted by the method of least squares using the Gauss- Newton algorithm through the R software. The evaluation of the quality of the adjustment was made based on the values of the coefficient of determination, the residual standard deviation and the Akaike information criterion. The quality evaluators showed that for the two cultivars the models were adequate to describe the accumulation of macronutrients, however, in almost all adjustments the Logistic model adjusted better. Based on the confidence intervals of the parameter estimates, it was possible to observe that among the cultivars "AF-218" presented earlier inflection points and greater accumulations at the end of the experiment. And still on the "AF-218" cultivar, when cultivated under cover of polypropylene fabric, it showed better results.