Abstract
In order to estimate the response of biometric variables in different irrigation depths in radish crop, as well as their relations in the development of the crop, a fuzzy mathematical analysis was carried out from irrigation with depths of different percentages of the crop evapotranspiration (ETc), using Gaussian pertinence functions for the input variable and triangular for the biometric output variables. Validations were performed using neural network models, smoothing splines and polynomial regression. The relation among the biometric variables was measured applying the Pearson correlation coefficient. The results showed that the fuzzy modeling presented superiority in the crop development estimate over the quadratic polynomial regression model, neural network and smoothing splines, because it achieved an average reduction of errors among the biometric variables, of 7.8% 94.6% and 9.2% for the RMSE in the respective models, as well as a better adjustment of the data with average R2 of the variables. The modeling with neural network showed inadequate agronomic behavior in data representation. Regarding biometric variables, the length and diameter of the tuberous root are inversely correlated, and the fresh phytomass of the tuberous root is correlated only with the fresh phytomass of the root.
Highlights
Radish (Raphanus sativus) is a crop that has its biometric parameters highly influenced by external factors
Based on data of biometric parameters of radish yield, fuzzy models were employed by Gaussian pertinence functions for input variables and triangular functions for output values
According to the validation of the developed models, the fuzzy model showed to be superior over the statistical model for all biometric parameters, with higher R2 values and lower error indexes (MRSP and MAE), demonstrating its efficiency in data estimation for the decision-making in setting irrigation timing
Summary
Radish (Raphanus sativus) is a crop that has its biometric parameters highly influenced by external factors. It belongs to the Brassicaceae family and is composed of tuberous roots below ground, and stem and leaves above it (Embrapa, 2012). The edible part can be found in several shapes, from elliptical to elongated or round forms, with diameters ranging between 2 and 5 centimeters. It can be white, purple, red, or black colored, while its pulp is white (Dantas et al, 2015). One option is the introduction of mathematical modeling, as it allows, in more advanced processes, to consolidate the results obtained experimentally (Bordin, 2016)
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