Forecasting of yields in Jarillo peach crops at the Province of Pamplona using random variables
DOI:
https://doi.org/10.17981/ingecuc.18.1.2022.06Keywords:
Agricultural production systems, Stochastical models, Peach production, Discrete-variable simulation, Probability distributionAbstract
Introduction— As a result of a research project, this article shows the crop yield forecast for a peach variety named jarillo. For this, a model was designed to simulate the production of peach fruits, generating random variables of the number of fruits and total weight, from probability distributions deduced from crop samples.
Objective— Forecasting the yield of a peach crop, by simulating variables that follow a probability distribution associated with it, obtaining a statistical behavior similar to a real production scenario.
Methodology— A bibliographic review was made of studies on production forecasting in other plant species. Production samples were also taken from farms in various zones and a linear regression analysis at a fixed interval (stepwise) was made, taking yield as a dependent variable and the physical dimensions of the branch as an independent variable. In addition, data was collected for determine the production probability distribution and based on it a simulator software was designed and implemented, with which various simulations of production scenarios were made.
Results— Models were obtained with a lower number of variables resulting from applying the stepwise procedure in order to forecasting the number of fruits and performance. When characterizing input variables, the mathematical model was built with random inputs to predict yield, such as crop area, planting system, planting density, crop age and branch length, leaf area, fruit diameters, among others variables.
Conclusions— Is feasible the forecasting of peach crops yield under several assumptions, from samples observed in real production scenarios. It was posible to implement a forecast model based on random variables, whose variability with respect to real data is significantly small.
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