Bayesian and non-parametric estimations of the weed inventory in the cultivation of chrysanthemum using rigid grid quadrats

Abstract

Studies that involve the inventory of weeds are frequently carried out by students and professionals of the agricultural and/or environmental sciences with the principal objective of obtaining information on the distribution pattern, frequency, coverage, density or biodiversity of the species in a studied region. On many occasions, the only purpose consists of identifying those species that are considered important by farmers, perhaps because they are beneficial or because they compete with the crops in production. When the sampling of weeds is done using the quadrat method, some of the species which are present in the cultivated field of interest may not be sampled, meaning they will be absent in the final inventory. The principal objective of this article was to show how the quantity of weeds in an observed sample can be estimated Bayesian estimators, as well as non-parametric estimators, such as Chao 2, Jackknife, of the first and second order, and Bootstrap. The inventory estimation of the weeds using the Bayesian and classical proposals in the case of cultivation of chrysanthemum produced similar results, with 19 species in all of the estimators, except in the Mingoti estimators, which produced 18 weeds.