2 results

Optimization algorithms for multivariate sampling reduction using spatial-temporal data

Tamara Cantú Maltauro ORCID logo , Luciana Pagliosa Carvalho Guedes ORCID logo , Miguel Angel Uribe-Opazo ORCID logo

31/Jul/2025

ABSTRACT Knowing and defining the spatial and temporal variability of soil chemical properties becomes important for soil management. The definition of application zones in agricultural areas consists of dividing the area into homogeneous subareas, thus allowing the development of localized management. These zones can be defined by cluster methods and one of their advantages is to direct the determination of a future soil sampling, with a possible sample reduction. This study aimed to propose a methodology that integrates multivariate and […]

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Spatial multivariate optimization for a sampling redesign with a reduced sample size of soil chemical properties

Tamara Cantú Maltauro ORCID logo , Luciana Pagliosa Carvalho Guedes ORCID logo , Miguel Angel Uribe-Opazo ORCID logo , Letícia Ellen Dal Canton ORCID logo

22/Mar/2023

ABSTRACT Precision agriculture can improve the decision-making process in agricultural production, as it gathers, processes and analyzes spatial data, allowing, for example, specific fertilizer application in each location. One of the proposals to deal with spatial heterogeneity of the soil or the distribution of chemical properties is to define application zones (homogeneous subareas). These zones allow reducing both spatial variability of the yield of the crop under study and of the environmental impacts. Considering the soil data, application zones can […]

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