Use of geostatistical analyses for wheat production areas throung the variables NDVI, surface temperature and yield
Laen...
Kuupäev
2024
Kättesaadavus
Ajakirja pealkiri
Ajakirja ISSN
Köite pealkiri
Kirjastaja
Estonian University of Life Sciences
Abstrakt
Geostatistics is a crucial tool for data analysis in the field of precision agriculture,
allowing the characterization of spatial variability magnitude, optimizing profitability and yield
in agricultural areas. In this context, the present study aimed to evaluate the spatial dependence
of the variables yield, Normalized Difference Vegetation Index (NDVI), and surface temperature
in winter wheat plants. This was achieved through fitting semivariograms with different statistical
models and interpolating the study variables using Ordinary kriging. The experiment was
conducted at Fazenda Santa Helena, located in the municipality of Lavras in the state of Minas
Gerais, Brazil, with a 12-hectare winter wheat crop of the TBIO Calibre variety. Data were
collected using a grid sampling method at different stages of wheat plant growth (tillering and
elongation). The analyzed variables included yield, NDVI, and surface temperature. Statistical
analyses were performed using the R software. Initially, the spatial dependence of the study
variables was analyzed by fitting semivariograms using the Restricted Maximum Likelihood
(REML) method and considering spherical, exponential, and gaussian models. The evaluation of
errors was carried out through cross-validation, and subsequently, the data interpolation was
performed using ordinary kriging with the best-fitted semivariogram model. The results
demonstrated a proper fit of semivariograms for the study models, with the spherical model
standing out for surface temperature variables (elongation and tillering), NDVI (tillering), and the
exponential model for NDVI (elongation) and yield. Therefore, the use of geostatistics is
emphasized as an important tool to assist in precision agriculture management in winter wheat crops.
Kirjeldus
Received: February 1st, 2024 ; Accepted: April 8th, 2024 ; Published: April 20th, 2024 ; Correspondence:gabriel.ferraz@ufla.br
Märksõnad
spatial analyses, winter wheat, cross-validation, active sensor, vegetation index, articles