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Título
Estimating Soil Properties and Nutrients by Visible and Infrared Diffuse Reflectance Spectroscopy to Characterize Vineyards
Autor
Facultad/Centro
Área de conocimiento
Título de la revista
Agronomy
Número de la revista
10
Datos de la obra
Rodríguez-Pérez, J. R., Marcelo, V., Pereira-Obaya, D., García-Fernández, M., & Sanz-Ablanedo, E. (2021). Estimating Soil Properties and Nutrients by Visible and Infrared Diffuse Reflectance Spectroscopy to Characterize Vineyards. Agronomy, 11(10). https://doi.org/10.3390/AGRONOMY11101895
Editor
MDPI
Fecha
2021
Abstract
[EN] Visible, near, and shortwave infrared (VIS-NIR-SWIR) reflectance spectroscopy, a cost-
effective and rapid means of characterizing soils, was used to predict soil sample properties for four
vineyards (central and north-western Spain). Sieved and air-dried samples were measured using a
portable spectroradiometer (350–2500 nm) and compared for pistol grip (PG) versus contact probe
(CP) setups. Raw data processed using standard normal variate (SVN) and detrending transformation
(DT) were grouped into four subsets (VIS: 350–700 nm; NIR: 701–1000 nm; SWIR: 1001–2500 nm;
and full range: 350–2500 nm) in order to identify the most suitable range for determining soil
characteristics. The performance of partial least squares regression (PLSR) models in predicting soil
properties from reflectance spectra was evaluated by cross-validation. The four spectral subsets and
transformed reflectances for each setup were used as PLSR predictor variables. The best performing
PLSR models were obtained for pH, electrical conductivity, and phosphorous (R2 values above 0.92),
while models for sand, nitrogen, and potassium showed moderately good performances (R2 values
between 0.69 and 0.77). The SWIR subset and SVN + DT processing yielded the best PLSR models for
both the PG and CP setups. VIS-NIR-SWIR reflectance spectroscopy shows promise as a technique
for characterizing vineyard soils for precision viticulture purposes. Further studies will be carried
out to corroborate our findings
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