Near infrared spectroscopy as a tool for intensive mapping of vineyards soil

Lopo, Miguel; Santos, Cláudia A. Teixeira dos; Páscoa, Ricardo N.M.J.; Graça, António; Lopes, João A.

doi:10.1007/s11119-017-9529-2

Cited by 15 publications

(10 citation statements)

References 33 publications

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“…The CR of the independent test set is higher than the cross-validation CR indicating that the samples in the independent test set are generally well discriminated by the Please cite this article as: Petit, J et al, Potential of visible/near infrared spectroscopy coupled with chemometric methods for discriminating and estimating the thickness of clogging in drip-irrigation, Biosystems Engineering, https://doi.org/10.1016/ j.biosystemseng.2021.07.013 model compared to some samples in cross-validation. Classification results obtained in the test set are satisfactory compared to those obtained in the literature: Xie et al (2015) and Lopo et al (2018) obtained CR of 90% when discriminating clays, sand and calcium carbonate in soil samples. This means that the PLS-DA model can be considered suitable for sample classification for the four studied classes.…”

Section: Discrimination Between the Different Types Of Clogging Materials Using Pls-dasupporting

confidence: 67%

“…In general, chemometric methods can be used to solve problems in qualitative/quantitative and discrimination analysis (Xie et al, 2015;Lopo, Teixeira dos Santos, P ascoa, Grac ¸a, & Lopes, 2018). Among them, partial least squares regression (PLSR) (Geladi & Kowalski, 1986) and its modification partial least squares with discriminant analysis (PLS-DA) (Wold et al, 1984) are the most commonly used.…”

Section: Introductionmentioning

confidence: 99%

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Potential of visible/near infrared spectroscopy coupled with chemometric methods for discriminating and estimating the thickness of clogging in drip-irrigation

Petit

Ait-Mouheb

Garcia

et al. 2021

Biosystems Engineering

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Section: Discrimination Between the Different Types Of Clogging Materials Using Pls-dasupporting

confidence: 67%

Section: Introductionmentioning

confidence: 99%

Potential of visible/near infrared spectroscopy coupled with chemometric methods for discriminating and estimating the thickness of clogging in drip-irrigation

Petit

Ait-Mouheb

Garcia

et al. 2021

Biosystems Engineering

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“…Páscoa et al [27] developed a method for indirect soil differentiation based on grapevine leaf spectra, demonstrating that leaf spectral information can be used to define soil maps for vineyards. For Northern Portugal, Lopo et al [28] demonstrated the ability of NIR spectroscopy to discriminate between vineyard soil types, showing that water content is not a significant factor in differentiating between soils.…”

Section: Introductionmentioning

confidence: 99%

Estimating Soil Properties and Nutrients by Visible and Infrared Diffuse Reflectance Spectroscopy to Characterize Vineyards

et al. 2021

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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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“…Para la extrapolación del modelo, a otras regiones, deben incluirse espectros que integren la variabilidad de los suelos, para una mejor predicción. Las 48 muestras fueron debidamente clasificadas conforme al ICS obteniendo mejores resultados estadísticos que los reportados por Levi et al (2020); y resultados del R 2 mayores a 0.90; que es similar a los obtenidos por Lopo et al (2018). En el grupo de entrenamiento se obtuvieron valores de RMSE bajos y coeficientes de determinación altos (cercanos a 1) (Cuadro 2).…”

Section: Modelo De Clasificación Del íNdice De Calidad De Suelo Media...unclassified

Evaluación de la calidad de suelo de Tabasco, México, con métodos convencionales, espectroscopia de infrarrojo cercano y quimiometría

Ramírez-García¹,

Guerrero-Peña

Zavala-Cruz³

et al. 2023

Terra Latinoam

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Se realizó una investigación retrospectiva – prospectiva, para establecer un índice de calidad de los suelos (ICS) de la región de los Ríos (RR) en Tabasco, México y su modelación con la tecnología de infrarrojo cercano (NIR) y la quimiometría. Con la relación MO / (arcilla + limo) se estableció el ICS para evaluar los suelos Cambisoles de la RR. El porcentaje de MO y el ICS fueron comparados para definir el mejor calificador de la calidad de los suelos. Con base en el ICS, el 58% de los suelos de la RR presentan degradación, mientras que, solo el 14% de los suelos indican que presentan baja concentración de MO. Por lo que se concluye que el ICS es más sensible para cuantificar la degradación de los suelos cuando se comparó con la evaluación basada en la MO. Se recomienda un programa de manejo sostenible del suelo y prácticas edafológicas adaptadas a las condiciones locales, ambientales, sociales y económicas, para incrementar la MO y mejorar el ICS. Con el ICS se estableció un modelo de clasificación mediante espectroscopía de infrarrojo cercano y quimiometría. Se registraron los espectros de cada muestra de suelo y mediante interpretación quimiométrica se demostró que es posible establecer un modelo de análisis discriminante por mínimos cuadrados parciales (PLS-DA) para predecir el ICS. El modelo cumple con todos los calificadores estadísticos y predice correctamente el ICS en el 100% de los casos. Se concluye que la tecnología NIR genera información suficiente para predecir el ICS; con la ventaja de, eliminar el consumo de reactivos, no se generan residuos de laboratorio, se reduce el tiempo de análisis a minutos y no se destruye la muestra en estudio. Y solo se necesita secar, moler y tamizar las muestras de suelos para evaluar la calidad estructural de suelos.

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Near infrared spectroscopy as a tool for intensive mapping of vineyards soil

Cited by 15 publications

References 33 publications

Potential of visible/near infrared spectroscopy coupled with chemometric methods for discriminating and estimating the thickness of clogging in drip-irrigation

Potential of visible/near infrared spectroscopy coupled with chemometric methods for discriminating and estimating the thickness of clogging in drip-irrigation

Estimating Soil Properties and Nutrients by Visible and Infrared Diffuse Reflectance Spectroscopy to Characterize Vineyards

Evaluación de la calidad de suelo de Tabasco, México, con métodos convencionales, espectroscopia de infrarrojo cercano y quimiometría

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