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Data · dataset · 2026

Replication Data for: Soil Properties and Vis–NIR Reflectance Dataset in Andean Highland and Rainforest Agroecosystems

Listed in International Potato Center

This dataset corresponds to a study that evaluated the use of visible and near-infrared (Vis–NIR) spectroscopy combined with machine learning (ML) algorithms to predict soil fertility-related properties in two contrasting agroecological regions of Peru: the Highlands and the Rainforest.

Description

A total of 297 soil samples were analyzed using portable spectroradiometers covering a spectral range of 350–2500 nm. Spectral preprocessing techniques, including Savitzky–Golay smoothing, first derivative transformation, and band depth normalization, were applied.

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Where it is published

Catalogue records · 1

Topics

Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
International Potato Centerdoi:10.21223/P3/FVQLPK5 d agoJSON v1
FieldAssertionExtractorEvidence
concepts[field].dataverse_subject:agricultural-sciencessource · data cipotato orgconnector:data_cipotato_org@1.0.0/subjects
concepts[field].dataverse_subject:earth-and-environmental-sciencessource · data cipotato orgconnector:data_cipotato_org@1.0.0/subjects
concepts[field].local:field:earth-environmentalmapping · data cipotato orgconnector:data_cipotato_org@1.0.0/subjects
concepts[field].local:field:life-sciencesmapping · data cipotato orgconnector:data_cipotato_org@1.0.0/subjects
concepts[modality].local:modality:remote-sensingmapping · data cipotato orgvocabulary-mapper@1.0.0keywords['Remote sensing']
created_datesource · data cipotato orgconnector:data_cipotato_org@1.0.0
descriptionsource · data cipotato orgconnector:data_cipotato_org@1.0.0/description
publication_datesource · data cipotato orgconnector:data_cipotato_org@1.0.0
titlesource · data cipotato orgconnector:data_cipotato_org@1.0.0/name
updated_datesource · data cipotato orgconnector:data_cipotato_org@1.0.0
version_labelsource · data cipotato orgconnector:data_cipotato_org@1.0.0