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Assessment of cocoa input needs using soil types and soil spectral analysis
Author(s) -
Singh Kanika,
Vasava Hitesh B.,
Snoeck Didier,
Das Bhabani S.,
Yinil David,
Field Damien,
Sanderson Todd,
Fidelis Chris,
Majeed Israr,
Panigrahi Niranjan
Publication year - 2019
Publication title -
soil use and management
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.709
H-Index - 81
eISSN - 1475-2743
pISSN - 0266-0032
DOI - 10.1111/sum.12499
Subject(s) - environmental science , soil test , soil carbon , shortwave , partial least squares regression , reflectivity , soil science , mathematics , soil water , statistics , physics , quantum mechanics , optics , radiative transfer
In this study, diffuse reflectance spectroscopy ( DRS ) approach was examined for making input recommendations in the smallholder cocoa farms of Papua New Guinea ( PNG ). Soil samples were collected from four provinces of PNG . Soil samples from four different depths (0–10, 10–30, 30–60 and 60–90 cm) of 32 profiles in each of these site were used to create a database of soil chemical and physical properties. Spectral reflectance values at 1 nm interval covering visible to shortwave‐infrared (350–2,500 nm) were collected for each of these soil samples to develop partial least squares regression models. Soil textural fractions, soil organic carbon contents and available N were well predicted by the DRS approach with R 2 values larger than 0.75. Moderate to poor estimation efficiencies were observed for remaining parameters. Nevertheless, the estimated soil attributes and their corresponding measured soil parameters were used as inputs to an input recommendation model of soil diagnosis to create input recommendation for a targeted cocoa yield of 1,000 kg dry cocoa beans ha ‐1 Resulting input recommendations were similar for both of these input sources (measured and DRS ‐estimated) suggesting that the DRS approach may provide an easy way to create input recommendations.