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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 R2 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.

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Rapid soil testing and soil quality assessment are essential to address soil degradation and low farm incomes in smallholder farms. With the objective of testing diffuse reflectance spectroscopy (DRS) to rapidly assess soil chemical properties, nutrient content and a soil quality index (SQI), samples of surface soil were collected from 1113 smallholder farms in seven districts in Bundelkhand region of Uttar Pradesh, India. A minimum dataset (MDS) approach was followed to estimate SQI using the three chemical parameters of soil pH, electrical conductivity (EC) and soil organic carbon (SOC), and 11 different soil nutrients. Principal component and correlation analyses showed that soil pH, SOC content and three available nutrients À copper (Cu), iron (Fe) and sulphur (S) À may constitute the MDS. Estimated SQI values showed strong positive correlation with crop yields. Results of chemometric modelling showed that the DRS approach could yield the coefficient of determination (R 2 ) values in the validation datasets ranging from 0.79 to 0.94 for exchangeable calcium (Ca) followed by 0.67-0.88 for exchangeable potassium (K), 0.52-0.86 for SOC and 0.53-0.81 for available boron (B) content. Except in one district, the DRS approach could be used to estimate SQI values with R 2 values in the range of 0.63-0.81; an R 2 value of 0.71 was obtained in the pooled dataset. We also estimated the three-tier soil test crop response (STCR) ratings to compare DRS and wet chemistry soil testing approaches. Similar STCR ratings were obtained for both these approaches in more than 86% of the samples. Parameters for which both the methods yielded similar ratings in more than 80% of the samples were EC (>98%), pH and exchangeable Ca (>81%) and available B (>89%). With similar ratings, these results suggest that the DRS approach may safely be used for farmers' fields, replacing the traditional wet analysis approach of soil testing.

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