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Calibration models database of near infrared spectroscopy to predict agricultural soil fertility properties.

ABSTRACT: Presented paper describes spectroscopic dataset and calibration models database of near infrared spectroscopy (NIRS) used to predict agricultural soil fertility properties. Near infrared spectra data in form of absorbance spectrum were acquired in wavelength range from 1000 to 2500 nm for a total of 40 bulk soil samples amounted of 10 g per each bulk. Soil fertility properties, presented as soil nitrogen (N), phosphorus (P). potassium (K), soil pH, magnesium (Mg) and calcium (Ca), were measured by means of wet chemical analysis. Calibration models, used to predict those soil fertility parameters were developed using two different regression algorithms namely principal component regression (PCR) and partial least square regression (PLSR) respectively. Prediction performance can be evaluated and justified by looking their statistical indicators: correlation of determination (R2), correlation coefficient (r), root mean square error (RMSE) and residual predictive deviation (RPD). Spectra data can also be corrected in order to improve and enhance prediction performance. Obtained NIRS dataset and models database can be used as a rapid and simultaneous method to determine agricultural soil fertility properties.

SUBMITTER: Munawar AA

PROVIDER: S-EPMC7163313 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Calibration models database of near infrared spectroscopy to predict agricultural soil fertility properties.

Munawar Agus Arip AA Yunus Yuswar Y Devianti Satriyo Purwana P

Data in brief 20200408

Presented paper describes spectroscopic dataset and calibration models database of near infrared spectroscopy (NIRS) used to predict agricultural soil fertility properties. Near infrared spectra data in form of absorbance spectrum were acquired in wavelength range from 1000 to 2500 nm for a total of 40 bulk soil samples amounted of 10 g per each bulk. Soil fertility properties, presented as soil nitrogen (N), phosphorus (P). potassium (K), soil pH, magnesium (Mg) and calcium (Ca), were measured ...[more]

PMID: 32322619

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Project description:Optimal management of free-ranging herbivores requires the accurate assessment of an animal's nutritional status. For this purpose 'near-infrared reflectance spectroscopy' (NIRS) is very useful, especially when nutritional assessment is done through faecal indicators such as faecal nitrogen (FN). In order to perform an NIRS calibration, the default protocol recommends starting by generating an initial equation based on at least 50-75 samples from the given species. Although this protocol optimises prediction accuracy, it limits the use of NIRS with rare or endangered species where sample sizes are often small. To overcome this limitation we tested a single NIRS equation (i.e., multispecies calibration) to predict FN in herbivores. Firstly, we used five herbivore species with highly contrasting digestive physiologies to build monospecies and multispecies calibrations, namely horse, sheep, Pyrenean chamois, red deer and European rabbit. Secondly, the equation accuracy was evaluated by two procedures using: (1) an external validation with samples from the same species, which were not used in the calibration process; and (2) samples from different ungulate species, specifically Alpine ibex, domestic goat, European mouflon, roe deer and cattle. The multispecies equation was highly accurate in terms of the coefficient of determination for calibration R2 = 0.98, standard error of validation SECV = 0.10, standard error of external validation SEP = 0.12, ratio of performance to deviation RPD = 5.3, and range error of prediction RER = 28.4. The accuracy of the multispecies equation to predict other herbivore species was also satisfactory (R2 > 0.86, SEP < 0.27, RPD > 2.6, and RER > 8.1). Lastly, the agreement between multi- and monospecies calibrations was also confirmed by the Bland-Altman method. In conclusion, our single multispecies equation can be used as a reliable, cost-effective, easy and powerful analytical method to assess FN in a wide range of herbivore species.

Dataset Information

Calibration models database of near infrared spectroscopy to predict agricultural soil fertility properties.

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Calibration models database of near infrared spectroscopy to predict agricultural soil fertility properties.

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