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Determination of N Mineralization, Total N and Cation Exchange Capacity of Soil Through Nir Spectroscopy for Decision Support in Rice Farming

M. N. A. Siddique
Senior Scientific Officer
District office, Soil Resource Development Institute, Ministry of Agriculture, Pabna-6600, Bangladesh

Abstract/ Executive Summary:

Inefficient use of inputs and conventional management practices that are applied during crop production is leading the depletion of soil quality. The need of sustainable management appeals for alternative approaches which will increase the productivity and resources efficiency; and will be desirable in the ecological context as well. Thus, sustainable development has reinforced the process to evolve as a more quantitative manner to optimize soil management and impart spatially differentiated treatments. There is a global need to develop tools that will evaluate soil quality and contribute in the effectiveness and sustainability of farm management. Soil properties delineation at field and landscape scale is extremely important for a variety of agronomic and environmental concerns. The existing knowledge and recent researches on soil-NIR measurements for soil analysis by the NIR spectroscopic technique could be used potentially for estimation of available nitrogen (N) and cation exchange capacity (CEC) of soils. However, this is worth mentioning that NIR measurements are not new in this scientific arena but it has not been practiced so far for estimation of soil properties in Bangladesh. Exploration of its potential would be beneficial for soil property analysis .

Keywords: NIR spectroscopy, Soil analysis, Mineralization, CEC, Decision support

Location: Laboratory of Soil Resource Development Institute, Ministry of Agriculture, Pabna-6600,Bangladesh

Start Date: 00-01-2013

End Date: 00-06-2013

Program Area: Crop-Soil-Water Management

Commodity: Land management

Objectives:

To determine the N mineralization content, total N and cation exchange capacity of soil through NIR spectroscopy for decision support in rice farming.

Methodology:

Methodology that is involved with NIR spectroscopy includes desired soil sampling, sample preparation, data pretreatment and spectroscopic multivariate calibration for prediction equation development and calibration. Soil sampling: Soil samples could be collected after a growing season from targeted rice fields. Among the existing sampling methods, such as grid, random (simple and stratified), continuous, adaptive; the adaptive sampling (sampling on previous information) and stratified sampling (heterogeneous soils; homogeneous sub-population isolated as strata), could be used for soil sample collection. For the estimation of N and CEC on field scale, and or preferably at regional scale eventually it could increase the number of samples. Sample preparation and data pretreatment: The soil samples require being freeze dried, grinded and sieved (2 mm) before sample setting for the spectral measurements. Soil spectra (1300-2500 nm) data collection would be done with a Spectrophotometer. All spectra recorded were checked visually, necessary preprocessing would be done to correct for non-linearities, sample variations and noisy spectra. Most spectroscopy-dedicated software contains a collection to choose from the preprocessing transformations techniques, such as Multiplicative Scatter Correction; first and second derivatives; smoothing methods (averaging spectra) etc. could be used depending on data sets to identify the more chemically relevant peaks in the spectra. Spectroscopic multivariate calibrations: It consisted of a crucial task associated with the calibration phase for prediction equation development and a validation phase. During calibrations, careful selection of the calibration and validation samples would be done. The size and distribution of the calibration data set would be representative not only of the variation in the soil property being considered, but also of the variation in the spectra. The validation samples would be independent of the calibration samples. However, Principal Component Regression (PCR) and or Partial Least-Squares Regression (PLSR) were used to calibrate the spectral data with reference soil data which will enable relating the NIR spectra to estimate soil properties such as values of N and CEC in the soils.

Source of Information: Intern. J. Bussin. Managt. Soci. Res. 01(01): 47-50 (2015)

Article Link (Online Journal):

Funding Source:

1. Government

Budget:

Total Budget (Tk.) :

Achievement/Findings:

Finially, potential soil analysis results derived from NIR spectroscopy could increase the efficiency of inputs and farm management options by allowing the farmer and producer to manage crops on both spatial and temporal basis with a prescriptive manner rather than conventional farming.

Knowledge Management: Journal