A fast and convenient soil analytical technique is needed for soil quality assessment and precision soil management. The main objective of this study was to evaluate the ability of near-infrared reflectance spectroscopy (NIRS) to predict diverse soil properties. Near-infrared reflectance spectra, obtained from a Perstrop NIR Systems 6500 scanning monochromator (Foss NIRSystems, Silver Spring, MD), and 33 chemical, physical, and biochemical properties were studied for 802 soil samples collected from four Major Land Resource Areas (MLRAs). Calibrations were based on principal component regression (PCR) using the first derivatives of optical density [log(1/R)] for the 1300- to 2500-nm spectral range. Total C, total N, moisture, cation-exchange capacity (CEC), 1.5 MPa water, basal respiration rate, sand, silt, and Mehlich III extractable Ca were successfully predicted by NIRS (r 2 > 0.80). Some Mehlich III extractable metals (Fe, K, Mg, Mn) and exchangeable cations (Ca, Mg, and K), sum of exchangeable bases, exchangeable acidity, clay, potentially mineralizable N, total respiration rate, biomass C, and pH were also estimated by NIRS but with less accuracy (r 2 = 0.80∼0.50). The predicted results for aggregation (wt% > 2, 1, 0.5, 0.25 mm, and macroaggregation) were not reliable (r 2 = 0.46∼0.60). Mehlich III extractable Cu, P, and Zn, and exchangeable Na could not be predicted using the NIRS-PCR technique (r 2 < 0.50). The results indicate that NIRS can be used as a rapid analytical technique to simultaneously estimate several soil properties with acceptable accuracy in a very short time.

https://lib.dr.iastate.edu/cgi/viewcontent.cgi?article=1718&context=abe_eng_pubs

Near-Infrared Reflectance Spectroscopy–Principal Components Regression Analyses of Soil Properties

This chapter provides a review on the state of soil visible–near infrared (vis–NIR) spectroscopy Our intention is for the review to serve as a source of up-to-date information on the past and current role of vis–NIR spectroscopy in soil science It should also provide critical discussion on issues surrounding the use of vis–NIR for soil analysis and on future directions To this end, we describe the fundamentals of visible and infrared diffuse reflectance spectroscopy and spectroscopic multivariate calibrations A review of the past and current role of vis–NIR spectroscopy in soil analysis is provided, focusing on important soil attributes such as soil organic matter (SOM), minerals, texture, nutrients, water, pH, and heavy metals We then discuss the performance and generalization capacity of vis–NIR calibrations, with particular attention on sample pretratments, covariations in data sets, and mathematical data preprocessing Field analyses and strategies for the practical use of vis–NIR are considered We conclude that the technique is useful to measure soil water and mineral composition and to derive robust calibrations for SOM and clay content Many studies show that we also can predict properties such as pH and nutrients, although their robustness may be questioned For future work we recommend that research should focus on: (i) moving forward with more theoretical calibrations, (ii) better understanding of the complexity of soil and the physical basis for soil reflection, and (iii) applications and the use of spectra for soil mapping and monitoring, and for making inferences about soils quality, fertility and function To do this, research in soil spectroscopy needs to be more collaborative and strategic The development of the Global Soil Spectral Library might be a step in the right direction

/pdf/visible-and-near-infrared-spectroscopy-in-soil-science-l2f7v53g20.pdf

Visible and Near Infrared Spectroscopy in Soil Science

https://pubag.nal.usda.gov/download/25515/PDF

Global soil characterization with VNIR diffuse reflectance spectroscopy

Precision agriculture is the application of technologies and principles to manage spatial and temporal variability associated with all aspects of agricultural production for the purpose of improving crop performance and environmental quality. Success in precision agriculture is related to how well it can be applied to assess, manage, and evaluate the space-time continuum in crop production. This theme is used here to assess the current and potential capabilities of precision agriculture. Precision agriculture is technology enabled. It is through the integration of specific technologies that the potential is created to assess and manage variability at levels of detail never before obtainable and, when done correctly, at levels of quality never before achieved. The agronomic feasibility of precision agriculture has been intuitive, depending largely on the application of traditional management recommendations at finer scales, although new approaches are appearing. The agronomic success of precision agriculture has been limited and inconsistent although quite convincing in some cases, such as N management in sugar beet (Beta vulgaris L.). Our analysis suggests prospects for current precision management increase as the degree of spatial dependence increases, but the degree of difficulty in achieving precision management increases with temporal variance. Thus, management parameters with high spatial dependence and low temporal variance (e.g., liming, P, and K) will be more easily managed precisely than those with large temporal variance (e.g., mobile insects). The potential for economic, environmental, and social benefits of precision agriculture is complex and largely unrealized because the space-time continuum of crop production has not been adequately addressed.

Aspects of precision agriculture

with the Agricultural Research Service (ARS) and various government agencies and private institutions have provided a great deal of fundamental information relating spectral reflectance and thermal emittance properties of soils and crops to their agronomic and biophysical characteristics. This knowledge has facilitated the development and use of various remote sensing methods for non-destructive monitor- ing of plant growth and development and for the detection of many environmental stresses which limit plant productivity. Coupled with rapid advances in computing and position- locating technologies, remote sensing from ground-, air-, and space-based platforms is now capable of providing detailed spatial and temporal information on plant response to their local environment that is needed for site specific agricultural management approaches. This manuscript, which empha- sizes contributions by ARS researchers, reviews the biophysi- cal basis of remote sensing; examines approaches that have been developed, refined, and tested for management of water, nutrients, and pests in agricultural crops; and as- sesses the role of remote sensing in yield prediction. It con- cludes with a discussion of challenges facing remote sens- ing in the future.

/pdf/remote-sensing-for-crop-management-323qhffpqs.pdf

Remote Sensing for Crop Management

Recent breakthroughs in remote-sensing technology have led to the development of high spectral resolution imaging sensors for observation of earth surface features. This research was conducted to evaluate the effects of organic matter content and composition on narrowband soil reflectance across the visible and reflective infrared spectral ranges. Organic matter from four Indiana agricultural soils, ranging in organic C content from 0.99 to 1.72 percent, was extracted, fractionated, and purified. Six components of each soil were isolated and prepared for spectral analysis. Reflectance was measured in 210 narrow bands in the 400- to 2500-nm wavelength range. Statistical analysis of reflectance values indicated the potential of high dimensional reflectance data in specific visible, near-infrared, and middle-infrared bands to provide information about soil organic C content, but not organic matter composition. These bands also responded significantly to Fe- and Mn-oxide content.

High dimensional reflectance analysis of soil organic matter

Significance of organic matter in determining soil colors.

/pdf/effects-of-organic-matter-on-the-multispectral-properties-of-4l6omtdg8m.pdf

Effects of organic matter on the multispectral properties of soils

Spectral responses of two glaciated soils, Chalmers silty clay loam and Fincastle silt loam, formed under prairie grass and forest vegetation, respectively, were measured in the laboratory under controlled moisture equilibria using an Exotech Model 20C spectroradiometer to obtain spectral data in the laboratory under artificial illumination. The same spectroradiometer was used outdoors under solar illumination to obtain spectral response from dry and moistened field plots with and without corn residue cover, representing the two different soils. Results indicate that laboratory-measured spectra of moist soil are directly proportional to the spectral response of that same field-measured moist bare soil over the 0.52 micrometer to 1.75 micrometer wavelength range. The magnitudes of difference in spectral response between identically treated Chalmers and Fincastle soils are greatest in the 0.6 micrometers to 0.8 micrometer transition region between the visible and near infrared, regardless of field condition or laboratory preparation studied.

/pdf/extension-of-laboratory-measured-soil-spectra-to-field-2q09b05v2z.pdf

Extension of Laboratory-Measured Soil Spectra to Field Conditions

Soil cores taken at incremental depths from a Typic Hapludalf were examined to investigate the relationships among the chemical, physical, and spectral reflectance properties which occur as the proportion of various horizons change in the soil samples. Results of these studies were compared to soil samples taken from selected Typic Hapludalfs in Indiana which represented various degrees of natural erosion. Two important properties affecting the spectral reflectance of these soils were the organic matter and iron oxide contents. High organic matter contents tend to cause the reflectance to be low and give a concave character to the spectral response in the 0.5- to 0.8-µm region. High iron oxide content along with the reduction in organic matter tends to cause an increase in the overall spectral response; however, the presence of iron oxides causes a leveling off of the spectral response in the 0.8- to 1.1-µm region. Intermediate contents of organic matter and iron oxide affect the spectral response relative to their proportions within the soil sample. These distinctive reflectance characteristics can be related to the severity of erosion. Comparison of laboratory data to simulated Landsat data suggests that satellite multispectral scanner data can be useful in detecting eroded soils. Separability of erosion classes for the Alfisols studied was best determined by observing the slope of the simulated Landsat plots between 0.75 and 0.95 µm, bands 3 and 4. As the severity of erosion increases, the slope of the plot decreases in this region.

M. F. Baumgardner

Papers

High dimensional reflectance analysis of soil organic matter

Significance of organic matter in determining soil colors.

Effects of organic matter on the multispectral properties of soils

Extension of Laboratory-Measured Soil Spectra to Field Conditions

Characteristic Variations in Spectral Reflectance of Selected Eroded Alfisols