Near-Infrared Spectroscopy as a Rapid and Simultaneous Assessment of Agricultural Groundwater Quality Parameters (original) (raw)
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Assessment and monitoring of soil quality using near-infrared reflectance spectroscopy (NIRS
European Journal of Soil Science, 2009
Soil degradation processes have dramatically increased in their extent and intensity over the last decades. Progressively, actions have been taken in order to evaluate and reduce the major threats that have already wreaked havoc on soil conditions. Efficient and standardized monitoring of soil conditions is thus required but soil quality research is facing an important technological challenge because of the number of properties involved in soil quality. The objective of the present review is to examine critically the suitability of near-infrared reflectance spectroscopy (NIRS) as a tool for soil quality assessment. We first detail the soil quality-related parameters (chemical, physical and biological) that can be predicted with NIRS through laboratory measurements. The ability of imaging NIRS (airborne or satellite) for mapping a minimum data set of soil quality is also discussed. Then we review the most recent research using soil reflectance spectra as an integrated measure of soil quality, from global site classification to the prediction of specific soil quality indices. We conclude that imaging NIRS enables the direct mapping of some soil properties and soil threats, but that further developments to solve several technological limitations identified are needed before it can be used for soil quality assessment. The robustness of laboratory NIRS for soil quality assessment allows its implementation in soil monitoring networks. However, its routine use requires the development of international soil spectral libraries that should become a priority for soil quality research.RésuméEvaluation et surveillance de la qualité des sols par spectroscopie proche infrarouge (SPIR)Les processus de dégradation des sols ont fortement augmenté au cours des dernières décennies. Des mesures sont progressivement mises en place afin d’évaluer et de limiter l’impact des principales menaces qui ont déjà provoqué une diminution préoccupante de la qualité des sols. Des méthodes efficaces et standardisées de suivi de la qualité des sols sont donc indispensables, mais les nombreuses propriétés impliquées dans la qualité des sols compliquent son évaluation rigoureuse. L’objectif de cette revue est d’examiner le potentiel de la spectroscopie proche infrarouge (SPIR) comme outil rapide de caractérisation de la qualité des sols. Nous dressons d’abord l’inventaire des propriétés du sol liées à sa qualité qui sont prédictibles par des mesures SPIR en laboratoire. Le potentiel de l’imagerie embarquée SPIR (satellite, avion) est également abordé. Nous réalisons ensuite une synthèse des applications utilisant la réflectance spectrale des sols comme mesure intégrée de leur qualité, depuis la classification de sites selon leur état de dégradation jusqu’à la prédiction d’indices spécifiques de qualité du sol. Nous concluons que l’imagerie SPIR permet de cartographier quelques propriétés et menaces pesant sur les sols, mais les limites technologiques relevées exigent d’importants développements pour en faire un outil robuste d’évaluation de la qualité des sols. La fiabilité de la technique SPIR par mesures en laboratoire permet sa mise en œuvre rapide dans les réseaux de mesures de la qualité des sols. Toutefois, son utilisation en routine nécessitera le développement de librairies spectrales internationales, qui devrait constituer une des priorités de recherche sur la qualité des sols.
Canadian Journal of Soil Science, 2009
limitations of, near infrared reflectance spectroscopy applications in soil analysis: A review. Can. J. Soil Sci. 89: 531Á541. Near infrared reflectance spectroscopy (NIRS) is a cost-and time-effective and environmentally friendly technique that could be an alternative to conventional soil analysis methods. In this review, we focussed on factors that hamper the potential application of NIRS in soil analysis. The reported studies differed in many aspects, including sample preparation, reference methods, spectrum acquisition and pre-treatments, and regression methods. The most significant opportunities provided by NIRS in soil analysis include its potential use in situ, the determination of various biological, chemical, and physical properties using a single spectrum per sample, and an estimated reduction of analytical cost of at least 50%. Contradictory results among studies on NIRS utilisation in soil analysis are partly related to variations in sample preparation and reference methods. The following calibration statistics appear to be most appropriate for comparing NIRS performance across soil attributes: (i) coefficient of determination (r 2 ), (ii) ratio of performance deviation (RPD), (iii) coefficient of regression (b), and (iv) ratio of the standard error of prediction (SEP) to the standard error of the reference method (SER), i.e., the ratio of standard errors (RSE). Further investigations on issues such as (i) RSE guidelines, (ii) correlation between NIRS spectrophotometers, (iii) correlation of different reference methods for a given attribute to soil spectra, (iv) identification of key factors affecting the accuracy of NIRS predictions, and (v) efficient use of spectral libraries are required to enhance the acceptability of NIRS as a soil analysis technique and to make it more user-friendly. Standardized guidelines are proposed for the assessment of the accuracy of NIRS predictions of soil attributes.
Evaluating near infrared spectroscopy for field prediction of soil properties
This paper demonstrates the application of near infrared diffuse reflectance spectroscopy (NIR-DRS) measurements as part of digital soil mapping. We also investigate whether calibration functions developed from a spectral library can be used for rapid characterisation of soil properties in the field. Soil samples were collected along 24 toposequences in the Pokolbin irrigation district,~7 km 2 of predominantly agricultural land in the Hunter Valley, NSW, Australia. Soil samples at 2 depths: 0-0.10 and 0.40-0.50 m were collected. The soil samples were scanned using NIR under 3 different conditions: field condition, dried unground, and dried ground. A separate spectral library containing soil laboratory measurements was used to develop functions to predict 3 main soil properties from NIR spectra (total C content, clay content, and sum of exchangeable cations). The absorbance spectra were found to be different for the 3 soil conditions. The field spectra appear to have higher absorbance, followed by dried unground samples and then dried ground samples. Although most spectral signatures or peaks were similar for the 3 soil conditions, field samples appear to have higher absorbance, particularly at 1400 nm and 1900 nm. The convex hull of the first 2 principal components of the soil spectra is an easy tool to evaluate the similarity of spectra from a calibration set to an observation. For field prediction, samples need to be calibrated using field samples. Finally, this study shows that NIR-DRS measurement is a useful part of digital soil mapping.
2016
Visible and near-infrared reflectance spectroscopy (Vis-NIRS) technology has the potential to provide a reliable, cost effective and nondestructive analysis of soils in a short period of time. The ability of Vis-NIRS technology was invest igated to predict a range of soil properties in the Kazova watershed of middle Black Sea Region of Turkey. A total of 400 surface soil s amples (0-30 cm) collected from various crop rotations were used. Partial least squ ares regression (PLSR) method was used to develop c alibration models between reflectance spectral data obtained with a fiber-typ e Vis-NIR, Agro Spec spectrophotometer with a spect ral range of 350–2500 nm, and measured values of soil properties obtained using t raditional laboratory methods. Spectra were divided into calibration and prediction sets and the calibration spectra were subjected to a PLS R with leave-one-out cross validation using ParLeS 3.1 software. The performances of the methods were evaluated using the coefficien...
Wastewater salinity assessment using near infrared spectroscopy
The visible and near infrared spectroscopy is a fast and inexpensive non-destructive technique for the prediction of concentrations of salts in wastewater. Conventional chemical methods are usually used, which are very accurate, take more time and require special techniques for sampling, storing and pretreatment of wastewater. In this work we studied the spectral characteristics of water and the effect of salts on the perturbations in the water absorption bands. The generation of multiple regression models with principal components was carried out on standard solutions with composition of salts similar to that of wastewater samples taken along the drainage channel network of the Mexico City Metropolitan Area. The spectral signatures were obtained in situ and in the laboratory using a portable high-resolution spectroradiometer (ASD FieldSpec 3). The prediction model generated showed high precision in the estimation of salinity in wastewater, a coefficient of determination of 89.6% and a low root mean square error of 0.12‰. Other compounds, which are not discussed here, cause distortion of the absorption bands of water at wavelengths less than 900 nm or near the visible region, while our results showed distortions in the water spectrum at higher wavelengths (>1,000 nm).
Estimation of salinity wastewater using near infrared spectroscopy
2013
The visible and near infrared spectroscopy is a fast, and inexpensive non-destructive technique for the prediction of concentrations of salts in wastewater. Conventional chemical methods are usually used which are very accurate but take time and require special techniques for sampling, storing and pretreatment of wastewater. In this work we studied the spectral characteristics of water and the effect of salts on the perturbations in the water absorption bands. The generation of multiple regression models with principal components (PCR) was carried out on standard solutions with composition of salts similar to that of wastewater samples taken along the drainage channel network of the Mexico City Metropolitan Area. The spectral signatures were obtained in situ and laboratory using a portable highresolution spectroradiometer (ASD FieldSpect3). The prediction model generated showed high precision in the estimation of salinity in wastewater, a coefficient of determination of 89.6% and a ...
Prediction of soil organic matter and clay contents by near-infrared spectroscopy - NIRS
Ciência Rural
ABSTRACT: Among the soil constituents, special attention is given to soil organic matter (SOM) and clay contents, since, among other aspects, they are key factors to nutrient retention and soil aggregates formation, which directly affect the crop production potential. The methods commonly used for the quantification of these constituents have some disadvantages, such as the use of chemical reactants and waste generation. An alternative to these methods is the near-infrared spectroscopy (NIRS) technique. The aim of this research is to evaluate models for SOM and clay quantification in soil samples using spectral data by NIRS. A set (n = 400) of soil samples previously analyzed by traditional methods were used to generate a NIRS calibration curve. The clay content was determined by the hydrometer method while SOM content was determined by sulfochromic solution. For calibration, we used the original spectra (absorbance) and spectral pretreatment (Savitzky-Golay smoothing derivative) in...
Adnan Menderes Üniversitesi Ziraat Fakültesi Dergisi, 2017
Due to the global climate change, salinity is in arid and semi-arid climates a major problem for the soils. In this connection it is very important to determine the organic carbon content in saline soils. This is aimed at the study that prediction of the organic carbon content in saline soils using NIRS and to evaluate the success of near infrared reflection spectroscopy (NIRS). NIRS device of 116 soil samples from different levels of soil salinity were collected between (350-2500 nm). Partial Least Square (PLS) regression analysis was used to conclude between the results obtained from the reflection values and traditional analyses methods at the laboratoary. NIRS calibrations were developed with modified partial least square regression and tested with independent validation samples. The best equations were obtained with the first derivative of the spectra without scatter corrections. The results obtained from the experiment concluded that soils of resource area texture, organic matter, CaCO 3 and salinity are affects on the reflection values. Good predictions were obtained for organic carbon contents in salt effected soils. According to the results obtained from the study, NIRS could be used as a practical and economic technique to predict organic carbon contents in salt effected soils.
2018
Soil salinization is the primary obstacle to the sustainable development of agriculture and eco-environment in arid regions. The accurate inversion of the major water-soluble salt ions in the soil using visible-near infrared (VIS-NIR) spectroscopy technique can enhance the effectiveness of saline soil management. However, the accuracy of spectral models of soil salt ions turns out to be affected by high dimensionality and noise information of spectral data. This study aims to improve the model accuracy by optimizing the spectral models based on the exploration of the sensitive spectral intervals of different salt ions. To this end, 120 soil samples were collected from Shahaoqu Irrigation Area in Inner Mongolia, China. After determining the raw reflectance spectrum and content of salt ions in the lab, the spectral data were pre-treated by standard normal variable (SNV). Subsequently the sensitive spectral intervals of each ion were selected using methods of gray correlation (GC), ste...
Soil characterization by near-infrared spectroscopy and principal component analysis
REVISTA CIÊNCIA AGRONÔMICA, 2021
This research aimed to use principal component analysis (PCA) as an exploratory method for spectral data of soil absorbance from the Baturité Massif and Central Hinterland (Ceará State, Brazil) to verify the potential of the technique in soil characterization. We analyzed 46 soil samples from different areas (native and cultivated). Each sample was analyzed in two particle sizes: 2 and 0.2 mm. We obtained spectral data by near-infrared spectroscopy (NIR), selecting the 1,360-2,260 nm range (2,376 variables). We evaluated three data pretreatment methods: multiplicative scatter correction (MSC), first derivative, and second derivative of the Savitzky-Golay filter. The absorption bands observed were: 1,414 nm (C-H stretching and deformation combination), 1,450 nm (O-H associated with the carbon chain), 1,780 nm (second overtone of C-H), 1,928 nm (O-H associated with molecular water), and 2,208 nm (C-H stretch and C=O combination). The best pretreatment was verified using only the multiplicative scatter correction (MSC). Two principal components explained 98% of the data variability, being the first principal component (PC1) related to the characteristic band of moisture, with negative values in the 1,928 nm region, while the second principal component (PC2) was related to the total organic matter (OM) originating from the C-H, C=O, and N-H bonds, wavelength region 1,414 nm. The PCA allowed characterizing the samples in terms of moisture and OM contents, with emphasis on soils under irrigated agroforestry system with higher values of moisture and OM, while the soil in degradation process presented lower values for these attributes. The NIR spectroscopy, associated with data processing methods (PCA and MSC), allows identifying changes in soil attributes, such as moisture and OM.