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Soil is critical to the world, supplying virtually all of the food and fiber that sustain the human population and providing the space for the ecosystems that support life. The characterization of soil properties through laboratory analysis is an essential part of the diagnosis of the potential use of lands and their fertility. However, conventional soil chemical analyses are expensive and time consuming, hampering the adoption of soil management practices. In recent years, farmers are also increasingly demanding rapid, cost-effective, and nondestructive methods for monitoring changes as well as measuring the physical–chemical properties in soils. This article reviews applications of near infrared (NIR) spectroscopy to assess, monitor, and classify soils in South America. [ABSTRACT FROM AUTHOR]

The aim of the experiment was to study diurnal variation in water-soluble carbohydrate (WSC) concentrations in leaf and stem of tall fescue and lucerne in autumn and to determine the impact of these changes on the rate and the extent of in vitro fermentation. Vegetative herbage of lucerne and tall fescue were sampled at 0900, 1300 and 1700 h, following three consecutive regrowths between April and May. Whole plants, leaf and stem were analysed for chemical composition and in vitro gas production. There was a linear increase in WSC throughout the day for all plants and plant components (P< 0.001). In both fescue and lucerne, this rise resulted in an increased rate of gas production, although this relationship was more pronounced in fescue. Use of time of day to govern grazing management decisions to potentially improve the rumen supply of WSC and nitrogen in autumn can be achieved from tall fescue or lucerne pastures. [ABSTRACT FROM AUTHOR]

As a fast and easy-to-operate technique, infrared (IR) spectroscopy has gained wide industrial acceptance for routine wine analysis. Considering the continuing improvements in hardware and software design and the analytical requirements of real-time or multiparametric analysis by the modern grape and wine industry, it is anticipated that in the near future IR spectroscopy will progressively become a routine method for process monitoring and process control in different stages of grape and wine production. This review highlights recent developments and applications of IR spectroscopy (near- and mid-infrared) to measure compositional parameters in wine grapes, grape juice, and grapevine tissues (e.g., leaves, stems, grapevine wood). In addition, some critical aspects and limitations in instrument availability, type of application, and overall understanding of the technology, which can be barriers for adoption of IR technologies by the grape and wine industry, will be discussed. [ABSTRACT FROM AUTHOR]

This study reports the use of near-infrared (NIR) reflectance spectroscopy combined with two-dimensional correlation (2D-COS) spectroscopy to monitor the effect of soaking and water uptake by the barley endosperm (Hordeum vulgare, L). The synchronous 2D-COS maps derived from the NIR spectra of barley endosperm showed similarities that could be explained by the regions in the spectra associated with water as well as with the biochemical and biophysical changes as a consequence of the water uptake by the grain. The results also demonstrated the potential of 2D-COS combined with NIR spectroscopy as an analytical tool to study changes in the biophysical characteristics of whole barley during steeping or soaking. This method can be used to obtain information about the effect of water uptake in other chemical characteristics of the endosperm of cereal grains. [ABSTRACT FROM PUBLISHER]

This study evaluated an in-field near-infrared (NIR) instrument to predict the contents of total nitrogen (TN), organic carbon (OC), potassium (K), sulfur (S), phosphorus (P), pH, and electric conductivity (EC) in soil vineyard samples (n = 70) sourced from three wine regions of Australia. Samples were analyzed using a portable NIR spectrophotometer (ASD FieldSpec III, 350–1800 nm). Partial least squares (PLS) regressions yield a coefficient of determination in calibration (R2) and a standard error in cross validation (SECV) of 0.74 (0.03) for TN, 0.92 (2.19) for S, 0.81 (0.42) for OC, 0.70 (109.2) for K, 0.84 (0.03) for EC, 0.83 (0.44) for pH, and 0.69 (24.6) for P, respectively. This study showed that it is possible to measure soil chemical properties in the vineyard, and the main advantages of this approach will be the speed, low cost, and ability to better manage and monitor soil fertility. [ABSTRACT FROM AUTHOR]

Abstract: Verification of the authenticity of natural and agricultural foods has become a potential application of spectroscopic methods such as ultraviolet (UV), visible (VIS), near infrared (NIR), and mid-infrared (MIR). Adulteration can take many forms, including the addition of sugars, acids, volatile oils, overdilution of concentrate, addition of juices of other fruits, use of concentrate in a fresh product, and use of low-quality product recovered from what are normally waste products of manufacture. Food adulteration has been practiced since ancient times but has become more sophisticated in the recent past. Foods or ingredients most likely to be targets for adulteration include those that are of high value or subject to the vagaries of weather during their growth or harvest. The practice of adulteration commonly arises for two main reasons: firstly, it can be profitable, and secondly, adulterants can be easily mixed and are subsequently difficult to detect. To counter this problem, manufacturers subject their raw material and by-products to a series of quality controls, including high-performance liquid chromatography (HPLC), thin-layer chromatography (TLC), enzymatic tests, and physical tests. This mini-review highlights recent applications on the use of NIR and MIR spectroscopy to trace and authenticate natural and agricultural products. [ABSTRACT FROM PUBLISHER]

Commercial meat pate samples, comprised of 100% pork (n = 7), 100% beef (n = 5) meat, and binary mixtures (beef and pork, w/w) (n = 18) were used. Fresh samples were analysed in a scanning spectrophotometer NIRSystems 6500 in reflectance mode (1100-2500 nm). Principal component analysis (PCA) and stepwise linear discriminant analysis (SLDA) were used to classify samples according to the animal species based on their near infrared reflectance (NIR) spectra. Full cross validation was used as validation method when classification models were developed. Both beef and pork pate samples were classified correctly (100%) while binary mixture samples only achieved 72% of correct classification using SLDA technique. The results demonstrated the usefulness of NIR spectra combined with chemometrics as an objective and rapid method to classify pate samples according to meat type. Nevertheless, NIR spectroscopic methods might provide initial screening in the food chain and enable more costly methods to be used more efficiently. Se utilizaron muestras de pates de carne comerciales, compuestos de 100% carne de cerdo (n = 7), 100% carne de buey (n = 5) y mezclas binarias (buey y cerdo) (n = 18). Las muestras frescas se analizaron en un espectrofotometro de escaneo NIRSystems 6500 en modo reflectante (1100-2500 nm). El analisis de componente principal (PCA) y el analisis discriminante lineal progresivo (SLDA) se usaron para clasificar muestras de segun las especie animal basandose en sus espectros NIR. La validacion cruzada completa se utilizo como metodo de validacion cuando se desarrollaron metodos de clasificacion. Las muestras de ambos pates, de buey y cerdo, se clasificaron correctamente (100%), mientras las muestras de mezcla binaria solo alcanzaron un 72% de clasificacion correcta usando la tecnica SLDA. Los resultados mostraron la utilidad del espectro NIR combinado con quimometria como un objetivo y metodo rapido para clasificar muestras de pate segun el tipo de carne. Sin embargo, los metodos espectroscopicos NIR podrian proveer una revision inicial de la cadena de comida y permitir que metodos costosos fuesen usados mas eficientemente. [ABSTRACT FROM AUTHOR]

Honey is a carbohydrate-rich syrup and viscous fluid produced by honeybees (Apis mellifera) from the nectar of flowers that, by definition, does not include any other substances. Honey is produced primarily from floral nectars, and fructose and glucose are the major components. Overall, the chemical composition of honey varies depending on plant source, season, production methods, and storage conditions. Analytical methods applied to honey generally deal with different topics such as determination of botanical or geographical origin, quality control according to the current standards, and detection of adulteration or residues. Traditional chemical composition analysis and physical properties assessment are routinely performed in commercial trading of honey using time-consuming analytical methods that require considerable sample preparation and analytical skills. Spectroscopic techniques in the infrared (IR) wavelength region of the electromagnetic spectrum have been used in the food industry to monitor and evaluate the composition of foods and are becoming one of the most attractive and commonly used methods of analysis. This review discusses the use, with advantages and limitations, of IR spectroscopy technologies to evaluate and monitor the composition of honey. [ABSTRACT FROM PUBLISHER]

This study evaluates the effect of soil particle size (SPS) on the measurement of exchangeable sodium (Na) (EXC-Na) by near-infrared reflectance (NIR) spectroscopy. Three hundred thirty-two (n = 332) top soil samples (0-10 cm) were taken from different locations across Uruguay, analyzed by EXC-Na using emission spectrometry, and scanned in reflectance using a NIR spectrophotometer (1100-2500 nm). Partial least squares (PLS) and principal component regression (PCR) models between reference chemical data and NIR data were developed using cross validation (leaving one out). The coefficient of determination in calibration (R2) and the root mean square of the standard error of cross validation (RMSECV) for EXC-Na concentration were 0.44 (RMSECV: 0.12 mg kg-1) for soil with small particle size (SPS-0.053) and 0.77 (RMSECV: 0.09 mg kg-1) for soils with particle sizes greater than 0.212 mm (SPS-0.212), using the NIR region after second derivative as mathematical transformation. The R2 and RMSECV for EXC-Na concentration using PCR were 0.54 (RMSECV: 0.07 mg kg-1) and 0.80 (RMSECV: 0.03 mg kg-1) for SPS-0.053 and SPS-0.212 samples, respectively. [ABSTRACT FROM AUTHOR]

The use of ultraviolet (UV), visible (VIS), near infrared reflectance (NIR), and midinfrared (MIR) spectroscopy techniques have been found to be successful in determining the concentration of several chemical properties in soils. The aim of this study was to evaluate the effect of two reference methods, namely Bray and Resins, on the VIS and NIR calibrations to predict phosphorus in soil samples. Two hundred (n=200) soil samples were taken in different years from different locations across Uruguay with different physical and chemical characteristics due to different soil types and management. Soil samples were analyzed by two reference methods (Bray and Resins) and scanned using an NIR spectrophotometer (NIRSystems 6500). Partial least square (PLS) calibration models between reference data and NIR data were developed using cross-validation. The coefficient of determination in calibration (R2) and the root mean square of the cross validation (RMSECV) were 0.58 (RMSECV: 3.78 mg kg-1) and 0.61 (RMSECV: 2.01 mg kg-1) for phosphorus (P) analyzed by Bray and Resins methods, respectively, using the VIS and NIR regions. The R2 and RMSECV for P using the NIR region were 0.50 (RMSECV: 3.78 mg kg-1) and 0.58 (RMSECV: 2.01 mg kg-1). This study suggested that differences in accuracy and prediction depend on the method of reference used to develop an NIR calibration for the measurement of P in soil. [ABSTRACT FROM AUTHOR]

Abstract The field of analytical chemistry has been significantly advanced by the availability of state-of-the-art instrumentation, allowing for the development of novel applications in this field. However, in many cases, the direct interpretation of the recorded data is often not straightforward, hence some level of pre-processing is required (e.g., baseline correction, derivatives, normalization, smoothing). These techniques have become a critical first step for the successful analysis of the data recorded, and it is recommended to use them before the application of chemometrics (e.g., classification, calibration development). The aim of this paper is to provide with an overview of the most used pre-processing methods applied to instrumental analytical methods (e.g., spectroscopy, chromatography). Examples of their application in near infrared and UV-VIS spectroscopy as well as in gas chromatography will be also discussed. Overall, this paper provides with a comprehensive understanding of pre-processing techniques in analytical chemistry, highlighting their importance during the analysis and interpretation of data, as well as during the development of accurate and reliable chemometric models. [ABSTRACT FROM AUTHOR]