This study investigated the detection of contamination of animal feed by melamine and its derivatives by rapid analytical methods. The main goal was to propose an effective tool to detect contaminantion by using multivariate calibration equations built on a large database of non-contaminated feed ingredients. Soybean meal, maize gluten and wheat gluten samples were contaminated by different percentages of melamine and cyanuric acid. The influence of these additives on near infrared (NIR) predicted values of crude protein was studied. The predicted values of protein, in terms of the adulteration percentage, were compared with those obtained by conventional methods (Kjeldahl and Dumas). The addition of the contaminant led to an increase in the protein value when measured by classical methods and to a decrease in the value when predicted by the NIR calibration models. Among the modifications in the spectral profile of affected feed was the intensity of the spectrum at about 2170 nm, characteristic of the absorption of proteins which might explain the reduction in NIR predicted protein values when contaminants were added. An important advantage of the approach is the simultaneous detection of several analytes, making it possible to detect melamine and cyanuric acid at the same time. Contaminated feed was analysed using the near infrared (NIR) general feed ingredient database. Calibration equations were developed and applied to the samples in this study to visualise their distribution with regard to the existing data set that does not contain contaminants. Contaminated samples presented global H (GH) (Mahalanobis distance) values greater than three and were easily distinguished from the rest. Both the full spectrum and a selected spectral region between 2130 nm and 2230 nm, including wavelengths relevant for discrimination, were used to develop mathematical equations to predict the protein content and to detect contaminated samples.
The Foss NIRSystem 6500 is one of the most commonly used laboratory instruments in agriculture and in particular in feed. New technological developments include micro-electro mechanical system (MEMS) technology, used in miniature handheld instruments such as the Polychromix Phazir spectrometer that are increasingly required for on-site analysis. The objective of this study was to assess the potential of a calibration transfer from the Foss NIRSystem 6500 to the Polychromix Phazir. The results show that good calibration models were obtained for various feed properties (fat, fiber, protein, and starch) developed on a Foss NIRSystem 6500, based on a spectral database of 9164 samples transferred to a Polychromix Phazir handheld spectrometer.
There have been a number of recent developments in NIR technology which may prove to be significant in the near future. The overall objective of this work is to compare the performance of different NIR devices (i.e. bench-top, hyperspectral imaging and pocket NIR spectrometers) for the determination of a classical quality parameter, the protein content. In order to achieve this goal, several studies have been carried out with the different instrumentation on wheat flours (selected as a "homogeneous" product). These studies should determine if NIR hyperspectral imaging and NIR pocket instruments are as efficient as classical NIR bench-top instruments for predicting protein content.
The purpose of this study was to evaluate two different locally based regression methods (LOCAL and Local Calibration by Customized Radii Selection) and compare their performance to the classical global PLS for large NIR data. The data used in this study came from two inter-laboratory studies for wheat grain analysis organized in 2016 in the framework of the REQUASUD network. The results showed that improved predictions in terms of prediction errors can be obtained using local approaches compared to the classical global PLS. Moreover, the study highlighted clear differences between inter-laboratory studies and participating laboratories, which were even more evident when working with local procedures.
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