scholarly journals Detection of Parasitised Fly Puparia Using near Infrared Spectroscopy

2000 ◽  
Vol 8 (4) ◽  
pp. 259-265 ◽  
Author(s):  
Floyd E. Dowell ◽  
Alberto B. Broce ◽  
Feng Xie ◽  
James E. Throne ◽  
James E. Baker

Near infrared (NIR) spectroscopy was used to identify house fly ( Musca domestica L.) puparia that contained viable parasitoids. Results derived from a partial least squares analysis of NIR spectra showed that about 80–90% of puparia containing parasitoids could be identified correctly. Difference spectra and beta coefficients indicated that absorption differences between parasitised and unparasitised puparia may have been due to moisture content and/or differences in composition of chitin or lipid components. Detection of viable hymenopterous parasitoids within puparia could assist commercial insectaries in delivering known quantities of parasitised puparia for biological control of house flies and other filth flies and in rapidly determining levels of parasitisation of these flies in confined livestock and poultry operations.

2021 ◽  
Author(s):  
Ekaterina Tounis

Near-infrared spectroscopy can characterize wood surfaces fast and without significant surface preparation. It is based on molecular overtone and combination vibrations which are typically very broad, leading to complex spectra. Multivariate calibration techniques are often employed to extract the desired chemical information. This study focused on the potential of near-infrared spectroscopy combined with partial least squares for identifying and sorting wood with respect to species and physical properties and on the effects of wood preparation and weathering on the precision of analysis. It was shown that a range of moisture content values and artificial weathering periods could be well predicted indepenedently of wood species analyzed. Species within the spruce-pine-fir species group could be predicted reasonably well when tested under similar conditions. When different moisture contents and weathering exposure periods were introduced, species prediction was still possible, but, with decreased prediciton ability.


2021 ◽  
Author(s):  
Ekaterina Tounis

Near-infrared spectroscopy can characterize wood surfaces fast and without significant surface preparation. It is based on molecular overtone and combination vibrations which are typically very broad, leading to complex spectra. Multivariate calibration techniques are often employed to extract the desired chemical information. This study focused on the potential of near-infrared spectroscopy combined with partial least squares for identifying and sorting wood with respect to species and physical properties and on the effects of wood preparation and weathering on the precision of analysis. It was shown that a range of moisture content values and artificial weathering periods could be well predicted indepenedently of wood species analyzed. Species within the spruce-pine-fir species group could be predicted reasonably well when tested under similar conditions. When different moisture contents and weathering exposure periods were introduced, species prediction was still possible, but, with decreased prediciton ability.


Recycling ◽  
2021 ◽  
Vol 6 (1) ◽  
pp. 11
Author(s):  
Kirsti Cura ◽  
Niko Rintala ◽  
Taina Kamppuri ◽  
Eetta Saarimäki ◽  
Pirjo Heikkilä

In order to add value to recycled textile material and to guarantee that the input material for recycling processes is of adequate quality, it is essential to be able to accurately recognise and sort items according to their material content. Therefore, there is a need for an economically viable and effective way to recognise and sort textile materials. Automated recognition and sorting lines provide a method for ensuring better quality of the fractions being recycled and thus enhance the availability of such fractions for recycling. The aim of this study was to deepen the understanding of NIR spectroscopy technology in the recognition of textile materials by studying the effects of structural fabric properties on the recognition. The identified properties of fabrics that led non-matching recognition were coating and finishing that lead different recognition of the material depending on the side facing the NIR analyser. In addition, very thin fabrics allowed NIRS to penetrate through the fabric and resulted in the non-matching recognition. Additionally, ageing was found to cause such chemical changes, especially in the spectra of cotton, that hampered the recognition.


2011 ◽  
Vol 301-303 ◽  
pp. 1093-1097 ◽  
Author(s):  
Shi Rong Ai ◽  
Rui Mei Wu ◽  
Lin Yuan Yan ◽  
Yan Hong Wu

This study attempted the feasibility to determine the ratio of tea polyphenols to amino acids in green tea infusion using near infrared (NIR) spectroscopy combined with synergy interval PLS (siPLS) algorithms. First, SNV was used to preprocess the original spectra of tea infusion; then, siPLS was used to select the efficient spectra regions from the preprocessed spectra. Experimental results showed that the spectra regions [7 8 18] were selected, which were out of the strong absorption of H2O. The optimal PLS model was developed with the selected regions when 6 PCs components were contained. The RMSEP value was equal to 0.316 and the correlation coefficient (R) was equal to 0.8727 in prediction set. The results demonstrated that NIR can be successfully used to determinate the ration of tea polyphenols to amino acids in green tea infusion.


2019 ◽  
Vol 27 (4) ◽  
pp. 286-292
Author(s):  
Chongchong She ◽  
Min Li ◽  
Yunhui Hou ◽  
Lizhen Chen ◽  
Jianlong Wang ◽  
...  

The solidification point is a key quality parameter for 2,4,6-trinitrotoluene (TNT). The traditional solidification point measurement method of TNT is complicated, dangerous, not environmentally friendly and time-consuming. Near infrared spectroscopy (NIR) analysis technology has been applied successfully in the chemical, petroleum, food, and agriculture sectors owing to its characteristics of fast analysis, no damage to the sample and online application. The purpose of this study was to study near infrared spectroscopy combined with chemometric methods to develop a fast and accurate quantitative analysis method for the solidification point of TNT. The model constructed using PLS regression was successful in predicting the solidification point of TNT ([Formula: see text] = 0.999, RMSECV = 0.19, RPDCa = 33.5, [Formula: see text] = 0.19, [Formula: see text] = 0.999). Principal component analysis shows that the model could identify samples from different reactors. The results clearly demonstrate that the solidification point can be measured in a short time by NIR spectroscopy without any pretreatment for the sample and skilled laboratory personnel.


2011 ◽  
Vol 65 (9) ◽  
pp. 1056-1061 ◽  
Author(s):  
Sharon L. P. Sakirkin ◽  
Cristine L. S. Morgan ◽  
James C. MacDonald ◽  
Brent W. Auvermann

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