Estimating the Food Processing Characteristics of Pulses by near Infrared Spectroscopy, Using Ground or Whole Samples

1998 ◽  
Vol 6 (1) ◽  
pp. 213-220 ◽  
Author(s):  
P.C. Flinn ◽  
R.G. Black ◽  
L. Iyer ◽  
J.B. Brouwer ◽  
C. Meares

The use of near infrared spectroscopy (NIR) was investigated for its ability to predict a range of chemical constituents (protein, moisture, fat, ash, total dietary fibre) and functional properties (100 seed weight, hydration capacity, hull percentage, dehulling efficiency, colour, cooking quality) of field peas and chickpeas. NIR calibrations were developed using 165 samples of field peas and 151 samples of chickpeas which had been spectrally selected from larger populations encompassing two seasons. For both species, calibration accuracy was generally better on ground than whole samples for chemical composition, but better on whole than ground samples for physical or functional properties. For most properties measured, accuracy of NIR calibrations was either satisfactory or promising, but successful implementation in a breeding programme will depend on further evaluation using independent samples, broadening the sample populations or improvements in the reference methods.

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.


2019 ◽  
pp. 289-294
Author(s):  
S.H.E.J. Gabriels ◽  
B. Brouwer ◽  
H. de Villiers ◽  
E. Westra ◽  
E.J. Woltering

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