Predicting the nutritional quality of feed ingredients for pigs using near-infrared spectroscopy (NIRS) and chemical analysis

Capacity to routinely, accurately and cost-effectively measure variation in the nutritional quality of feed ingredients before diet formulation represents a fundamental pillar of sustainable pork production worldwide. Factors driving sustainable pork production include pork price, feed cost, utilisation of co-products and downgraded raw materials and variation in pork production, with all being related to the definition and ultimate nutritional quality of feed ingredients. The present paper defines rapid measures of nutritional quality in feed ingredients for pigs and demonstrates the range that can exist in these parameters, specifically digestible energy of cereal grains and the reactive-lysine concentration of oilseed meals. It provides an overview of the development of near-infrared spectroscopy (NIRS) calibrations for key nutritional-quality parameters and how they are being applied by the pork industry. Adjunct ways to measure nutritional quality of feed ingredients for pigs such as the glucose-release index and how these can be used in conjunction with NIRS are reviewed. The paper reports advanced correlation analysis between chemical components and digestible-energy concentration of cereals, and how these could be used for screening of NIRS outliers, and discusses future opportunities for application of nutritional-quality analysis using NIRS calibrations, including feed intake and portable solutions. Using advanced NIRS calibrations for digestible energy in cereals and reactive lysine in oilseed meals, pork producers will ensure that they make best use of limited resources and, as a consequence, pork will remain a nutritionally accretive food source for increasingly discerning consumers worldwide.

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Use of Near-Infrared Spectroscopy for On-Line Monitoring the Quality of Prepreg Cloth

Advanced Composites Letters ◽

10.1177/096369350801700201 ◽

2008 ◽

Vol 17 (2) ◽

pp. 096369350801700 ◽

Cited By ~ 2

Author(s):

Wei Li ◽

Yu Dong Huang ◽

Ping Chen

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Resin Content ◽

Quality Analysis ◽

Volatile Content ◽

On Line ◽

Spectral Ranges ◽

Major Emphasis

On-line monitoring the prepreg quality in the polymer composite industry continues to be a major emphasis, it will reduce the amount of prepreg manufactured under “outside specifications”. A near-infrared spectroscopy has been implemented for measurement of resin content, pre-curing degree of resin and volatile content during the manufacture of glass/phenolic resin prepreg cloth. The regression method employed was partial least squares (PLS). The optimum models were obtained by selecting different spectral pretreatments and spectral ranges. The determination coefficients (R2) for the resin content, pre-curing degree and volatile content were 98.36, 98.76 and 98.33, respectively. The root mean squares of cross-validation (RMSECV) were 0.364, 0.145 and 0.182 respectively for the resin content, pre-curing degree and volatile content, respectively. The NIR method was applied to monitor the quality of prepreg cloth on line. The results showed that the monitored values were closed to the actual values. The study indicates that the on-line quality analysis of prepreg cloth was realised by using NIR technique.

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Textile Recognition and Sorting for Recycling at an Automated Line Using Near Infrared Spectroscopy

Recycling ◽

10.3390/recycling6010011 ◽

2021 ◽

Vol 6 (1) ◽

pp. 11

Author(s):

Kirsti Cura ◽

Niko Rintala ◽

Taina Kamppuri ◽

Eetta Saarimäki ◽

Pirjo Heikkilä

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Near Infrared ◽

Nir Spectroscopy ◽

Automated Recognition ◽

Textile Materials ◽

Input Material ◽

Adequate Quality ◽

Automated Line

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.

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