Application of near infrared spectroscopy to peanut grading and quality analysis: overview

2009 ◽  
Vol 3 (3) ◽  
pp. 156-164 ◽  
Author(s):  
Jaya Sundaram ◽  
Chari V. Kandala ◽  
Christopher L. Butts
2018 ◽  
Vol 58 (4) ◽  
pp. 709 ◽  
Author(s):  
R. J. van Barneveld ◽  
H. Graham ◽  
S. Diffey

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.


2008 ◽  
Vol 17 (2) ◽  
pp. 096369350801700 ◽  
Author(s):  
Wei Li ◽  
Yu Dong Huang ◽  
Ping Chen

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.


Molecules ◽  
2021 ◽  
Vol 26 (3) ◽  
pp. 749
Author(s):  
Jian Zeng ◽  
Yuan Guo ◽  
Yanqing Han ◽  
Zhanming Li ◽  
Zhixin Yang ◽  
...  

Near-infrared spectroscopy (NIRS) combined with pattern recognition technique has become an important type of non-destructive discriminant method. This review first introduces the basic structure of the qualitative analysis process based on near-infrared spectroscopy. Then, the main pretreatment methods of NIRS data processing are investigated. Principles and recent developments of traditional pattern recognition methods based on NIRS are introduced, including some shallow learning machines and clustering analysis methods. Moreover, the newly developed deep learning methods and their applications of food quality analysis are surveyed, including convolutional neural network (CNN), one-dimensional CNN, and two-dimensional CNN. Finally, several applications of these pattern recognition techniques based on NIRS are compared. The deficiencies of the existing pattern recognition methods and future research directions are also reviewed.


2012 ◽  
pp. 97-100
Author(s):  
Éva Kónya ◽  
Géza Kovács ◽  
Zoltán Győri

The near infrared spectroscopy is widely used in the different industries as a rapid, non-invasive analitical tool. It is suitable for identification, qualification and quantitative analysis as well. As this technique is indirect, to make accurate calibration equations we need a proper sample population. Before the quantitaive analysis, developing calibiration modells we have to collect and examine the spectra. In our study we examined wheat samples with known origins to find if there is any effect of the growing area on the NIR spectra.


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