A rapid screening method for determining the digestibility of kale using near infrared reflectance

1983 ◽  
Vol 34 (2) ◽  
pp. 175-180 ◽  
Author(s):  
Michael J. Allison
Keyword(s):  
Near Infrared ◽  
Screening Method ◽  
Rapid Screening ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Rapid Screening Method

scholarly journals Diagnostic ability of confocal near-infrared reflectance fundus imaging to detect retrograde microcystic maculopathy from chiasm compression. A comparative study with OCT findings

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0253323
Author(s):  
Mário L. R. Monteiro ◽  
Rafael M. Sousa ◽  
Rafael B. Araújo ◽  
Daniel Ferraz ◽  
Mohammad A. Sadiq ◽  
...  
Keyword(s):  
Optic Atrophy ◽  
Near Infrared ◽  
Screening Method ◽  
Fundus Photography ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance ◽  
Chiasmal Compression ◽  
Fundus Imaging ◽  
Cell Layers ◽  
Level Of Agreement

Purpose To evaluate the ability of confocal near-infrared reflectance (NIR) to diagnose retrograde microcystic maculopathy (RMM) in eyes with temporal visual field (VF) loss and optic atrophy from chiasmal compression. To compare NIR findings with optical coherence tomography (OCT) findings in the same group of patients. Methods Thirty-four eyes (26 patients) with temporal VF loss from chiasmal compression and 41 healthy eyes (22 controls) underwent NIR fundus photography, and macular OCT scanning. VF loss was estimated and retinal layers thickness were measured on OCT. Two examiners blinded to the diagnosis randomly examined NIR images for the presence of hyporeflective abnormality (HA) and OCT scans for the presence of microcystic macular abnormalities (MMA). The total average and hemi-macular HA area and number of microcysts were determined. The groups were compared and the level of agreement was estimated. Results The OCT-measured macular retinal nerve fiber and ganglion cell layers were thinner and the inner nuclear layer was thicker in patients compared to controls. HA and MMA were detected in 22 and 12 patient eyes, respectively, and in 0 controls (p<0.001, both comparisons). HA was significantly more frequent than MMA in patients with optic atrophy, and agreement between HA and MMA (both total and hemi-macular) was fair (kappa range: 0.24–0.29). The mean HA area was significantly greater in the nasal than temporal hemi-macula. A re-analysis of the 14 eyes with discrepant findings allowed to confirm RMM in 20 eyes (20/34) indicating that OCT detected RMM in 12 and missed it in 8 eyes. On the other hand, NIR correctly detected 18 out of 20 eyes, overcalled 4 and missed 2. Conclusions RMM is a frequent finding in eyes with severe VF loss from long-standing chiasmal compression. NIR photography appears to be more sensitive than OCT for detecting RMM and may be useful as screening method for its presence.

Application of Near Infrared Reflectance Spectroscopy to Compositional Analysis of Commercial Pig Feed Mixes

1987 ◽  
Vol 70 (3) ◽  
pp. 420-423
Author(s):  
Shih-Ling Y Chen ◽  
Ali Hsu ◽  
Mane-Lane Lee
Keyword(s):  
Near Infrared ◽  
Screening Method ◽  
Compositional Analysis ◽  
Correlation Coefficients ◽  
Reflectance Spectroscopy ◽  
Infrared Reflectance ◽  
Near Infrared Reflectance Spectroscopy ◽  
Near Infrared Reflectance ◽  
Infrared Reflectance Spectroscopy ◽  
Pig Feed

Abstract Official samples of commercial pig feed mixes taken for routine inspection were analyzed by near infrared reflectance spectroscopy (NIRS). Separate calibrations were established for pre-starting pig, starting pig, growing pig, finishing pig, and lactating sow feeds. Mean correlation coefficients and standard errors of calibration, respectively, obtained by comparing NIRS values with conventional chemical analysis values, were as follows: calibration set (about 35 samples per category)-moisture 0.87,0.44%; protein 0.90,0.75%; fiber 0.8b, 0.49%; analytical set (about 15 samples per category)—moisture 0.73, 0.42%; protein 0.90, 0.72%; fiber 0.83, 0.40%. Mean coefficients of variation for NIRS were moisture 3.9%, protein 4.2%, and fiber 14.8%; those for conventional analyses were moisture 2.7%, protein 1.1%, and fiber 11.7%. The results indicated that for moisture, protein, and fiber determinations in commercial pig feed mix products with various and unknown formulations, successful rapid NIRS analysis could be achieved by using a filter-type spectrometer and advanced mathematical data treatments. Among 246 samples inspected, protein content in 70% of them exceeded by 1-8% the legal minimum protein level. Application of NIRS provides an accurate and prompt on-line technique for feed mix analysis during the formulation process and can be beneficial to the operation of feed mills. For official inspection, the technique might serve as a preliminary screening method.

Meat Speciation by near Infrared Reflectance Spectroscopy on Dry Extract

1997 ◽  
Vol 5 (4) ◽  
pp. 195-208 ◽  
Author(s):  
Kari Thyholt ◽  
Ulf Geir Indahl ◽  
Kjell Ivar Hildrum ◽  
Marit Risberg Ellekjær ◽  
Tomas Isaksson
Keyword(s):  
Near Infrared ◽  
Screening Method ◽  
Poultry Meat ◽  
Rapid Screening ◽  
Prediction Errors ◽  
Near Infrared Reflectance ◽  
Dry Extract ◽  
Model Study ◽  
Minced Beef ◽  
Minced Meat

Professionals and consumers want to control the origin of meat, while producers can profit by mixing minced meat from low cost species into high value meat. Near infrared (NIR) spectroscopy on dry extracts was studied as a method for speciation of minced beef, pork, mutton and mechanically recovered poultry meat. This was divided into three levels: (1) classifying into “labelled species or not?”, (2) into one of four possible species or (3) predicting the degree of substitution of minced beef with other species in a model study. Minced meat from 68 carcasses from four animal species ranging from low to high fat contents were centrifuged. Extracted meat juices (0.5 mL) were dried on glass microfibre filters and the reflectance measured. Using the range 780–2500 nm and different methods of discriminant analysis by cross-validation, the 68 samples were classified 90–100% correctly according to speciation at levels 1) and 2). Level 3) included a Simplex design model study using 350 mixtures of the 68 centrifuged juices. Predicting the relative amounts from each species in samples containing 50–100% beef juice gave cross-validated prediction errors of 12% (w/w) for beef, 8% for pork and 7% for mutton and poultry. The results showed that NIR on dry extract might be used as a rapid screening method for classification and optimised to detect species adulteration.

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