scholarly journals Near-infrared spectroscopy (NIRS) for quality assurance in breeding, cultivation and marketing of high-oleic sunflowers

Helia ◽  
2006 ◽  
Vol 29 (45) ◽  
pp. 73-80 ◽  
Author(s):  
B. Biskupek-Korell ◽  
C.R. Moschner
Keyword(s):  
Quality Assurance ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
High Oleic

Oil and Fat Classification by Selected Bands of Near-Infrared Spectroscopy

2000 ◽  
Vol 54 (8) ◽  
pp. 1168-1174 ◽  
Author(s):  
Pierre Hourant ◽  
Vincent Baeten ◽  
Maria T. Morales ◽  
Marc Meurens ◽  
Ramon Aparicio
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
High Performance ◽  
Near Infrared ◽  
Discriminant Functions ◽  
Linear Discriminant ◽  
High Oleic ◽  
Infrared Spectral ◽  
Filter Type ◽  
Different Sources

One hundred and four edible oil and fat samples from 18 different sources, either vegetable (Brazil nut, coconut, corn, sunflower, walnut, virgin olive, peanut, palm, canola, soybean, sunflower) or animal (tallow and hydrogenated fish), have been analyzed by high-performance gas chromatography (HPGC) and near-infrared spectroscopy (NIRS). Fatty acids were quantified by HPGC. The near-infrared spectral features of the most noteworthy bands were studied and discussed to design a filter-type NIR instrument. An arborescent structure, based on stepwise linear discriminant analysis (SLDA), was built to classify the samples according to their sources. Seven discriminant functions permitted a successive discrimination of saturated fats, corn, soybean, sunflower, canola, peanut, high oleic sunflower, and virgin olive oils. The discriminant functions were based on the absorbance values, between three and five, from the 1700–1800 and 2100–2400 nm regions. Chemical explanations are given in support of the selected wavelengths. The arborescent structure was then checked with a test set, and 90% of the samples were correctly classified.

Near-infrared spectroscopy as a potential quality assurance tool for the wood preservation industry

2013 ◽  
Vol 89 (05) ◽  
pp. 654-658 ◽  
Author(s):  
Rod Stirling
Keyword(s):  
Quality Assurance ◽  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Untreated Wood ◽  
Wood Properties ◽  
Wood Preservation ◽  
Wide Range ◽  
Spot Tests ◽  
Potential Use

Preservatives are used to extend the service life of wood used in situations where it is vulnerable to biodegradation. Wood preservation standards typically specify quality assurance procedures to differentiate heartwood and sapwood and to measure preservative loading and penetration. For spruce and hem–fir there are no reliable chemical spot tests to differentiate sapwood and heartwood. This makes it more difficult for these species to meet penetration requirements. For many of the recently introduced carbon-based preservatives, the only methods available to determine penetration involve detecting a surrogate in the formulation, or only some of the active ingredients. Multivariate models based on near-infrared spectroscopy (NIRS) have been used to predict a wide range of wood properties over the past 20 years. The present research evaluates the potential use of NIRS-based models as quality assurance tools for the wood preservation industry. Models were developed to differentiate hemlock and amabilis fir sapwood and heartwood. NIRS-based models were also able to differentiate untreated wood from wood treated with DDACarbonate and wood treated with tebuconazole. Models developed to predict DDACarbonate and tebuconazole retention were moderately accurate, but likely not precise enough to replace current quantitative assays.

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