Measuring Potassium in Plant Tissues Using near Infrared Spectroscopy

1998 ◽  
Vol 6 (A) ◽  
pp. A63-A66 ◽  
Author(s):  
Susan Ciavarella ◽  
Graeme D. Batten ◽  
Anthony B. Blakeney
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Nitrogen Fertilizer ◽  
Near Infrared ◽  
Nir Spectroscopy ◽  
Essential Elements ◽  
Cereal Crops ◽  
Standard Errors ◽  
Plant Tissues

Near infrared (NIR) spectroscopy is routinely used to determine constituents with organic bonds which absorb electromagnetic radiation in the region 1100 to 2500 nm. The nitrogen fertilizer requirements of cereal crops are determined from the analysis of vegetative samples by NIR spectroscopy. Simultaneous determination of other plant-essential elements would enhance the value of the analysis. Compared to nitrogen, other essential elements are either present at a lower concentration in the tissue or present largely in an inorganic form which is not detectable by NIR spectroscopy. In this paper we report NIR spectroscopic calibrations for potassium in grape petioles, grape leaves, rice shoots and orange leaves. When tested against a set of verification samples the NIR spectroscopic calibrations accounted for 96, 89, 93 and 85% of the concentration of K with standard errors of performance of 0.16, 0.12, 0.18 and 0.17%K respectively.

Analysis of Pinus radiata D. Don Bark by Near Infrared Spectroscopy

Holzforschung ◽  
2003 ◽  
Vol 57 (5) ◽  
pp. 520-526 ◽  
Author(s):  
L. R. Schimleck ◽  
Y. Yazaki
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Pinus Radiata ◽  
Near Infrared ◽  
Practical Importance ◽  
Nir Spectroscopy ◽  
Hot Water ◽  
Standard Errors ◽  
Test Set

Summary The estimation of a range of Pinus radiata D. Don bark properties by calibrated near infrared (NIR) spectroscopy is reported. A series of P. radiata samples were characterised in terms of hot water extractives, NaOH extractives and Stiasny value. NIR spectra were obtained from the milled bark of each sample and used to develop calibrations for each parameter. Coefficients of determination (R2) ranged from 0.84 (NaOH extractives) to 0.94 (Stiasny value). Standard errors of calibration ranged from 0.96 (NaOH extractives) to 2.47 (Stiasny value). When applied to a separate test set, the hot water extractives and Stiasny value calibrations performed well, while the NaOH calibration was disappointing. The calibration developed for Stiasny value could be of considerable practical importance as the method used to determine Stiasny value is particularly time consuming.

scholarly journals Determination of fatty acid content in sheep milk by means of near infrared spectroscopy

2014 ◽  
Vol 83 (10) ◽  
pp. S27-S34 ◽  
Author(s):  
Táňa Lužová ◽  
Květoslava Šustová ◽  
Jan Kuchtík ◽  
Jiří Mlček ◽  
Lenka Vorlová ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Fatty Acid Content ◽  
Correlation Coefficients ◽  
Standard Errors ◽  
Sheep Milk ◽  
Calibration Models ◽  
The Fourier Transform

The study focused on the use of the Fourier transform near infrared spectroscopy in determining the content of selected fatty acids in raw non-homogenized sheep milk. The raw sheep milk sample spectra were scanned in reflectance mode using the FT NIR Antaris spectrophotometer. The reliable functional calibration models were created for estimation of the contents of myristic, oleic, lauric, palmitic, and stearic acids (with calibration correlation coefficients of R = 0.999; 0.999; 0.993; 0.992; 0.858) and with standard errors SEC = 0.056; 0.152; 0.066; 0.367; 1.36%.

scholarly journals Real-time simultaneous detection of microbial contamination and determination of an ultra low-content active pharmaceutical ingredient in tazarotene gel by near-infrared spectroscopy

RSC Advances ◽  
2018 ◽  
Vol 8 (48) ◽  
pp. 27037-27044 ◽  
Author(s):  
Qian Xie ◽  
Ruanqi Wu ◽  
Xiaoxiao Zhong ◽  
Yanhong Dong ◽  
Qi Fan
Keyword(s):  
Infrared Spectroscopy ◽  
Real Time ◽  
Near Infrared Spectroscopy ◽  
Microbial Contamination ◽  
Near Infrared ◽  
Simultaneous Detection ◽  
Nir Spectroscopy ◽  
Active Pharmaceutical Ingredient ◽  
Non Destructive

This paper proposes a real-time and non-destructive strategy for sensitive and simultaneous detection of microbial contamination and determination of an ultra low-content active pharmaceutical ingredient in tazarotene gel by NIR spectroscopy.

Near Infrared Spectroscopy Used in Purification and Determination of Pharmaceutical Cocrystal

2013 ◽  
Vol 41 (12) ◽  
pp. 1928
Author(s):  
Zong-Liang CHI ◽  
Miao-Miao WANG ◽  
Xiao-Dong CONG ◽  
Shao-Guang LIU ◽  
Bao-Chang CAI
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Pharmaceutical Cocrystal

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

Recycling ◽  
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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