Improved experimental setup for in situ UV-vis-NIR spectroscopy under catalytic conditions

2003 ◽  
Vol 5 (20) ◽  
pp. 4366-4370 ◽  
Author(s):  
Jörg Melsheimer ◽  
Manfred Thiede ◽  
Rafat Ahmad ◽  
Genka Tzolova-Müller ◽  
Friederike C. Jentoft
2021 ◽  
pp. 096703352110079
Author(s):  
Agustan Alwi ◽  
Roger Meder ◽  
Yani Japarudin ◽  
Hazandy A Hamid ◽  
Ruzana Sanusi ◽  
...  

Eucalyptus pellita F. Muell. has become an important tree species in the forest plantations of SE Asia, and in Malaysian Borneo in particular, to replace thousands of hectares of Acacia mangium Willd. which has suffered significant loss caused by Ceratocystis manginecans infection in Sabah, Malaysia. Since its first introduction at a commercial scale in 2012, E. pellita has been planted in many areas in the region. The species replacement requires new silvicultural practices to induce the adaptability of E. pellita to grow in the region and this includes relevant research to optimise such regimes as planting distance, pruning, weeding practices and nutrition regimes. In this present study, the nutritional status of the foliage was investigated with the aim to develop near infrared spectroscopic calibrations that can be used to monitor and quantify nutrient status, particularly total foliar nitrogen (N) and phosphorus (P) in the field. Spectra acquired on fresh foliage in situ on the tree could be used to predict N and P with accuracy suitable for operational decision-making regards fertiliser application. If greater accuracy is required, spectra acquired on dry, milled foliage could be used to predict N and P within a relative error of 10% (R2c, r2CV, RMSEP, RPD = 0.77, 0.71, 0.02 g 100/g, 1.9 for foliar P and = 0.90, 0.88, 0.21 g 100/g, 3.0 for foliar N on dry, milled foliage). The ultimate application of this is in situ nutrient monitoring, particularly to aid longitudinal studies in fertiliser trial plots and forest operations, as the non-destructive nature of NIR spectroscopy would enable regular monitoring of individual leaves over time without the need to destructively sample them. This would aid the temporal and spatial analysis of field data.


2021 ◽  
Vol 60 (15) ◽  
pp. 5494-5503
Author(s):  
Valerio Loianno ◽  
Antonio Baldanza ◽  
Giuseppe Scherillo ◽  
Rezvan Jamaledin ◽  
Pellegrino Musto ◽  
...  

2019 ◽  
Vol 90 (8) ◽  
pp. 083905 ◽  
Author(s):  
Prakhyat Hejmady ◽  
Lucien C. Cleven ◽  
Lambèrt C. A. van Breemen ◽  
Patrick D. Anderson ◽  
Ruth Cardinaels

2014 ◽  
Vol 31 (4) ◽  
pp. 925-933 ◽  
Author(s):  
M. M. E. Colmán ◽  
D. L. Chicoma ◽  
R. Giudici ◽  
P. H. H. Araújo ◽  
C. Sayer

Author(s):  
Marie Dabos ◽  
Nicolas Lecysyn ◽  
Khanh-Hung Tran ◽  
Isabelle Ranc-Darbord ◽  
Marc Genetier ◽  
...  

Chemosensors ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 88
Author(s):  
Boniphace Elphace Kanyathare ◽  
Benjamin Asamoah ◽  
Muhammad Umair Ishaq ◽  
James Amoani ◽  
Jukka Räty ◽  
...  

The knowledge of the plastic type, thickness, and the nature of the surface is important towards the monitoring of microplastic pollution in water bodies, especially when vis-NIR spectroscopy is utilized. Factors such as complex environment and surface roughness induced-light scattering of the probing light limit the optical detection of these parameters in in-situ measurements, however. In this paper, a novel application of Kramers–Kronig analysis was exploited to identify both smooth and rough film-type macroplastics with unknown thickness. This method is particularly useful in the in-situ identification of unknown film-like macroplastics; although the sample is large, the ratio function is detected from an area that corresponds to the size of a MP. Therefore, it can be applied for the case of large size MPs. The validity of the method was demonstrated using transmittance data for smooth and roughened plastics given in Kanyathare et al., 2020.


2016 ◽  
Vol 253 (6) ◽  
pp. 1069-1075 ◽  
Author(s):  
Smriti Sahu ◽  
Shivendra Kumar Pandey ◽  
Anbarasu Manivannan ◽  
Uday Prabhakarrao Deshpande ◽  
Vasant G. Sathe ◽  
...  

2015 ◽  
Vol 51 (s1) ◽  
pp. 322-331 ◽  
Author(s):  
Zhigang Ling ◽  
Naruhito Hori ◽  
Tadahisa Iwata ◽  
Akio Takemura

2017 ◽  
Vol 650 ◽  
pp. 8-17 ◽  
Author(s):  
Maren Erdmann ◽  
Volker Trappe ◽  
Heinz Sturm ◽  
Ulrike Braun ◽  
Erik Duemichen

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