Near infrared reflectance spectroscopy (NIRS) to predict biological parameters of maize silage: effects of particle comminution, oven drying temperature and the presence of residual moisture

Maize silage nutritive quality is routinely determined by near infrared reflectance spectroscopy (NIRS). However, little is known about the impact of sample preparation on the accuracy of the calibration to predict biological traits. A sample population of 48 maize silages representing a wide range of physiological maturities was used in a study to determine the impact of different sample preparation procedures (i.e., drying regimes; the presence or absence of residual moisture; the degree of particle comminution) on resultant NIR prediction statistics. All silages were scanned using a total of 12 combinations of sample pre-treatments. Each sample preparation combination was subjected to three multivariate regression techniques to give a total of 36 predictions per biological trait. Increased sample preparations procedure, relative to scanning the unprocessed whole plant (WP) material, always resulted in a numerical minimisation of model statistics. However, the ability of each of the treatments to significantly minimise the model statistics differed. Particle comminution was the most important factor, oven-drying regime was intermediate, and residual moisture presence was the least important. Models to predict various biological parameters of maize silage will be improved if material is subjected to a high degree of particle comminution (i.e., having been passed through a 1 mm screen) and developed on plant material previously dried at 60 degrees C. The extra effort in terms of time and cost required to remove sample residual moisture cannot be justified. (c) 2005 Elsevier B.V. All rights reserved.

Using near infrared reflectance spectroscopy (NIRS) to predict the biological parameters of maize silage

The microbial fermentability, ruminal degradability and digestibility of 48 maize silages were determined using in vitro gas production (GP), in situ degradability and in vitro digestibility procedures. The silages were produced from forage maize harvested throughout the summer of 1998, and represent a wide range of physiological maturities. Large variations among samples were observed for all biological parameters, with the exception of in vitro digestibility and the asymptote of in vitro GP. The potential of near infrared reflectance spectroscopy (NIRS) to predict the biological parameters measured was determined by regression of the biological data against the respective spectral profile. NIRS demonstrated only a moderate ability (R-2 > 0.60-0.80) to predict in vitro digestibility, modelled kinetics of gas production (excluding the asymptote of gas production) and the modelled ruminally soluble dry matter (DM) fraction. Calibration statistics for remaining biological parameters were unacceptably poor (R-2 = 0.60). (C) 2004 Elsevier B.V. All rights reserved.

Whole crop cereals 2. Prediction of apparent digestibility and energy value from in vitro digestion techniques and near infrared reflectance spectroscopy and of chemical composition by near infrared reflectance spectroscopy

Samples of whole crop wheat (WCW, n = 134) and whole crop barley (WCB, n = 16) were collected from commercial farms in the UK over a 2-year period (2003/2004 and 2004/2005). Near infrared reflectance spectroscopy (NIRS) was compared with laboratory and in vitro digestibility measures to predict digestible organic matter in the dry matter (DOMD) and metabolisable energy (ME) contents measured in vivo using sheep. Spectral models using the mean spectra of two scans were compared with those using individual spectra (duplicate spectra). Overall NIRS accurately predicted the concentration of chemical components in whole crop cereals apart from crude protein. ammonia-nitrogen, water-soluble carbohydrates, fermentation acids and solubility values. In addition. the spectral models had higher prediction power for in vivo DOMD and ME than chemical components or in vitro digestion methods. Overall there Was a benefit from the use of duplicate spectra rather than mean spectra and this was especially so for predicting in vivo DOMD and ME where the sample population size was smaller. The spectral models derived deal equally well with WCW and WCB and Would he of considerable practical value allowing rapid determination of nutritive value of these forages before their use in diets of productive animals. (C) 2008 Elsevier B.V. All rights reserved.

The infra-red spectra of silyl fluoride and silyl fluoride-d3

Infra-red spectra have been recorded for silyl fluoride and silyl fluoride-d3 at a resolution of circa 0·3 cm-1. Rotational structure has been observed for parallel fundamentals in both molecules, and for all perpendicular fundamentals. In both SiH3F and SiD3F the A1 and E species deformation modes interact strongly via a Coriolis perturbation; this has been analysed, and the band origin of v5 for SiH3F is reassigned. A hybrid-orbital force field based on the experimental data is also reported.

Cosmic ray modulation of infra-red radiation in the atmosphere

Cosmic rays produce molecular cluster ions as they pass through the lower atmosphere. Neutral molecular clusters such as dimers and complexes are expected to make a small contribution to the radiative balance, but atmospheric absorption by charged clusters has not hitherto been observed. In an atmospheric experiment, a narrowband thermopile filter radiometer centred on 9.15 {\mu}m, an absorption band previously associated with infra-red absorption of molecular cluster ions, was used to monitor changes following events identified by a cosmic ray telescope sensitive to high-energy (>400 MeV) particles, principally muons. The average change in longwave radiation in this absorption band due to molecular cluster ions is 7 mWm sup{-2}. The integrated atmospheric energy density for each event is 2 Jm sup{-2}, representing an amplification factor of 10 sup{12} compared to the estimated energy density of a typical air shower. This absorption is expected to occur continuously and globally, but calculations suggest that it has only a small effect on climate.

Extended optimal estimation techniques for sea surface temperature from the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI)

Sea surface temperature (SST) can be estimated from day and night observations of the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) by optimal estimation (OE). We show that exploiting the 8.7 μm channel, in addition to the “traditional” wavelengths of 10.8 and 12.0 μm, improves OE SST retrieval statistics in validation. However, the main benefit is an improvement in the sensitivity of the SST estimate to variability in true SST. In a fair, single-pixel comparison, the 3-channel OE gives better results than the SST estimation technique presently operational within the Ocean and Sea Ice Satellite Application Facility. This operational technique is to use SST retrieval coefficients, followed by a bias-correction step informed by radiative transfer simulation. However, the operational technique has an additional “atmospheric correction smoothing”, which improves its noise performance, and hitherto had no analogue within the OE framework. Here, we propose an analogue to atmospheric correction smoothing, based on the expectation that atmospheric total column water vapour has a longer spatial correlation length scale than SST features. The approach extends the observations input to the OE to include the averaged brightness temperatures (BTs) of nearby clear-sky pixels, in addition to the BTs of the pixel for which SST is being retrieved. The retrieved quantities are then the single-pixel SST and the clear-sky total column water vapour averaged over the vicinity of the pixel. This reduces the noise in the retrieved SST significantly. The robust standard deviation of the new OE SST compared to matched drifting buoys becomes 0.39 K for all data. The smoothed OE gives SST sensitivity of 98% on average. This means that diurnal temperature variability and ocean frontal gradients are more faithfully estimated, and that the influence of the prior SST used is minimal (2%). This benefit is not available using traditional atmospheric correction smoothing.

Estimation of sea surface temperature from the Spinning Enhanced Visible and Infra Red Imager, improved using numerical weather prediction

Most of the operational Sea Surface Temperature (SST) products derived from satellite infrared radiometry use multi-spectral algorithms. They show, in general, reasonable performances with root mean square (RMS) residuals around 0.5 K when validated against buoy measurements, but have limitations, particularly a component of the retrieval error that relates to such algorithms' limited ability to cope with the full variability of atmospheric absorption and emission. We propose to use forecast atmospheric profiles and a radiative transfer model to simulate the algorithmic errors of multi-spectral algorithms. In the practical case of SST derived from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG), we demonstrate that simulated algorithmic errors do explain a significant component of the actual errors observed for the non linear (NL) split window algorithm in operational use at the Centre de Météorologie Spatiale (CMS). The simulated errors, used as correction terms, reduce significantly the regional biases of the NL algorithm as well as the standard deviation of the differences with drifting buoy measurements. The availability of atmospheric profiles associated with observed satellite-buoy differences allows us to analyze the origins of the main algorithmic errors observed in the SEVIRI field of view: a negative bias in the inter-tropical zone, and a mid-latitude positive bias. We demonstrate how these errors are explained by the sensitivity of observed brightness temperatures to the vertical distribution of water vapour, propagated through the SST retrieval algorithm.

Probabilistic physically-based cloud screening of satellite infra-red imagery for operational sea surface temperature retrieval

We propose and demonstrate a fully probabilistic (Bayesian) approach to the detection of cloudy pixels in thermal infrared (TIR) imagery observed from satellite over oceans. Using this approach, we show how to exploit the prior information and the fast forward modelling capability that are typically available in the operational context to obtain improved cloud detection. The probability of clear sky for each pixel is estimated by applying Bayes' theorem, and we describe how to apply Bayes' theorem to this problem in general terms. Joint probability density functions (PDFs) of the observations in the TIR channels are needed; the PDFs for clear conditions are calculable from forward modelling and those for cloudy conditions have been obtained empirically. Using analysis fields from numerical weather prediction as prior information, we apply the approach to imagery representative of imagers on polar-orbiting platforms. In comparison with the established cloud-screening scheme, the new technique decreases both the rate of failure to detect cloud contamination and the false-alarm rate by one quarter. The rate of occurrence of cloud-screening-related errors of >1 K in area-averaged SSTs is reduced by 83%. Copyright © 2005 Royal Meteorological Society.

Infra-red laser ablative micromachining of parylene-C on SiO2substrates for rapid prototyping, high yield, human neuronal cell patterning

Cell patterning commonly employs photolithographic methods for the micro fabrication of structures on silicon chips. These require expensive photo-mask development and complex photolithographic processing. Laser based patterning of cells has been studied in vitro and laser ablation of polymers is an active area of research promising high aspect ratios. This paper disseminates how 800 nm femtosecond infrared (IR) laser radiation can be successfully used to perform laser ablative micromachining of parylene-C on SiO2 substrates for the patterning of human hNT astrocytes (derived from the human teratocarcinoma cell line (hNT)) whilst 248 nm nanosecond ultra-violet laser radiation produces photo-oxidization of the parylene-C and destroys cell patterning. In this work, we report the laser ablation methods used and the ablation characteristics of parylene-C for IR pulse fluences. Results follow that support the validity of using IR laser ablative micromachining for patterning human hNT astrocytes cells. We disseminate the variation in yield of patterned hNT astrocytes on parylene-C with laser pulse spacing, pulse number, pulse fluence and parylene-C strip width. The findings demonstrate how laser ablative micromachining of parylene-C on SiO2 substrates can offer an accessible alternative for rapid prototyping, high yield cell patterning with broad application to multi-electrode arrays, cellular micro-arrays and microfluidics.

Further considerations of cosmic ray modulation of infra-red radiation in the atmosphere

Understanding effects of ionisation in the lower atmosphere is a new interdisciplinary area, crossing the traditionally distinct scientific boundaries between astro-particle and atmospheric physics and also requiring understanding of both heliospheric and magnetospheric influences on cosmic rays. Following the paper of Erlykin et al. (2014) we develop further the interpretation of our observed changes in long-wave (LW) radiation, Aplin and Lockwood (2013) by taking account of both cosmic ray ionisation yields and atmospheric radiative transfer. To demonstrate this, we show that the thermal structure of the whole atmosphere needs to be considered along with the vertical profile of ionisation. Allowing for, in particular, ionisation by all components of a cosmic ray shower and not just by the muons, reveals that the effect we have detected is certainly not inconsistent with laboratory observations of the LW absorption cross section. The analysis presented here, although very different from that of Erlykin et al., does come to the same conclusion that the events detected by AL were not caused by individual cosmic ray primaries – not because it is impossible on energetic grounds, but because events of the required energy are too infrequent for the 12 h_1 rate at which they were seen by the AL experiment. The present paper numerically models the effect of three different scenario changes to the primary GCR spectrum which all reproduce the required magnitude of the effect observed by AL. However, they cannot solely explain the observed delay in the peak effect which, if confirmed, would appear to open up a whole new and interesting area in the study of water oligomers and their effects on LW radiation. We argue that a technical artefact in the AL experiment is highly unlikely and that our initial observations merit both a wide-ranging follow-up experiment and more rigorous, self-consistent, three-dimensional radiative transfer modelling

Structural diversity in supramolecular architectures of Mn(II) through non-covalent interactions

Two mononuclear complexes of manganese(II), [Mn(OCN)(2)(phen)(2)] 1 and [Mn(NCO)(2)(bpy)(2)] 2 [1,10-phenanthroline (phen); 2,2'-bipyridine (bpy)], have been synthesized and characterized by single crystal X-ray analysis, infra-red spectroscopy and magnetic studies. The coordination structure of complex 2 is already reported. The cyanate anions are pendent in both the complexes. In 1, cyanate anion links manganese(II) through O-atom, whereas in 2 it coordinates through N-atom. The mononuclear fragments of 1 are built up to a supramolecular lamellar 3D architecture by pi-pi interactions only. On the other hand, mononuclear fragments of 2 are assembled to a 2D supramolecular brick-wall architecture by C-H-... pi interactions.

Chemical, physical and electrical properties of aged dodecylbenzene 3: thermal ageing of mixed isomers in nitrogen and under sealed conditions

Commercial dodecylbenzene cable fluid was aged at temperatures of 105 and 135 degrees C in dry oxygen-free nitrogen. In addition, selected samples were aged at 135 degrees C under sealed conditions where air was excluded from the headspace above the oil. A variety of analytical techniques, such as ultra-violet visible and infra-red spectroscopy, acid number and water content measurements, were then used to characterize the aged oils. In addition, their electrical properties were assessed by dielectric spectroscopy. Compared with ageing in air, the ageing rate was reduced significantly and, as expected, no major oxidation peaks were detected in the infrared spectrometer. Significantly, very little absorbance at 680 nm ("red absorbers") was detected in samples aged with copper and, consequentially, no large increases in dielectric loss were recorded within the ageing times considered here. This study compliments previous investigations on cable fluid and 1-phenyldodecane aged in air and show that the same ageing indicators are valid in oils aged under conditions which more closely resemble those found in high voltage plant.

Chemical, physical and electrical properties of aged dodecylbenzene: thermal ageing of mixed isomers in air

A commercial dodecylbenzene (DDB) cable oil was aged at temperatures between 90 and 135 degrees C in air and was analyzed using various analytical techniques including optical and infra-red spectroscopy and dielectric analysis. On ageing, the oil darkened, significant oxidation features were found by infra-red spectroscopy and the acid number, water content and dielectric loss all increased. Ageing in the presence of paper or aluminum did not affect the ageing process, whereas ageing was significantly modified by the presence of copper. An absorption at 680 nm ("red absorbers") was detected by ultra-violet/visible spectroscopy followed by the production of an opaque precipitate. A reaction between copper and the acid generated on ageing is thought to produce copper carboxylates, and X-ray fluorescence confirmed that copper was indeed present in both the aged oil and the precipitate. Significantly, once red absorbers were detected, the dielectric loss increased to catastrophically high values and, therefore, the appearance of these compounds may serve as a useful diagnostic indicator. The development of acidity on ageing appears to be key in initiating the destructive copper conversion reaction and hence the control of oil acidity may be key to prolonging the life of DDB cable oils.

Optimization algorithms in FMRF model-based segmentation for LIDAR data and co-registered bands

In this paper, a fuzzy Markov random field (FMRF) model is used to segment land-objects into free, grass, building, and road regions by fusing remotely, sensed LIDAR data and co-registered color bands, i.e. scanned aerial color (RGB) photo and near infra-red (NIR) photo. An FMRF model is defined as a Markov random field (MRF) model in a fuzzy domain. Three optimization algorithms in the FMRF model, i.e. Lagrange multiplier (LM), iterated conditional mode (ICM), and simulated annealing (SA), are compared with respect to the computational cost and segmentation accuracy. The results have shown that the FMRF model-based ICM algorithm balances the computational cost and segmentation accuracy in land-cover segmentation from LIDAR data and co-registered bands.