Linking the Spectra of Decomposing Litter to Ecosystem Processes: Tandem Close-Range Hyperspectral Imagery and Decomposition Metrics

Efforts to monitor terrestrial decomposition dynamics at broad spatial scales are hampered by the lack of a cost-effective and scalable means to track the decomposition process. Recent advances in remote sensing have enabled the simulation of litter spectra throughout decomposition for grasses in general, yet unique decomposition pathways are hypothesized to create subtly different litter spectral signatures with unique ecosystem functional significance. The objectives of this study were to improve spectra–decomposition linkages and thereby enable the more comprehensive monitoring of ecosystem processes such as nutrient and carbon cycles. Using close-range hyperspectral imaging, litter spectra and multiple decomposition metrics were concurrently monitored in four classes of naturally decayed litter under four decomposition treatments. The first principal component accounted for approximately 94% of spectral variation in the close-range imagery and was attributed to the progression of decomposition. Decomposition-induced spectral changes were moderately correlated with the leaf carbon to nitrogen ratio (R2 = 0.52) and sodium hydroxide extractables (R2 = 0.45) but had no correlation with carbon dioxide flux. Temperature and humidity strongly influenced the decomposition process but did not influence spectral variability or the patterns of surface decomposition. The outcome of the study is that litter spectra are linked to important metrics of decomposition and thus remote sensing could be utilized to assess decomposition dynamics and the implications for nutrient recycling at broad spatial scales. A secondary study outcome is the need to resolve methodological challenges related to inducing unique decomposition pathways in a lab environment. Improving decomposition treatments that mimic real-world conditions of temperature, humidity, insolation, and the decomposer community will enable an improved understanding of the impacts of climatic change, which are expected to strongly affect microbially mediated decomposition.

Chemometrics: An Excavator in Temperature-Dependent Near-Infrared Spectroscopy

Temperature-dependent near-infrared (NIR) spectroscopy has been developed and taken as a powerful technique for analyzing the structure of water and the interactions in aqueous systems. Due to the overlapping of the peaks in NIR spectra, it is difficult to obtain the spectral features showing the structures and interactions. Chemometrics, therefore, is adopted to improve the spectral resolution and extract spectral information from the temperature-dependent NIR spectra for structural and quantitative analysis. In this review, works on chemometric studies for analyzing temperature-dependent NIR spectra were summarized. The temperature-induced spectral features of water structures can be extracted from the spectra with the help of chemometrics. Using the spectral variation of water with the temperature, the structural changes of small molecules, proteins, thermo-responsive polymers, and their interactions with water in aqueous solutions can be demonstrated. Furthermore, quantitative models between the spectra and the temperature or concentration can be established using the spectral variations of water and applied to determine the compositions in aqueous mixtures.

Spectral radiance characteristics and vegetative indices of crops -A ground based remote sensing technique

The spectral radiance characteristics and vegetation indices like simple difference, ratio vegetation, normalised vegetation perpendicular vegetation transformed vegetation and tasseled cap transformation of mung been sunflower and groundnut crops at different growth stages have been studied. The experiment was conducted in post rainy season during 1990-91 in the farm of Agricultural College. Pune using hand held multi-spectral radiometer. The significance of spectral variation of radiance and vegetative indices with respect to the phenological stages are discussed.

Near-UV Reddening Observed in the Reflectance Spectrum of High-inclination Centaur 2012 DR30

Centaurs with high orbital inclinations and perihelia (i > 60°; q ≳ 5 au) are a small group of poorly understood minor planets that are predicted to enter the giant planet region of the solar system from the inner Oort Cloud. As such, they are one of the few samples of relatively unaltered Oort Cloud material that can currently be directly observed. Here we present two new reflectance spectra of one of the largest of these objects, 2012 DR30, in order to constrain its color and surface composition. Contrary to reports that 2012 DR30 has variable optical color, we find that consistent measurements of its spectral gradient from most new and published data sets at 0.55–0.8 μm agree with a spectral gradient of S ′ ≃ 10 % ± 1 % / 0.1 μ m within their uncertainties. The spectral variability of 2012 DR30 at near-UV/blue and near-IR wavelengths, however, is still relatively unconstrained; self-consistent rotationally resolved follow-up observations are needed to characterize any spectral variation in those regions. We tentatively confirm previous detections of water ice on the surface of 2012 DR30, and we also consistently observe a steady steepening of the gradient of its spectrum from λ ∼ 0.6 μm toward near-UV wavelengths. Plausible surface materials responsible for the observed reddening may include ferric oxides contained within phyllosilicates and aromatic refractory organics.

Why was the sky red in Jambi during the forest fire?

Extreme biomass burning occurred in Jambi, Indonesia, in 2019 and coincided exacerbated with El Nino. Peak burning season was in September, with a total hotspot of 7034. Red sky has been reported on September 21 during the day. Sun photometer measurements in Jambi as one of the Aerosol Robotic Network (AERONET) stations in Indonesia from 1 to September 26, 2019, were used to investigate the red sky phenomenon. Assessment of aerosol optical properties and spectral variation analysis is conducted. The study reveals that the red sky occurred due to, firstly, very high aerosol loading with fine size particles were present. The aerosol optical depth (AOD) was 0.34 at 500 nm on a non-hazy day (early September) and increased sharply to 5.74 during a hazy day. A high level of fine-mode particle was indicated with Angstrom Exponent>1. Secondly, during September 23, only longer wavelengths of AOD were measured at 675, 870, 1020, and 1640 nm, while AOD in shorter wavelengths cannot be retrieved. Highest AOD on September 23 was 6.19 at 675 nm, which is associated with the red sky in the previous day. Thirdly, SSA was near 1, indicating purely aerosol scattering due to coagulated fine-mode particles due to high humidity.

Surface-enhanced Raman spectroscopy for the characterization of Vaccinium myrtillus L. bilberries of the Baltic–Nordic regions

In this study, an investigation of the wild bilberries (Vaccinium myrtillus L.) of the different Baltic–Nordic regions using surface-enhanced Raman spectroscopy (SERS) combined with principal component analysis (PCA) is presented. The bilberries were collected in Lithuania, Latvia, Finland and Norway. The set of the SERS spectra of the berry extracts (pH ~ 4) were recorded on the silver nanoparticles based SERS substrates. The SERS spectra of the extracts were acquired using 532 nm laser as an excitation source. The morphology of the SERS substrates was evaluated by scanning electron microscopy (SEM) and the presence of the silver nanoparticles was confirmed by the energy-dispersive X-ray spectroscopy (EDX). The enhancement factor (EF) of the silver SERS substrates was found to be 105. It has been shown that a strong fluorescence background, associated with the phenolic compounds found in bilberries, can be subtracted due to the fluorescence-quenching properties of the silver nanoparticles. Therefore, an application of the SERS technique allowed to observe the characteristic peaks of the bilberries and the PCA tool enabled to evaluate the spectral variation across the entire SERS data set. The results presented in this paper show that the SERS technique coupled with PCA chemometric analysis might serve as a complementary method that allows to identify the country of origin of the bilberries based on the spectral differences.

EXPRESS: Correlation and Difference Between Raman Spectral Characteristic and Feature Evaluation for Leukocytes and Tumor Cells

Tumor detection supported by Raman spectroscopy is becoming increasingly popular, yet the relevance of spectral variation and feature selection retains unclear. Here we determined the correlation and difference between spectral characteristic and feature evaluation for leukocytes and tumor cells. Some peaks were found to show noticeable spectral differences, and their intensity distributions were investigated, finding using Log-Normal distribution to describe Raman intensity pattern may be more appropriate. Further the importance of all Raman features was calculated, where some other peak features occupied the top status. By surveying the intensity variation and feature evaluation for those peaks, we concluded the peak with the highest importance does not correspond to the peak location with the most noticeable intensity difference in spectra. Moreover, the peak-intensity-ratio of I₁₅₁₇/I₇₁₉ associated with protein to nucleic acid level presented the maximum separation, thus it can be recognized as a special indicator to develop an alternative cancer detection. It is inspiring to introduce advanced statistical models into bio-spectroscopic fields but those intrinsic spectral variations rather than classification performance should be valued. Our explorations can provide possibilities to reveal the essences within tumor carcinogenesis based on Raman spectroscopy, further overwhelming the obstacles during the translation into clinical applications.

Routine Monitoring of Instrument Stability in a Milk Testing Laboratory With ASCA: A Pilot Study

Mid-infrared spectroscopy has been developed as a reliable and rapid tool for routine analysis of fat, protein, lactose and other components in liquid milk. However, variations within and between FTIR instruments, even within the same milk testing laboratory, present a challenge to the accuracy of measurement of particularly minor components in the milk, such as individual fatty acids or proteins. In this study we have used Analysis of variance–Simultaneous Component Analysis (ASCA), to monitor the spectral variation between and within each of four different FOSS FTIR spectrometers over each week in an independent milk testing laboratory over 4 years, between August 2017 and March 2021 (223 weeks). On everyday of each week, spectra of the same pilot milk sample were recorded approximately every hour on each of the four instruments. Overall, variations between instruments had the largest effect on spectral variation over each week, making a significant contribution every week. Within each instrument, day-to-day variations over the week were also significant for all but two of the weeks measured, however it contributed less to the variance overall. At certain times other factors not explained by weekday variation or inter-instrument variation dominated the variance in the spectra. Examination of the scores and loadings of the weekly ASCA analysis allowed identification of changes in the spectral regions affected by drifts in each instrument over time. This was found to particularly affect some of the fatty acid predictions.

A Cross-Cultural Analysis of the Influence of Timbre on Affect Perception in Western Classical Music and Chinese Music Traditions

Timbre is one of the psychophysical cues that has a great impact on affect perception, although, it has not been the subject of much cross-cultural research. Our aim is to investigate the influence of timbre on the perception of affect conveyed by Western and Chinese classical music using a cross-cultural approach. Four listener groups (Western musicians, Western nonmusicians, Chinese musicians, and Chinese nonmusicians; 40 per group) were presented with 48 musical excerpts, which included two musical excerpts (one piece of Chinese and one piece of Western classical music) per affect quadrant from the valence-arousal space, representing angry, happy, peaceful, and sad emotions and played with six different instruments (erhu, dizi, pipa, violin, flute, and guitar). Participants reported ratings of valence, tension arousal, energy arousal, preference, and familiarity on continuous scales ranging from 1 to 9. ANOVA reveals that participants’ cultural backgrounds have a greater impact on affect perception than their musical backgrounds, and musicians more clearly distinguish between a perceived measure (valence) and a felt measure (preference) than do nonmusicians. We applied linear partial least squares regression to explore the relation between affect perception and acoustic features. The results show that the important acoustic features for valence and energy arousal are similar, which are related mostly to spectral variation, the shape of the temporal envelope, and the dynamic range. The important acoustic features for tension arousal describe the shape of the spectral envelope, noisiness, and the shape of the temporal envelope. The explanation for the similarity of perceived affect ratings between instruments is the similar acoustic features that were caused by the physical characteristics of specific instruments and performing techniques.

Coupling spectral and resource-use complementarity in experimental grassland and forest communities

Reflectance spectra provide integrative measures of plant phenotypes by capturing chemical, morphological, anatomical and architectural trait information. Here, we investigate the linkages between plant spectral variation, and spectral and resource-use complementarity that contribute to ecosystem productivity. In both a forest and prairie grassland diversity experiment, we delineated n -dimensional hypervolumes using wavelength bands of reflectance spectra to test the association between the spectral space occupied by individual plants and their growth, as well as between the spectral space occupied by plant communities and ecosystem productivity. We show that the spectral space occupied by individuals increased with their growth, and the spectral space occupied by plant communities increased with ecosystem productivity. Furthermore, ecosystem productivity was better explained by inter-individual spectral complementarity than by the large spectral space occupied by productive individuals. Our results indicate that spectral hypervolumes of plants can reflect ecological strategies that shape community composition and ecosystem function, and that spectral complementarity can reveal resource-use complementarity.