Pinndorama dilatata sp. nov. is described based on specimens from Amazonas State, Brazil. The genus is firstly recorded from the Brazilian states of Amazonas, Goiás, Maranhão, and São Paulo and a ...distribution map is provided, including new records to P. dianae, P. guartela, P. melanocephala, P. ronurensis, and P. pitanga. The key to males is updated to include the new species and minor improvements.
Ab initio calculations based on density functional theory were performed to determine the structural parameters of the LuXCo2Sb2 (X = V, Nb and Ta) double half Heusler compounds and verify their ...thermodynamic stability in an orthorhombic structure as well as to predict their electronic and optical properties. The predicted electronic band structures show that LuVCo2Sb2, LuNbCo2Sb2, and LuTaCo2Sb2 are semiconductors with indirect bandgaps of 0.728, 0.845, and 0.898 eV, respectively. The effective masses calculated at the valence band maximum at the conduction band minimum show a strong anisotropy. It can be seen that electrons are lighter than holes. The nature of the electronic states involved in the formation of the energy bands has been determined thanks to the density of states calculations. The character of chemical bonds was analyzed through the charge density distribution map. Linear optical functions, namely complex dielectric function, absorption coefficient, optical reflectivity and refractive index, were calculated for all compounds in an energy range up to 20 eV. The calculated optical spectra exhibit a noticeable anisotropy. The compounds under consideration are characterized by strong absorption of incident electromagnetic radiation in a wide energy range.
Polyphenols are the key taste and health components of tea. Typically, chemical analysis is used to determine the total polyphenol (TP) content of tea. However, this process is time consuming. In ...this study, the TP content of six tea types, namely green, white, yellow, oolong, black, and dark, was assessed using near-infrared hyperspectral imaging. Here, 100% accuracy was achieved for both the calibration and prediction sets for qualitative discrimination of tea by using the principal component analysis-K-nearest neighbor model. Important wavelengths of TP were selected using the regression coefficients (RCs) of the partial least squares regression (PLSR) model. The proposed RC-PLSR model yielded satisfactory prediction results with a residual predictive deviation of 3.34. The differences in the spatial distribution of TP in various tea samples were visualized using distribution maps. This study provided a rapid and nondestructive method for the identification of tea types and the visualization of the TP content of tea.
•Considerable differences in TP content were analyzed in different types of tea.•PCA-KNN model yielded accurate discriminations of tea types.•RC-PLSR model gave accurate prediction of the total polyphenols in different teas.•Distribution maps of total polyphenols content in intact tea samples were obtained.
•First time HSI was used to detect adulterated sorghum.•Watershed algorithm could effectively segment sorghum grains.•PCA and CA could effectively find abnormal samples in a single sorghum ...variety.•PLS-DA model could rapidly and nondestructively detect sorghum adulteration.•The distribution map of the sorghum was obtained through visualization.
This paper proposes a sorghum adulteration detection model using hyperspectral imaging technology (HSI), image processing technology, and multivariate analysis technology. The model used a watershed algorithm to extract hyperspectral data from sorghum grains. Principal component analysis (PCA) and clustering analysis (CA) were used to remove abnormal samples of sorghum. Partial least squares discriminant analysis (PLS-DA) was used to identify the variety of sample, and a sorghum distribution map and adulteration ratios were obtained by marking varieties with different colors. This paper presents, for the first time, HSI use for identification of adulteration in sorghum using PCA and CA. Accuracy of the model identification for the validation set reached 96%, and for the adulterated samples reached 91%, and comprehensive accuracy of the model could reach more than 90%. These results show that the model can rapidly and nondestructively detect sorghum adulteration.
Aim
The EUNIS Habitat Classification is a widely used reference framework for European habitat types (habitats), but it lacks formal definitions of individual habitats that would enable their ...unequivocal identification. Our goal was to develop a tool for assigning vegetation‐plot records to the habitats of the EUNIS system, use it to classify a European vegetation‐plot database, and compile statistically‐derived characteristic species combinations and distribution maps for these habitats.
Location
Europe.
Methods
We developed the classification expert system EUNIS‐ESy, which contains definitions of individual EUNIS habitats based on their species composition and geographic location. Each habitat was formally defined as a formula in a computer language combining algebraic and set‐theoretic concepts with formal logical operators. We applied this expert system to classify 1,261,373 vegetation plots from the European Vegetation Archive (EVA) and other databases. Then we determined diagnostic, constant and dominant species for each habitat by calculating species‐to‐habitat fidelity and constancy (occurrence frequency) in the classified data set. Finally, we mapped the plot locations for each habitat.
Results
Formal definitions were developed for 199 habitats at Level 3 of the EUNIS hierarchy, including 25 coastal, 18 wetland, 55 grassland, 43 shrubland, 46 forest and 12 man‐made habitats. The expert system classified 1,125,121 vegetation plots to these habitat groups and 73,188 to other habitats, while 63,064 plots remained unclassified or were classified to more than one habitat. Data on each habitat were summarized in factsheets containing habitat description, distribution map, corresponding syntaxa and characteristic species combination.
Conclusions
EUNIS habitats were characterized for the first time in terms of their species composition and distribution, based on a classification of a European database of vegetation plots using the newly developed electronic expert system EUNIS‐ESy. The data provided and the expert system have considerable potential for future use in European nature conservation planning, monitoring and assessment.
EUNIS Habitat Classification is a standard classification of European habitats. We developed the classification expert system EUNIS‐ESy, which assigns vegetation plots to EUNIS habitats based on their species composition and geographic location. We classified 1,261,373 vegetation plots from the European Vegetation Archive and determined characteristic species combinations and prepared distribution maps for 199 habitats at Level 3 of EUNIS hierarchy.
•Small woodlots represent a relevant element of natural and human-modified land-uses.•These resources support a good level of naturalness also in human-altered areas.•The contribution of alien plant ...species to the overall diversity was low.•DBH variation was higher in natural and agricultural small patches than in urban ones.•Alien and native plants showed different responses to environmental drivers.
Even if the ecological role of trees outside forests (TOF) is acknowledged, few studies provide an exhaustive census and define their principal characteristics, considering not only the patch size but also the effect of the surrounding land-use type on TOF biodiversity. Using a multiphase sampling design, we provided a map showing the spatial distribution of small woodlots outside forest (SWOF), a type of TOF, embedded in different land-use types in Sardinia, a Mediterranean hotspot of biodiversity conservation. Once located and mapped, we investigated the differences among SWOFs enclosed in different land-use types, in terms of vegetation structure and plant species richness (native and alien), searching for indicator species able to characterize SWOFs located in different land-use types. Hence, we explored the effect of environmental factors and vegetation structure on native and alien contingent in SWOF's plant communities.
Our findings indicated that SWOFs were widely spread along the land-use intensification gradient, both in natural and human-modified land-use types. The area covered by SWOFs increased following the gradient of land-use intensification, reaching the highest value in urban zones (0.85%), and the lower in agricultural and natural and semi-natural areas (0.31% and 0.23%, respectively).
We found dissimilarities between SWOFs located in different land-use types in terms of species richness, composition and indicator species, both native and alien. Notably, the contribution of alien species to the overall diversity was low both in natural and human-modified land-uses.
Nevertheless, alien and native taxa showed different responses to environmental drivers: alien taxa were not affected by landscape variables, while the native ones were significantly influenced by all investigated environmental drivers and by the structural complexity of vegetation.
SWOFs embedded in human-altered areas, in particularly in agricultural land-use, show good levels of naturalness: these results indicate that SWOFs represent an opportunity for natural conversion and rewilding of altered ecosystems.
Small woodlands outside the forest can be the pillars to build and extend the green infrastructure network in both natural and modified land-uses, delivering important benefits for ecosystem services, and offering nature-based solutions to pamper fragmentation effects.
A new species of jumping spiders (Araneae, Salticidae), Afraflacilla goaensis Gawas & Tripathi sp. nov., is described, diagnosed and illustrated based on a single male specimen collected from a ...mangrove in Goa, India. Considering this finding, the genus Afraflacilla previously known from the Indian states of Tamil Nadu, Kerala, Gujarat, and Rajasthan, is now documented for the first time in Goa. Finally, the Indian records of the genus Afraflacilla are mapped.
It is critical to establish response thresholds for fungal communities to global environmental change and assess the relationship between fungal diversity and nutrient cycling in soils. However, ...these have not yet been evaluated in agro-ecosystems. Here we report the findings of a survey across eastern China on the soil fungi and physicochemical properties in adjacent maize and rice fields. The results revealed a wider range of environmental thresholds for soil fungi in rice than maize fields. We found that the dominant fungal taxa only accounted for 0.6% of all taxa, but constituted >50% of total fungi. Based on their habitat preferences, distinct distribution maps between maize and rice fields were constructed, which indicated niche differentiation of soil fungi between dry and waterlogged soils. Rice fields showed higher fungal richness in low latitude regions, consistent with latitudinal richness patterns found in natural terrestrial ecosystems; however, no such trend was observed in maize fields. Fungal richness was positively correlated with nutrient cycling in rice soils and fungal beta diversity with nutrient cycling in maize soils. These findings provide response thresholds for fungal community change across environmental gradients, advancing our understanding of soil fungal diversity patterns in agricultural ecosystems. Differences between wetland and dryland should be taken into consideration when formulating sustainable management plans and baselines for assessments of future global change and resilience of agricultural fields.
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•We report a systematic large-scale survey of soil fungi and environmental data.•Soil fungi show wider range of environmental thresholds in rice than maize fields.•Soil fungi show distinct continental atlases between maize and rice fields.•Fungal diversities are respectively associated with multi-nutrients cycling.
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•FNN was developed for monitoring color changes in large yellow croaker fillets.•FNN presented high predictive power for color changes based on optimal spectra.•Different freshness of ...fish fillets can be distinguished by distribution maps.
Vis-NIR hyperspectral imaging (HSI) system combined with artificial neural networks was investigated for the first time to monitor color changes of large yellow croaker (Larimichthys crocea) fillets during low-temperature storage. Feed-forward neural networks (FNN) empowered with the leaky rectified linear unit (Leaky-Relu) have been developed as a non-linear quantitative analysis model. It presented accurate predictive power for color changes based on optimal spectra (with R2P of 0.908, 0.915, and 0.977; and RMSEP of 1.062, 3.315, and 0.082 for L*, a*, and b*, respectively). In final, the simplified FNN-Leaky-Relu model (S-FNN-L) was utilized to visualize the distribution maps of color parameters in the fillets. The results demonstrated the feasibility of HSI could replace the traditional colorimeter to determine the spatial distribution in the color measurement of fish fillets with a rapid and non-invasive technique.
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