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Fig. 3 in Cuticular wax composition contributes to different strategies of foliar water uptake in six plant species from foggy rupestrian grassland in tropical mountains

Fig. 3. Gas chromatographic analysis of cuticular waxes of the six plant species with two different strategies of foliar water uptake (FWU). Data are shown as mean ± SD (n = 3). Different letters indicate significant differences among plant species (P ≤ 0.05, One-Way ANOVA). Note that the x-axis scale is modified after the break.

Fig. 2 in Cuticular wax composition contributes to different strategies of foliar water uptake in six plant species from foggy rupestrian grassland in tropical mountains

Fig. 2. Leaf surfaces of the three plant species with fast foliar water uptake strategy under scanning electron microscopy. (A–C) Leandra australis (B) adaxial and (C) abaxial surfaces. (D–F) Byrsonima variabilis (E) adaxial and (F) abaxial surfaces. (G–I) Ocotea pulchella (H) adaxial and (I) abaxial surfaces. St: stomata; T: trichomes. Bars = 10 μm.

Fig. 1 in Cuticular wax composition contributes to different strategies of foliar water uptake in six plant species from foggy rupestrian grassland in tropical mountains

Fig. 1. Leaf surfaces of the three plant species with slow foliar water uptake strategy under scanning electron microscopy. (A–C) Pleroma heteromallum (B) adaxial and (C) abaxial surfaces. (D–F) Trembleya laniflora (E) adaxial and (F) abaxial surfaces. (G–I) Senna reniformis (H) adaxial and (I) abaxial surfaces. Em: emergence; St: stomata; T: trichomes; GT: glandular trichomes. Bars = 10 μm.

Fig. 3 in Halocarbon emissions by selected tropical seaweeds exposed to different temperatures

Fig. 3. Average emission rates of halocarbons ± standard deviation (pmol gFW 1 h 1; n = 4) for the four seaweeds, G. manilaensis, U. reticulata, K. alvareii and T. conoides after 4- and 28-h exposure to the 25 ◦ C ambient temperature or the treatment temperature levels of 40, 35, 30 and 20 ◦ C. a,b,c indicate homogeneous groups based on Tukey's post hoc test (p <0.05).

Fig. 2 in Halocarbon emissions by selected tropical seaweeds exposed to different temperatures

Fig. 2. PCA analysis based on log10 of the halocarbon emissions by the four selected seaweeds, G. manilaensis, U. reticulata, K. alvarezii and T. conoides, exposed to ambient temperature ○, and exposed to treatment temperatures of 40, 35, 30, 25 and 20◦ C for 4 △ and 28 ★ h. Numerals next to the coloured symbols indicate temperature levels.

Fig. 1 in Halocarbon emissions by selected tropical seaweeds exposed to different temperatures

Fig. 1. Total emission rates for halocarbons (pmol gFW 1 h 1; n = 60) for the four seaweeds, G. manilaensis (GM), U. reticulata (UR), K. alvarezii (KA) and T. conoides (TC) for all experimental temperatures and treatment durations. In this, the horizontal bar represents the median value, the box gives the upper and lower quartile range and the error bar shows the spread of the data. The circles denote excluded outlier data (+ between 1.5 and 3 box lengths from the box edges) and extreme cases (⁄> 3 box lengths from the box edges).

Fig. 5. Chl-a in Halocarbon emissions by selected tropical seaweeds exposed to different temperatures

Fig. 5. Chl-a (μg g 1), carotenoid (μg g 1) contents and the Chl-a: carotenoid ratios (average ± standard deviation; n = 12) of the four seaweeds, G. manilaensis (GM), U. reticulata (UR), K. alvarezii (KA) and T. conoides (TC), measured after a 28 h exposure to temperatures of 40, 35, 30, 25 and 20 ◦ C. Data were analysed using a oneway ANOVA. a,b,c, indicate homogeneous groups across temperature based on Tukey's post hoc test (p <0.05).

Fig. 4. Averaged F in Halocarbon emissions by selected tropical seaweeds exposed to different temperatures

Fig. 4. Averaged F/Fvalues (with standard deviation; n = 4) of seaweeds measured before (/B) and after (/A) incubation, under the ambient 25 ◦ C condition and v m the temperature treatments of 40, 35, 30 and 20 ◦ C, after 4 and 28 h exposure. a,b,c, indicate homogenous groups based on Tukey's post hoc test (p <0.05).

Economic impacts of tropical cyclone-induced multiple hazards in China

The data and codes will be deposited in a repository that is appropriate for my scientific domain and that it is interoperable and reusable.

Fig. 6 in Tropical vibes from Sri Lanka - cyclotides from Viola betonicifolia by transcriptome and mass spectrometry analysis

Fig. 6. Multiple sequence alignment for the catalytic domain of V. betonicifolia protein disulfide isomerases, VbPDI1-2 with previously reported PDIs from Rubiaceae (OaPDI) and Violaceae (GbPDI). The active site residues CGHC are highlighted.

Fig. 4 in Tropical vibes from Sri Lanka - cyclotides from Viola betonicifolia by transcriptome and mass spectrometry analysis

Fig. 4. Vibe cyclotide/acyclotide properties A. Graphical representation of net acidity, basicity and hydrophobicity of cyclotide/acyclotide* from V. betonicifolia, calculated using a peptide property calculation tool, https://www.peptide2.com/N_peptide_hydrophobicity_hydrophilicity.php (Kyte and Doolittle, 1982; Sims, 2010). B. Sequence alignment highlighting physicochemical similarity. Hydrophobic residues are highlighted in yellow, basic in red and acidic in blue. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 3 in Tropical vibes from Sri Lanka - cyclotides from Viola betonicifolia by transcriptome and mass spectrometry analysis

Fig. 3. Vibe cyclotides identified from small scale extraction of V. betonicifolia. A. Base peak ion (BPI) chromatogram from V. betonicifolia containing deconvoluted masses for (M + H)+ of candidate cyclotides. B. Isotopic mass pattern of native, reduced/alkylated, endoproteinase GluC cleaved cyclotides exemplified by kalata S/ varv A (B), vibe 13 (C) and a new cyclotide present in the extract but absent in the transcriptome (D).

Collection of The tropical cyclones best-track data (CMABSTdata) and the daily surface climatological stations dataset for China (V3.0) from CMA

This dataset contains the tropical cyclones best-track data from the China Meteorological Administration (CMABSTdata)[1] and the daily surface climatological stations dataset for China (V3.0)[2] from 1979-2019 from China Meteorological Administration. [1] Ying, M., Zhang, W., Yu, H., Lu, X., Feng, J., Fan, Y., . . . Chen, D. (2014). An overview of the China Meteorological Administration tropical cyclone database. Journal of Atmospheric and Oceanic Technology, 31(2), 287-301. [2](CMA, http://data.cma.cn)

Fig. 2 in Tropical vibes from Sri Lanka - cyclotides from Viola betonicifolia by transcriptome and mass spectrometry analysis

Fig. 2. Schematic representation of the general organisation of cyclotide precursors and multiple sequence alignment of 28 cyclotide precursor proteins obtained from the de novo transcriptome assembly of V. betonicifolia. A. ER signal domain at the start of each precursor sequence is highlighted in blue where cleavage of the signal domain is predicted to occur between blue and pink residues (Dutton et al., 2004). The precursor is organised with an N-terminal propeptide domain, NTPP (black), N-terminal repeat, NTR (green), mature cyclotide domain (red) and C-terminal propeptide domain, CTPP (purple). An AEP mediated cleavage potentially occurs at the conserved Asn/Asp adjacent to the CTPP of all cyclotide sequences; B. New cyclotides are named vibe 1–25. In varv A/kalata S and vibe 24 transcripts, two repeating mature domains are present. In acyclotides, either the conserved Asn/Asp or CTPP sequence is absent. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 1 in Tropical vibes from Sri Lanka - cyclotides from Viola betonicifolia by transcriptome and mass spectrometry analysis

Fig. 1. Example structures and sequences from the three main cyclotide subfamilies. The structures are based on the PDB files for kalata B1 (1nb1), cycloviolacin O1 (1nbj) and Momordica cochinchinensis II (MCoTI-II) (1ib9). The unique cyclic cystine knot (CCK) topology of cyclotides arises when the ring formed by CysI-CysIV and CysII-CysV together with the backbone loops 1 and 4 are penetrated by the third disulfide between CysIII and CysVI. The cyclotide producing plant families are denoted by RRubiaceae VViolaceae, FFabaceae, SSolanaceae and CCucurbitaceae. The conserved Cys residues are highlighted in yellow and the cis-pro in loop 5 that defines the M¨obius subfamily is highlighted in blue. The conserved Asn/Asp residue at which cyclisation occurs is highlighted in red. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

Fig. 5 in Tropical vibes from Sri Lanka - cyclotides from Viola betonicifolia by transcriptome and mass spectrometry analysis

Fig. 5. Multiple sequence alignment of vibe AEPs and other functionally verified ligase- and protease-type AEPs identified in cyclic peptide producing plants. The AEP conserved catalytic triad residues Asn, Cys and His are highlighted in red. In the aligned AEPs, ligase activity determinant 1 (LAD1) containing gate keeper residue (highlighted in green/cyan, position orthologous to CYS247 in OaAEP1b (Harris et al., 2015) and ligase activity determinant 2 (LAD2) regions (highlighted in pink/blue) (Hemu et al., 2019), poly-proline region (Jackson et al., 2018) and marker of ligase activity region (MLA) (Jackson et al., 2018) are highlighted in boxes. VyPAL2 from V. yedoensis (Hemu et al., 2019), HeAEP3 from H. enneaspermus (Jackson et al., 2018), OaAEP1b from O. affinis (Harris et al., 2015) and butelase 1 from C. ternatea (Nguyen et al., 2014) are functionally verified ligases. MCoAEP2 has also shown efficient in vitro ligase activity, despite the presence of protease-type ligase activity determinant regions (Du et al., 2020). VyAEP1 from V. yedoensis and HaAEP1 from H. annus are protease-type AEPs with weaker ligase activity at high/neural pH (Haywood et al., 2018; Hemu et al., 2019). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

weight gain and nutrient utilization performances of tropical goats feed moringa leaves with cafeteria leftover

Abstract Background: Dairy cattle feed supplies in the tropics, and particularly in Ethiopia, are mostly derived from base diets (natural and improved grasslands, agricultural wastes, fodder trees and shrubs), agro-industrial by-products, and non-conventional feeds. The availability of major feed resource kinds, sources, and dairy cattle feeding practises are primarily influenced by agro-ecology and season, as well as their interactions. Objectives: The research was carried out in the Chencha district of Gamo Zone, Southern Ethiopia, with the goals of assessing available, feeding system, opportunity, limits, and copying strategy of dairy cattle production, as well as estimating feed balance. Methods: Data was gathered through primary and secondary data sources, field observations, key informant interviews, focus group talks, and individual interviews. The survey data was stratified into altitudes, coded, and analysed using the Statistical Package for Social Sciences version 20 and the general linear model approach. Cross tabulation was used to examine the statistical variance of categorical data. Results: The presence of different feed resource types, distinct agro-ecologies (P < 0.05), and crop residue accessibility were the major opportunities for dairy cattle production in the study district, but land scarcity, a lack of dry season forages, and land degradation due to erosion were the major constraints for dairy cattle feed production. In the research district, the main feed resource copying approaches were reducing the number of dairy animals, saving optional feeds, and purchasing optional feeds. The total mean of dairy cow feed supply to TLU in terms of DM production each year was 3.86 tonnes of DM/HH/annual, with a negative feed balance of 8.09 tonnes that varied with seasons and agro-ecology (P < 0.05). Conclusions: According to the findings of this study, the low production of dairy cattle in the district is clearly related to the scarcity of feed resources. To address these issues, alternative feed production technologies should be implemented, such as farmers practising forage development on their own crop land and collecting crop residues during crop harvesting times and storing them under shed, the nutritive value of different types of fodder trees and shrubs should be further determined in the future, and feed storage methods, particularly hay and silage, should be used when there are an abundance of feed resources available.

Data for "Using Convolutional Neural Network to Emulate Seasonal Tropical Cyclone Activity"

The trained 600-member ensemble convolutional neural networks (CNNs) for seasonal tropical cyclone (TC) activity to allow future studies. Please refer Fu et al. (2023; Using Convolutional Neural Network to Emulate Seasonal Tropical Cyclone Activity) for more details.

opennotspecifiedAug 2023View details →

FIGURE 5 in Pilularia ethiopica (Pteridophyta, Marsileaceae), a new species of pillwort from the tropical African mountains of Ethiopia

FIGURE 5. Distribution map of Pilularia globulifera, P. minuta, P. ethiopica, P. bokkeveldensis, and P. dracomontana. After Fomin (1934), Bobrov (1974), Dostál & Reichstein (1984), Dubina & Czorna (2009), Crouch et al. (2011), Christenhusz et al. (2017), and Minissale et al. (2017).