scholarly journals Agave Steroidal Saponins as Potential Bioherbicides

Agronomy ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 2404
Author(s):  
Alexandra G. Durán ◽  
Javier Benito ◽  
Francisco A. Macías ◽  
Ana M. Simonet
Keyword(s):  
Extraction Method ◽  
Principal Component ◽  
Activity Levels ◽  
Target Species ◽  
Steroidal Saponins ◽  
Sugar Chain ◽  
Natural Herbicides ◽  
Phytotoxic Activity ◽  
Hydrolysis Of ◽  
Better Than

Agave saponins are a valuable resource for the prospective development of new forms of agrochemicals. The extraction method was optimized and applied to 17 Agave species. Thirteen saponin fractions (SFs) were assayed on wheat etiolated coleoptiles, and analysed using UPLC-QTOF-MSE, NMR spectroscopy and the HMBC method for aglycone identification (HMAI). Six SFs were assayed on standard target species (STS) and weeds. The new extraction method reduces costs to obtain SFs with the same activity. The tested SFs assayed on etiolated wheat coleoptiles that belong to the subgenus Agave were among those with the highest activity levels. The combination of HMAI together with UPLC-MS allowed the identification of 20 aglycones in the SFs, and no isolation or hydrolysis of the saponins was required. A Principal Component Analysis (PCA) showed that for the active SFs the structural key would be the length of their sugar chain. The presence of a carbonyl group at C-12 implied an enhancement in phytotoxic activity. Six SFs were assayed on seeds, and no activity on Solanum lycopersicum (tomato) was observed; however, good activity profiles were obtained on weed E. crus-galli (IC50 < 80 ppm), better than the commercial herbicide Logran®. These findings represent a possible lead for the development of natural herbicides through the use of saponins of subgenus Agave species.

The Natural Higher Fatty Acid Soaps in Natural Rubber Latex and Their Effect on the Mechanical Stability of the Latex

1984 ◽  
Vol 57 (2) ◽  
pp. 243-253 ◽  
Author(s):  
Seong-Fong Chen ◽  
Chiew-Sum Ng
Keyword(s):  
Fatty Acid ◽  
Extraction Method ◽  
Surface Charge Density ◽  
Mechanical Stability ◽  
Natural Rubber Latex ◽  
Rubber Latex ◽  
Latex Particles ◽  
Rate Of Increase ◽  
Hydrolysis Of ◽  
Better Than

Abstract The natural HFA soaps present in ammoniated NR latex concentrates are derived from the hydrolysis of the saponifiable lipids on the surfaces of the latex particles. A method based on cold extraction of the soaps has been developed for determining the natural HFA soaps in freshly concentrated latices. This method is better than the hot extraction method, which has been shown to cause some hydrolysis of the lipids. The natural HFA soaps in NR latex increase with time and reach a constant value in 3 to 6 weeks. The rate of increase of the soaps is divided into two linear regions and is more rapid in the first 1 to 2 weeks. More than 92% of the natural HFA soaps are adsorbed on the surfaces of the latex particles. This results in an increase in the negative electrical surface charge density of the particles and causes an increase in the mechanical stability of the latex. In fact, the increase in log MST is linearly proportional to the increase in natural HFA soaps in the latex. After the natural HFA soaps become constant, further increase in MST value is likely to be caused partly by the oxygen from the air.

scholarly journals Phytotoxicity of Triterpenes and Limonoids from the Rutaceae and Meliaceae. 5α,6β,8α,12α-Tetrahydro-28-norisotoonafolin – a Potent Phytotoxin from Toona ciliata

2015 ◽  
Vol 10 (1) ◽  
pp. 1934578X1501000 ◽  
Author(s):  
Liliane Nebo ◽  
Rosa M. Varela ◽  
José M. G. Molinillo ◽  
Vanessa G. P. Severino ◽  
André L. F. Sarria ◽  
...  
Keyword(s):  
Biological Activities ◽  
Crop Protection ◽  
Lepidium Sativum ◽  
Wheat Coleoptile ◽  
Ecological Interactions ◽  
Target Species ◽  
Phytotoxic Activity ◽  
Toona Ciliata ◽  
Allelopathic Compounds ◽  
Better Than

Limonoids and triterpenes are the largest groups of secondary metabolites and have notable biological activities. Meliaceae and Rutaceae are known for their high diversity of metabolites, including limonoids, and are distinguished from other families due to the frequent occurrence of such compounds. The increased interest in crop protection associated with the diverse bioactivity of these compounds has made these families attractive in the search for new allelopathic compounds. In the study reported here we evaluated the bioactivity profiles of four triterpenes (1–4) and six limonoids (5–10) from Meliaceae and Rutaceae. The compounds were assessed in a wheat coleoptile bioassay and those that had the highest activities were tested on the standard target species Lepidium sativum (cress), Lactuca sativa (lettuce), Lycopersicon esculentum (tomato) and Allium cepa (onion). Limonoids showed phytotoxic activity and 5 α,6 β,8 α,12 α-tetrahydro-28-norisotoonafolin (10) and gedunin (5) were the most active, with bioactivity levels similar to, and in some cases better than, those of the commercial herbicide Logran. The results indicate that these products could also be allelochemicals involved in the ecological interactions of these plant species.

scholarly journals SPPD: A Novel Reassembly Method for 3D Terracotta Warrior Fragments Based on Fracture Surface Information

2021 ◽  
Vol 10 (8) ◽  
pp. 525
Author(s):  
Wenmin Yao ◽  
Tong Chu ◽  
Wenlong Tang ◽  
Jingyu Wang ◽  
Xin Cao ◽  
...  
Keyword(s):  
Fracture Surface ◽  
Principal Component ◽  
Point Clouds ◽  
Three Dimension ◽  
Registration Method ◽  
Series Of Experiments ◽  
Coarse To Fine ◽  
Fine Registration ◽  
Common Situation ◽  
Better Than

As one of China′s most precious cultural relics, the excavation and protection of the Terracotta Warriors pose significant challenges to archaeologists. A fairly common situation in the excavation is that the Terracotta Warriors are mostly found in the form of fragments, and manual reassembly among numerous fragments is laborious and time-consuming. This work presents a fracture-surface-based reassembling method, which is composed of SiamesePointNet, principal component analysis (PCA), and deep closest point (DCP), and is named SPPD. Firstly, SiamesePointNet is proposed to determine whether a pair of point clouds of 3D Terracotta Warrior fragments can be reassembled. Then, a coarse-to-fine registration method based on PCA and DCP is proposed to register the two fragments into a reassembled one. The above two steps iterate until the termination condition is met. A series of experiments on real-world examples are conducted, and the results demonstrate that the proposed method performs better than the conventional reassembling methods. We hope this work can provide a valuable tool for the virtual restoration of three-dimension cultural heritage artifacts.

scholarly journals Variety Identification of Orchids Using Fourier Transform Infrared Spectroscopy Combined with Stacked Sparse Auto-Encoder

Molecules ◽  
2019 ◽  
Vol 24 (13) ◽  
pp. 2506 ◽  
Author(s):  
Yunfeng Chen ◽  
Yue Chen ◽  
Xuping Feng ◽  
Xufeng Yang ◽  
Jinnuo Zhang ◽  
...  
Keyword(s):  
Fourier Transform ◽  
Principal Component ◽  
Fourier Transform Infrared ◽  
Spectroscopic Technique ◽  
Variety Identification ◽  
Support Vector ◽  
K Nearest Neighbors ◽  
Discriminant Models ◽  
The Fourier Transform ◽  
Better Than

The feasibility of using the fourier transform infrared (FTIR) spectroscopic technique with a stacked sparse auto-encoder (SSAE) to identify orchid varieties was studied. Spectral data of 13 orchids varieties covering the spectral range of 4000–550 cm−1 were acquired to establish discriminant models and to select optimal spectral variables. K nearest neighbors (KNN), support vector machine (SVM), and SSAE models were built using full spectra. The SSAE model performed better than the KNN and SVM models and obtained a classification accuracy 99.4% in the calibration set and 97.9% in the prediction set. Then, three algorithms, principal component analysis loading (PCA-loading), competitive adaptive reweighted sampling (CARS), and stacked sparse auto-encoder guided backward (SSAE-GB), were used to select 39, 300, and 38 optimal wavenumbers, respectively. The KNN and SVM models were built based on optimal wavenumbers. Most of the optimal wavenumbers-based models performed slightly better than the all wavenumbers-based models. The performance of the SSAE-GB was better than the other two from the perspective of the accuracy of the discriminant models and the number of optimal wavenumbers. The results of this study showed that the FTIR spectroscopic technique combined with the SSAE algorithm could be adopted in the identification of the orchid varieties.

Pathways for the steroidal saponins conversion to diosgenin during acid hydrolysis of Dioscorea zingiberensis C. H. Wright

2011 ◽  
Vol 89 (12) ◽  
pp. 2620-2625 ◽  
Author(s):  
Yue’e Peng ◽  
Zhihua Yang ◽  
Yanxin Wang ◽  
Zhenyu Liu ◽  
Jianguo Bao ◽  
...  
Keyword(s):  
Acid Hydrolysis ◽  
Steroidal Saponins ◽  
Dioscorea Zingiberensis ◽  
Hydrolysis Of

scholarly journals Low-temperature thermal hydrolysis of sludge prior to anaerobic digestion: principal component analysis (PCA) of experimental data

Data in Brief ◽  
2021 ◽  
pp. 107323
Author(s):  
Mohamed N.A. Meshref ◽  
Seyed Mohammad Mirsoleimani Azizi ◽  
Wafa Dastyar ◽  
Rasha Maal-Bared ◽  
Bipro Ranjan Dhar
Keyword(s):  
Experimental Data ◽  
Principal Component Analysis ◽  
Anaerobic Digestion ◽  
Low Temperature ◽  
Principal Component ◽  
Component Analysis ◽  
Thermal Hydrolysis ◽  
Hydrolysis Of

scholarly journals Molecular Cloning and Characterization of Bifidobacterium bifidum 1,2-α-l-Fucosidase (AfcA), a Novel Inverting Glycosidase (Glycoside Hydrolase Family 95)

2004 ◽  
Vol 186 (15) ◽  
pp. 4885-4893 ◽  
Author(s):  
Takane Katayama ◽  
Akiko Sakuma ◽  
Takatoshi Kimura ◽  
Yutaka Makimura ◽  
Jun Hiratake ◽  
...  
Keyword(s):  
Amino Acid ◽  
Genomic Library ◽  
Bifidobacterium Bifidum ◽  
Glycoside Hydrolases ◽  
Glycoside Hydrolase Family ◽  
Amino Acid Residues ◽  
Gene Encoding ◽  
Sugar Chain ◽  
Hydrolysis Of

ABSTRACT A genomic library of Bifidobacterium bifidum constructed in Escherichia coli was screened for the ability to hydrolyze the α-(1→2) linkage of 2′-fucosyllactose, and a gene encoding 1,2-α-l-fucosidase (AfcA) was isolated. The afcA gene was found to comprise 1,959 amino acid residues with a predicted molecular mass of 205 kDa and containing a signal peptide and a membrane anchor at the N and C termini, respectively. A domain responsible for fucosidase activity (the Fuc domain; amino acid residues 577 to 1474) was localized by deletion analysis and then purified as a hexahistidine-tagged protein. The recombinant Fuc domain specifically hydrolyzed the terminal α-(1→2)-fucosidic linkages of various oligosaccharides and a sugar chain of a glycoprotein. The stereochemical course of the hydrolysis of 2′-fucosyllactose was determined to be inversion by using 1H nuclear magnetic resonance. The primary structure of the Fuc domain exhibited no similarity to those of any glycoside hydrolases (GHs) but showed high similarity to those of several hypothetical proteins in a database. Thus, it was revealed that the AfcA protein constitutes a novel inverting GH family (GH family 95).

Left ventricle transcriptomic analysis reveals connective tissue accumulation associates with initial age-dependent decline in V̇o2peak from its lifetime apex

2017 ◽  
Vol 49 (1) ◽  
pp. 53-66 ◽  
Author(s):  
Gregory N. Ruegsegger ◽  
Ryan G. Toedebusch ◽  
Joshua F. Braselton ◽  
Thomas E. Childs ◽  
Frank W. Booth
Keyword(s):  
Connective Tissue ◽  
Left Ventricle ◽  
Wheel Running ◽  
Protein Translation ◽  
Transcriptomic Analysis ◽  
Peak Oxygen Consumption ◽  
Activity Levels ◽  
Tissue Development ◽  
Female Wistar Rats ◽  
Better Than

Peak oxygen consumption (V̇o2peak) strongly predicts morbidity and mortality better than other established risk factors, yet mechanisms associated with its age-associated decline are unknown. Our laboratory has shown that V̇o2peak first begins to decrease at the same age of 19–20 wk in both sedentary and wheel-running, female Wistar rats (Toedebusch et al., Physiol Genomics. 48: 101–115, 2016). Here, we employed a total systemic approach using unsupervised interrogation of mRNA with RNA sequencing. The purpose of our study was to analyze transcriptomic profiles from both sedentary (SED) and wheel-running (RUN) conditions as a strategy to identify pathways in the left ventricle that may contribute to the initial reductions in V̇o2peak occurring between 19 and 27 wk of age. Transcriptomic comparisons were made within both SED and RUN rats between 19 and 27 wk ( n = 5–8). Analysis of mRNAs shared in SED and RUN between 19 and 27 wk found 17 upregulated (e.g., Adra1d, Rpl17, Xpo7) and 8 downregulated (e.g., Cdo1, Ctfg, Sfrp1) mRNAs, at 19 wk, respectively. Furthermore, bioinformatics analysis of mRNAs common to SED and RUN produced networks suggestive of increased connective tissue development at 27 vs. 19 wk. Additionally, Ctfg mRNA was negatively associated with V̇o2peak in both SED and RUN ( P < 0.05). In summary, transcriptomic analysis revealed mRNAs and networks associated with increased connective tissue development, decreased α-adrenergic activity, and decreased protein translation in the left ventricle that could, in part, potentially influence the initiation of the lifelong reduction in V̇o2peak, independent of physical activity levels.

scholarly journals An Empirical Investigation on a Multiple Filters-Based Approach for Remaining Useful Life Prediction

Machines ◽  
2018 ◽  
Vol 6 (3) ◽  
pp. 35 ◽  
Author(s):  
Hung-Cuong Trinh ◽  
Yung-Keun Kwon
Keyword(s):  
Scoring Function ◽  
Principal Component ◽  
Remaining Useful Life ◽  
Filter Method ◽  
Feature Construction ◽  
Training Set ◽  
Robust Solution ◽  
Benchmark Datasets ◽  
Useful Life ◽  
Better Than

Feature construction is critical in data-driven remaining useful life (RUL) prediction of machinery systems, and most previous studies have attempted to find a best single-filter method. However, there is no best single filter that is appropriate for all machinery systems. In this work, we devise a straightforward but efficient approach for RUL prediction by combining multiple filters and then reducing the dimension through principal component analysis. We apply multilayer perceptron and random forest methods to learn the underlying model. We compare our approach with traditional single-filtering approaches using two benchmark datasets. The former approach is significantly better than the latter in terms of a scoring function with a penalty for late prediction. In particular, we note that selecting a best single filter over the training set is not efficient because of overfitting. Taken together, we validate that our multiple filters-based approach can be a robust solution for RUL prediction of various machinery systems.

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