scholarly journals EFEITO DE DOSES DE INSETICIDA E ADJUVANTE NO CONTROLE DE PHYLLOCNISTIS CITRELLASTAINTON (LEPIDOPTERA: GRACILLARIIDAE) EM LIMA ÁCIDA TAHITI

2018 ◽  
Vol 14 (3) ◽  
pp. 72-81
Author(s):  
Marcos Doniseti Michelotto ◽  
Willians César Carrega ◽  
Juliana Altafin Galli ◽  
Maycon Ferraz ◽  
Tamiris Marion de Souza ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Statistical Design ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Fruit Production ◽  
Leaf Miner ◽  
Control Treatment ◽  
Citrus Leaf ◽  
Acid Lime ◽  
And Control

Citrus leaf miner, Phyllocnistis citrellaStainton,1856 (Lepidoptera,Gracillariidae), is one of the main pests of the culture of acid lime Tahiti and control chemical is the primary method of control. The objective of this study was to testthe effect of insecticide treatments associated with adjuvant, in increasing the efficiency of control of citrus leaf miner in acid lime Tahiti. An experiment was installed in statistical design of randomized blocks with five treatments and four repetitions. The treatments consisted of a control treatment without application of pesticides and the use of the insecticide Ampligo® (clorantraniliprole + lambda-cialotrina) at the recommended dosage, at half the recommended dose and associated with the adjuvant. Three applications were carried out respecting the shortage period of the product. The damages of citrus leaf miner wereassessed in five branches of the central plant.Fruits wereharvest and determining the number and the mass (kg) of fruit per plant.The data were subjected to analysis of variance (F test) and the means were compared by Tukey test (P ≤ 0.05). Also the data were submitted to multivariate analysis using hierarchical cluster analysis techniques and principal component analysis (PCA). All treatments were effective in reducing the attack symptoms of citrus leaf miner, highlighting insecticide in half dosage and application of insecticide in half dosage with the adjuvant.The multivariate analysis was effective in discriminating application treatments of insecticides and adjuvant, and showa direct relationship between the citrus leaf miner and the decrease in fruit production.

Diversity and population dynamics of parasitoids of citrus leaf miner on acid lime in Karnataka

2018 ◽  
Vol 80 (3) ◽  
pp. 971
Author(s):  
Hanamantagouda V. Paul ◽  
Venkateshalu J. B. Gopali ◽  
Mallikarjun Awati
Keyword(s):  
Population Dynamics ◽  
Leaf Miner ◽  
Citrus Leaf ◽  
Acid Lime

scholarly journals A study of new antimalarial artemisinins through molecular modeling and multivariate analysis

2010 ◽  
Vol 75 (11) ◽  
pp. 1533-1548 ◽  
Author(s):  
João Ferreira ◽  
Antonio Figueiredo ◽  
Jardel Barbosa ◽  
Maria Cristino ◽  
Williams Macedo ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Antimalarial Activity ◽  
External Validation ◽  
Geometry Optimization ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Partial Least Square ◽  
Least Square ◽  
Basis Set ◽  
Validation Parameters

Artemisinin and 18 derivatives with antimalarial activity against W-2 strains of Plasmodium falciparum were studied through quantum chemistry and multivariate analysis. The geometry optimization of the structures was realized with the Hartree-Fock (HF) theory and 3-21G basis set. Maps of molecular electrostatic potential (MEP) and molecular docking were used to investigate the interaction between the ligands and the receptor (heme). Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA) were employed to select the most important descriptors related to activity. A predictive model was generated by the Partial Least Square (PLS) method through 15 molecules and 4 used as an external validation set, which were selected in the training set, the validation parameters of which are Q2 = 0.85 and R2 = 0.86. The model included as molecular parameters, the radial distribution function, RDF060e, the hydration energy, HE, and the distance between the O1 atom from the ligand and the iron atom from heme, d(Fe-O1). Thus, the synthesis of new derivatives may follow the results of the MEP maps and the PLS analysis.

scholarly journals Application of Multivariate Analysis in the Evaluation of Metals Distribution in Soil from Awwal Mining Site Kebbi, Nigeria

2020 ◽  
Vol 27 (1) ◽  
pp. 17-24
Author(s):  
G. Shehu ◽  
I.B. Koki
Keyword(s):  
Multivariate Analysis ◽  
Health And Safety ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Underground Water ◽  
Soil Samples ◽  
Toxic Heavy Metals ◽  
Multivariate Statistical ◽  
Mining Site ◽  
Metal Levels

Multivariate statistical techniques such as principal component analysis (PCA), factor analysis (FA), and hierarchical cluster analysis (HCA) were utilized for the evaluation of metal distribution and variations in the soil at Awwal mining site. PCA was used to determine a reduced number of three principal components (PC) indicating about 82% of the total variation in the soil samples. The result of FA justifies the results of the PCA obtained. HCA classified the soil samples at the sites into two clusters, with cluster one having the higher metal levels, while cluster two had low metal levels but characterized with dominant toxic heavy metals (As and Pb). The results of the multivariate analysis showed that natural percentage abundance in soil and mineral composition of the mining ores were the main sources of the metals under study. Due to high metal levels in the soils, disposal and management of the mining waste/tailings and rehabilitation of the mining site after closure of mining should be done with care and caution to avoid leaching of the toxic metals to surface and underground water for the protection of health and safety of the neighboring community. Keywords: Soil, Metals, Mining, Multivariate analysis, Awwal.

scholarly journals PHENETIC AND UNSUPERVISED MULTIVARIATE ANALYSIS SYZYGIUM POLYANTHUM (WIGHT) WALP

2021 ◽  
Vol 52 (1) ◽  
pp. 249-258
Author(s):  
Abdulrahman & et al.
Keyword(s):  
Multivariate Analysis ◽  
Woody Plants ◽  
De Novo ◽  
Morphological Variability ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Peninsular Malaysia ◽  
Data Matrix ◽  
Documented Information ◽  
Study Species

Myrtaceae family is widely distributed in Asia has been the largest group of plant; mainly trees and few shrubs. Distributed all over the world in tropical and subtropical areas. Syzygium is the largest genus with economical value found all over the Malaysian Peninsular. Evolutionary relationships within the Syzygium is unclear and there are currently no reliable criteria to divide the genus into manageable entities for systematic study. Species of Syzygium is the richest genus of woody plants in South East Asia with approximately 1000 or more species but little is known about the genus. Syzygium polyanthum Wight is one of the favourites Ulam that have been consumed for ages in Peninsular Malaysia and also as herbal medicine. The species is widely misunderstood due to extreme morphological variability, similarity in aroma and flavor. The species is substituted or adulterated with several other species. The study was aimed to construct phenetic tree and unsupervised multivariate analysis from morphological and anatomical the data matrix.  Phenetic analysis, Principal component and hierarchical cluster analysis revealed they are two different cultivars species  but inter variation exited among cultivars of same species.  The above documented information has added new  taxonomic information with regard to the identification of the cultivars in Peninsular Malaysia. The study recommends further study on de novo sequence of Serai kayu and Serai kayu hutan.

scholarly journals Total luminescence spectroscopy for differentiating between brandies and wine distillates

2009 ◽  
Vol 27 (No. 6) ◽  
pp. 425-432 ◽  
Author(s):  
J. Tóthová ◽  
J. Sádecká ◽  
P. Májek
Keyword(s):  
Multivariate Analysis ◽  
Emission Spectra ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Luminescence Spectroscopy ◽  
Luminescence Spectra ◽  
Classification Error ◽  
Excitation Wavelength ◽  
Data Sets ◽  
Excitation Spectra

In this study, the differentiation was investigated between brandy and wine distillate samples by fluorescence spectroscopy in combination with multivariate analysis. The samples corresponding to eight brandies from three producers and sixteen wine distillates from five producers were acquired in the local supermarkets. Total luminescence spectra of diluted and undiluted samples were recorded. In order to extract reliable information from the data sets, two multivariate analysis methods, Principal Component Analysis (PCA) and Hierarchical Cluster Analysis (HCA), were applied separately on the excitation and emission spectra. The best differentiation was achieved using the emission spectra (400–470 nm) recorded at the excitation wavelength of 340 nm, or the excitation spectra (240–380 nm) recorded at the emission wavelength of 450 nm. The similarity map defined by the PC1 and PC2 of the PCA performed on the excitation spectra accounted for 94.9% of the total variance (PC1 90.3%, PC2 4.6%) and allowed a good discrimination between the beverages. Although the PCA similarity map defined by the PC1 (84.2%) and PC2 (13.0%) performed on the emission spectra did not lead to a clear discrimination between the beverages, a general trend pointing out the brandies and wine distillates was observed on the map. HCA performed on the excitation spectra provided a better differentiation between the two classes, without any classification error, while HCA performed on the emission spectra allowed 95.8% correct classification.

scholarly journals Selection of Experimental Hybrids of Strawberry Using Multivariate Analysis

Agronomy ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 598 ◽  
Author(s):  
Eneide Barth ◽  
Juliano Tadeu Vilela de Resende ◽  
Aline Fabiana Paladini Moreira ◽  
Keny Henrique Mariguele ◽  
André Ricardo Zeist ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Block Design ◽  
Selection Index ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
High Variability ◽  
Soluble Solids ◽  
Fresh Market ◽  
Commercial Cultivars ◽  
Selection Of

The selection of superior strawberry genotypes is a complex process due to the high variability after hybridization that is caused by the octoploid nature and the heterozygosis, making the selection of multiple traits difficult. This study aimed to select strawberry hybrids with the potential for fresh consumption and/or processing by applying multivariate analysis to obtain traits of interest simultaneously. Hybrids were obtained from the crossing among seven commercial cultivars, defining a selection of 10% of them. The experimental design consisted of an augmented block design, with two commercial cultivars, Camarosa and Camino Real, as the controls. Different variables, including the number and average mass of commercial fruits, total fruit mass, pH, soluble solids (SS), titratable acidity (TA), SS/TA ratio, reducing sugars, pectin, ascorbic acid, phenolic compounds, and anthocyanin’s, were assessed. The selection of hybrids was based on the Mulamba and Mock rank-summation index, principal component analysis, and Ward’s hierarchical cluster analysis. The selection index was based on different weights being adopted for fresh market and processing. The assessed traits had high variability between hybrids. The highest selection gains were obtained for production traits, but the different weight assignment resulted in different classifications of hybrids for both fresh consumption and processing. Most of the hybrids selected by the index remained in the same group in the principal component and hierarchical cluster analyses, which indicates that multivariate analysis is a valuable tool for assisting in the selection of superior hybrids in the strawberry crop.

scholarly journals Essential metals and phenolic acids in commercial herbs and spices. Multivariate analysis of correlations among them

2015 ◽  
Vol 13 (1) ◽  
Author(s):  
Agnieszka Arceusz ◽  
Marek Wesolowski
Keyword(s):  
Multivariate Analysis ◽  
Phenolic Acids ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Biologically Active ◽  
Essential Metals ◽  
Lemon Balm ◽  
Sodium Magnesium ◽  
Low Levels ◽  
Herbs And Spices

AbstractThe purpose of this study was to show relationships among the levels of essential metals (zinc, iron, sodium, magnesium, calcium and potassium) and phenolic acids (caffeic, chlorogenic, ferulic, gallic, rosmarinic and syringic) in commercial herbs (lemon balm, thyme, rosemary, mint, sage and angelica) and spices (caraway, lovage, hyssop and oregano). In the herbs higher quantities of metals and phenolic compounds were found than in spices. All plants contained high levels of calcium, potassium and rosmarinic acid, but low levels of zinc and gallic acid. By using principal component and hierarchical cluster analyses several clusters were identified grouping samples originating from a plant of a particular botanical species. Multivariate analysis has also shown that the contents of phenolic acids had a stronger impact on the scattering of herbs and spices than the metals levels. Furthermore, statistically significant correlations were found between calcium and ferulic, gallic, rosmarinic and syringic acids as well as between zinc and sodium and caffeic acid. This suggests co-operate between these biologically active constituents in metabolic processes occurring in plants.

scholarly journals Detection and classification of Bacteria using Raman Spectroscopy Combined with Multivariate Analysis

2017 ◽  
Vol 2 (4) ◽  
pp. 435 ◽  
Author(s):  
S. Sil ◽  
R. Mukherjee ◽  
N. S. Kumar ◽  
Aravind S. ◽  
J. Kingston ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Multivariate Analysis ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Spectroscopic Techniques ◽  
Hybrid Technique ◽  
Chemometric Method ◽  
Linear Discriminant ◽  
Linear Discrimination

<p class="p1">Vibrational spectroscopic techniques have advantages over conventional microbiological approaches towards identification &amp; detection of pathogens. Since unique spectral fingerprint is obtained, one can identify very closely related bacteria using such methods. In this study Raman microspectroscopy in combination with chemometric method has been used to classify four strains of <em>E</em>. <em>coli </em>(two pathogenic &amp; two non-pathogenic). Different multivariate approaches such as hierarchical cluster analysis, principal component analysis &amp; linear discriminant analysis were explored to obtain efficient classification of the Raman signals obtained from the four strains of <em>E.coli</em>. It was observed that multivariate analysis was able to classify the bacteria at strain level. Linear discrimination analysis using PC scores (PC-LDA) was found to give very good result with as high as 100% accuracy. This hybrid technique (Raman spectroscopy &amp; multivariate analysis) has tremendous potential to be developed as a tool for bacterial identification.<span class="Apple-converted-space"> </span></p>

scholarly journals Data on phenology, parasitism and control of citrus leaf miner, Phyllocnistis citrella Stainton (Lepidoptera, Gracillariidae), in Greece

2006 ◽  
Vol 58 (4) ◽  
pp. 239-244 ◽  
Author(s):  
Anagnou Veroniki ◽  
D.C. Kontodimas ◽  
N.G. Kavallieratos ◽  
D. Doukas ◽  
G. Staroyiannis ◽  
...  
Keyword(s):  
Lower Surface ◽  
Leaf Miner ◽  
Phyllocnistis Citrella ◽  
Citrus Leaf ◽  
Central Greece ◽  
Different Types ◽  
Neochrysocharis Formosa ◽  
Citrostichus Phyllocnistoides ◽  
And Control ◽  
Citrus Trees

Research was conducted to determine whether Phyllocnistis citrella Stainton (Lepidoptera, Gracillariidae) has any preference in attacking either the upper or the lower surface of the leaves of citrus trees. This investigation took place during the year 1999 at Marathon (Attica, Central Greece) while studying the dispersal of P. citrella on the leaves of three different types of citrus trees. Data on the overwintering and parasitism of P. citrella from different areas in Greece are also presented during the years 1999-2002. In addition, the effect of P. citrella infestation on imidacloprid-treated and untreated tangerine trees was comparatively studied. The parasitoids collected were Pnigalio sp. (Hymenoptera, Eulophidae), Cirrospilus sp. (Hymenoptera, Eulophidae), Neochrysocharis formosa (Westwood) (Hymenoptera, Eulophidae) and Citrostichus phyllocnistoides (Narayanan) (Hym., Eulophidae).

scholarly journals On the Use of Multivariate Analysis and Land Evaluation for Potential Agricultural Development of the Northwestern Coast of Egypt

Agronomy ◽  
2020 ◽  
Vol 10 (9) ◽  
pp. 1318 ◽  
Author(s):  
Mohamed El Sayed Said ◽  
Abdelraouf. M. Ali ◽  
Maurizio Borin ◽  
Sameh Kotb Abd-Elmabod ◽  
Ali A. Aldosari ◽  
...  
Keyword(s):  
Multivariate Analysis ◽  
Agricultural Development ◽  
Agricultural Sector ◽  
Soil Depth ◽  
Principal Component ◽  
Hierarchical Cluster ◽  
Land Evaluation ◽  
Land Capability ◽  
Soil Suitability ◽  
Agglomerative Hierarchical Cluster Analysis

The development of the agricultural sector is considered the backbone of sustainable development in Egypt. While the developing countries of the world face many challenges regarding food security due to rapid population growth and limited agricultural resources, this study aimed to assess the soils of Sidi Barrani and Salloum using multivariate analysis to determine the land capability and crop suitability for potential alternative crop uses, based on using principal component analysis (PCA), agglomerative hierarchical cluster analysis (AHC) and the Almagra model of MicroLEIS. In total, 24 soil profiles were dug, to represent the geomorphic units of the study area, and the soil physicochemical parameters were analyzed in laboratory. The land capability assessment was classified into five significant classes (C1 to C5) based on AHC and PCA analyses. The class C1 represents the highest capable class while C5 is assigned to lowest class. The results indicated that about 7% of the total area was classified as highly capable land (C1), which is area characterized by high concentrations of macronutrients (N, P, K) and low soil salinity value. However, about 52% of the total area was assigned to moderately high class (C2), and 29% was allocated in moderate class (C3), whilst the remaining area (12%) was classified as the low (C4) and not capable (C5) classes, due to soil limitations such as shallow soil depth, high salinity, and increased erosion susceptibility. Moreover, the results of the Almagra soil suitability model for ten crops were described into four suitability classes, while about 37% of the study area was allocated in the highly suitable class (S2) for wheat, olive, alfalfa, sugar beet and fig. Furthermore, 13% of the area was categorized as highly suitable soil (S2) for citrus and peach. On the other hand, about 50% of the total area was assigned to the marginal class (S4) for most of the selected crops. Hence, the use of multivariate analysis, mapping land capability and modeling the soil suitability for diverse crops help the decision makers with regard to potential agricultural development.

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