scholarly journals Pengelompokan 33 Aksesi Kakao Berdasarkan Karakter Morfologi Komponen Buah

2017 ◽  
Vol 4 (2) ◽  
pp. 67
Author(s):  
Edi Wardiana ◽  
Juniaty Towaha ◽  
Syafaruddin Syafaruddin
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Discriminant Analysis ◽  
Hierarchical Cluster Analysis ◽  
Morphological Character ◽  
Hierarchical Cluster ◽  
Dry Weight ◽  
Morphological Characters ◽  
Fresh Weight ◽  
Experimental Station

<em>Identification and grouping of diverse cacao accessions based on morphological character of pod components is important in breeding activities to generate superior varieties. This study aimed to grouping 33 cocoa accessions based on morphological characters of pod components, conducted at Pakuwon Experimental Station, Sukabumi, West Java, at an altitude of 450 asl with Latosol soil and B type climate (Schmidt and Fergusson), from January until December 2015. Observation was taken on 33 cacao accessions of Kaliwining (KW), planted in 2012 with 3 m x 3 m spacing under 26 years old Genjah Salak coconut trees as shading. Ten mature pods were randomly harvested from 10 cocoa plants of each accession at respective two seasons (February and December 2015). The variables observed were 7 characters of pod components i.e.: (1) fresh weight of pod, (2) number of beans, (3) fresh weight of beans, (4) dry weight of beans, (5) fresh weight of pod husk, (6) number of pod furrow, and (7) fresh weight of pulp. Data were analyzed by factor analysis followed by hierarchical cluster analysis in Ward's method and discriminant analysis. The result showed that 19 accessions were classified as high in bean and pod husk component characters, 9 accessions were classified as high in pulp characters, and 5 accessions i.e. KW 162, KW 528, KW 570, KW 571, and KW 720 were classified as high in all characters of pod components, and potential as parents in generating superior cacao varieties.</em>

scholarly journals Ultraviolet Spectroscopy Used to Fingerprint Five Wild-Grown Edible Mushrooms (Boletaceae) Collected from Yunnan, China

2016 ◽  
Vol 2016 ◽  
pp. 1-8 ◽  
Author(s):  
Yan Li ◽  
Ji Zhang ◽  
Tao Li ◽  
Tianwei Yang ◽  
Yuanzhong Wang ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Hierarchical Cluster Analysis ◽  
Visual Discrimination ◽  
Uv Spectroscopy ◽  
Hierarchical Cluster ◽  
Uv Spectra ◽  
Edible Mushrooms ◽  
Ultraviolet Spectroscopy

Nowadays, wild-grown edible mushrooms which are natural, nutritious, and healthy get more and more popular by large consumers. In this paper, UV spectra of different Boletaceae mushrooms with the aid of partial least squares discriminant analysis (PLS-DA) and hierarchical cluster analysis (HCA) were shown to be a practical and rapid method for discrimination purpose. The specimens of Boletus edulis, Boletus ferrugineus, Boletus tomentipes, Leccinum rugosiceps, and Xerocomus sp. were described based on the UV spectra. From the results, all the specimens were characterized by strong absorption at the wavelengths of 274 and 284 nm and showed the shoulder at 296 nm. However, changes could be seen in the peak heights at the same wavelength for different samples. After analyzing by chemometrics, visual discrimination among samples was presented and the relationships among them were also obtained. This study showed that UV spectroscopy combined with chemometrics methods could be used successfully as a simple and effective approach for characterization of these five wild-grown edible mushrooms at species and genus levels. Meanwhile, this rapid and simple methodology could also provide reference for the discrimination of edible mushrooms.

scholarly journals Correlation of Volatile Compounds and Sensory Attributes of Chinese Traditional Sweet Fermented Flour Pastes Using Hierarchical Cluster Analysis and Partial Least Squares-Discriminant Analysis

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Meigui Huang ◽  
Yulin Li ◽  
Ping Zhan ◽  
Ping Liu ◽  
Honglei Tian ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Least Squares ◽  
Volatile Compounds ◽  
Partial Least Squares ◽  
Hierarchical Cluster Analysis ◽  
Solid Phase ◽  
Hierarchical Cluster ◽  
Sensory Attributes ◽  
Volatile Components

The aroma compositions, sensory attributes, and their correlations of various traditional Chinese sweet fermented flour pastes (SFFPs) were investigated. SFFPs, including LEEJ, LEEH, and XH6, showed high overall acceptance scores of 8.00, 8.21, and 7.50, respectively. Ninety-six volatile compounds were detected using solid-phase microextraction gas chromatography mass spectrometry. Hierarchical cluster analysis grouped SFFPs into three clusters according to their concentrations and compositions of volatile components. Partial least squares-discriminant analysis showed that volatile compounds, including ethyl phenylacetate, 5-methyl furfural, amyl cinnamal, ethyl myristate, decyl aldehyde, 1-phenylethyl acetate, 1-octen-3-ol, 3-buten-2-ol, butanoic acid, and caproaldehyde, were highly negatively correlated with saltiness, sourness, and bitterness, while they were positively correlated with sweetness, umami, richness, and acceptance. The obvious correlation between flavor profiles and sensory attributes could help online monitoring of SFFPs’ flavor quality during production.

scholarly journals Use of Factorial Analysis of Mixed Data (FAMD) and Hierarchical Cluster Analysis on Principal Component (HCPC) for Multivariate Analysis of Academic Performance of Industrial Engineering Programs

2020 ◽  
Vol 55 (5) ◽  
Author(s):  
Delimiro Visbal-Cadavid ◽  
Adel Mendoza-Mendoza ◽  
Enrique De La Hoz-Dominguez
Keyword(s):  
Higher Education ◽  
Cluster Analysis ◽  
Factor Analysis ◽  
Academic Performance ◽  
Hierarchical Cluster Analysis ◽  
Higher Education Institutions ◽  
Hierarchical Cluster ◽  
Industrial Engineering ◽  
Mixed Data ◽  
Engineering Programs

The article describes a new idea about using Factor Analysis, Mixed Data, and Hierarchical Cluster Analysis on Principal Components to study the academic performance in 82 Industrial Engineering Programs in Colombia. For this, we used the data from the results of the standardized test of the Saber Pro.). The authors find that the first three components explain 89.12% of the original data set variability. The quantitative variables associated with the Factor Analysis are the first dimension, while the two qualitative variables are related to the second dimension. The first factor explains 95.83% of the dispersion of the scores in Critical Reading, 94.72% of the variability in Quantitative Reasoning, 94.51% of the variation in Mathematics and Statistics, among others. This study shows a strong positive correlation between the quantitative variables and the first factorial axis. It assumes that the Industrial Engineering Programs of public higher education institutions perform better than private ones. The article stipulates that the higher education institutions belonging to the Andean Region present a better performance, followed by the higher education institutions located in the Pacific Region. In general terms, the results confirm that the best performing universities usually appear in the first places in the different rankings and are located in the big cities.

scholarly journals The organization of taste sensibilities in hamster chorda tympani nerve fibers.

1988 ◽  
Vol 91 (6) ◽  
pp. 861-896 ◽  
Author(s):  
M E Frank ◽  
S L Bieber ◽  
D V Smith
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Hierarchical Cluster Analysis ◽  
Nerve Impulse ◽  
Hierarchical Cluster ◽  
Nerve Fibers ◽  
Chorda Tympani ◽  
Chorda Tympani Nerve ◽  
Activation Patterns ◽  
Response Profiles

Electrophysiological measurements of nerve impulse frequencies were used to explore the organization of taste sensibilities in single fibers of the hamster chorda tympani nerve. Moderately intense taste solutions that are either very similar or easily discriminated were applied to the anterior lingual surface. 40 response profiles or 13 stimulus activation patterns were considered variables and examined with multivariate statistical techniques. Three kinds of response profiles were seen in fibers that varied in their overall sensitivity to taste solutions. One profile (S) showed selectivity for sweeteners, a second (N) showed selectivity for sodium salts, and a third (H) showed sensitivity to salts, acids, and other compounds. Hierarchical cluster analysis indicated that profiles fell into discrete classes. Responses to many pairs of effective stimuli were covariant across profiles within a class, but some acidic stimuli had more idiosyncratic effects. Factor analysis of profiles identified two common factors, accounting for 77% of the variance. A unipolar factor was identified with the N profile, and a bipolar factor was identified with the S profile and its opposite, the H profile. Three stimulus activation patterns were elicited by taste solutions that varied in intensity of effect. Hierarchical cluster analysis indicated that the patterns fell into discrete classes. Factor analysis of patterns identified three common unipolar factors accounting for 82% of the variance. Eight stimuli (MgSO4, NH4Cl, KCl, citric acid, acetic acid, urea, quinine HCl, HCl) selectively activated fibers with H profiles, three stimuli (fructose, Na saccharin, sucrose) selectively activated fibers with S profiles, and two stimuli (NaNO3, NaCl) activated fibers with N profiles more strongly than fibers with H profiles. Stimuli that evoke different patterns taste distinct to hamsters. Stimuli that evoke the same pattern taste more similar. It was concluded that the hundreds of peripheral taste neurons that innervate the anterior tongue play one of three functional roles, providing information about one of three features that are shared by different chemical solutions.

Spatial–Temporal Neighborhood Patterns in Four Legacy Cities

2020 ◽  
pp. 107808741989782
Author(s):  
Kelly L. Kinahan
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Hierarchical Cluster Analysis ◽  
Temporal Trends ◽  
Hierarchical Cluster ◽  
Neighborhood Scale ◽  
Legacy Cities ◽  
Over 40 Years ◽  
Neighborhood Typology

Legacy cities are characterized by long-term, declining trends in both population and economic characteristics, but how these events translate to the neighborhood scale is less well understood. This research investigates the evolution of neighborhood types in four legacy cities—Baltimore, Cleveland, Philadelphia, and St. Louis—from 1970 to 2010. Working from a multidimensional framework of variables across five census decades, hierarchical cluster analysis and discriminant analysis are used to develop a neighborhood typology, identify temporal trends, and describe the pathways of transition. Results reveal four crosscutting neighborhood types: Black Distressed; Lower Middle; Multifamily, Educated, Turnover; and Upper Middle, which persist across space and time. Most neighborhoods (61%) remained classified within the same type over 40 years, and transitions were concentrated in two decades (1970–1980 and 2000–2010). The results offer a new descriptive dimension for understanding the unevenness present across legacy cities and suggest that existing policy approaches continually reproduce the same neighborhood outcomes.

scholarly journals Novel anti-tuberculosis drug designs by data mining for similarity in substituent substitution and structure modification

2011 ◽  
Vol 1 (1) ◽  
pp. 15 ◽  
Author(s):  
Ronald Lee Bartzatt
Keyword(s):  
Data Mining ◽  
Molecular Weight ◽  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Surface Area ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Log P ◽  
Polar Surface Area ◽  
Pharmaceutical Properties

<em>Mycobacterium tuberculosis</em> (TB) is among the most common of infectious diseases that cause death, and as many as one-third of the world’s population may be infected. This work presents 17 novel hydrazide agents formed by focused in silico data mining utilizing search parameters restricted to substituent replacement only. Substituent substitution has been highly successful in design of novel antibacterial and antiviral drugs. This diverse set of hydrazide constructs possess molecular properties indicating favorable bioavailability with excellent intestinal absorption for oral administration. All agents have zero violations of the Rule of 5, indicating favorable druglikeness. Important pharmaceutical properties including polar surface area, Log P, and formula weight were determined and compared to that of the parent structure of isoniazid by hierarchical cluster analysis and discriminant analysis. The average Log P with range is -0.258 and -2.165 to 1.373, respectively. The average polar surface area (PSA) with range is 75.19 A2 and 55.121 A2 to 94.036 A2, respectively. The diverse range of PSA and Log P, with other descriptors, portend a versatile group of hydrazide drugs having substantial potential to expand the application and effectiveness for clinical treatment of multi-organ infected TB patients. Analysis of similarity indicated that all 17 agents are significantly similar to isoniazid, however discriminant analysis and hierarchical cluster analysis are able to differentiate isoniazid based upon molecular properties. Molecular weight and number of atoms were highly correlated by Pearson r (r &gt; 0.9000), with Log P moderately correlated (r &gt; 0.5500) to number of atoms, molecular weight, and volume. Seventeen hydrazide compounds (success rate of approximately 38%) having diverse pharmaceutical properties resulted from substituent data mining with potential for clinical application.

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