Study on Integrated Climatic Index for Low Temperature Injury of Loquat in Putian

2013 ◽  
Vol 726-731 ◽  
pp. 4436-4441
Author(s):  
Kai Yang ◽  
Bin Bin Chen ◽  
Hui Chen ◽  
Jing Lin ◽  
Jia Yi Wang ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Critical Temperature ◽  
Low Temperature ◽  
Correlation Analysis ◽  
Minimum Temperature ◽  
Principal Component ◽  
Climate Data ◽  
Climatic Index ◽  
Extreme Minimum Temperature ◽  
Inducing Factors

Based on the daily climate data in winter and relative meteorological yield of loquat for 2 meteorological stations in Putian from 1992 to 2009, this paper studied the disaster-inducing factors and integrated climatic index for low temperature injury of loquat. The results showed that the critical temperature for low temperature injury of loquat could be determined as 3.0°C. The disaster-inducing factors included extreme minimum temperature, the sum of daily numbers for less than or equal to 3.0°C, the sustained days of low temperature injury for less than or equal to 3.0°C, and harmful chilling accumulation for less than or equal to 3.0°C, and there were obvious correlations among these factors. According to the method of principal component analysis, an integrated climatic index was obtained. By the correlation analysis of integrated climatic index for low temperature injury and the relative meteorological yield of loquat in Putian, the value of integrated climatic index of low temperature injury was significantly negatively correlated with the yield of loquat, and could be used to analyze the degree of low temperature injury of loquat.

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

Evaluation of the morphological diversity of tea roses (Rosa x odorata) based on phenotypic traits

2020 ◽  
Vol 18 (3) ◽  
pp. 149-158
Author(s):  
Bixuan Cheng ◽  
Chao Yu ◽  
Heling Fu ◽  
Lijun Zhou ◽  
Le Luo ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Correlation Analysis ◽  
Morphological Traits ◽  
Significant Positive Correlation ◽  
Flower Colour ◽  
Principal Component ◽  
Morphological Diversity ◽  
Component Analysis ◽  
Germplasm Resources ◽  
Trait Correlation

AbstractRosa x odorata (sect. Chinenses, Rosaceae) is an important species distributed only in Yunnan Province, China. There is an abundance of wild variation within the species. Using 22 germplasm resources collected from the wild, as well as R. chinensis var. spontanea, R. chinensis ‘Old Blush’ and R. lucidissima, this study involved morphological variation analysis, inter-trait correlation analysis, principal component analysis and clustering analysis based on 16 morphological traits. This study identified a high degree of morphological diversity in R. x odorata germplasm resources and the variation coefficients had a distribution range from 18.00 to 184.04%. The flower colour had the highest degree of variation, while leaflet length/width had the lowest degree of variation. Inter-trait correlation analysis revealed that there was an extremely significant positive correlation between leaflet length and leaflet width. There was also a significant positive correlation between the number of petals and duration of blooming, and the L* and a* values of flower colour were significantly negatively correlated. Principal component analysis screened five principal components with the highest cumulative contribution rate (81.679%) to population variance. Among the 16 morphological traits, style length, sepal width, flower diameter, flower colour, leaflet length and leaflet width were important indices that influenced the morphology of R. x odorata. This study offers guidance for the further development and utilization of R. x odorata germplasm resources.

scholarly journals Correlation Analysis Between Antioxidant Activity and Phytochemicals in Korean Colored Corns Using Principal Component Analysis

2014 ◽  
Vol 6 (4) ◽  
pp. 1 ◽  
Author(s):  
Kang Mo Ku ◽  
Hye Suk Kim ◽  
Soon Kwon Kim ◽  
Young-Hwa Kang
Keyword(s):  
Principal Component Analysis ◽  
Antioxidant Activity ◽  
Correlation Analysis ◽  
Principal Component ◽  
Total Content ◽  
Component Analysis ◽  
Total Anthocyanin ◽  
Reducing Ability ◽  
Good Target ◽  
Diammonium Salt

The colored corns are used as food as well as for feed in Asian countries; however, the active component of antioxidant activity in Korean colored corns has not been investigated. Thus, we measured the total content of carotenoids, phenols, flavonoids, and anthocyanins from 40 Korean colored corn genotypes for correlation analysis between antioxidant activity and these phytochemicals. The ferric reducing ability power (FRAP) and 2,2'-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) diammonium salt (ABTS) activity were measured in order to study this correlation. As a result, there was large variation in total anthocyanin (coefficient of variation, CV 85.0%) and total carotenoid contents (CV 87.8%), while CVs of total phenol, total flavonoid contents, ABTS and FRAP was relatively low (CV 15.0%, 22.8%, 15.5%, and 16.3% respectively). There were meaningful correlations between ABTS and anthocyanins, phenols, and flavonoids, as well as correlations between FRAP and phenols as well as FRAP and flavonoids. We also obtained a more informative and easily visualized result by using principal component analysis (PCA). Anthocyanins and carotenoids showed a large variation as compared to other compounds. Anthocyanins are a good target to increase antioxidant activity in colored corns.

An Affective Approach to Developing Marketing Strategies of Mineral Water

2012 ◽  
Vol 16 (4) ◽  
pp. 514-520 ◽  
Author(s):  
Junzo Watada ◽  
◽  
Le Yu ◽  
Munenori Shibata ◽  
Marzuki Khalid ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Correlation Analysis ◽  
Mineral Water ◽  
Principal Component ◽  
Component Analysis ◽  
Marketing Strategies ◽  
Taste Preferences ◽  
Self Organizing Map ◽  
Water Based ◽  
Self Organizing

This study is concerned with the development of marketing strategies for mineral water based on consumers’ taste preferences, by analyzing the taste components of mineral water. In this study, we used a twodimensional analysis to classify taste data. We conducted a correlation analysis to identify the characteristics of taste data. We applied a combination of principal component analysis and self-organizing map to classify mineral water tastes. Based on this evaluation, we identified some marketing strategies in the conclusion. According to this study, the taste of mineral water is not determined by the origin and is not influenced by the hardness of the water.

scholarly journals Analisis Partial Least Square Menghasilkan Output Alternatif Antarmuka Tambahan Dari Kansei Engineering

2020 ◽  
Vol 17 (2) ◽  
pp. 67
Author(s):  
Arief Ginanjar ◽  
Awan Setiawan
Keyword(s):  
Principal Component Analysis ◽  
Factor Analysis ◽  
Correlation Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Partial Least Square ◽  
Least Square ◽  
Type I ◽  
Kansei Engineering ◽  
Coefficient Corrélation

Ketika menggunakan Kansei Engineering dalam mencari kandidat terbaik untuk menentukan model perancangan antarmuka website, peneliti menggunakan metode analisis Partial Least Square (PLS) yang dilakukan secara berulang hingga ditemukan elemen terbaik yang dapat diimplementasikan. PLS sebagai alat bantu untuk menentukan nilai terbaik antara elemen website. Output perbandingan yang dihasilkan akan dikelompokkan berdasarkan Kansei Word sebagaimana yang telah ditentukan dalam rencana awal implementasi Kansei Engineering, output perbandingan PLS iterasi pertama mempunyai kemungkinan mendapatkan nilai usulan terbaik jika digabung dengan melakukan iterasi kedua terhadap asimilasi dua atau tiga elemen yang mempunyai nilai tertinggi. Metodologi yang digunakan mengacu kepada Kansei Engineering Type I dengan melalui pengolahan data menggunakan Cronbach’s Alpha untuk menguji kelayakan responden, kemudian untuk mengetahui hubungan Kansei Words dapat menggunakan Coefficient Correlation Analysis (CCA), sedangkan hubungan antara Kansei Words dengan spesimen dapat menggunakan Principal Component Analysis (PCA), sedangkan mencari pengaruh Kansei Words paling kuat dapat menggunakan Factor Analysis (FA) dan analisis Partial Least Square (PLS) namun harus dilakukan iterasi proses PLS hingga variabel rekomendasi model perancangan antarmuka yang dihasilkan menjadi lebih bervariatif.

scholarly journals Gerris Lacustris (Linaeus 1758) and Gerris Costae (Herrich-Schäffer 1850) Species - Habitat Relations on Mountainous Tributaries of Vişeu River (Maramureş, Romania)

2013 ◽  
Vol 15 (1) ◽  
pp. 11-18
Author(s):  
Horea Olosutean ◽  
Daniela Minodora Ilie
Keyword(s):  
Principal Component Analysis ◽  
Correlation Analysis ◽  
Human Impact ◽  
Principal Component ◽  
Habitat Conditions ◽  
Stagnant Water ◽  
Habitat Changes ◽  
Habitat Variation ◽  
Steep Slopes ◽  
Habitat Variables

ABSTRACT Semi aquatic Heteroptera species from some mountainous tributaries of the Vişeu River were collected and their relations with habitat variables were investigated. Only two species, Gerris lacustris and Gerris costae were found, either one or both species, in almost half of the investigated sampling stations. Correlation analysis between samplings and habitat conditions showed that Gerris lacustris prefers small deep ponds or river banks with steep slopes and is easily adaptable to habitat changes, while Gerris costae is mostly found in large marshes with low, stagnant water and high amounts of vegetation. Both species are relatively tolerant to human impact in their habitat, Gerris lacustris more so. The two species are negatively correlated to each other, as an expression of competition between them. Principal Component Analysis resulted in two dominant factors explaining almost 60% of the habitat variation, and their graphic representation proved the observed correlations.

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