/pulp content, were evaluated in a collection of ‘Wonderful’ pomegranate fruits of variable sizes. Correlations between fruit characteristics were determined. In addition, factor analysis was used to establish a fruit index that can be used to select and rate
Hazel Y. Wetzstein, Zibin Zhang, Nadav Ravid and Michael E. Wetzstein
Tzu-Fang Yeh and Li-Chun Huang
absolute value of factor loading not greater than 0.3 in factor analysis were also deleted. As a result, 33 questions were accepted for the final version of the questionnaire. The data were recorded with the participants' agreement regarding the statements
Product behavior represents how consumers perceive and use a product. Its importance in predicting consumer buying behavior is well documented in marketing research. There are, however, no data available investigating the role of product behavior in the floral market. This study addressed this deficiency. Data were first analyzed using factor analysis to extract the principal determinants of product behavior in the floral market. As a result, six primary behavioral factors were identified and named as: “using flowers as daily essentials,” “perceived product value,” “negative attitude toward flowers,” “using flowers as gifts,” “eventbased usage,” and “experience in receiving flowers.” The effects of these extracted behavioral factors on consumer flower purchase frequency were then further investigated with multinomial logistic regression analysis. Analytical results revealed that behaviors “using flowers as daily essentials” and “using flowers as gifts” forced consumers to become heavy users in the floral market. Conversely, “negative attitude toward flowers” negatively affected the floral purchase frequency. Experimental results in this study also suggest that promoting a positive attitude toward flowers is essential in encouraging consumers to become flower users. The intended use of flower product purchase, whether for personal use or as gifts, was the main factor affecting the frequent purchasing of flowers.
Tina M. Waliczek, Kathryn M. Parsley, Paula S. Williamson and Florence M. Oxley
invasive species. Table 4. Results of an exploratory factor analysis indicating correlations and communality based on principal axis factoring for seven items from the invasive species knowledge and attitudes instrument in the study lecture and laboratory
Carlos A. Parera, Daniel J. Cantliffe, Peter J. Stoffella and Brian T. Scully
Poor emergence and seedling vigor are common characteristics of many sweet corn (Zea mays L.) cultivars with the shrunken-2 (sh2) mutant endosperm. A rapid and reliable predictor of sweet corn seed field emergence would improve the potential for high quality crops. Field emergence of seven sh2 sweet corn cultivars grown at seven environments in Florida were correlated with laboratory vigor tests. Factor analysis was used to separate noncollinear vigor tests for subsequent multiple regression models. The best single predictor test (R 2 = 0.93***) was an index based on leachate conductivity and germination percentage after a complex stress vigor test involving incubation at 15C. Leachate conductivity after 3 h soaking at 25 or 30C (R 2 = 0.9W***), soil cold test (R 2 = 0.9***), alternate temperature stress conductivity test (R 2 = 0.88***), standard germination test at 30C (R 2 = 0.88***), and an index involving incubation at 25C (R 2 = 0.88***) were also good predictors of field emergence. Noncollinear tests including the towel germination test at 25 C and an alternate temperature stress conductivity test resulted in the best two factor predictor (r 2 = 0.89***), and with glutamic acid decarboxylase activity (GADA) was the best three factor predictor (r 2 = 0.93***). The index of conductivity and complex vigor test (ICS) evaluated seed membrane integrity and potential for pathogen infection, respectively, and can be considered as major factors affecting emergence in sh2 sweet corn.
Thomas L. Prince, Harry K. Tayama and John R. Grabner Jr.
Retail florists' performance ratings of services provided by wholesale growers, wholesale florists, and grower-shippers/brokers were factor-analyzed to yield a hierarchical classification of customer service in floral distribution. Nine customer service factors were identified and three major independent classes of customer service were defined, including 1) physical distribution, 2) marketing, and 3) product quality services. Florists rated the performance of suppliers' physical distribution services higher than marketing and product quality services. Florists' perception of physical distribution and product quality services did not vary across type of supplier, but for marketing services, florists rated wholesale growers higher in performance than wholesale florists. The hierarchical classification of customer service and service performance profiles provide the floral industry with relevant market information for the successful development and effective implementation of customer service programs.
Anne Plotto, Anita N. Azarenko, Mina R. McDaniel, Patrick W. Crockett and James P. Mattheis
Eating quality of `Gala' and `Fuji' apples (Malus domestica Borkh.) from multiple harvests and storage durations was assessed using an untrained consumer panel. Apples were harvested at weekly intervals for 6 weeks and stored in air. Changes due to harvest maturity and storage for overall liking (OL), sweetness, tartness, firmness, and flavor intensity were evaluated over 8 months. A multivariate factor analysis revealed multicollinearity for OL, sweetness, and flavor intensity ratings in both cultivars. These attributes had the highest loadings in the first factor, explaining 51% and 52% of the variance of `Gala' and `Fuji' data sets, respectively, and were interpreted as a quality factor. Tartness and firmness had the highest loadings in the second factor for `Gala', explaining an additional 23% of the variability and reducing that cultivar's data set to two factors. For `Fuji', however, tartness and firmness were independent and included in factors 2 and 3, respectively. Factors 2 and 3 were interpreted as maturity factors, which explained 23% and 12% of the variance. The plots of the mean factor scores provided a multivariate technique to illustrate that panelists could differentiate between the stages of maturity of apples. Canonical correlations were calculated between the sensory and instrumental data. Only firmness measurements were correlated with sensory ratings for firmness (r = 0.53 and 0.44 for `Gala' and `Fuji', respectively).
Kourosh Vahdati, Naser Lotfi, Bahman Kholdebarin, Darab Hassani, Reza Amiri, Mohammad Reza Mozaffari and Charles Leslie
). Factor analysis ( Adam and Hwang, 1999 ) was then used to more clearly identify the most important determinants of drought tolerance. Factor analysis using a principal component method with varimax rotation was performed on correlation matrices for all
Kristin L. Getter and Bridget K. Behe
using the Wilcoxon–Mann–Whitney test [PROC NPAR1WAY (SAS version 9.3)]. Attitudinal questions (scored on a five-point Likert scale) were additionally evaluated using factor analysis [PROC FACTOR (SAS version 9.3)] to elucidate relationships among the
Mahdi Fendri, Isabel Trujillo, Ahmed Trigui, María Isabel Rodríguez-García and Juan de Dios Alché Ramírez
DICE coefficient 0.27). Finally, factor analysis has been conducted to characterize clustering tendencies among the identified cultivars ( Fig. 2 ). The analysis revealed only 16.38% and 12.14% of clustering according to two principal components. Such