Multivariate approach to analyzing survey data: a case study of beekeeping in Lebanon

 

Beekeeping and honey production have been of great historical, economic, and health interest in Lebanon. However, the Lebanese beekeeping sector is poorly documented, not to mention the challenging natural and economical threats the beekeepers face which result in a decrease in honey production. In order to inform needed outreach and education activities in Lebanon, a comprehensive survey was conducted among beekeepers covering all the Lebanese territory. This survey allowed the collection of valuable information from each beekeeper about the hives’ location and number as well as the harvest season and the beekeeping practices. Principal Component Analysis (PCA), a novel approach to analyzing survey data was used as it proved to be an efficient and rapid tool. PCA showed a significant difference among beekeepers regarding 1- their acquired knowledge in beekeeping, 2- their membership in a cooperative, 3- the number of hives they own, and 4- the honey storage conditions they use. In addition, the application of PCA attributed the difference in beekeeping practices between Lebanese beekeepers to the different geographical agricultural zones in the country. Finally, the results showed that beekeepers coming from the Baalbeck-Hermel zone lacked proper beekeeping training and management and that most of the surveyed-Lebanese beekeepers (87%) practiced migratory beekeeping all year long in relation to flowering plants. Our findings demonstrated that PCA was able to extract useful information from survey data and this study is the first document about the beekeeper situation in Lebanon, representing a cornerstone for improvement of this sector across the country.

Keywords:

• Survey analysis
• beekeeping practices
• migratory beekeeping
• pp-ANOVA
• PCA

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was funded by CNRS-L.