African Journal of
Agricultural Research

  • Abbreviation: Afr. J. Agric. Res.
  • Language: English
  • ISSN: 1991-637X
  • DOI: 10.5897/AJAR
  • Start Year: 2006
  • Published Articles: 6574

Full Length Research Paper

A Bayesian confirmatory factor analysis of precision agricultural challenges

Maryam Omidi Najafabadi√ô¬≠, Seyed Jamal Farajollah Hosseini and Somayeh Bahramnejad  
Department of Agricultural Extension and Education, Science and Research Branch, Islamic Azad University, Tehran, Iran.
Email: [email protected]

  •  Accepted: 24 January 2011
  •  Published: 31 March 2011



Precision agriculture (PA) is designed to provide data to assist farmers when making site-specific management decisions. By making more informed management decisions, farmers can become more efficient, spend less and make more profit. Such benefits may lead to a sustainable agriculture. In implementation of PA, farmers encountered several challenges; therefore it is necessary to identify such challenges. A survey questionnaire was developed and mailed to a group of 40 experts in Qazvin province. The results showed that the challenges can be classified into nine latent variables namely: educational, economic, operator demographic, technical, data quality, high risk, time, institution-education and incompatibility challenges. The results suggested educational and economic challenges as the two most important challenges in the application of PA. Among the variables which build the educational challenges, lack of local experts and lack of a knowledgeable research and extension personnel provides more impact when compared to others, while lack of allocation funds to performance PA and Initial cost provides more impact in the economic challenges, among other variables.


Key words: Bayesian confirmatory factor analysis, challenges, precision agriculture (PA), sustainable agriculture, Iran.