EXPERIMENTAL DESIGN APPROACH TO LAND PRODUCTIVITY ASSESSMENT: A CASE STUDY IN SINOP, TURKEY


ŞİŞMAN Y., Dengiz O., Şişman A., Turan I. D.

FRESENIUS ENVIRONMENTAL BULLETIN, cilt.26, sa.3, ss.1941-1948, 2017 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 26 Sayı: 3
  • Basım Tarihi: 2017
  • Dergi Adı: FRESENIUS ENVIRONMENTAL BULLETIN
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED)
  • Sayfa Sayıları: ss.1941-1948
  • Anahtar Kelimeler: Land productivity assessment, Experimental design, Fractional Factorial Experimental Design, the Regression Model, FULL-FACTORIAL DESIGN
  • Ondokuz Mayıs Üniversitesi Adresli: Evet

Özet

The evaluation and mapping of spatial variations of land productivity are important for an effective and sustainable management of land and soil resources. However, to evaluate complex phenomena such as land productivity, several experiments may be required. Therefore, experimental designs that are time and cost-effective are needed. The main and interaction effect of different factors on a response variable can be investigated using different experimental design methods, one of which is the Fractional Factorial Design. The main objective of this research was to evaluate the land productivity of an agricultural area in Sinop, Turkey using a parametric method. A total of 432 soil samples were collected from the depth of 0-20 cm using a global positioning system. After determining certain physical and chemical properties of the samples, the fractional factorial design was applied to the land productivity data to create an experimental model. Using this model, six factors; namely slope, soil depth, texture, permeability, pH, Cation Exchange Capacity, organic matter and salt concentration were analyzed in terms of their effect on the land quality index. The significance of the effects of experimental factors was evaluated using the Minitab 16 software. Then, a regression model was created for the study area represented with 432 soil samples. The resulting model was found efficient and thus can be used for the assessment of other land areas.