Soil quality assessment based on hybrid computational approach with spatial multi-criteria analysis and geographical information system for sustainable tea cultivation

Saygln F., Savşatll Y., Dengiz O., Yazlcl K., Namll A., KARATAŞ A., ...Daha Fazla

Journal of Agricultural Science, cilt.161, sa.2, ss.187-204, 2023 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 161 Sayı: 2
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1017/s0021859623000138
  • Dergi Adı: Journal of Agricultural Science
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, PASCAL, Periodicals Index Online, Agricultural & Environmental Science Database, Aquatic Science & Fisheries Abstracts (ASFA), BIOSIS, CAB Abstracts, Environment Index, Food Science & Technology Abstracts, Geobase, Pollution Abstracts, Veterinary Science Database
  • Sayfa Sayıları: ss.187-204
  • Anahtar Kelimeler: Black sea region, evaluation of soil quality, soil indicators, tea plant
  • Ankara Üniversitesi Adresli: Evet

Özet

Long-Term intensive tea cultivation is suspected of deteriorating soil quality status and degrading land sustainability. This study aimed to determine the soil quality index of soils in a micro-catchment in Rize Province, Turkey, used for long-Term intensive tea cultivation, by means of Spatial Multi-Criteria Analysis (SMCA) and Standard Scoring Function (SSF) integrated with Geographical Information System (GIS) and geostatistics, considering bio-physical-chemical properties of a detailed soil dataset. Soil samples (102) were collected from the surface layer (0-20 cm). In the Soil Quality Index for tea-cultivated soils (TSQI), soil indicators were weighted by an analytical hierarchy. Various indicator units were normalized with the SSF. The TSQI model was divided into five main criteria: i) physical properties, ii) chemical properties, iii) fertility, iv) biological indicators, and v) soil erosion susceptibility parameters. Principal components analysis (PCA) was applied and minimum dataset (MDS) created to determine the most effective indicators. The spatial distribution pattern of the tea total dataset soil quality index (TSQITDS) and tea minimum dataset soil quality index (TSQIMDS) values were statistically similar. TSQITDS low and very low-class areas accounted for 34.1% of the total area, while TSQIMDS low and very low-class areas constituted 33.6%. These areas, especially those with low soil quality properties, were in the northern and north-western parts of the micro-catchment. TSQITDS very high and high-class areas accounted for 56.2% of the total area, while TSQIMDS very high and high-class areas were found in 55.3% of the total area. These areas are located in the south of the micro-catchment.