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Today, crop models have been developed to products of strategic importance for precision agriculture management in the countries. The objective of this study was to generate the wheat suitability index (WSI) by using hybrid system that is including qualitative and quantitative reasons such as expert and sciencific knowledge weighted with analytic hierarchy process (AHP). This aproach was integrated into the GIS based on Linear Combination Teqnique in the study. For this purpose, the study was conducted in the field of wheat cultivation in Soğulca Basin with an area of 68.04 km2 located on Central Anatolia Region of Turkey. We have selected 10 criteria as physical, chemical and topographical that affects wheat cultivation in the basin which has been divided into 47 land units according to thematic soil map. With the WSI model, 32.05% of the study area was classified as highly and moderately suitable whereas, 67.95% of the total study area has marginally and not suitable properties for wheat cultivation. According to results, the most effective factors on the last score values for WSI were found soil depth, texture and slope indicators. The score values of the WSI were compared with 5 years (2013–2017) yields and NDVI values for testing of the model and it has been determined that land classification for wheat has been done with high accuracy for yield r2 = 0.83% and for NDVI r2 = 0.78%. The results of the study showed that the WSI was found as convenient model in semi-arid climate condition. However, we suggest that the WSI model should also be tested in similar climatic conditions and in different soil types in order to be available as a general - pass index. In addition, using AHP with GIS capabilities, we have high capacity to the integration of heterogeneous data for determination and classification of suitability in the agriculture areas.
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Belge Türü
Kaynak: COMPUTERS AND ELECTRONICS IN AGRICULTURE
Anahtar Kelimeler (WoS)
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Scimago Dergi Bilgisi
Otomatik ISSN Eşleştirmesi
2019 yılı verileri
Computers and Electronics in Agriculture
Q1
SJR Quartile
1,058
SJR Skoru
188
H-Index
Kategoriler: Agronomy and Crop Science (Q1) · Animal Science and Zoology (Q1) · Computer Science Applications (Q1) · Forestry (Q1) · Horticulture (Q1)
Alanlar: Agricultural and Biological Sciences · Computer Science
Ülke: Netherlands
· Elsevier B.V.
Bu bilgiler makale yılına göre Scimago veritabanından ISSN eşleştirmesiyle otomatik getirilmektedir.
Dergi sıralama verileri Scimago'nun ilgili yılı baz alınmaktadır.
Anahtar Kelimeler
WoS |
Bir kelimeye tıklayıp ilgili kaynaktaki yayınları görün.
Makale Bilgileri
Dergi
COMPUTERS AND ELECTRONICS IN AGRICULTURE
ISSN
0168-1699
Yıl
2019
/ 12. ay
Cilt / Sayı
2019
/ 167
Makale Türü
Özgün Makale
Hakemlik
Hakemli
Endeks
SCI-Expanded
Teşvik Puanı
144,00
· YÖKSİS Akademik Teşvik
Yayın Dili
İngilizce
Kapsam
Uluslararası
Toplam Yazar
2 kişi
Erişim Türü
Basılı+Elektronik
Alan
Ziraat, Orman ve Su Ürünleri Temel Alanı-
Toprak Bilimi ve Bitki Besleme
YÖKSİS Yazar Kaydı
Yazar Adı
DEDEOĞLU MERT,DENGİZ ORHAN
YÖKSİS ID
4158958