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Year 2015, Volume: 21 Issue: 4, 585 - 595, 15.12.2015
https://doi.org/10.1501/Tarimbil_0000001359

Abstract

References

  • Allbed A & Kumar L (2013). Soil salinity mapping and monitoring in arid and semi-arid regions using remote sensing technology: A review. Advances in Remote Sensing 2: 373-385
  • Ayers R S & Westcot D W (1989). Water quality for agriculture. irrigation and drainage paper, Food and Agriculture Organization of the United Nations, 29, Rev. 1. Rome, 1-pp: 174
  • Ayyıldız M (1990). Sulama Suyu Kalitesi ve Tuzluluk Problemleri. Ankara Üniversitesi, Ziraat Fakültesi Yayınları: 1196, Ders Kitabı: 344, Ankara
  • Bresler E & Charter D L (1982). Saline and Sodic Soils. Principles Dynamics-Modelling. Springer Verlag, Berlin Heidelberg, New York., pp: 227
  • Büker C, Clevers J G P W & Kuhbauch W (1992). Measuring the intensity of nitrogen fertilization of grassland by means of remote sensing. European “International Space Year Conference” Remote Sensing for Environmental Monitoring and Resource Management, 30 March-4 April, Munich, Germany
  • Bhatt C M, Singh R K, Litoria P K & Sharma P K (2004). Use of remotely sensed data and GIS techniques for assessment of aterlogged and salt-affected area Tehsilwise in Muktsar district of Punjab. GSDI 7 Conference. January 30- February 6, 2004 Theme: Spatial Data Infrastructures for a Sustainable Future Bangalor, India http://gsdidocs.org/gsdiconf/GSDI-7/ papers/Pcmb.pdf (Erişim tarihi 15.12.2012)
  • Campbell J B (2006). Introduction to Remote Sensing. Fourth Edition The Guilford Publications, New York. pp: 6
  • CCRS (2003). Canada Centre of Remote Sensing. http:// www.ccrs.nrcan.gc.ca/http://www.crisp.nus. edu.sg/~research/tutorial/em.htm (Erişim tarihi 14.12.2012)
  • Craig J C & Shih S F (1998). The spectral response of stress conditions in citrus trees: Development of methodology. Soil and Crop Science Society of Florida 57: 16-20
  • CRISP (2011). Principles on remote sensing. Centre for remote imaging, sensing & processing. http://www. crisp.nus.edu.sg/~research/tutorial/em.htm (Erişim tarihi 14.12.2012)
  • Çakırlar H & Topçuoğlu S F (1985). Stres terminolojisi. Çölleşen dünya ve Türkiye örneği. Sempozyum-7, 13- 17 Mayıs, Erzurum, s. 108-129
  • Çetin M, Baz İ, Kayzoğlu T & Geymen A (2003). Çok zamanlı uydu görüntüleri ile açık maden ocaklarındaki yeryüzü değişiminin incelenmesi. 9. Türkiye Harita Bilimsel ve Teknik Kurultayı, 31 Mart-4 Nisan 2003, Ankara, s. 231-241
  • Duran C (2007). Uzaktan algılama teknikleri ile bitki örtüsü analizi. Doğa Dergisi 13: 45-67
  • Eldiery A A, Garcia L & Reich R M (2005). Estimating soil salinity from remote sensing data in corn fields. http://hydrologydays.colostate.edu/Papers_2005/ Ahmed_paper.pdf (Erişim tarihi 29.12.2012)
  • FAO (1979). Yield response to water. Irrigation and Drainage Paper Rome 33: 115
  • Filella I & Penuelas J (1994). The red edge pozition and shape as indicators of plant chlorophyl content, biomass and hydric status. International Journal of Remote Sensing 15(7): 1459-1470
  • Jackson R D (1984). Remote sensing of vegetation characteristics for farm management. Sixth in the SPIE Critical Reviews of Technology Series: Remote Sensing 475: 81-96
  • Jacquemoud S & Ustin S I (2001). Leaf optical properties: A state of the art. Proc. 8th Int. Symp. “Phyisical Measurements and Signatures in Remote sensings”, 8-12 Jan, France, pp: 223-232
  • James D W, Hanks R J & Jurinak J J (1982). Modern Irrigated Soils. John Wiley and Sons Print., USA
  • Khan N M & Sato Y (2001). Monitoring hydro-salinity status and its impact in irrigated semi-arid areas using IRS-1B LISS-II data. Asian Journal of Geology 1(3): 63–73
  • Köksal E S (2007). Sulama suyu yönteminde uzaktan algılama tekniklerinin kullanımı. OMÜ Ziraat Fakültesi Dergisi 22(3): 306-315
  • Leone A P, Menenti M, Buondonno A, Letizia A, Maffei C & Sorrentino G (2007). A field experiment on spectrometry of crop response to soil salinity. Agricultural Water Management 89: 39-48
  • Maktav D & Sunar F (1991). Uzaktan Algılama-Kantitatif Yaklaşım (Remote Sensing-A Quantitative Approach; Swain/Davis), Çeviri Kitap, Hürriyet Ofset, İstanbul
  • Merzlyak M N, Gitelson A A, Chivkunova O B, Solovchenko A E & Pogosyan S I (2003). Application of reflectance spectroscopy for analysis of higer plant pigments. Russian Journal of Plant Physiology 50: 704-710
  • NASA (2003). National aeronautics and space administration. http://daac.gsfc.nasa.gov/CAMPAIN_ DOCS/(Erişim tarihi 5.12.2012)
  • Oscar V (1998). Vegetation. http://137.224.135.82/cgi/ projects/bcrs/multisensor/ report1/ 4.htm#f_4_1_1. (Erişim tarihi 10.12.2012)
  • Rahman S, Vance G F & Munn L C (1994). Detecting salinity and soil nutrient deficiencies uusing SPOT satellite data. Journal of Soil Science 158: 31-39
  • Rees W G (1990). Remote Sensing Physical Principles of Remote Sensing. Cambridge University Press. Cambridge, United Kingdom
  • Robinson S P, Downton W J S & Millhouse J A (1983). Photosynthesis and ion content of leaves and isolated chloroplasts in relation to ionic compartmentation in leaves. Agricultural Biochemistry and Biology 228: 197-206
  • Sharma D A (1980). Effect of using saline water to supplement canal water irrigation on the crop growth of rice. Current Agriculture 4: 79-82
  • Slaton M R, Hunt E R & Smith W K (2001). Estimating near infrared leaf reflectance from leaf structural characteristics. American Journal of Botany 88(2): 278-284
  • White K (1998). Remote Sensing. Progress in Physical Geography 22(1): 95-102

Farklı Tuz Stresi Altındaki Domates Bitkisinin Spektral Yansıma İlişkileri

Year 2015, Volume: 21 Issue: 4, 585 - 595, 15.12.2015
https://doi.org/10.1501/Tarimbil_0000001359

Abstract

Bu çalışmada farklı tuzluluk düzeyine sahip sulama sularının domates bitkisinin enerji kullanımı üzerine etkileri incelenmiştir. Deneme, tesadüf parselleri deneme desenine göre ve kontrollü sera ortamında saksı denemesi şeklinde gerçekleştirilmiştir. Denemede bitki yetiştirme periyodu süresince domates bitkisine kontrol konusuna (0.5 dS m-1) ek olarak dört farklı tuzluluk düzeyine (1.5 dS m-1, 2.2 dS m-1, 3.4 dS m-1, 5.8 dS m-1) sahip sulama suyu uygulaması yapılmıştır. Bu süreçte, elektromanyetik spektrumun 330-1075 nm aralığında algılama yapan el spektroradyometresi ile her bir deneme konusu için spektral ölçümler gerçekleştilmiştir. Çalışmada ayrıca, Bitki İndeks Oranı (VI), Normalize Edilmiş Bitki İndeksi (NDVI), Tuzluluk İndeksi (SI) ve Normalize Edilmiş Tuzluluk İndeksi (NDSI) hesaplamaları da yapılmıştır. Deneme sonucunda yapılan istatistiksel analizlerde, tuz stresinin belirlenmesinde bitkinin yansıma değerleri ile hesaplanan indeks değerleri arasında önemli ilişkiler bulunmuştur. Araştırma sonucunda domates bitkisinde tuzluluktan kaynaklanan bitki stres koşularının, mavi ve kırmızı dalga boyunda bitki gelişim periyodunun 16. haftasında, yeşil dalga boyu bölgesinde ise 13. haftasında ortaya çıktığı belirlenebilmiştir. Hesaplanan VI değeri gelişim periyodunun 12. haftasında, NDVI değerleri 14. haftasında, SI değerleri 16. haftasında, NDSI hesaplaması ise 14. haftasında belirleyici olmuştur.

References

  • Allbed A & Kumar L (2013). Soil salinity mapping and monitoring in arid and semi-arid regions using remote sensing technology: A review. Advances in Remote Sensing 2: 373-385
  • Ayers R S & Westcot D W (1989). Water quality for agriculture. irrigation and drainage paper, Food and Agriculture Organization of the United Nations, 29, Rev. 1. Rome, 1-pp: 174
  • Ayyıldız M (1990). Sulama Suyu Kalitesi ve Tuzluluk Problemleri. Ankara Üniversitesi, Ziraat Fakültesi Yayınları: 1196, Ders Kitabı: 344, Ankara
  • Bresler E & Charter D L (1982). Saline and Sodic Soils. Principles Dynamics-Modelling. Springer Verlag, Berlin Heidelberg, New York., pp: 227
  • Büker C, Clevers J G P W & Kuhbauch W (1992). Measuring the intensity of nitrogen fertilization of grassland by means of remote sensing. European “International Space Year Conference” Remote Sensing for Environmental Monitoring and Resource Management, 30 March-4 April, Munich, Germany
  • Bhatt C M, Singh R K, Litoria P K & Sharma P K (2004). Use of remotely sensed data and GIS techniques for assessment of aterlogged and salt-affected area Tehsilwise in Muktsar district of Punjab. GSDI 7 Conference. January 30- February 6, 2004 Theme: Spatial Data Infrastructures for a Sustainable Future Bangalor, India http://gsdidocs.org/gsdiconf/GSDI-7/ papers/Pcmb.pdf (Erişim tarihi 15.12.2012)
  • Campbell J B (2006). Introduction to Remote Sensing. Fourth Edition The Guilford Publications, New York. pp: 6
  • CCRS (2003). Canada Centre of Remote Sensing. http:// www.ccrs.nrcan.gc.ca/http://www.crisp.nus. edu.sg/~research/tutorial/em.htm (Erişim tarihi 14.12.2012)
  • Craig J C & Shih S F (1998). The spectral response of stress conditions in citrus trees: Development of methodology. Soil and Crop Science Society of Florida 57: 16-20
  • CRISP (2011). Principles on remote sensing. Centre for remote imaging, sensing & processing. http://www. crisp.nus.edu.sg/~research/tutorial/em.htm (Erişim tarihi 14.12.2012)
  • Çakırlar H & Topçuoğlu S F (1985). Stres terminolojisi. Çölleşen dünya ve Türkiye örneği. Sempozyum-7, 13- 17 Mayıs, Erzurum, s. 108-129
  • Çetin M, Baz İ, Kayzoğlu T & Geymen A (2003). Çok zamanlı uydu görüntüleri ile açık maden ocaklarındaki yeryüzü değişiminin incelenmesi. 9. Türkiye Harita Bilimsel ve Teknik Kurultayı, 31 Mart-4 Nisan 2003, Ankara, s. 231-241
  • Duran C (2007). Uzaktan algılama teknikleri ile bitki örtüsü analizi. Doğa Dergisi 13: 45-67
  • Eldiery A A, Garcia L & Reich R M (2005). Estimating soil salinity from remote sensing data in corn fields. http://hydrologydays.colostate.edu/Papers_2005/ Ahmed_paper.pdf (Erişim tarihi 29.12.2012)
  • FAO (1979). Yield response to water. Irrigation and Drainage Paper Rome 33: 115
  • Filella I & Penuelas J (1994). The red edge pozition and shape as indicators of plant chlorophyl content, biomass and hydric status. International Journal of Remote Sensing 15(7): 1459-1470
  • Jackson R D (1984). Remote sensing of vegetation characteristics for farm management. Sixth in the SPIE Critical Reviews of Technology Series: Remote Sensing 475: 81-96
  • Jacquemoud S & Ustin S I (2001). Leaf optical properties: A state of the art. Proc. 8th Int. Symp. “Phyisical Measurements and Signatures in Remote sensings”, 8-12 Jan, France, pp: 223-232
  • James D W, Hanks R J & Jurinak J J (1982). Modern Irrigated Soils. John Wiley and Sons Print., USA
  • Khan N M & Sato Y (2001). Monitoring hydro-salinity status and its impact in irrigated semi-arid areas using IRS-1B LISS-II data. Asian Journal of Geology 1(3): 63–73
  • Köksal E S (2007). Sulama suyu yönteminde uzaktan algılama tekniklerinin kullanımı. OMÜ Ziraat Fakültesi Dergisi 22(3): 306-315
  • Leone A P, Menenti M, Buondonno A, Letizia A, Maffei C & Sorrentino G (2007). A field experiment on spectrometry of crop response to soil salinity. Agricultural Water Management 89: 39-48
  • Maktav D & Sunar F (1991). Uzaktan Algılama-Kantitatif Yaklaşım (Remote Sensing-A Quantitative Approach; Swain/Davis), Çeviri Kitap, Hürriyet Ofset, İstanbul
  • Merzlyak M N, Gitelson A A, Chivkunova O B, Solovchenko A E & Pogosyan S I (2003). Application of reflectance spectroscopy for analysis of higer plant pigments. Russian Journal of Plant Physiology 50: 704-710
  • NASA (2003). National aeronautics and space administration. http://daac.gsfc.nasa.gov/CAMPAIN_ DOCS/(Erişim tarihi 5.12.2012)
  • Oscar V (1998). Vegetation. http://137.224.135.82/cgi/ projects/bcrs/multisensor/ report1/ 4.htm#f_4_1_1. (Erişim tarihi 10.12.2012)
  • Rahman S, Vance G F & Munn L C (1994). Detecting salinity and soil nutrient deficiencies uusing SPOT satellite data. Journal of Soil Science 158: 31-39
  • Rees W G (1990). Remote Sensing Physical Principles of Remote Sensing. Cambridge University Press. Cambridge, United Kingdom
  • Robinson S P, Downton W J S & Millhouse J A (1983). Photosynthesis and ion content of leaves and isolated chloroplasts in relation to ionic compartmentation in leaves. Agricultural Biochemistry and Biology 228: 197-206
  • Sharma D A (1980). Effect of using saline water to supplement canal water irrigation on the crop growth of rice. Current Agriculture 4: 79-82
  • Slaton M R, Hunt E R & Smith W K (2001). Estimating near infrared leaf reflectance from leaf structural characteristics. American Journal of Botany 88(2): 278-284
  • White K (1998). Remote Sensing. Progress in Physical Geography 22(1): 95-102
There are 32 citations in total.

Details

Primary Language Turkish
Journal Section Makaleler
Authors

Namık Sönmez

Namık Kemal Sönmez

Gülçin Ece Aslan This is me

Ahmet Kurunç This is me

Publication Date December 15, 2015
Submission Date February 13, 2015
Published in Issue Year 2015 Volume: 21 Issue: 4

Cite

APA Sönmez, N., Sönmez, N. K., Aslan, G. E., Kurunç, A. (2015). Farklı Tuz Stresi Altındaki Domates Bitkisinin Spektral Yansıma İlişkileri. Journal of Agricultural Sciences, 21(4), 585-595. https://doi.org/10.1501/Tarimbil_0000001359

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