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UZAKTAN ALGILAMA SİSTEMİ KULLANILARAK KOYUN YUMAĞI (Festuca ovina L.) BİTKİSİNDE FOSFOR VE POTASYUM KONSANTRASYONLARININ BELİRLENME OLANAKLARI

Yıl 2014, Cilt: 29 Sayı: 1, 63 - 69, 05.02.2014
https://doi.org/10.7161/anajas.2014.29.1.63

Öz

Bu çalışma, koyun yumağı (Festuca ovina) bitkisinde spektral yansıma değerleri kullanılarak fosfor ve potasyum seviyelerinin belirlenebilirliğini araştırmak amacıyla tarla ve sera koşullarında yürütülmüştür. Spektral yansıma ölçümleri için elektromanyetik spektrumun 325-1075 nm dalga boyları arasında yansıma ölçümleri yapabilen taşınabilir bir spektroradyometre kullanılmıştır. Çalışmada parsellere ve saksılara 0, 20 ve 40 kg dadozlarında fosfor ve potasyum uygulanmıştır. Spektral yansıma ölçümleri hem kanopi hem de tek yaprak düzeyinde yapılmıştır. Çalışmadan elde edilen sonuçlara göre fosfor ve potasyum düzeylerindeki değişimler spektrumun mavi (400-500 nm) ve yakın kızıl ötesi (700-900 nm) bölgelerindeki yansımaları etkilemektedir. Sonuçlar, koyun yumağı bitkisinde fosfor ve potasyum konsantrasyonlarının tahmininde spektral yansıma değerlerinin (özellikle mavi ve yakınkızıl ötesi bölgeler) kullanılabileceğini göstermiştir.

Kaynakça

  • Aktaş, M. 2004. Bitkilerde beslenme bozuklukları ve tanınmaları. Türkiye 3. Ulusal Gübre Kongresi, Tarım Sanayi Çevre, 11-13 Ekim 2004, Tokat. Cilt 2: 1118118
  • Al-Abbas, A.H., Barr, R., Hall, J.D., Crane, F.L., Baumgardner, M.F. 1974. Spectra of normal and nutrient deficient maize leaves. Agron. J., 66:16–20.
  • Albayrak, S. 2008. Use of reflectance measurements for the detection of N, P, K, ADF and NDF contents in sainfoin pasture. Sensors, 8: 7275-7286.
  • Ayala-Silva, T., Beyl, C.A. 2005. Changes spectral reflectance of wheat leaves in response to specific macronutrients deficiency. Adv. Space Res., 35: 3053
  • Bakırcıoğlu, D. 2009. Toprakta Makro ve Mikro Element Tayini. Trakya Üniversitesi Fen Bilimleri Enstitüsü Kimya Anabilim Dalı, Doktora Tezi, 134 sayfa.
  • Beeri, O., Phillips, R., Hendrickson, J., Frank, A.B., Kronberg, S. 2007. Estimating forage quantity and quality using aerial hyperspectral imagery for Northern mixed-grass prairie. Remote Sens. Environ., 110: 216– 2
  • Biolley, J.P., Jay, M. 1993. Anthocyanins in modern roses: Chemical and colorimetric features in relation to the colour range. J. Exp. Bot., 44: 1725-1734.
  • Böğrekçi I., Lee, W.S., Jordan, J.D., Craig, J.C. 2005. Multispectral Image Analysis for Phosphorus Measurement in Bahia Grass. ASAE Paper No. 051067, Fl. Tampa, MI: ASAE.
  • Brink, G.E., Rowe, D.E., Sistani, K.R., Adeli, A. 2003. Bermudagrass cultivar response to swine effluent application. Agron. J., 95:597–601.
  • Carter, G.A., Knapp, A.K. 2001. Leaf optical properties in higher plants: linking spectral characteristics to stress and chlorophyll concentration. Am. J. Bot., 88 (4): 677– 68
  • Castro-Esau, K.L., Sánchez-Azofeifa, G.A., Rivard, B. 200 Comparison of spectral indices obtained using multiple spectroradiometers. Remote Sens. Environ., 103: 276–288. Graeff, S., Steffens, D., Schubert, S. 2001. Use of reflectance measurements for the early detection of N, P, Mg, and Fe deficiencies in corn (Zea mays L.). J. Plant Nutr. Soil Sc., 164: 445–450.
  • Halgerson, J.L., Sheaffer, C.C., Martin, N.P., Peterson, P.R., Weston, S.J. 200 Near-infrared reflectance spectroscopy prediction of leaf and mineral concentrations in alfalfa. Agron. J., 96: 344–351. Han, L., Rundquist, D.C. 2003. The spectral responses of Ceratophyllum demersum at varying depths in an experimental tank. Int. J. Remote Sens., 24(4): 859-864. Jacob, J., Lawlor, D.W. 1991. Stomatal and mesophyll limitations of photosynthesis in phosphate-deficient sunflower, maize and wheat plants. J. Exp. Bot. 42: 1003–1011.
  • Kacar, B. 1977. Bitki Besleme. Ankara Üniversitesi Ziraat Fakültesi Yayınları: 637, Ders Kitabı: 200, Ankara, 317 ss.
  • Karaca, S., Çimrin, K.M. 2002. Adi Fiğ (Vicia sativa L.)+Arpa (Hordeum vulgare L.) Karışımında Azot ve Fosforlu Gübrelemenin Verim ve Kaliteye Etkileri. Yyü. Tar. Bil. Derg., 12(1): 47-52.
  • Kruse, J.K. 2004. Remote sensing of moisture and nutrient stress in turfgrass systems. Ph.D Thesis, Iowa State University, Ames, Iowa, 69 pp.
  • Kruse, J.K., Christians, N.E., Chaplin, M.H. 2006. Remote Sensing of Nitrogen Stress in Creeping Bentgrass. Agron. J., 98:1640-1645.
  • Kokaly, R.F., Clark, R.N. 199 Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise multiple linear regression. Remote Sens. Environ., 67(3): 26728
  • Li, B., Liew, O.W., Asundi, A.K. 2006. Pre-visual detection of iron and phosphorus deficiency by transformed reflectance spectra. J. Photoch. Photobio. B., 85: 131– 1
  • Lin, Y., Liquan, Z. 2006. Identification of the spectral characteristics of submerged plant Vallisneria spiralis. Acta Ecol. Sin., 26(4):1005–1011.
  • Mutanga, O., Skidmore, A.K., Prins, H.H.T. 2004. Predicting in situ pasture quality in the Kruger National Park, South Africa, using continuum-removed absorption features. Remote Sens. Environ., 89: 39340
  • Osborne, S.L., Schepers, J.S., Francis, D.D., Schlemmer, M.R. 2002. Detection of phosphorous and nitrogen deficiencies in corn using spectral radiance measurements. Agron. J., 94: 1215-1221.
  • Salisbury, F.B., Ross, C.W. 1992. Photomorphogenesis (Chapter 20), Plant Physiology. (4nd ed.) Wadsworth Publ. Co., Belmont, CA, p.438-463.
  • Smart, D.R., Whiting, M.L., Stockert, C. 2007. Remote sensing of grape K deficiency symptoms using leaf level hyperspectral reflectance. Western Nutrient Management Conference. Vol. 7. Salt Lake City, UT. p.19Summy, K.R., Little, C.R., Mazariegos, R.A., Everitt, J.H., Davis, M.R., French, J.V., Scott, A.W. 2003. Detecting stress in glasshouse plants using color infrared imagery: a potential new application for remote sensing. Subtrop. Plant Sci., 55: 51–58.
  • Whitehead, D.C. 2000. Nutrient Elements in Grassland : Soil-Plant-Animal Relationships. CABI Publishing, Wallingford, 383 pp.
  • Wright, D.L., Rasmussen, V.P., Ramsey, R.D. 2005. Comparing the Use of Remote Sensing with Traditional Techniques to Detect Nitrogen Stress in Wheat. Geocarto Int., 20(1): 63-68
  • Yıldız, N., Bilgin, N. 2008. Erzurum Ovası Topraklarının Fosfor ve Potasyum Durumunun Neubauer Fide Yöntemi ile Belirlenmesi. Atatürk Üniv. Zir. Fak. Derg., 39 (2): 159-165.
  • Zhao, D., Starks, P.J., Brown, M.A., Phillips, W.A., Coleman, S.W. 2007. Assessment of forage biomass and quality parameters of bermudagrass using proximal sensing of pasture canopy reflectance. J. Jap. Soc. Grassland Sci., 53:39-49

THE POSSIBILITY OF DETERMINE PHOSPHORUS AND POTASSIUM CONCENTRATIONS IN SHEEP FESCUE (Festuca ovina L.) USING REMOTE SENSING SYSTEM

Yıl 2014, Cilt: 29 Sayı: 1, 63 - 69, 05.02.2014
https://doi.org/10.7161/anajas.2014.29.1.63

Öz

This study was carried out to determine phosphorus and potassium levels in sheep fescue (Festuca ovina L.) using spectral reflectance data in field and greenhouse conditions. Spectral reflectance measurements were undertaken using a portable spectroradiometer measuring the wavelength range of 325-1075 nm of the electromagnetic spectrum. The treatments consisted of different concentrations (0, 20 and 40 kg da-1) of phosphorus and potassium for each pots and plots. Spectral reflectance values were measured in both canopy level and single-leaf. According to result of the study, the changes in phosphorus and potassium levels were affected reflectance values of blue and near infrared region of spectrum which located in the range of 400-500 nm and 700-900 nm, respectively. The results have shown that spectral reflectance data (especially blue and near infrared region) could be used to estimate the phosphorus and potassium concentration in sheep fescue.

Kaynakça

  • Aktaş, M. 2004. Bitkilerde beslenme bozuklukları ve tanınmaları. Türkiye 3. Ulusal Gübre Kongresi, Tarım Sanayi Çevre, 11-13 Ekim 2004, Tokat. Cilt 2: 1118118
  • Al-Abbas, A.H., Barr, R., Hall, J.D., Crane, F.L., Baumgardner, M.F. 1974. Spectra of normal and nutrient deficient maize leaves. Agron. J., 66:16–20.
  • Albayrak, S. 2008. Use of reflectance measurements for the detection of N, P, K, ADF and NDF contents in sainfoin pasture. Sensors, 8: 7275-7286.
  • Ayala-Silva, T., Beyl, C.A. 2005. Changes spectral reflectance of wheat leaves in response to specific macronutrients deficiency. Adv. Space Res., 35: 3053
  • Bakırcıoğlu, D. 2009. Toprakta Makro ve Mikro Element Tayini. Trakya Üniversitesi Fen Bilimleri Enstitüsü Kimya Anabilim Dalı, Doktora Tezi, 134 sayfa.
  • Beeri, O., Phillips, R., Hendrickson, J., Frank, A.B., Kronberg, S. 2007. Estimating forage quantity and quality using aerial hyperspectral imagery for Northern mixed-grass prairie. Remote Sens. Environ., 110: 216– 2
  • Biolley, J.P., Jay, M. 1993. Anthocyanins in modern roses: Chemical and colorimetric features in relation to the colour range. J. Exp. Bot., 44: 1725-1734.
  • Böğrekçi I., Lee, W.S., Jordan, J.D., Craig, J.C. 2005. Multispectral Image Analysis for Phosphorus Measurement in Bahia Grass. ASAE Paper No. 051067, Fl. Tampa, MI: ASAE.
  • Brink, G.E., Rowe, D.E., Sistani, K.R., Adeli, A. 2003. Bermudagrass cultivar response to swine effluent application. Agron. J., 95:597–601.
  • Carter, G.A., Knapp, A.K. 2001. Leaf optical properties in higher plants: linking spectral characteristics to stress and chlorophyll concentration. Am. J. Bot., 88 (4): 677– 68
  • Castro-Esau, K.L., Sánchez-Azofeifa, G.A., Rivard, B. 200 Comparison of spectral indices obtained using multiple spectroradiometers. Remote Sens. Environ., 103: 276–288. Graeff, S., Steffens, D., Schubert, S. 2001. Use of reflectance measurements for the early detection of N, P, Mg, and Fe deficiencies in corn (Zea mays L.). J. Plant Nutr. Soil Sc., 164: 445–450.
  • Halgerson, J.L., Sheaffer, C.C., Martin, N.P., Peterson, P.R., Weston, S.J. 200 Near-infrared reflectance spectroscopy prediction of leaf and mineral concentrations in alfalfa. Agron. J., 96: 344–351. Han, L., Rundquist, D.C. 2003. The spectral responses of Ceratophyllum demersum at varying depths in an experimental tank. Int. J. Remote Sens., 24(4): 859-864. Jacob, J., Lawlor, D.W. 1991. Stomatal and mesophyll limitations of photosynthesis in phosphate-deficient sunflower, maize and wheat plants. J. Exp. Bot. 42: 1003–1011.
  • Kacar, B. 1977. Bitki Besleme. Ankara Üniversitesi Ziraat Fakültesi Yayınları: 637, Ders Kitabı: 200, Ankara, 317 ss.
  • Karaca, S., Çimrin, K.M. 2002. Adi Fiğ (Vicia sativa L.)+Arpa (Hordeum vulgare L.) Karışımında Azot ve Fosforlu Gübrelemenin Verim ve Kaliteye Etkileri. Yyü. Tar. Bil. Derg., 12(1): 47-52.
  • Kruse, J.K. 2004. Remote sensing of moisture and nutrient stress in turfgrass systems. Ph.D Thesis, Iowa State University, Ames, Iowa, 69 pp.
  • Kruse, J.K., Christians, N.E., Chaplin, M.H. 2006. Remote Sensing of Nitrogen Stress in Creeping Bentgrass. Agron. J., 98:1640-1645.
  • Kokaly, R.F., Clark, R.N. 199 Spectroscopic determination of leaf biochemistry using band-depth analysis of absorption features and stepwise multiple linear regression. Remote Sens. Environ., 67(3): 26728
  • Li, B., Liew, O.W., Asundi, A.K. 2006. Pre-visual detection of iron and phosphorus deficiency by transformed reflectance spectra. J. Photoch. Photobio. B., 85: 131– 1
  • Lin, Y., Liquan, Z. 2006. Identification of the spectral characteristics of submerged plant Vallisneria spiralis. Acta Ecol. Sin., 26(4):1005–1011.
  • Mutanga, O., Skidmore, A.K., Prins, H.H.T. 2004. Predicting in situ pasture quality in the Kruger National Park, South Africa, using continuum-removed absorption features. Remote Sens. Environ., 89: 39340
  • Osborne, S.L., Schepers, J.S., Francis, D.D., Schlemmer, M.R. 2002. Detection of phosphorous and nitrogen deficiencies in corn using spectral radiance measurements. Agron. J., 94: 1215-1221.
  • Salisbury, F.B., Ross, C.W. 1992. Photomorphogenesis (Chapter 20), Plant Physiology. (4nd ed.) Wadsworth Publ. Co., Belmont, CA, p.438-463.
  • Smart, D.R., Whiting, M.L., Stockert, C. 2007. Remote sensing of grape K deficiency symptoms using leaf level hyperspectral reflectance. Western Nutrient Management Conference. Vol. 7. Salt Lake City, UT. p.19Summy, K.R., Little, C.R., Mazariegos, R.A., Everitt, J.H., Davis, M.R., French, J.V., Scott, A.W. 2003. Detecting stress in glasshouse plants using color infrared imagery: a potential new application for remote sensing. Subtrop. Plant Sci., 55: 51–58.
  • Whitehead, D.C. 2000. Nutrient Elements in Grassland : Soil-Plant-Animal Relationships. CABI Publishing, Wallingford, 383 pp.
  • Wright, D.L., Rasmussen, V.P., Ramsey, R.D. 2005. Comparing the Use of Remote Sensing with Traditional Techniques to Detect Nitrogen Stress in Wheat. Geocarto Int., 20(1): 63-68
  • Yıldız, N., Bilgin, N. 2008. Erzurum Ovası Topraklarının Fosfor ve Potasyum Durumunun Neubauer Fide Yöntemi ile Belirlenmesi. Atatürk Üniv. Zir. Fak. Derg., 39 (2): 159-165.
  • Zhao, D., Starks, P.J., Brown, M.A., Phillips, W.A., Coleman, S.W. 2007. Assessment of forage biomass and quality parameters of bermudagrass using proximal sensing of pasture canopy reflectance. J. Jap. Soc. Grassland Sci., 53:39-49
Toplam 27 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Tarla Bitkileri
Yazarlar

Yaşar Özyiğit

Mehmet Bilgen

Yayımlanma Tarihi 5 Şubat 2014
Yayımlandığı Sayı Yıl 2014 Cilt: 29 Sayı: 1

Kaynak Göster

APA Özyiğit, Y., & Bilgen, M. (2014). UZAKTAN ALGILAMA SİSTEMİ KULLANILARAK KOYUN YUMAĞI (Festuca ovina L.) BİTKİSİNDE FOSFOR VE POTASYUM KONSANTRASYONLARININ BELİRLENME OLANAKLARI. Anadolu Tarım Bilimleri Dergisi, 29(1), 63-69. https://doi.org/10.7161/anajas.2014.29.1.63
Online ISSN: 1308-8769