Roka (Eruca sativa L.) Yetiştiriciliğinde Katı ve Sıvı Organik Gübre Uygulamalarının Spektral Yansıma Üzerine Etkisi

Öz

Bitkilerin spektral yansıma karakteristikleri bitki besin maddesi konsantrasyonları, stres ve diğer faktörlerin etkisi ile vejetasyon periyodu boyunca farklılık göstermektedir. Roka (Eruca sativa L.) gibi yaprağı yenen sebzelerde verimi arttırmak ve tüketicinin tercih ettiği koyu yeşil yaprak rengini kısa sürede sağlayabilmek için yoğun gübreleme yapılmaktadır. Bu çalışmada roka bitkisine artan dozlarda tabandan uygulanan katı ve sıvı organik gübre uygulamalarının, elektromanyetik spektrumun farklı dalga boyu aralığındaki enerji kullanımı üzerine etkileri araştırılmıştır. Çalışma kontrollü sera ortamında tesadüf parselleri deneme desenine göre yürütülmüştür. Denemede bitki yetişme periyodu süresince farklı dozlarda tabandan katı organik gübre (KOG) ve damlamadan sıvı organik gübre (SOG) uygulanmıştır. Bu süreçte elektromanyetik spektrumun 330-1075 nm dalga boyu aralığında el spektroradyometresi ile spektroradyometrik ölçümler gerçekleştirilmiştir.  Araştırma sonucunda, her ölçümde uygulamalar ve dönemler arasında istatistiksel olarak farklılıkların olduğu tespit edilmiştir. Katı+sıvı organik gübre uygulamalarının spektral yansıma üzerinde oluşturduğu varyasyonun en fazla ve en az olduğu ölçümler sırasıyla mavi band bölgesinde; 4. ve 8. ölçümler, yeşil band bölgesinde; 5. ve 3. ölçümler, kırmızı band bölgesinde; 2. ve 8. ölçümler, yakın infrared band bölgesinde ise; 2. ve 7. ölçüm dönemlerinde tespit edilmiştir. Bu sonuçlar doğrultusunda varyasyonun en fazla ve en az olduğu ölçüm dönemlerinin bitki stres koşullarının tespit edilmesinde belirleyici olduğu sonucuna ulaşılmıştır.

Anahtar Kelimeler

• Roka,Katı-sıvı organik gübre,spektral yansıma

The Effect of Solid and Liquid Organic Fertilizer Applications on Spectral Reflection in Rocket (Eruca sativa L.) Cultivation

Abstract

Spectral reflection characteristics of plants vary during the vegetation period with the effect of plant nutrient concentrations, stress and other factors. Intense fertilization is done in order to increase the yield and to provide the dark green leaf color preferred by the consumer in a short time, such as rocket (Eruca sativa L.). In this study, the effects of solid and liquid organic fertilizer applications applied to the arugula at increasing doses on the energy usage in different wavelength ranges of the electromagnetic spectrum were investigated. The study was carried out in a controlled greenhouse environment according to randomized plot design. In the experiment, solid organic fertilizer (KOG) and liquid organic fertilizer (SOG) were applied at different doses throughout the plant growing period. In this process, spectroradiometric measurements were performed by hand spectroradiometer in the wavelength range of 330-1075 nm of the electromagnetic spectrum. As a result of the research, it has been found that there are statistical differences between applications and periods in each measurement. Measurements where the variation on spectral reflection of the solid + liquid organic fertilizer applications were the highest and the least were in the blue band region respectively; Measurements 4 and 8, in the green band region; Measurements 5 and 3, in the red band region; Measurements 2 and 8 are in the near infrared band; It was determined during the 2nd and 7th measurement periods. In line with these results, it was concluded that the measurement periods with the highest and lowest variations were determinative in determining plant stress conditions.

Keywords

• Rocket,Solid-liquid organic fertilizer,Spectral reflection

References

1. Alagöz, Z., Yılmaz, E., & Öktüren, F. (2006). Organik materyal ilavesinin bazı iziksel ve kimyasal toprak özellikleri üzerine etkileri. Akdeniz Üniversitesi Ziraat Fakültesi Dergisi, 19 (2), 245-254.
2. Altunbas, S., Gozukara, G., Sonmez, N.K., Maltaş, A.Ş., & Kaplan, M. (2018a). Relationship between spectral reflectance and plant nutrient-chlorophyll content in lettuce (Lactuca Sativa L.) growing. Fresenius Environmental Bulletin, 27(5A), 3624-3632.
3. Altunbas, S., Sonmez, N.K., Gozukara, G., Maltaş, A.Ş., & Kaplan, M. (2018b). Relationship between solid-liquid organic fertilization and spectral reflectance in lettuce (Lactuca Sativa L.) growing. Fresenius Environmental Bulletin, 27(8), 5355-5362.
4. Başayiğit, L., Dedeoğlu, M., & Akgül, H. (2015). The prediction of iron content in orchards using VNIR spectroscopy. Turkish Journal of Agriculture and Forestry, 39,123-134.
5. Blackmer, T.M., Schepers, J.S., & Varvel, G.E. (1994). Light reflectance compared with other nitrogen stress measurements in corn leaves. Agronomy Journal, 86, 934–938.
6. Black, C.A. (1965). Methods of Soil Analysis. Part 2, Amer. Society of Agronomy Inc., Publisher Madisson, Wilconsin, U.S.A., 1372-1376.
7. Bouyoucos, G.J. (1955). A recalibration of the hydrometer method for making mechanical analysis of the soils. Agronomy Journal, 4(9), 434.
8. Cao H., Zhan Y. (2014). Near-infrared spectra quantitative analysis for flue gas of thermal power plant based on wavelength selection. Scientific Research and Essay, 9, 288–292.

9. Chappelle, E.W., Kım, M.S., & Mcmurtrey, J.E. (1992). Ratio analysis of reflectance spectra (RARS): an algorithm for the remote estimation of the concentrations of chlorophyll a, chlorophyll b, and carotenoids in soybean leaves. Remote Sensing of Environment, 39, 239–247.
10. Gözükara, G., Kalkan, H., & Kaplan, M. (2014). Evaluation of differences in fertilizer consumption of autumn tomato production in greenhouse. 9 th Internatıonal soil science congress. 14-16 October. Antalya. 685-689.
11. Gözükara, G., Kaplan., M. & Kalkan, H. (2016). Evaluation of Soil Analysis Results and Fertilizer Consumption in Autumn Greenhouse Tomato Cultivation. 2. International Conference on Science, Ecology and Technology. 14-16 October. Barcelona. 721-726.
12. Gözükara, G., Altunbaş, S., Şimşek, O., Sarı, O., Buyurgan, K., Maltaş, A.Ş., Sönmez, N.K. & Kaplan, M. (2019). Roka (Eruca vesicaria) yetiştiriciliğinde spektral yansıma ile bitki besin maddesi konsantrasyonu arasındaki ilişkinin belirlenmesi. Mediterranean Agriculturel Sciences, 32,55-62.
13. Evliya, H. (1964). Kültür bitkilerinin beslenmesi. Ankara. Üniv. Ziraat Fak. Yayınları, Yayın no:36, 292- 294 Ankara.
14. 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.
15. Jackson, M.C. (1967). Soil Chemical Analysis. Prentice Hall of India Private’Limited, New Delhi.
16. Kacar, B. (1995). Bitki ve toprağın kimyasal analizler: III. Toprak Analizleri. A. Ü. Ziraat Fakültesi Geliştirme Vakfı Yayınları No: 3.
17. Kacar, B. & İnal, A. (2008). Bitki Analizleri. Nobel Yayın Dağıtım, Ankara.
18. Kalkan, H., Gözükara, G., & Kaplan, M. (2017). Sera Güzlük Domates Yetiştiriciliğinde Yeni Eğilim: Sıvı Organik Gübre Tüketimi. Academia Journal of Engineering and Applied Sciences, 2(3), 92-100.
19. Kellog, C.E. (1952). Our garden soils. The Macmillan Company, Newyork.
20. Lennartsson, M., & Ögren, E. (2003). Predicting the cold hardiness of willow stems using visible and near-infrared spectra and sugar concentrations. Trees-Structure Function, 17,463–470.
21. 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.
22. Lillhonga, T., Geladi, P. (2011). Three-way analysis of a designed compost experiment using near-infrared spectroscopy and laboratory measurements. Journal of Chemometrics, 25, 193–200.
23. Lindsay, W.L., & Norvell, W.A. (1978). Development of a DTPA soil test for Zinc, Iron, Manganese and Copper. Soil Science Society of America Journal, 42, (3), 421-428.
24. Loue, A. (1968). Diagnostic petiolaire de prospection etudes sur la nutrition et al. fertilisation potassiques de la vigne. Societe Commerciale des Potasses d’ Alsace Services Agronomiques, 31-41.
25. 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.
26. Olsen, S.R. & Sommers, E.L. (1982). Phosphorus Soluble in Sodium Bicarbonate, Methods of Soil Analysis, Part 2, Chemical and Microbiological Properties. Edit: A.L. Page, P.H. Miller, D.R. Keeney 404-430.
27. Pizer, N.H. (1967). Some advisory aspect soil potassium and magnesium. Tech. Bull No: 14-184.
28. Rahman, S., Vance, G.F., & Munn, L.C. (1994). Detecting salinity and soil nutrient deficiencies using SPOT satellite data. Journal of Soil Science, 158, 31-39.
29. Sari, M., Sonmez, N.K., & Kurklu, A. (2005a). Determination of seasonal variation of solar energy utilization by the leaves of Washington Navel Orange Trees (Citrus sinensis L. Osbeck). International Journal of Remote Sensing, 26, 3295-3307.
30. Sari, M., Sonmez, N.K., & Karaca, M. (2005b). Relationship between chlorophyll content and canopy reflectance in washington navel orange trees (cıtrus sınensıs (L.) osbeck). Pakistan Journal of Botany, 37(4), 1093-1102.
31. 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.
32. Sonmez, N.K., Emekli, Y., Sari, M., & Bastug, R. (2008). Relationship between spectral reflectance and water stress conditions of Bermuda grass (Cynodon dactylon L.). New Zealand Journal of Agriculturel Research, 51, 223-233.
33. Sonmez, N.K., & Sari, M., Sonmez, S. (2008). Relationship between mineral content and canopy reflectance in Washington navel orange trees. Asian Journal of Chemistry. 20(6):4760-4772.
34. Sonmez, N.K., Aslan, G.E., & Kurunc, A. (2015). Relationship spectral reflectance under different salt stress conditions of tomato. Jorunal Of Agriculturel Sciences, 21,585-595.
35. Thun, R., Hermann, R., & Knıckman, E. (1955). Die untersuchung von boden neuman verlag, Radelbeul und Berlin, s: 48-48.
36. Uz, İ., Sönmez, S., Tavali, İ.E., Citak, S., Üras, D.S., & Çitak, S. (2016). Effect of Vermicompost on Chemical and Biological Properties of an Alkaline Soil with High Lime Content during Celery (Apium graveolens L. var. dulce Mill.) Production", Notulae Botanıcae Hortı Agrobotanıcı Cluj-Napoca, 44, 280-290.
37. Viscarra, Rosse,l R.A., Walvoort, D.J.J., McBratney, A.B., Janik, L.J., & Skjemstad, J.O. (2006). Visible, near infrared, mid-infrared or combined diffuse reflectance spectroscopy for simultaneous assessment of various soil properties. Geoderma, 131, 59–75.
38. Vural, H., Eşiyok, D., & Duman, İ. (2000). Kültür Sebzeleri (Sebze Yetiştirme). Ege Üniversitesi Ziraat Fakültesi Bahçe Bitkileri Bölümü, Bornova, İzmir, S. 440.
39. Zhao, D., Reddy, K.R., Kakanı, V.G., Read, J.J., & Carter, G.A. (2003). Corn (Zea mays L.) growth, leaf pigment concentration, photosynthesis and leaf hyperspectral reflectance properties as affected by nitrogen supply. Plant and Soil, 257,205–217.
40. Zhao, C., Liu, L., Wang, J., Huang, W., Song, X., & Li, C. (2005). Predicting grain protein content of winter wheat using remote sensing data based on nitrogen status and water stress. International Journal of Applied Earth Observation and Geoinformation, 7, 1-9.
41. 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. Grassland Science, 53, 39–49.
42. Zhao, X., Hui, B., Hu, L., Cheng, Q., Via, B.K., Nadel, R., Starkey, T., & Enebak, S. (2017). Potential of near infrared spectroscopy to monitor variations insoluble sugars in Loblolly pine seedlings after cold acclimation. Agricultural and Forest Meteorology, 232, 536–542.
43. Yilmaz, E., & Sönmez, M. (2017). The role of organic/bio–fertilizer amendment on aggregate stability and organic carbon content in different aggregate scales. Soil&Tillage Research. 168:118-124.
44. White, K. (1998). Progress in Physical Geography, Remote Sensing. 22(1), 95-102.