Determination of the Relationship Between Ndvi and Yield by Using Remote Sensing for Silage Corn in Konya Region
This study focuses on the yield estimation of silage corn in the province of Konya. This study was carried out in Selcuk University Sarıcalar Research and Application Farm in province of Konya. In this study, normalized difference vegetation index (NDVI) values obtained by using remote sensing yield were compared with yield and the availability of estimation of yield by using NDVI was determined.
In the Study, approximately 1000 m2 of silage corn planted in the field. The field is divided into plots. Different doses of nitrogen applied to different plots to obtain different yields on different plots. In this way, 5 parcels having different yields are obtained.
Aerial image taken with the multispectral camera from this plots during flowering period, before flowering period and after flowering period. NDVI values were calculated from these images. Yields of plots were measured in the time of harvest. NDVI values were compared with the yield values. The highest correlation (R2=0.945) were found between the images obtained during the flowering period and yields. It show that the estimation of the yield is available with image taken during this period.
Ahmad, M. U. D., Turral, H., & Nazeer, A. (2009). Di-agnosing irrigation performance and water produc-tivity through satellite remote sensing and secon-dary data in a large irrigation system of Pakistan. Agricultural Water Management, 96(4), 551-564.
Asher, J. B., Yosef, B. B., & Volinsky, R. (2013). Gro-und-based remote sensing system for irrigation scheduling. Biosystems engineering, 114(4), 444-453.
Bernardes, T., Moreira, M. A., Adami, M., Giarolla, A., & Rudorff, B. F. T. (2012). Monitoring biennial be-aring effect on coffee yield using MODIS remote sensing imagery. Remote Sensing, 4(9), 2492-2509.
Berni, J. A., Zarco-Tejada, P. J., Suárez, L., & Fereres, E. (2009). Thermal and narrowband multispectral remote sensing for vegetation monitoring from an unmanned aerial vehicle. IEEE Transactions on Geoscience and Remote Sensing, 47(3), 722-738.Ibrikci 2012
Biradar, C. M., Thenkabail, P. S., Noojipady, P., Li, Y., Dheeravath, V., Turral, H., ... & Xiao, X. (2009). A global map of rainfed cropland areas (GMRCA) at the end of last millennium using remote sensing. In-ternational journal of applied earth observation and geoinformation, 11(2), 114-129.
Bozkurt, Y., Yazar, A., Gençel, B., & Sezen, M. S. (2006). Optimum lateral spacing for drip-irrigated corn in the Mediterranean Region of Turkey. Agri-cultural water management, 85(1-2), 113-120.
Deering, D. W. (1978). Rangeland reflectance characte-ristics measured by aircraft and spacecraft sensors. Ph. D Dissertation. Texas A&M Universtiy.
Delrue, J., Bydekerke, L., Eerens, H., Gilliams, S., Pic-card, I., & Swinnen, E. (2013). Crop mapping in co-untries with small-scale farming: A case study for West Shewa, Ethiopia. International journal of re-mote sensing, 34(7), 2566-2582.
Fang, H., Liang, S., & Hoogenboom, G. (2011). Integ-ration of MODIS LAI and vegetation index pro-ducts with the CSM–CERES–Maize model for corn yield estimation. International Journal of Remote Sensing, 32(4), 1039-1065.
Fang, H., Liang, S., Hoogenboom, G., Teasdale, J., & Cavigelli, M. (2008). Corn‐yield estimation through assimilation of remotely sensed data into the CSM‐CERES‐Maize model. International Journal of Remote Sensing, 29(10), 3011-3032.
Fritz, S., Massart, M., Savin, I., Gallego, J., & Rembold, F. (2008). The use of MODIS data to derive acrea-ge estimations for larger fields: A case study in the south-western Rostov region of Russia. Internatio-nal Journal of Applied Earth Observation and Geo-information, 10(4), 453-466.
Gallego, F. J., Kussul, N., Skakun, S., Kravchenko, O., Shelestov, A., & Kussul, O. (2014). Efficiency as-sessment of using satellite data for crop area esti-mation in Ukraine. International Journal of Applied Earth Observation and Geoinformation, 29, 22-30.
Gholamhoseini, M., AghaAlikhani, M., Sanavy, S. M., & Mirlatifi, S. M. (2013). Interactions of irrigation, weed and nitrogen on corn yield, nitrogen use effi-ciency and nitrate leaching. Agricultural water ma-nagement, 126, 9-18.
Guillén-Climent, M. L., Zarco-Tejada, P. J., & Villalo-bos, F. J. (2012). Estimating radiation interception in an olive orchard using physical models and mul-tispectral airborne imagery. Israel Journal of Plant Sciences, 60(1-2), 107-121.
Hanbing, Z., Xiaoping, Y., & Jialin, L. (2011). MODIS data based NDVI Seasonal dynamics in agro-ecosystems of south bank Hangzhouwan bay. Af-rican Journal of Agricultural Research, 6(17), 4025-4033.
Hatfield, J. L., & Prueger, J. H. (2010). Value of using different vegetative indices to quantify agricultural crop characteristics at different growth stages under varying management practices. Remote Sensing, 2(2), 562-578.
Hayes, M. J., & Decker, W. L. (1996). Using NOAA AVHRR data to estimate maize production in the United States Corn Belt. Remote Sensing, 17(16), 3189-3200.
Herwitz, S. R., Johnson, L. F., Dunagan, S. E., Higgins, R. G., Sullivan, D. V., Zheng, J., ... & Slye, R. E. (2004). Imaging from an unmanned aerial vehicle: agricultural surveillance and decision support. Computers and electronics in agriculture, 44(1), 49-61.
Ibrikci, H., & Ulger, A. C. (2012). Assesment of corn (zea mays l.) genotypes in relation to nitrogen ferti-lization under irrigated cropping conditions in Tur-key.
Kogan, F., Salazar, L., & Roytman, L. (2012). Forecas-ting crop production using satellite-based vegeta-tion health indices in Kansas, USA. International journal of remote sensing, 33(9), 2798-2814.
Li, Z., & Chen, Z. (2011, July). Remote sensing indica-tors for crop growth monitoring at different scales. In Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International (pp. 4062-4065). IEEE.
Meroni, M., Marinho, E., Sghaier, N., Verstrate, M. M., & Leo, O. (2013). Remote sensing based yield esti-mation in a stochastic framework—Case study of durum wheat in Tunisia. Remote Sensing, 5(2), 539-557.
Prasad, A. K., Chai, L., Singh, R. P., & Kafatos, M. (2006). Crop yield estimation model for Iowa using remote sensing and surface parameters. Internatio-nal Journal of Applied Earth Observation and Geo-information, 8(1), 26-33.
Sakamoto, T., Gitelson, A. A., Nguy-Robertson, A. L., Arkebauer, T. J., Wardlow, B. D., Suyker, A. E., ... & Shibayama, M. (2012). An alternative method using digital cameras for continuous monitoring of crop status. Agricultural and Forest Meteorology, 154, 113-126.
Sugiura, R., Noguchi, N., & Ishii, K. (2005). Remote-sensing technology for vegetation monitoring using an unmanned helicopter. Biosystems engineering, 90(4), 369-379.
Şimşek, O., Yıldız, A. M. H., Özaydın, K. A., & Çak-mak, B. (2007). AgroMetShell modeli kullanılarak Türkiye’de buğdayın verim tahmini. TARIM Bİ-LİMLERİ DERGİSİ, 13(3), 299-307.
Tucker, C. J., Holben, B. N., Elgin Jr, J. H., & McMurt-rey III, J. E. (1980). Relationship of spectral data to grain yield variation. Photogrammetric Engineering and Remote Sensing, 46(5), 657-666.
Ulger, A. C., Ibrikci, H., Cakir, B., & Guzel, N. (1997). Influence of nitrogen rates and row spacing on corn yield, protein content, and other plant parameters. Journal of plant nutrition, 20(12), 1697-1709.
Ünal, E. and Aydoğdu, M. (2012). Çankırı Meraların-da Biyokütle ve Vejetasyon İndeks İlişkisi. Tarım Bilimleri Araştırma Dergisi, (2), 118-121.
Üstüntaş, T., Bacaksız, P., (2010), Fotogrometride Küresel Yüzeyli Objelerin Resim Çekim Ve Değer-lendirmesi Üzerine Deneysel Bir Uygulama, 5. Ulu-sal Mühendislik Ölçmeleri Sempozyumu, ZKÜ Merkez Kampusu Zonguldak.
Wu, S., Huang, J., Liu, X., Fan, J., Ma, G., & Zou, J. (2011, October). Assimilating MODIS-LAI into crop growth model with EnKF to predict regional crop yield. In International Conference on Computer and Computing Technologies in Agriculture (pp. 410-418). Springer, Berlin, Heidelberg.
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