Determination of the Relationship between NDVI and Yield by Using Remote Sensing for Silage Corn in Konya Region

Nurettin Kayahan, Taner Ustuntas, Cevat Aydın

Abstract


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 tecniques 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 were obtained. Aerial images were taken from these plots before the flowering period, during the flowering period and after the 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 showed that the estimation of the yield is available with image taken during this period.

Keywords


Remote Sensing NDVI Yield estimation Precision agriculture

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References


Ahmad MUD, Turral H, Nazeer A (2009). Diagnosing irrigation performance and water productivity thro-ugh satellite remote sensing and secondary data in a large irrigation system of Pakistan. Agricultural Water Management, 96(4), 551-564.

Asher JB, Yosef BB, Volinsky R (2013). Ground-based remote sensing system for irrigation scheduling. Bi-osystems engineering, 114(4), 444-453.

Bernardes T, Moreira MA, Adami M, Giarolla A, Ru-dorff BFT (2012). Monitoring biennial bearing effect on coffee yield using MODIS remote sensing imagery. Remote Sensing, 4(9), 2492-2509.

Berni JA, Zarco-Tejada PJ, 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 CM, Thenkabail PS, Noojipady P, Li Y, Dhee-ravath V, Turral H, Xiao X (2009). A global map of rainfed cropland areas (GMRCA) at the end of last millennium using remote sensing. International journal of applied earth observation and geoinformation, 11(2), 114-129.

Bozkurt Y, Yazar A, Gençel B, Sezen MS (2006). Opti-mum lateral spacing for drip-irrigated corn in the Mediterranean Region of Turkey. Agricultural water management, 85(1-2), 113-120.

Deering DW (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, Piccard I, Swinnen E (2013). Crop mapping in countries with small-scale farming: A case study for West Shewa, Ethiopia. International journal of remote sensing, 34(7), 2566-2582.

Fang H, Liang S, Hoogenboom G (2011). Integration of MODIS LAI and vegetation index products with the CSM–CERES–Maize model for corn yield estimation. International Journal of Remote Sen-sing, 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 acreage estimations for larger fields: A case study in the south-western Rostov region of Russia. International Journal of Applied Earth Observation and Geoinformation, 10(4), 453-466.

Gallego FJ, Kussul N, Skakun S, Kravchenko O, Sheles-tov A, Kussul O (2014). Efficiency assessment of using satellite data for crop area estimation in Ukraine. International Journal of Applied Earth Observation and Geoinformation, 29, 22-30.

Gholamhoseini M, AghaAlikhani M, Sanavy SM, Mirlatifi S M (2013). Interactions of irrigation, weed and nitrogen on corn yield, nitrogen use efficiency and nitrate leaching. Agricultural water manage-ment, 126, 9-18.

Guillén-Climent ML, Zarco-Tejada PJ, Villalobos FJ (2012). Estimating radiation interception in an olive orchard using physical models and multispectral 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. African Journal of Agricultural Research, 6(17), 4025-4033.

Hatfield JL, Prueger JH (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 MJ, Decker WL (1996). Using NOAA AVHRR data to estimate maize production in the United States Corn Belt. Remote Sensing, 17(16), 3189-3200.

Herwitz SR, Johnson LF, Dunagan SE, Higgins RG, Sullivan DV, Zheng J, Slye RE (2004). Imaging from an unmanned aerial vehicle: agricultural sur-veillance and decision support. Computers and electronics in agriculture, 44(1), 49-61.

Ibrikci H, Ulger AC (2012). Assesment of corn (zea mays l.) genotypes in relation to nitrogen fertilization under irrigated cropping conditions in Turkey.

Kogan F, Salazar L, Roytman L (2012). Forecasting crop production using satellite-based vegetation health indices in Kansas, USA. International journal of remote sensing, 33(9), 2798-2814.

Li Z, Chen Z (2011). Remote sensing indicators for crop growth monitoring at different scales. In Ge-oscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International (pp. 4062-4065). IEEE.

Meroni M, Marinho E, Sghaier N, Verstrate MM, Leo O (2013). Remote sensing based yield estimation in a stochastic framework—Case study of durum wheat in Tunisia. Remote Sensing, 5(2), 539-557.

Prasad AK, Chai L, Singh RP, Kafatos M (2006). Crop yield estimation model for Iowa using remote sensing and surface parameters. International Journal of Applied Earth Observation and Geoinformation, 8(1), 26-33.

Sakamoto T, Gitelson AA, Nguy-Robertson AL, Arkebauer TJ, Wardlow BD, Suyker AE, 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 un-manned helicopter. Biosystems engineering, 90(4), 369-379.

Şimşek O, Yıldız AMH, Özaydın KA, Çakmak B (2007). AgroMetShell modeli kullanılarak Türkiye’de buğdayın verim tahmini. TARIM BİLİMLERİ DERGİSİ, 13(3), 299-307.

Tucker CJ, Holben BN, Elgin JJH, McMurtrey III JE (1980). Relationship of spectral data to grain yield variation. Photogrammetric Engineering and Remote Sensing, 46(5), 657-666.

Ulger AC, 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, Aydoğdu M (2012). Çankırı Meralarında Biyokütle ve Vejetasyon İndeks İlişkisi. Tarım Bilimleri Araştırma Dergisi, (2), 118-121.

Üstüntaş T, Bacaksız P (2010). Fotogrometride Küresel Yüzeyli Objelerin Resim Çekim Ve Değerlendirmesi Üzerine Deneysel Bir Uygulama, 5. Ulusal 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.




DOI: https://doi.org/10.15316/SJAFS.2020.199

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