İNSANSIZ HAVA ARACI TEKNOLOJİSİ KULLANILARAK AYÇİÇEĞİ (HELİANTHUS ANNUUS) BİTKİSİNİN KLOROFİL İÇERİKLERİNİN TAHMİN EDİLEBİLİRLİĞİNİN ARAŞTIRILMASI
Yazarlar (3)
Elif Günal
Türkiye
Türkiye
Doç. Dr. Orhan Mete KILIÇ Tokat Gaziosmanpaşa Üniversitesi, Türkiye
Dr. Öğr. Üyesi Şaziye DÖKÜLEN Tokat Gaziosmanpaşa Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (Diğer hakemli uluslarası dergilerde yayınlanan tam makale) | ||
| Dergi Adı | EJONS International Journal on Mathematic, Engineering and Natural Sciences | ||
| Dergi ISSN | 2602-4136 | ||
| Dergi Tarandığı Indeksler | INDEX COPERNICUS; Eurasian Scientific Journal Index; Scientific Indexing Service; CrossRef Database; ISSUU Journal Listings; BRITISH INDEX; worldcat | ||
| Makale Dili | Türkçe | Basım Tarihi | 09-2021 |
| Cilt / Sayı / Sayfa | 5 / 19 / 691–700 | DOI | 10.38063/ejons.624 |
| Makale Linki | http://dx.doi.org/10.38063/ejons.624 | ||
| UAK Araştırma Alanları |
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| Özet |
| High-resolution images obtained with multispectral cameras mounted on unmanned aerial vehicles (UAVs) offer significant potential for agricultural monitoring activities. Chlorophyll content is one of the important parameters in monitoring the growing periods of sunflower plants. In this study, the potential of UAV technology to monitor spatial and temporal changes of sunflower (Helianthus annuus) chlorophyll content was tested. Chlorophyll and vegetation indices calculated using multispectral images taken from the UAV were compared with field chlorophyll measurements using a Spad meter. Significant (p< 0.01) high correlations were obtained between the calculated indices and chlorophyll values. The results revealed that the chlorophyll content of sunflower plants can reliably be modeled at p< 0.001 significance level using a multivariate linear regression model. The model obtained could successfully explain … |
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| Google Scholar | 1 |