Spectral signature reflectance of rice to monitor the response of rice to ozone stresses using in-situ measured hyperspectral remote sensing technology
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Abstract
The purpose of this research was to study spectral signature reflectance of RD43 rice variety on stress conditions from the effect of ozone gas at the concentrations which was less than 10 ppb (control), 40 ppb and 80 ppb measured by the hyperspectral remote sensing technology in each growth phases. The results showed that the in-situ measured hyperspectral remote sensing technology was able to classify the RD43 rice that has received ozone compared with the control group (no ozone fumigation) at reproductive growth phase (14 days ozone fumigated). The strong correlations of the reflectances of green band, red band, near-infrared (NIR) and shortwave infrared (SWIR) were clearly observed between experimental group and control group with significantly different at p<0.05. During the reproductive growth; under near infrared wave of 740 - 1350 nm, the concentration of ozone gas 80 ppb exhibited the highest reflectivity of the electromagnetic wave by 0.385 ± 0.024, followed by the concentration of 40 ppb (0.373 ± 0.019) and control group (0.256 ± 0.011), respectively. The findings of this research could benefit for using as a guideline to monitor the effects of ozone gas on rice with hyperspectral remote sensing technology.
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References
จรัณธร บุญญานุภาพ. 2557. หลักการรับรู้จากระยะไกลด้านนิเวศวิทยาพืชพรรณและการอนุรักษ์. สำนักพิมพ์โอเดียนสโตร์. กรุงเทพฯ.
สถาบันวิจัยข้าว. 2548. การใช้แผ่นเทียบสี (Leaf Color Chart) เพื่อการจัดการปุ๋ยไนโตรเจนในการปลูกข้าวนาชลประทาน. แหล่งข้อมูล: http://www.brrd.in.th/rkb/content/manual/E-book/Eb_015.pdf. ค้นเมื่อ 23 มกราคม 2561.
Akhtar, N., M. Yamaguchi, H. Inada, D. Hoshino, T. Kondo, F.R. Fukami, and T. Izuta. 2010. Effects of ozone on growth, yield and leaf gas exchange rates of four Bangladeshi cultivars of rice (Oryza sativa L.). Environmental Pollution. 158: 2970-2976.
ASD. 2010. FieldSpec® 3 User Manual. Field Spec Pro spectrometer; Analytical Spectral Devices: Boulder, CO, USA. Available: http://www.geo-informatie.nl/manuals/600540-JFieldSpec3User Manual.pdf. Accessed Mar.14, 2020.
Boschetti M., F. Nutini, G. Manfron, P.A. Brivio, and A. Nelson. 2014. Comparative analysis of normalised difference spectral indices derived from MODIS for detecting surface water in flooded rice cropping systems. PloS One. 9: e88741.
Chi, G., B. Huang, Y. Shi, X. Chen, Q. Li, and J. Zhu. 2016. Detecting ozone effects in four wheat cultivars using hyperspectral measurements under fully open-air field conditions. Remote Sensing of Environment. 184: 329-336.
Fiscus E.L., F.L. Booker, and K.O. Burkey. 2005. Crop responses to ozone: uptake, modes of action, carbon assimilation and partitioning. Plant Cell and Environment. 28: 997-1011.
Guan, X., C. Huang, G. Liu, X. Meng, and Q. Liu. 2016. Mapping rice cropping systems in vietnam using an NDVI-based time-series similarity measurement based on DTW distance. Remote Sensing. 8: 19.
Jensen, J. R. 2007. Remote Sensing of the Environment: An Earth Resource Perspective. 2nd Edition. Practice Hall. USA.
Leinenkugel, P., C. Kuenzer, N. Oppelt, and S. Dech. 2013. Characterisation of land surface phenology and land cover based on moderate resolution satellite data in cloud prone areas — A novel product for the Mekong Basin. Remote Sensing of Environment. 136: 180-198.
Meroni, M., C. Panigada, M. Rossini, V. Picchi, S. Cogliati, and R. Colombo. 2009. Using optical remote sensing techniques to track the development of ozone-induced stress. Environmental Pollution. 157: 1413-1420.
Mosleh, M.K., Q.K. Hassan, and E.H. Chowdhury. 2015. Application of remote sensors in mapping rice area and forecasting its production: a review. Sensors. 15: 769–791.
Phothi, R., C. Umponstira, C. Sarin, W. Siriwong, and N. Nabheerong. 2016. Combining effects of ozone and carbon dioxide application on photosynthesis of Thai jasmine rice (Oryza sativa L.) cultivar Khao Dawk Mali 105. Australian Journal of Crop Science. 10: 591-597.
Sanz, J., I. González-Fernández, H. Calvete-Sogo, J.S. Lin, R. Alonso, R. Muntifering, and V. Bermejo. 2014. Ozone and nitrogen effects on yield and nutritive quality of the annual legume Trifolium cherleri. Atmospheric Environment. 94: 765-772.
Sarkar, A., and S. Agrawal. 2009. Identification of ozone stress in Indian rice through foliar injury and differential protein profile. Environmental Monitoring and Assessment. 161: 205-215.
Shwetank, K.J., and K.J. Bhatia. 2010. Review of rice crop identification and classification using hyperspectral image processing system. International Journal of Computer Science & Communication. 1: 253-258.
Thenkabail, P.S., I. Mariotto, M.K., Gumma, E.M. Middleton, D.R. Landis, and F.K. Huemmrich. 2013. Selection of hyperspectralnarrowbands (HNBs) and composition of hyperspectraltwoband vegetation indices (HVIs) for biophysical characterization and discrimination of crop types using field reflectance and Hyperion/EO-1 data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 6: 427–439.
