Spectral Pattern of Paddy as Response to Drought Condition: An Experimental Study

  • Arif Kurnia Wijayanto Center for Environmental Research, Institute of Research and Community Services
  • Lilik Budi Prasetyo Department Forest Resources Conservation and Ecotourism, Faculty of Forestry and Environment, IPB Darmaga Campus, Bogor, 16680, Indonesia
  • Yudi Setiawan Department Forest Resources Conservation and Ecotourism, Faculty of Forestry and Environment, IPB Darmaga Campus, Bogor, 16680, Indonesia
Keywords: drought, paddy, spectral response

Abstract

Every single physical object has a different response to the electromagnetic wave emitted to it. The response is in the form of how it absorbs and reflects the energy in every range of wavelength. The absorption and reflection curve is known as a spectral pattern. The spectral pattern of each object can be used to determine the object. In agriculture, the spectral pattern of plants can be used to determine the health condition of the plant. Drought is one factor that can affect the health of the plant. By identifying the spectral pattern of the plants, the effect of drought on paddy can be identified. This experimental study tried to identify the spectral pattern of some varieties of paddy and different growth stages. A spectrophotometer with a wavelength range of 350-1052 nm was used. Four varieties of paddy were planted in a greenhouse and being treated in drought conditions from the stage of vegetative, generative, and reproductive. Based on the result, the spectral response from the generative phase of all varieties gave the most different pattern compared to the control. This result compromising the rapid detection of paddy fields affected by drought using optical remote sensing data. Especially for plants in the stage of generative.

Downloads

Download data is not yet available.

Author Biographies

Arif Kurnia Wijayanto, Center for Environmental Research, Institute of Research and Community Services

Arif Kurnia Wijayanto, Department of Forest Resources Conservation and Ecotourism, Faculty of Forestry, IPB University, Indonesia (Scopus ID)/(Google Scholar ID)

Lilik Budi Prasetyo, Department Forest Resources Conservation and Ecotourism, Faculty of Forestry and Environment, IPB Darmaga Campus, Bogor, 16680, Indonesia

Lilik Budi Prasetyo, Department of Forest Resources Conservation and Ecotourism, Faculty of Forestry, IPB University, Indonesia (Scopus ID)/(Google Scholar ID)

Yudi Setiawan, Department Forest Resources Conservation and Ecotourism, Faculty of Forestry and Environment, IPB Darmaga Campus, Bogor, 16680, Indonesia

Yudi Setiawan, Department of Forest Resources Conservation and Ecotourism, Faculty of Forestry, IPB University, Indonesia (Scopus ID)/(Google Scholar ID)

References

Anusha, N, and B Bharathi. 2020. “Flood Detection and Flood Mapping Using Multi-Temporal Synthetic Aperture Radar and Optical Data.” The Egyptian Journal of Remote Sensing and Space Science 23 (2): 207–19. https://doi.org/https://doi.org/10.1016/j.ejrs.2019.01.001.

Champagne, C., E. Pattey, A. Bannari, and I.B. Stratchan. 2001. “Mapping Crop Water Status: Issues of Scale in the Detection of Crop Water Stress Using Hyperspectral Indices.” In Proceedings of the 8th International Symposium on Physical Measurements and Signatures in Remote Sensing.

Congalton, Russell G. 2015. “Remote Sensing and Image Interpretation. 7th Edition.” Photogrammetric Engineering & Remote Sensing. https://doi.org/10.14358/pers.81.8.615.

Espinoza, Carlos Zúñiga, Lav R. Khot, Sindhuja Sankaran, and Pete W. Jacoby. 2017. “High Resolution Multispectral and Thermal Remote Sensing-Based Water Stress Assessment in Subsurface Irrigated Grapevines.” Remote Sensing. https://doi.org/10.3390/rs9090961.

Gao, Bo Cai. 1996. “NDWI - A Normalized Difference Water Index for Remote Sensing of Vegetation Liquid Water from Space.” Remote Sensing of Environment. https://doi.org/10.1016/S0034-4257(96)00067-3.

HUETE, A R. 2004. “11 - REMOTE SENSING FOR ENVIRONMENTAL MONITORING.” In Environmental Monitoring and Characterization, edited by Janick F Artiola, Ian L Pepper, and Mark L Brusseau, 183–206. Burlington: Academic Press. https://doi.org/https://doi.org/10.1016/B978-012064477-3/50013-8.

Hunt, E. Raymond, and Barrett N. Rock. 1989. “Detection of Changes in Leaf Water Content Using Near- and Middle-Infrared Reflectances.” Remote Sensing of Environment. https://doi.org/10.1016/0034-4257(89)90046-1.

Jacquemoud, Stéphane, and Susan Ustin. 2019. Leaf Optical Properties. Cambridge University Press. https://doi.org/10.1017/9781108686457.

Lillesand, T. M., and R. W. Kiefer. 1994. “Remote Sensing and Image Interpretation. 3rd Edition.” Remote Sensing and Image Interpretation. 3rd Edition.

Maes, Wouter H., and Kathy Steppe. 2019. “Perspectives for Remote Sensing with Unmanned Aerial Vehicles in Precision Agriculture.” Trends in Plant Science. https://doi.org/10.1016/j.tplants.2018.11.007.

Nio, Song Ai, and Audry Agatha Lenak. 2014. “Penggulungan Daun Pada Tanaman Monokotil Saat Kekurangan Air (Leaf Rolling in Monocotyledon Plants under Water Deficit).” JURNAL BIOS LOGOS. https://doi.org/10.35799/jbl.4.2.2014.5539.

Orych, Agata, Piotr Walczykowski, Rafał Dąbrowski, and Edyta Kutyna. 2014. “Using Plant Spectral Response Curves in Detecting Plant Stress.” Ecological Questions 17 (0): 67–74. https://apcz.umk.pl/czasopisma/index.php/EQ/article/view/ecoq-2013-0017.

Penuelas, J., I. Filella, C. Biel, L. Serrano, and R. Save. 1993. “The Reflectance at the 950-970 Nm Region as an Indicator of Plant Water Status.” International Journal of Remote Sensing. https://doi.org/10.1080/01431169308954010.

Penuelas, J., J. Pinol, R. Ogaya, and I. Filella. 1997. “Estimation of Plant Water Concentration by the Reflectance Water Index WI (R900/R970).” International Journal of Remote Sensing. https://doi.org/10.1080/014311697217396.

Reece, Jane B, and Campbell Neil A. 2012. Campbell Biology / Jane B Reece ... [et Al.]. 9th ed. (A. Pearson Australia Frenchs Forest, N.S.W.

Tran, Hoa Thi, James B. Campbell, Tri Dinh Tran, and Ha Thanh Tran. 2017. “Monitoring Drought Vulnerability Using Multispectral Indices Observed from Sequential Remote Sensing (Case Study: Tuy Phong, Binh Thuan, Vietnam).” GIScience and Remote Sensing. https://doi.org/10.1080/15481603.2017.1287838.

Wang, Lingli, and John J. Qu. 2007. “NMDI: A Normalized Multi-Band Drought Index for Monitoring Soil and Vegetation Moisture with Satellite Remote Sensing.” Geophysical Research Letters. https://doi.org/10.1029/2007GL031021.
Published
2021-04-01
How to Cite
Wijayanto, A. K., Prasetyo, L. B. and Setiawan, Y. (2021) “Spectral Pattern of Paddy as Response to Drought Condition: An Experimental Study”, Jurnal Pengelolaan Sumberdaya Alam dan Lingkungan (Journal of Natural Resources and Environmental Management), 11(1). Available at: https://dthh.journal.ipb.ac.id/index.php/jpsl/article/view/34967 (Accessed: 13May2021).