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All Journal agriTECH MAJALAH ILMIAH GLOBE
Chiharu Hongo, Chiharu
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Agriculture, Biological Sciences & Forestry Earth & Planetary Sciences Education

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IDENTIFICATION OF AGE CLASS AND VARIETIES OF RICE PLANT USING SPECTRORADIOMETRY AND CHLOROPHYLL CONTENT INDEX: (Identifikasi Kelas Umur dan Varietas Tanaman Padi Menggunakan Spektroradiometri dan Indeks Kandungan Klorofil) Munibah, Khursatul; Trisasongko, Bambang Hendro; Barus, Baba; Tjahjono, Boedi; Achmad, Alfredian; Uciningsih, Winda; Sigit, Gunardi; Hongo, Chiharu
Majalah Ilmiah Globe Vol. 24 No. 1 (2022): GLOBE VOL 24 NO 1 TAHUN 2022
Publisher : Badan Informasi Geospasial

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Abstract

Rice is the staple food for Indonesian society because more than 90% population eat rice every day. Estimation of the rice production can be monitored from the plant growth phase by utilizing remote sensing data. Spectroradiometry can be used to validate the remote sensing spectral because it has a wide wavelength range. Research objectives are to identify transplanting age class and varieties of rice plant based on spectroradiometry and its vegetation index, to analyze the relationship between spectroradiometry and chlorophyll content index (CCI). The results show that the transplanting date of 14 days, 21-32 days, and 56-68 days in three varieties (Inpari32; Padjadjaran Agritan; Siliwangi Agritan) are difficult to be distinguished at visible wavelength but it easy at infrared wavelength. The plant age class for the Siliwangi Agritan can be distinguished well on NDVI, SAVI, EVI while the Pajajaran Agritan is only on NDVI and EVI. All vegetation indexes, where the plant age of 14 days and 21-32 days for the Inpari32 are difficult to be distinguished between them, but easy to be distinguished with 56-68 days. This is due to the high sensitivity of chlorophyll to infrared wavelengths and the characteristics of rice plants itself (many tillers and plant height). Meanwhile, rice plants of every veriety are difficult to be distinguished, either on visible wavelength, infrared wavelength or on all vegetation indexes. Spectroradiometry has a high correlation with chlorophyll content index (CCI) (R2=0,88). This shows that the higher chlorophyll content in rice plants, the higher spectroradiometry for infrared wavelength.
Evaluation Trial of Drought Damage of Rice Based on RGB Aerial Image by UAV Giamerti, Yuti; Darmadi, Didi; Junaedi, Ahmad; Lubis, Iskandar; Sopandie, Didie; Yuanita Meishanti, Ospa Pea; Sari, Kartika; Hongo, Chiharu; Homma, Koki
agriTECH Vol 44, No 4 (2024)
Publisher : Faculty of Agricultural Technology, Universitas Gadjah Mada, Yogyakarta, Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/agritech.86077

Abstract

Unmanned Aerial Vehicle (UAV) remote sensing is recommended to evaluate damage quickly and quantitatively. Therefore, this study aimed to explore the use of RGB aerial images by UAV for evaluating drought damage of rice through canopy color and coverage. The procedures were conducted in the dry season of 2018 (August – September 2018) at the Balitkabi Experimental field, Muneng, Probolinggo, Indonesia. A split-plot experimental field design was used with 2 factors, namely drought treatments at growth stage (Vegetative/P1, Reproductive/ P2, Generative/P3, and Control/P0), and varieties (Jatiluhur/V1, IPB9G/V2, IPB 3S/V3, Hipa 19/V4, Inpari-17/ V5, Mekongga/V6, Mentik Wangi/V7, Ciherang/V8). Canopy temperature data were then obtained using FLUKE 574 Infrared Thermometer, while images were taken with an RGB camera (Zenmuse X5) attached to Drone DJI Inspire I. The images were taken twice during the treatment (4 DAT and 15 DAT), followed by analysis using QGIS 2.18 and ImageJ. The results showed that RGB aerial images by UAV could be used in agricultural insurance in Indonesia, and similar countries around the world. Although the effect on yield needed to be evaluated, quick assessment by UAV was still an effective tool. In addition, drought damage evaluation through canopy color was better than canopy coverage in terms of analysis. The conversion from RGB to Lab color space increased the determination coefficient in multiple regression of color values against temperature difference (Tc-Ta).
Co-Authors Achmad, Alfredian AHMAD JUNAEDI Baba Barus Bambang Hendro Trisasongko Boedi Tjahjono Didi Darmadi, Didi Homma, Koki Iskandar Lubis Jayawarsa, A.A. Ketut Khursatul Munibah Ospa Pea Yuanita Meishanti Sigit, Gunardi Sopandie, Didie Uciningsih, Winda Yuti Giamerti, Yuti