Drone-Based Vegetation Index Analysis to Estimated Nitrogen Content on The Rice Plantations

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Published Nov 29, 2022
https://doi.org/10.20956/at.vi.928
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Jurnal Agritechno Vol. 15, Nomor 2, Oktober 2022

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Ahmad Fauzan Adzima
Hasanuddin University
Risma Neswati
Universitas Hasanuddin
Sartika Laban
Universitas Hasanuddin
Muh Jayadi
Muhammad Fuad Anshori
Husnul Mubarak
Eva Noviyanti
Nur Qalbi Zaesar Muharram
Andi Dharmawan Mallarangen

Abstract

Nitrogen (N) is one of the essential nutrients needed for the growth of rice plants. Therefore, N fertilizing must be applied efficiently to achieve optimal results. Various methods have been used to calculate the N content in rice plants, such as tissue analysis and the use of Soil Plant Analysis Development (SPAD) technology. This technology still has lack of time efficiency. Other technologies are needed to quickly support precise agricultural analysis, such as Unmanned Aerial Vehicles (UAV). This study aimed to analyze the N content of rice crop using the UAV-based vegetation index and to compare the measurement of N content accuracy between SPAD chlorophyll and rice plant vegetation index. This study used survey methods and laboratory tests based on several approaches, namely analysis of photosynthesis physiology, leaves tissue analysis, and vegetation index using UAV. Based on the research results, it was found that the Normalized Difference Vegetation Index value had a strong correlation with N content of leaves tissue ​​and SPAD chlorophyll. While the results of the accuracy test, the results of chlorophyll with SPAD (CI A) have better accuracy than the NDVI vegetation index. The r value between CI A – N leaves and NDVI – N leaves did not show a significant difference. In addition, the correlation results show that N content of leaves (r=0.83), CI A (r=0.88), CI B (r=81), and CI TOT (r=0.87) have a very high correlation with NDVI. This shows a unidirectional relationship between variables so that the NDVI variable can be used as a consideration to determine chlorophyll in the plants studied.

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How to Cite
Adzima, A. F., Neswati, R., Laban, S., Jayadi, M., Anshori, M. F., Mubarak, H., Noviyanti, E., Zaesar Muharram, N. Q., & Mallarangen, A. D. (2022). Drone-Based Vegetation Index Analysis to Estimated Nitrogen Content on The Rice Plantations. Jurnal Agritechno, 15(```2), 132–140. https://doi.org/10.20956/at.vi.928
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