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The reliability of Unmanned Aerial Vehicles (UAVs) equipped with multispectral cameras for estimating chlorophyll content, plant height, canopy area, and fruit total number of Lemons (Citrus limon)

SAINS TANAH - Journal of Soil Science and Agroclimatology · Vol. 20 No. 2 (2023) · hlm. 221–230

DOI
10.20961/stjssa.v20i2.72485
ISSN
2356-1424, 1412-3606
Terbit
2023-12-04
Penerbit
Universitas Sebelas Maret
Bahasa
en

Abstrak

Monitoring lemon production requires appropriate and efficient technology. The use of UAVs can addressed these challenges. The purpose of this study was to determine the best vegetation indices (VIs) for estimating chlorophyll content, plant height (PH), canopy area (CA), and fruit total numberas (FTN). CCM 200 was used as a tool to measure the chlorophyll content index (CCI), the number of fruits was measured by hand-counter, and other variables were recorded in meters. The UAV used was a Phantom 4 with a multispectral camera capable of capturing five different bands. The VIs was obtained via analysis of digital numbers generated by the multispectral camera. Then, the VIs was correlated with the CCI, PH, CA and FTN. VIs tested included the following: the normalized difference vegetation index (NDVI), the normalized difference vegetation index-green (NDVIg), the normalized different index (NDI), green minus red (GMR), simple ratio (SR), the Visible Atmospherically Resistant Index (VARI), normalized difference red edge (NDRE), simple ratio red-edge (SRRE), the simple ratio vegetation index (SRVI), and the Canopy Chlorophyll Content Index (CCCI). The best model for predicting CCI was obtained using the NDVIg (R2=0.8480; RMSE=6.1665 and RRMSE=0.0908). Meanwhile, SR turned out to be the best model for predicting PH (R2=0.8266; RMSE=15.6432 and RRMSE=0.0883), CA (R2=0.6886; RMSE= 0.8826 and RRMSE=0.1907), and FTN (R2=0.6850; RMSE=24.5574 and RRMSE=0.3503). The implication of these results for future activities includes establishing early monitoring and evaluation systems for lemon yield and production. This model was developed and tested in this specific location and under these environmental conditions.

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  • University of Brawijaya
  • National Pingtung University of Science and Technology
  • Universitas Islam Malang
  • Yamaguchi University
  • World Agroforestry Centre
  • Universiti Putra Malaysia
  • Institut Pertanian Malang
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Rekan penulisOrganisasiArtikel bersama
Tsuyoshi ImaiYamaguchi University6
Didik SuprayogoUniversity of Brawijaya5
Takaya HiguchiYamaguchi University5
Soemarno SoemarnoUniversity of Brawijaya5
Budi PrasetyaUniversity of Brawijaya5
Zaenal KusumaUniversity of Brawijaya4
Rika Ratna SariUniversity of Brawijaya3
Mahayu Woro LestariUniversitas Islam Malang3
Retno SuntariUniversity of Brawijaya3
Kurniatun HairiahUniversity of Brawijaya2
Danny Dwi SaputraUniversity of Brawijaya2
Heru NurwarsitoUniversity of Brawijaya2
Ahmad Ali Yuddin FitraUniversity of Brawijaya2
Atiqah Aulia HanufUniversity of Brawijaya2
Bagyo YanuwiadiUniversity of Brawijaya2
Arief RachmansyahUniversity of Brawijaya2
Anisa ZairinaInstitut Pertanian Malang2
Simon OakleyUK Centre for Ecology & Hydrology2
Yu-Ting WengNational Pingtung University of Science and Technology1
Elmi Junita TariganNational Pingtung University of Science and Technology1
Chesly Kit KobuaNational Pingtung University of Science and Technology1
Ying-Tzy JouNational Pingtung University of Science and Technology1
Yu‐Min WangNational Pingtung University of Science and Technology1
Subekti RahayuWorld Agroforestry Centre1
Degi Harja AsmaraWorld Agroforestry Centre1
Widianto WidiantoUniversity of Brawijaya1
Rizki Maulana IshaqUniversity of Brawijaya1
Seca GandasecaUniversiti Putra Malaysia1
Haidar Fari AdityaUniversity of Pembangunan Nasional Veteran Jawa Timur1
Mochtar Lutfi RayesUniversity of Brawijaya1
Daljit Singh KaramUniversiti Putra Malaysia1
Gabryna Auliya NugrohoUniversity of Brawijaya1
Yulia NurainiUniversity of Brawijaya1
Bambang Edy SiswantoNational Nuclear Energy Agency of Indonesia1
Djuhari DjuhariUniversitas Islam Malang1

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Sumber metadata: OAI-PMH (metadata jurnal) https://jurnal.uns.ac.id/tanah/oai, pertama di-harvest 10 Nov 2026, terakhir terlihat 10 Nov 2026.
Metadata asli (oai_dc) 
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	<dc:title xml:lang="en">The reliability of Unmanned Aerial Vehicles (UAVs) equipped with multispectral cameras for estimating chlorophyll content, plant height, canopy area, and fruit total number of Lemons (Citrus limon)</dc:title>
	<dc:creator xml:lang="en">Al Fanshuri, Buyung</dc:creator>
	<dc:creator xml:lang="en">Prayogo, Cahyo</dc:creator>
	<dc:creator xml:lang="en">Soemarno, Soemarno</dc:creator>
	<dc:creator xml:lang="en">Prijono, Sugeng</dc:creator>
	<dc:creator xml:lang="en">Arfarita, Novi</dc:creator>
	<dc:subject xml:lang="en">Multispectral Unmanned Aerial Vehicle (UAV)</dc:subject>
	<dc:subject xml:lang="en">Image</dc:subject>
	<dc:subject xml:lang="en">Field Measurements</dc:subject>
	<dc:subject xml:lang="en">Nondestructive</dc:subject>
	<dc:subject xml:lang="en">Vegetation Indices</dc:subject>
	<dc:description xml:lang="en">Monitoring  lemon production requires appropriate and efficient technology. The use of UAVs can addressed these challenges. The purpose of this study was to determine the best vegetation indices (VIs) for estimating chlorophyll content, plant height (PH), canopy area (CA), and fruit total numberas (FTN). CCM 200 was used as a tool to measure the chlorophyll content index (CCI), the number of fruits was measured by hand-counter, and other variables were recorded in meters. The UAV used was a Phantom 4 with a multispectral camera capable of capturing five different bands. The VIs was obtained via analysis of digital numbers generated by the multispectral camera. Then, the VIs was correlated with the CCI, PH, CA and FTN. VIs tested included the following: the normalized difference vegetation index (NDVI), the normalized difference vegetation index-green (NDVIg), the normalized different index (NDI), green minus red (GMR), simple ratio (SR), the Visible Atmospherically Resistant Index (VARI), normalized difference red edge (NDRE), simple ratio red-edge (SRRE), the simple ratio vegetation index (SRVI), and the Canopy Chlorophyll Content Index (CCCI). The best model for predicting CCI was obtained using the NDVIg (R2=0.8480; RMSE=6.1665 and RRMSE=0.0908). Meanwhile, SR turned out to be the best model for predicting PH (R2=0.8266; RMSE=15.6432 and RRMSE=0.0883), CA (R2=0.6886; RMSE= 0.8826 and RRMSE=0.1907), and FTN (R2=0.6850; RMSE=24.5574 and RRMSE=0.3503). The implication of these results for future activities includes establishing early monitoring and evaluation systems for lemon yield and production. This model was developed and tested in this specific location and under these environmental conditions.</dc:description>
	<dc:publisher xml:lang="en">Universitas Sebelas Maret</dc:publisher>
	<dc:date>2023-12-04</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jurnal.uns.ac.id/tanah/article/view/72485</dc:identifier>
	<dc:identifier>10.20961/stjssa.v20i2.72485</dc:identifier>
	<dc:source xml:lang="en">SAINS TANAH - Journal of Soil Science and Agroclimatology; Vol. 20 No. 2 (2023): December; 221-230</dc:source>
	<dc:source>2356-1424</dc:source>
	<dc:source>1412-3606</dc:source>
	<dc:source>10.20961/stjssa.v20i2</dc:source>
	<dc:language>en</dc:language>
	<dc:relation>https://jurnal.uns.ac.id/tanah/article/view/72485/42951</dc:relation>
	<dc:rights xml:lang="en">Copyright (c) 2023 Buyung - Al Fanshuri, Cahyo - Prayogo, Soemarno - -, Sugeng - Prijono, Novi - Arfarita</dc:rights>
</oai_dc:dc>