ESTIMASI KANDUNGAN UNSUR HARA KALIUM DAN MAGNESIUM PADA TANAMAN NANAS (Ananas comosus (L) Merr.) Menggunakan Unmanned Aerial Vehicle (UAV) DI PT. GREAT GIANT PINEAPPLE
Keywords:
Ananas comosus, GNDVI, Magnesium, NDVI, Potassium, Unmanned Aerial VehicleAbstract
Central Lampung is one of the areas that produce a lot of pineapple. Pineapple plants require potassium and magnesium nutrients to produce optimal fruit. The apparent appearance of chlorotic symptoms due to nutrient deficiency of potassium and magnesium makes it possible to be detected using aerial photographs. This study aimed to compare between Green Normalized Difference Vegetation Index (GNDVI), Normalized Difference Vegetation Index (NDVI) and spectral values for predicting potassium and magnesium contents in pineapple plants. The result of regression test showed that GNDVI had the best relationship than NDVI and spectral values. The equation for predicting the potassium nutrient in pineapple plant was with the formula: K=3,342-1,501(GNDVI) with RMSE value 0,1634. The Estimation magnesium in pineapple plants, NDVI had a better relationship with magnesium than with GNDVI and spectral values. The equations for magnesium estimation in plants with NDVI were obtained by using the regression test, i.e.: Mg=0,083+0,288(NDVI) with RMSE of 0,0342. Paired T-test values of GNDVI with potassium (-1,007) and NDVI with magnesium (-1,048) showed that t count was smaller than t table (2,015) and the significance value of both was greater than alpha (α = 0,05). So it can be said that the value of estimation with the actual value in the field has no difference that significant.
Downloads
References
BAPPEDA. 2012. DFAFF Buku Putih Sanitasi. Percepatan Pembangunan Sanitasi Permukiman. Badan Perencanaan Pembangunan Daerah. Lampung Tengah.
Chemura, A., Onisimo, M. and Timothy, D. 2016. Integrating age in the detection and mapping of incongruous patches in coffee (Coffea arabica) plantations using Multi-Temporal Landsat 8 NDVI Anomalies. International Journal of Applied Earth Observation And Geoinformation 57: 1–13.
Gitelson, A., Kaufman, Y. and Merzlyak, M. 1996. Use of a green channel in remote sensing of global vegetation from EOS-MODIS. Remote Sensing of Environment 58: 289-298.
Govaerts, B. and Verhulst, N. 2010. The Normalized Difference Vegetation Index (NDVI) Greenseeker Handheld Sensor: Toward The Integrated Evaluation Of Crop Management. Part A: Concepts And Case Studies. Mexico.
Guo, X., Xicun, Z., Cheng, L., Yu, W., Xinyang, Y., Gengxing, Z. and Houxing, S. 2017. Hyperspectral Inversion of potassium content in apple leaves based on vegetation index. Agricultural Sciences (8): 825-836.
Hadiati, S. dan Ni Luh, P. 2008. Petunjuk Teknis Budidaya Nanas. Balai Penelitian Tanaman Buah Tropika. Pusat Penelitian Dan Pengembangan Holtikultura, Badan Penelitian dan Pengembangan Pertanian. Solok, Sumatra Barat.
Jia, L., Zihui, Y., Fei, L., Martin, G., Wolfgang, K., Georg, B., Yuxin, M., Xinpin, M. and Fusuo, Z. 2012. Nitrogen Status Estimation of Winter Wheat by Using an IKONOS Satellite Image in the North China Plain. IFIP International Federation for Information Processing 2012. IFIP AICT 369, Pp. 174–184.
Kumar, R. and Silva, L. 1972. Light Ray Tracing through a Leaf Cross Section. LARS Technical Reports. Paper 16. Purdue University.
Pramuji dan Bastaman. 2009. Teknik analisis mineral tanah untuk menduga cadangan sumber hara. Buletin Teknik Pertanian 14 (2): 80-82.
Prasetyo, B. dan Suriadikarta, D. 2006. Karakteristik, potensi, dan teknologi pengelolaan tanah Ultisols untuk pengembangan pertanian lahan kering di Indonesia. Jurnal Litbang Pertanian: 25 (2).
Roy, D., Finck, G. and Blair, H. 2006. Plant Nutrition For Food Security: A Guide For Integrated Nutrient Management. Fertilizer And Plant Nutrition Bulletin: 16. ISBN 92-5-105490-8. Food And Agriculture Organization. Rome.
Sims, D. and Gamon, J. 2002. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Remote Sensing of Environment (81) 337 – 354.
Sitompul, S.M. 2015. Nutrisi Tanaman: Diagnosis Defisiensi Nutrisi Tanaman. Laboratorium Fisiologi Tanaman, Fakultas Pertanian. Universitas Brawijaya. Malang.
Sugiyono. 2008. Metode Penelitian Kuantitatif, Kualitatif dan R & D. Alfabeta. Bandung.
Susanti, A. 2015. Outlook Nenas. Pusat Data Dan Sistem Informasi Pertanian. ISSN : 1907-1507. Sekretariat Jenderal Kementerian Pertanian. Jakarta.
Downloads
Published
Issue
Section
License
The copyright of the received article shall be assigned to the journal as the publisher of the journal. The intended copyright includes the right to publish the article in various forms (including reprints). The journal maintains the publishing rights to the published articles.
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
