ESTIMASI KANDUNGAN KLOROFIL TANAMAN KOPI ROBUSTA (Coffea canephora var. Robusta) MENGGUNAKAN NORMALIZED DIFFERENCE VEGETATION INDEX  (NDVI) DI BANGELAN, WONOSARI, MALANG

Ajral Mukhlisin; S Soemarno

doi:10.21776/ub.jtsl.2020.007.2.18

Authors

Ajral Mukhlisin Universitas Brawijaya
S Soemarno UB Malang

DOI:

https://doi.org/10.21776/ub.jtsl.2020.007.2.18

Abstract

Chlorophyll in leaves affects the reflection of infrared light, where healthy plants can reflect more infrared light than unhealthy plants which is one of the factors increasing production in coffee plants. Normalized Difference Vegetation Index (NDVI) is a plant index that utilizes red and infrared light. Therefore, in this study, the algorithm used to determine the chlorophyll content is NDVI. The purpose of this study was to assess the value of chlorophyll content, the value of vegetation index, and to estimate chlorophyll content in coffee plants in PTPN XII Bangelan Village using a remote sensing method. The results showed that the average chlorophyll content of coffee plants assessed using the SPAD (Soil Plant Analysis Development) aid was 65.95 mg g^-1. The average Vegetable Index of coffee plants was 0.59. NDVI vegetation index was directly proportional to the value of chlorophyll content in the leaves of coffee plants with the formula of y = 97.665x + 7.684 with R = 0.7153 where the x value is the NDVI value. Thus, remote sensing can be used to estimate the chlorophyll content of coffee plants.

References

Ai, N.S. dan Banyo, Y. 2011. Konsentrasi Klorofil Daun Sebagai Indikator Kekurangan Air pada Tanaman. Ilmiah Sains,11(2): 166-173.

Alves, H.M.R., Volpato, M.M.L., Vieira, T.G.C., Maciel, D.A., GonÃ§alves, T.G. and Dantas, M.F. 2016. Characterization and spectral monitoring of coffee lands in Brazil. In Embrapa CafÃ©-Artigo em anais de congresso (ALICE). In: The International Society For Photogrammetry And Remote Sensing, 23., 2016, Prague, Czeach Republic.

Araujo, W L., Dias, P C., Moraes, G A., Celin, E F., Cunha, R L., Barros, R S. and Da Matta, F.M. 2008. Limitations to photosynthesis in coffee leaves from different canopy positions. Plant Physiology and Biochemistry 46(10): 884-890.

ArauÌjo, A.V., Partelli, F.L., Oliosi, G. and Pezzopane, J.R.M. 2016. Microclimate, development and productivity of robusta coffee shaded by rubber trees and at full sun. Artigo CientiÌfico 47(4): 700-709.

Arnanto, A. 2013. Pemanfaatan transformasi NDVI citra landsat TM untuk zonasi vegetasi di lereng Merapi Selatan. Geomedia 11(2):155-170.

Badan Pusat Statistik. 2018. Statistik Kopi Indonesia 2017. Jakarta: Badan Pusat Statistik.

Barbosa, H.A., Huete, A.R. and Baethgen, W.E. 2006. A 20-year Study of NDVI Variability over the Northeast Region of Brazil. Arid Environments 67: 288-307.

Chemura, A., Mutanga, O. and Dube, T. 2017. 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.

Chemura,A., Mutanga, O. and Odindi, J. 2017. Empirical modeling of leaf chlorophyll content in coffee (Coffea arabica) plantations with Sentinel-2 MSI data: effects of spectral settings, spatial resolution, and crop canopy cover. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10(12): 5541-5550.

Cui, D., Li, M. and Zhang, Q. 2009. Development of an optical sensor for crop leaf chlorophyll content detection. Computers and Electronics in Agriculture 69(2): 171-176.

Da Matta, F.M. 2004. Ecophysiological constraints on the production of shaded and unshaded coffee: a review. Field Crops Research 86(2-3): 99-114.

Danoedoro, P. 2012. Pengantar Penginderaan Jauh Digital. Yogyakarta: Penerbit Andi.

Davis, T.A. and G.Bernard. 1985. The coconut hybrid PB-121 (MAWA). Oleagineux. Vol. 40, No. 5.

Departemen Kehutanan. 2003. Surat Keputusan Menteri Kehutanan No.305/Kpts-II/2003. Jakarta: Departemen Kehutanan.

Ferreira, de Brito E.P., Partelli, F.L., Didonet, A.D., Marra, G.E.R. and Braun, H. 2013. Vegetative growth of Coffea arabica L. as affected by irrigation and climatic conditions of the Cerrado of GoiÃ¡s State. Semina: CiÃªncias AgrÃ¡rias 34(6Supl1): 3235-3244.

Huang, J., Wang, H., Dai, Q. and Han, D. 2014. Analysis of NDVI data for crop identification and yield estimation. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(11): 4374-4384.

Mathew, C. and A. Ramadazan. 1975. Phosynthetic efficiency in relation to annual yield and chlorophyll content in coconut palm. Journal Plantation Crop 3(1):26-28.

Mukhlis, F. 2003. Pergerakan Unsur Hara Nitrogen Dalam Tanah. Universitas Sumatera Utara. USU Digital Library.

Prahasta, E. 2008. Praktis Penginderaan Jauh dan Pengolahan Citra digital dengan Perangkat Lunak ER Mapper. Informatika Bandung.

Rayes, M.L. 2007. Metode Inventarisasi Sumber Daya Lahan. Yogyakarta: Andi.

Reis, A.R., Favarin, J.L., Malavolta, E., JÃºnior, J.L. and Moraes, M.F. 2009. Photosynthesis, chlorophylls, and SPAD readings in coffee leaves in relation to nitrogen supply. Communications in Soil Science and Plant Analysis 40(9-10): 1512-1528.

Wang, J., Rich, P.M., Price, K.P., and Kettle, W.D. 2004. Relations between NDVI and tree productivity in the central Great Plains. International Journal of Remote Sensing 25(16): 3127-3138.

Wang, N., Jassogne, L., van Asten, P. J., Mukasa, D., Wanyama, I., Kagezi, G. and Giller, K.E. 2015. Evaluating coffee yield gaps and important biotic, abiotic, and management factors limiting coffee production in Uganda. European Journal of Agronomy 63: 1-11.

Wu, C., Niu, Z., Tang, Q., Huang, W., Rivard, B. and Feng, J. 2009. Remote estimation of gross primary production in wheat using chlorophyll-related vegetation indices. Agricultural and Forest Meteorology, 149(6-7): 1015-1021.

Wu, C., Wang, L., Niu, Z., Gao, S. and Wu, M. 2010. Nondestructive estimation of canopy chlorophyll content using Hyperion and Landsat/TM images. International Journal of Remote Sensing 31(8): 2159-2167.