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Rice (Oryza Sativa L.) is the main food source in Malaysia. Thus, to fulfill the needs, continuous rice production is required. Appropriate amount of nitrogen (N) fertilizer is needed to ensure high production of rice. In this research, the effect of N to plant height, SPAD reading, biomass and yield were firstly studied. It was later followed by the estimation of biomass and yield using Terrestrial Laser Scanning (TLS) data. Different amount of N i.e. 0 kg/ha, 85 kg/ha, 170 kg/ha and 250 kg/ha were applied to MR 219 and MR 220 paddy. The 2-way ANOVA results showed that all parameters were significantly different at each N level. The highest reading was achieved at 250 kg/ha of N level; 70.46 cm (plant height), 39.13 (SPAD reading), 927.29 g/m2 (biomass) and 830.99 g/m2 (grain yield) respectively. Therefore, these parameters can be used to indicate the level of input nitrogen at the plant. Later, the plant height calculated using developed Crop Surface Model (CSM) of the Terrestrial Laser Scanning (TLS) data was used to evaluate the biomass and grain yield of paddy. Results has shown that high correlations and regression were accomplished for CSM plant height and biomass (R2 = 0.809). However, the results between CSM plant height and grain were lower (R2 = 0.582). In accordance with the outcome, biomass and yield were best estimated at 94 Day After Sowing (DAS). An estimation model for biomass and grain yield using linear equation was developed. Then a t-test was done to test the estimated and measured biomass and grain yield. The outcome showed that there was no significance difference between measured and estimated values. The values for both parameters were 1 (p≥0.05). Thus, it can be said that CSM plant height can be used to estimate biomass and grain yield.


Biomass Yield Height Phase shift Laser scanner

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How to Cite
Zulkifli, Z. ., Bejo, S. K., Muharam, F. M. ., Yule, I. ., Pullanagari, R. ., Dan, L. ., & Abdulllah, W. N. Z. Z. . (2021). Biomass and Yield Estimation of MR219 and MR220 of Paddy Varieties using Terrestrial Laser Scanning Data. Basrah Journal of Agricultural Sciences, 34, 54–62.


  1. Azarpour, E., Moraditochaee, M., & Bozorgi, H. R. (2014). Effect of nitrogen fertilizer management on growth analysis of rice cultivars. International Journal of Biosciences, 4, 35–47.
  2. Bali, A. S., Siddique, M., Ganai, B. A., Khan, H. V., Singh, K. N., & Bali. A. S. (1995). Response of rice (Oryza sativa) genotypes to nitrogen levels under transplanted conditions in Kashmir valley. Indian Journal of Agronomy; 40, 35-37.
  3. Confalonieri, R., Bregaglio, S., Rosenmund, A.S., Acutis, M., & Savin, I. (2011). A model for simulating the height of rice plants. European Journal of Agronomy, 34, 20-25.
  4. Dalal, P. K., & Dixit, L. (1987). Response of medium duration rice varieties to levels of nitrogen. Indian Journal of Agronomy, 32, 286-287.
  5. Daniel, K. V., & Wahab, K. (1994). Levels and time of nitrogen in semi dry rice. Madras Agriculture Journal, 81, 357-358.
  6. Dixit, U. C., & Patro N. (1994). Effect of NPK levels, zinc and plant density on yield attributes and yield of summer rice. Environment and Ecology, 12, 72-74.
  7. Gholizadeh, A., Amin, M. S. M., Anuar, A. R., & Aimrun, W. (2009). Evaluation of leaf total nitrogen content for nitrogen management in a Malaysian paddy field by using soil plant analysis development chlorophyll meter. American Journal of Agricultural and Biological Sciences, 4, 278-282. 10.3844/ajabssp.2009.278.282.
  8. Gholizadeh, A., Amin, M., Soom, M., Rahim, A. A., & Wayayok, A. (2011). Using soil plant analysis development chlorophyll meter for two growth stages to assess grain yield of Malaysian rice (Oryza sativa). American Journal of Agricultural and Biological Sciences, 6, 209–213,
  9. Gao, S., Niu, Z., Huang, N., & Hou, X. (2013). Estimating the Leaf Area Index, height and biomass of maize using HJ-1 and RADARSAT-2. International Journal of Applied Earth Observation and Geoinformation, 24, 1–8.
  10. Keightley, K. E., & Bawden, G. W. (2010). 3D volumetric modelling of grapevine biomass using Tripod LiDAR. Computers and Electronics in Agriculture, 74, 305–312.
  11. Lumme, J., Karjalainen, M., Kaartinen, H., Kukko, A., Hyyppä, J., Hyyppä, H., Jaakkola, A., & Kleemola, J., (2008). Terrestrial laser scanning of agricultural crops. In: The International Achieves of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 37, 563–566.
  12. Lampayan, R. M., Bouman, B. A. M., Dios, J. L. D., Espiritu, A. J., Soriano, J. B., & Lactaoen A. T. (2010). Yield of aerobic rice in rain fed lowlands of the Philippines as affected by nitrogen management and row spacing. Journal of Field Crops Research, 116, 165-174.
  13. Manzoor, Z., Awan, T. H., Safdar, M. E., Ali, R. I., Ashraf, M. M., & Ahmad, M. (2006). Effect of nitrogen levels on yield and yield components of basmati. Journal of Agriculture Research, 44, 115-120.
  14. Marazi, A. R., Khan, G.M., Singh, K. H. & Bali A. S., (1993). Response of rice (Oryza sativa) to different Nitrogen levels and water regimes in Kashmir Valley. Indian Journal of Agricultural Sciences. 63, 726-727.
  15. Meena, S. L., Surendra. S., & Shivay Y.S. (2003). Response of hybrid rice (Oryza sativa) to nitrogen and potassium application in sandy clay loam soils. Indian Journal of Agricultural Science, 73, 8-11.
  16. Ntanos D. A., & Koutroubas S. D. (2002). Dry matter and N accumulation and translocation for Indica and Japonica rice under Mediterranean conditions. Field Crops Research, 74, 93–101. 4290(01)00203-9.
  17. Riczu, P., Tamas, J., Nagy, A., Forian, T., Nagy, G., & Jancso, T., (2011). 3D laser scanning and modeling of single trees in Karcag research center. Analele Universitatii din Oradea, Fascicula: Protectia Mediului, 17, 277-284.
  18. Shibu, M. E., Leffelaar P.A., Van Keulen, H, & Aggarwal, P. K., (2010). A simulation model for nitrogen-limited situations: Application to rice. European Journal of Agronomy, 32, 255-271.
  19. Sritarapipat, T., & Rakwatin, P. (2012). Rice crop height monitoring using field server and digital image analysis. The 33th Asian Conference on Remote Sensing, 623-627.
  20. Tilly, N., Hoffmeister, D., Cao, Q., Huang, S., Lenz-Wiedemann, V., Miao, Y., & Bareth, G., (2014). Multitemporal crop surface models: accurate plant height measurement and biomass estimation with terrestrial laser scanning in paddy rice. Journal of Applied Remote Sensing, 8, 083671-083671.
  21. Tilly, N., Hoffmeister, D., Cao, Q., Lenz-Wiedemann, V., Miao, Y., Bareth, G. (2015). Transferability of models for estimating paddy rice biomass from spatial plant height data. Agriculture, 5, 538–560.
  22. Zulkifli, Z., & Khairunniza-Bejo, S. (2015). Paddy growth monitoring using terrestrial laser scanner. Australian Journal of Basic and Applied Sciences, 9, 90-96.