Estimation on oil palm production is important for company planning. However, there are only few studies have been conducted in Kalimantan. The objective of the study was to identify agronomic and agroecological factors determined production of oil palm in Kalimantan. The study was conducted at PT Ladangrumpun Suburabadi, Minamas Plantation Angsana Estate, Tanah Bumbu District, South Kalimantan, Indonesia from February 15 to June 15, 2010. Data were collected from the company, government institutions and interviews with the company staffs. Results showed that seven parameters significantly determined estimation of oil palm production. Out of 18 possible linier models, 6 models showed good fit as predictor. The best modeling as predictor was determined by current plant age (in months), fertilizer application at 18 months before harvest (MBH), relative air humidity at 6 MBH (%), light intensity at 18 MBH (%), rainfall at 6 MBH (mm), level of water deficit at 24 MBH (mm) and number rainy day at 18 MBH (days). It was expressed in equation Y = 3.15 + 0.010 age -0.016 fertilizer -0.016 light intensity -0.005 water deficit -0.015 number of rainy day. This finding implies that recording data of agronomic and ecological factors are important for production estimation. Eventhough the model is best fit to the study site, however, it needs further verification when applied in larger area of the other sites in Kalimantan. Keywords: agronomic factors, Elaeis guineensis, linier regression, modeling, production estimation

Main Author: Santosa, Edi; Department of Agronomy and Horticulture, Faculty of Agriculture, Bogor Agricultural University, Jl. Meranti, Kampus IPB Darmaga 16680, Indonesia
Other Authors: Estimation on oil palm production is important for company planning. However, there are only few studies have been conducted in Kalimantan. The objective of the study was to identify agronomic and agroecological factors determined production of oil palm in Kalimantan. The study was conducted at PT Ladangrumpun Suburabadi, Minamas Plantation Angsana Estate, Tanah Bumbu District, South Kalimantan, Indonesia from February 15 to June 15, 2010. Data were collected from the company, government institutions and interviews with the company staffs. Results showed that seven parameters significantly determined estimation of oil palm production. Out of 18 possible linier models, 6 models showed good fit as predictor. The best modeling as predictor was determined by current plant age (in months), fertilizer application at 18 months before harvest (MBH), relative air humidity at 6 MBH (%), light intensity at 18 MBH (%), rainfall at 6 MBH (mm), level of water deficit at 24 MBH (mm) and number rainy day at 18 MBH (days). It was expressed in equation Y = 3.15 + 0.010 age -0.016 fertilizer -0.016 light intensity -0.005 water deficit -0.015 number of rainy day. This finding implies that recording data of agronomic and ecological factors are important for production estimation. Eventhough the model is best fit to the study site, however, it needs further verification when applied in larger area of the other sites in Kalimantan. , ">Keywords: agronomic factors, ">Elaeis, ">guineensis, linier regression, modeling, production estimation, ">
Format: Article info application/pdf eJournal
Bahasa: eng
Terbitan: Bogor Agricultural University
Online Access: http://journal.ipb.ac.id/index.php/jurnalagronomi/article/view/%20%3Cp%20class%3D%22BODYTEXT%22%3E%3Cem%3EEstimation%20on%20oil%20palm%20production%20is%20important%20for%20company%20planning.%20However%2C%20there%20are%20only%20few%20studies%20have%20been%20conducted%20in%20Kalimantan.%20The%20objective%20of%20the%20study%20was%20to%20identify%20agronomic%20and%20agroecological%20factors%20determined%20production%20of%20oil%20palm%20in%20Kalimantan.%20The%20study%20was%20conducted%20at%20PT%20Ladangrumpun%20Suburabadi%2C%20Minamas%20Plantation%20Angsana%20Estate%2C%20Tanah%20Bumbu%20District%2C%20South%20Kalimantan%2C%20Indonesia%20from%20February%2015%20to%20June%2015%2C%202010.%20Data%20were%20collected%20from%20the%20company%2C%20government%20institutions%20and%20interviews%20with%20the%20company%20staffs.%20Results%20showed%20that%20seven%20parameters%20significantly%20determined%20estimation%20of%20oil%20palm%20production.%20Out%20of%2018%20possible%20linier%20models%2C%206%20models%20showed%20good%20fit%20as%20predictor.%20The%20best%20modeling%20as%20predictor%20was%20determined%20by%20current%20plant%20age%20%28in%20months%29%2C%20fertilizer%20application%20at%2018%20months%20before%20harvest%20%28MBH%29%2C%20relative%20air%20humidity%20at%206%20MBH%20%28%25%29%2C%20light%20intensity%20at%2018%20MBH%20%28%25%29%2C%20rainfall%20at%206%20MBH%20%28mm%29%2C%20level%20of%20water%20deficit%20at%2024%20MBH%20%28mm%29%20and%20number%20rainy%20day%20at%2018%20MBH%20%28days%29.%20It%20was%20expressed%20in%20equation%20Y%20%3D%203.15%20%2B%200.010%20age%20-0.016%20fertilizer%20-0.016%20light%20intensity%20-0.005%20water%20deficit%20-0.015%20number%20of%20rainy%20day.%20%3C%2Fem%3E%3Cem%3E%3Cspan%20lang%3D%22sv%22%20xml%3Alang%3D%22sv%22%3EThis%20finding%20implies%20that%20recording%20data%20of%20agronomic%20and%20ecological%20factors%20are%20important%20for%20production%20estimation.%20Eventhough%20the%20model%20is%20best%20fit%20to%20the%20study%20site%2C%20however%2C%20it%20needs%20further%20verification%20when%20applied%20in%20larger%20area%20of%20the%20other%20sites%20in%20Kalimantan.%3C%2Fspan%3E%3C%2Fem%3E%3C%2Fp%3E%20%3Cp%20class%3D%22BODYTEXT%22%3E%3Cem%3E%C2%A0%3C%2Fem%3E%3C%2Fp%3E%20%3Cp%20class%3D%22BODYTEXT%22%20style%3D%22text-indent%3A0in%3B%22%3E%3Cem%3EKeywords%3A%20agronomic%20factors%2C%20%3Cspan%20style%3D%22text-decoration%3Aunderline%3B%22%3EElaeis%3C%2Fspan%3E%20%3Cspan%20style%3D%22text-decoration%3Aunderline%3B%22%3Eguineensis%3C%2Fspan%3E%2C%20linier%20regression%2C%20modeling%2C%20production%20estimation%3C%2Fem%3E%3C%2Fp%3E%20%3Cp%20class%3D%22BODYTEXT%22%20style%3D%22text-indent%3A0in%3B%22%3E%3Cem%3E%C2%A0%3C%2Fem%3E%3C%2Fp%3E
http://journal.ipb.ac.id/index.php/jurnalagronomi/article/view/%20%3Cp%20class%3D%22BODYTEXT%22%3E%3Cem%3EEstimation%20on%20oil%20palm%20production%20is%20important%20for%20company%20planning.%20However%2C%20there%20are%20only%20few%20studies%20have%20been%20conducted%20in%20Kalimantan.%20The%20objective%20of%20the%20study%20was%20to%20identify%20agronomic%20and%20agroecological%20factors%20determined%20production%20of%20oil%20palm%20in%20Kalimantan.%20The%20study%20was%20conducted%20at%20PT%20Ladangrumpun%20Suburabadi%2C%20Minamas%20Plantation%20Angsana%20Estate%2C%20Tanah%20Bumbu%20District%2C%20South%20Kalimantan%2C%20Indonesia%20from%20February%2015%20to%20June%2015%2C%202010.%20Data%20were%20collected%20from%20the%20company%2C%20government%20institutions%20and%20interviews%20with%20the%20company%20staffs.%20Results%20showed%20that%20seven%20parameters%20significantly%20determined%20estimation%20of%20oil%20palm%20production.%20Out%20of%2018%20possible%20linier%20models%2C%206%20models%20showed%20good%20fit%20as%20predictor.%20The%20best%20modeling%20as%20predictor%20was%20determined%20by%20current%20plant%20age%20%28in%20months%29%2C%20fertilizer%20application%20at%2018%20months%20before%20harvest%20%28MBH%29%2C%20relative%20air%20humidity%20at%206%20MBH%20%28%25%29%2C%20light%20intensity%20at%2018%20MBH%20%28%25%29%2C%20rainfall%20at%206%20MBH%20%28mm%29%2C%20level%20of%20water%20deficit%20at%2024%20MBH%20%28mm%29%20and%20number%20rainy%20day%20at%2018%20MBH%20%28days%29.%20It%20was%20expressed%20in%20equation%20Y%20%3D%203.15%20%2B%200.010%20age%20-0.016%20fertilizer%20-0.016%20light%20intensity%20-0.005%20water%20deficit%20-0.015%20number%20of%20rainy%20day.%20%3C%2Fem%3E%3Cem%3E%3Cspan%20lang%3D%22sv%22%20xml%3Alang%3D%22sv%22%3EThis%20finding%20implies%20that%20recording%20data%20of%20agronomic%20and%20ecological%20factors%20are%20important%20for%20production%20estimation.%20Eventhough%20the%20model%20is%20best%20fit%20to%20the%20study%20site%2C%20however%2C%20it%20needs%20further%20verification%20when%20applied%20in%20larger%20area%20of%20the%20other%20sites%20in%20Kalimantan.%3C%2Fspan%3E%3C%2Fem%3E%3C%2Fp%3E%20%3Cp%20class%3D%22BODYTEXT%22%3E%3Cem%3E%C2%A0%3C%2Fem%3E%3C%2Fp%3E%20%3Cp%20class%3D%22BODYTEXT%22%20style%3D%22text-indent%3A0in%3B%22%3E%3Cem%3EKeywords%3A%20agronomic%20factors%2C%20%3Cspan%20style%3D%22text-decoration%3Aunderline%3B%22%3EElaeis%3C%2Fspan%3E%20%3Cspan%20style%3D%22text-decoration%3Aunderline%3B%22%3Eguineensis%3C%2Fspan%3E%2C%20linier%20regression%2C%20modeling%2C%20production%20estimation%3C%2Fem%3E%3C%2Fp%3E%20%3Cp%20class%3D%22BODYTEXT%22%20style%3D%22text-indent%3A0in%3B%22%3E%3Cem%3E%C2%A0%3C%2Fem%3E%3C%2Fp%3E/3166

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