scholarly journals Classification of Oil Palm Fresh Fruit Bunches (FFB) Using Raman Spectroscopy

2018 ◽  
Vol 7 (4.11) ◽  
pp. 184
Author(s):  
S. A.M. Dan ◽  
F. H. Hashim ◽  
T. Raj ◽  
A. B. Huddin ◽  
A. Hussain
Keyword(s):  
Raman Spectroscopy ◽  
Oil Palm ◽  
Fresh Fruit ◽  
Carotenoid Content ◽  
Raman Shift ◽  
Palm Fruit ◽  
Fresh Fruit Bunches ◽  
Different Characteristics ◽  
Extraction Model

The current practice in determining oil palm fresh fruit bunches (FFB) ripeness is by its colour which could be inaccurate. This study investigates the classification of oil palm FFB ripeness using Raman spectroscopy. A feature extraction model is developed based on the different organic compositions that contribute to the ripeness classification. Samples are collected according to the Malaysian Palm Oil Board (MPOB) standards which are unripe, underripe, ripe, overripe, and rotten. Different characteristics of the Raman shift were detected which represent the material composition for each sample. The Raman intensity of the oil palm fruit increases from unripe to ripe before decreasing to rotten due to the carotenoid content in the fruit. In conclusion, Raman spectroscopy is a suitable technique to observe the changes in the composition of oil palm fruit classified by its ripeness.  

scholarly journals IMPLEMENTASI JARINGAN SYARAF TIRUAN (JST) DAN PENGOLAHAN CITRA UNTUK KlASIFIKASI KEMATANGAN TBS KELAPA SAWIT

2018 ◽  
Vol 15 (1) ◽  
pp. 36
Author(s):  
Minarni Minarni ◽  
Roni Salumbae ◽  
Zilhan Hasbi
Keyword(s):  
Oil Palm ◽  
Color Space ◽  
Human Perception ◽  
Image Data ◽  
Cost Effective ◽  
Fresh Fruit ◽  
Human Vision ◽  
Palm Fruit ◽  
Color Parameters ◽  
Fresh Fruit Bunches

The clasification of ripeness stages of oil palm fresh fruit bunches (FFBs) can be done using color parameters. These parameters are often evaluated by human vision, whose degree of accuracy is subjective which can cause doubt in judgement. Automatic clasifications offreshfruit bunches (FFBs) based on color parameters can be done using computer vision. This method is known as a nondestructive, fast and cost effective method. In this research, a MATLAB computer program has been developed which consists of RGB and HSV GUI which is used to record, display, and process FFB image data. The backpropagation artificial neural network (ANN) program is also developed which is used to classify the oil palm fruit fresh bunches (FFBs). Samples are fresh fruit bunches (FFB) of oil palm varieties of Tenera which comprise of Topaz, Marihat, and Lonsum clones. Each clone composed of three levels of ripeness represented by five fractions. The measurements were started by capturing images of oil palm, extracting RGB and HSV values, calculating weight values from the image database to make anANN program, preparing grid programs for oil palm FFBs, and comparing grading levels of oil palm FFBs using program and by harvester. This program successfully classified oil palm (FFBs) into three categories of ripeness which are unripe (F0 and F1), ripe (F1 and F1) and over ripe (F4 and F5). The RGB and HSV programs successfully classified 79 out of 216 FFBs or 36.57% and 106 out of 216 TBS or 49.07%. Respectively the HSV program is better than RGB program because the representation of HSV color space are more understood by human perception hence can be used in calibration and color comparison.

scholarly journals STUDY OF THE UTILIZATION OF PALM OIL INDUSTRY LIQUID WASTE

Konversi ◽  
2021 ◽  
Vol 10 (1) ◽  
Author(s):  
An Nisa Fitria ◽  
Vandhie Satyawira Gunawan ◽  
Mardiah Mardiah
Keyword(s):  
Palm Oil ◽  
Oil Palm ◽  
Economic Value ◽  
Liquid Waste ◽  
Oil Industry ◽  
Fresh Fruit ◽  
Added Value ◽  
Palm Fruit ◽  
Fresh Fruit Bunches ◽  
Plantation Crops

Palm oil is one of the plantation crops that have high economic value and is growing rapidly. The wider the area of oil palm plantations in Indonesia, the more palm oil mills will process palm fresh fruit marks and produce waste from processed palm oil, namely solid waste and liquid waste. Each tonne of fresh fruit bunches (FFB) processed at the plant will potentially leave waste of about 23% empty palm oil, 4% wet decanter solid, 6.5% shell, 13% fiber, and 50% liquid waste. This review will discuss the utilization of palm oil mill liquid waste (LCPKS) which is organic material that still contains many benefits such as nutrients, therefore the application of liquid waste is an effort to recycle some of the nutrients (recycling nutrients) which is followed by harvesting fresh fruit bunches (FFB) from oil palm so that it will reduce the cost of fertilization which is classified as very high for oil palm cultivation. During the processing of oil palm fruit into palm oil in the palm oil industry, the remaining process is obtained in the form of liquid waste. If done properly, the liquid waste of the palm oil industry is considerable potential and can increase the added value of waste itself.Keywords: liquid waste industry, palm oil, utilization  

Machine vision for the maturity classification of oil palm fresh fruit bunches based on color and texture features

2021 ◽  
Vol 286 ◽  
pp. 110245
Author(s):  
Anindita Septiarini ◽  
Andi Sunyoto ◽  
Hamdani Hamdani ◽  
Anita Ahmad Kasim ◽  
Fitri Utaminingrum ◽  
...  
Keyword(s):  
Machine Vision ◽  
Oil Palm ◽  
Texture Features ◽  
Fresh Fruit ◽  
Fresh Fruit Bunches ◽  
Color And Texture Features

scholarly journals Technical and economic assessment of two harvesting tools for young Elaeis oleifera x E. guineensis oil palms

2020 ◽  
Vol 38 (3) ◽  
pp. 418-428
Author(s):  
Elizabeth Ruiz Alvarez ◽  
Jhon Banguera ◽  
Wilson Pérez Toro ◽  
Juan Hernández Hernández ◽  
Javier Arévalo ◽  
...  
Keyword(s):  
Oil Palm ◽  
Cutting Tools ◽  
Cost Effective ◽  
Economic Assessment ◽  
Fresh Fruit ◽  
Labor Costs ◽  
Palm Fruit ◽  
Elaeis Oleifera ◽  
Time And Motion ◽  
Fresh Fruit Bunches

The harvest of oil palm fruit bunches represents 25% of the total cost of production of one metric ton of fresh fruit bunches (FFB), and nine-tenths of the costs of this process (i.e., harvest) are labor costs. This study was undertaken to analyze and compare the labor productivity and harvesting costs of young oil palm trees of the species Elaeis oleifera x E. guineensis (OxG) using two different cutting tools. The first tool was a chisel, and the second was a mechanized oil palm cutter. From a methodological perspective, we conducted a time and motion study. The results show that the average number of palms harvested by a worker using a chisel was 320 per workday (on average 291 fresh fruit bunches were cut per workday). A worker using a mechanized oil palm cutter (MOPC) harvested 546 palms per workday (on average 551 fresh fruit bunches were cut per workday). Finally, the cost per ton of fresh fruit bunches (FFB) harvested decreased by 15% following the MOPC; in other words, the implementation of this novel technology is cost-effective.

Classification of oil palm fresh fruit bunches based on their maturity using portable four-band sensor system

2012 ◽  
Vol 82 ◽  
pp. 55-60 ◽  
Author(s):  
Osama Mohammed Ben Saeed ◽  
Sindhuja Sankaran ◽  
Abdul Rashid Mohamed Shariff ◽  
Helmi Zulhaidi Mohd Shafri ◽  
Reza Ehsani ◽  
...  
Keyword(s):  
Oil Palm ◽  
Fresh Fruit ◽  
Sensor System ◽  
Fresh Fruit Bunches

scholarly journals Classification of oil palm fresh fruit maturity based on carotene content from Raman spectra

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Thinal Raj ◽  
Fazida Hanim Hashim ◽  
Aqilah Baseri Huddin ◽  
Aini Hussain ◽  
Mohd Faisal Ibrahim ◽  
...  
Keyword(s):  
Raman Spectroscopy ◽  
Oil Palm ◽  
Fresh Fruit ◽  
Classification Model ◽  
Oil Yield ◽  
Raman Peak ◽  
Molecular Fingerprint ◽  
Carotene Content ◽  
Palm Fruit ◽  
Palm Fruits

AbstractThe oil yield, measured in oil extraction rate per hectare in the palm oil industry, is directly affected by the ripening levels of the oil palm fresh fruit bunches at the point of harvesting. A rapid, non-invasive and reliable method in assessing the maturity level of oil palm harvests will enable harvesting at an optimum time to increase oil yield. This study shows the potential of using Raman spectroscopy to assess the ripeness level of oil palm fruitlets. By characterizing the carotene components as useful ripeness features, an automated ripeness classification model has been created using machine learning. A total of 46 oil palm fruit spectra consisting of 3 ripeness categories; under ripe, ripe, and over ripe, were analyzed in this work. The extracted features were tested with 19 classification techniques to classify the oil palm fruits into the three ripeness categories. The Raman peak averaging at 1515 cm−1 is shown to be a significant molecular fingerprint for carotene levels, which can serve as a ripeness indicator in oil palm fruits. Further signal analysis on the Raman peak reveals 4 significant sub bands found to be lycopene (ν1a), β-carotene (ν1b), lutein (ν1c) and neoxanthin (ν1d) which originate from the C=C stretching vibration of carotenoid molecules found in the peel of the oil palm fruit. The fine KNN classifier is found to provide the highest overall accuracy of 100%. The classifier employs 6 features: peak intensities of bands ν1a to ν1d and peak positions of bands ν1c and ν1d as predictors. In conclusion, the Raman spectroscopy method has the potential to provide an accurate and effective way in determining the ripeness of oil palm fresh fruits.

scholarly journals Potential Content of Palm Oil at Various Levels of Loose Fruit in Oil Palm Circle

2021 ◽  
pp. 91-98
Author(s):  
Fitrah Murgianto ◽  
Edyson Edyson ◽  
Adhy Ardiyanto ◽  
Shadiar Kesuma Putra ◽  
Lilik Prabowo
Keyword(s):  
Palm Oil ◽  
Oil Palm ◽  
Oil Content ◽  
Fresh Fruit ◽  
Ripe Fruit ◽  
Palm Fruit ◽  
Palm Trees ◽  
Fresh Fruit Bunches ◽  
Potential Content ◽  
Important Activity

Harvesting fresh fruit bunches (FFB) is an important activity in the oil palm plantation industry. This study aimed to analyze the potential content of palm oil at the level of loose fruit that falls on the oil palm circle. Observations were made on five fresh fruit bunches with criteria 1, 3, and 5 respectively loose fruit per bunch that falls on the oil palm circle from oil palm trees that were 22, 16, 12, and 7 years old. All sample fresh fruit bunches were analyzed for potential oil to bunch and oil to wet mesocarp in the analytical laboratory of Bumitama Gunajaya Agro. Content of oil to wet mesocarp in loose fruit 1, 3, and 5 were 48,50 % b, 51,98 % a, and 53,21 % a respectively. While the content of oil to bunch in loose fruit 1, 3, and 5 were 24,19 % a, 25,52 % a, and 25,71 % a respectively. The highest potential for oil content occurs in ripe palm fruit with a level of loose fruit 5 grains per bunch that falls on that oil palm circle. Five grains per bunch on the oil palm circle can be used as an indicator for harvesters to harvest ripe fruit with optimal oil content.   

ANALISIS TATANIAGA TANDAN BUAH SEGAR KELAPA SAWIT DI DESA TEMPAKAN KECAMATAN BATU ENGAU KABUPATEN PASER (Marketing Analysis of Fresh Fruit Bunches of Oil Palm in Tempakan Village, Batu Engau Subregency, Paser Regency)

2019 ◽  
Vol 2 (2) ◽  
pp. 113
Author(s):  
SIMON SUTRADO SIMANJUNTAK ◽  
ACHMAD ZAINI
Keyword(s):  
Oil Palm ◽  
Sampling Method ◽  
Marketing Channel ◽  
Marketing Channels ◽  
Fresh Fruit ◽  
Snowball Sampling ◽  
Level Zero ◽  
Average Share ◽  
Marketing Analysis ◽  
Fresh Fruit Bunches

The purposes of this study were to know marketing channel, marketing margin, share, and marketing profit of fresh fruit bunches of oil palm in Tempakan Village, Batu Engau Subregency, Paser Regency. The study was conducted from June to August 2016. The sampling method was done with two ways as random sampling in farmer level and in marketing channel as snowball sampling. Data analysis were done by calculating marketing margin, share, and marketing profit. The results of this study showed that there are two marketing channels in reserach location are channel of level zero and channel of level one. Marketing margin in farmer level was Rp40.39 kg-1 and margin in whole trader level was Rp314.44 kg-1. The average share of farmer level was 97.58% and in trader level was 81.48%. Margin and share that profitable for farmer is at channel of level zero. The average of profit in whole trader level of fresh fruit bunches was 112.75%, that meant marketing by whole trader is profitable.

scholarly journals Tauke and Emotional Network Model in Oil Palm Marketing: Getting Fresh Fruit from Smallholders in Indonesia

2020 ◽  
Vol 55 (4) ◽  
Author(s):  
Rizabuana Ismail ◽  
Slamet Haryono ◽  
Ira Maya Sofa Harahap ◽  
Ria Manurung
Keyword(s):  
Oil Palm ◽  
Marketing Channel ◽  
Marketing Channels ◽  
Fresh Fruit ◽  
Network Marketing ◽  
Marketing Model ◽  
Marketing Models ◽  
Cash Payment ◽  
Fresh Fruit Bunches ◽  
Depth Interviews

This article describes how fresh fruit bunches grown by oil palm smallholders are incorporated into oil palm marketing models in Indonesia. This emotional network marketing model is a supplementary model of marketing models in Malaysia which is called factory centered and middleman model. This research uses a descriptive qualitative method. The data was collected by conducted in-depth interviews with 28 informants coming from 4 (four) categories of oil palm smallholders: oil palm tauke (middleman) that included big tauke and small tauke, workers in the loading ramps, and workers in the oil palm factories who were involved in oil palm marketing channels. The result of the research showed that the oil palm marketing channel between smallholders and either small tauke and big tauke was based on an emotional network with a strong bond of friendship, brotherhood, dwelling location, cash payment, giving loan with reasonable requirements, and providing transportation for fresh fruit bunches. In contrast, oil palm marketing channel among smallholders, loading ramp buyers, and POF was based on regulations. This writing presented a different perspective of oil palm marketing channels in general by involving the emotional network of the existing actors for getting fresh fruit bunches and the advantages of oil palm marketing. In this marketing model, there is a longer marketing channel and actors with their varied roles.

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