scholarly journals Characteristic of Electrical Power Dissipation of Oil Palm Fruits during Storage Time

Author(s):  
Saktioto ◽  
Romi Fadli Syahputra ◽  
Yan Soerbakti ◽  
Andri Saputra ◽  
Syasudhuha ◽  
...  

Among oil-producing plants, the oil palm produces a high-yield vegetable oil. After the oil palm fruit is harvested as a fresh fruit bunch six to eight months after the flower bloom, the fresh fruit bunch is stored for several days to be collected and transported for manufacture. This storage time can influence the quality and maturity level of the fruit, affecting the yield of crude palm oil. Currently, several methods exist to detect the grade and maturity level of oil palm fruit, such as optical spectroscopy-based and electromagnetic-induced. However, these methods need improvement as they are limited in terms of practical use as well as accuracy. This study proposes a simple four-point probe for the characterization of oil palm fruit during five days when stored under ambient conditions. A direct current power source from a low-voltage battery (~9 V) was applied to produce electric potential in the oil palm fruit. The voltage response shows a distinguished result, directly indicating different storage period. Furthermore, the dissipated power of the first four days dramatically increased from 0.01 to 1.25 µW, and a drop to 0.09 µW was recorded on the fifth day. The estimated capacitance also demonstrates a dropping time, pointing to a change in the internal molecule and cell wall. This result, then, can be employed to detect the level of freshness of the oil palm fruit after harvesting.

2020 ◽  
Vol 8 (1) ◽  
pp. 9-14
Author(s):  
Rismen Sinambela

The paper aims to study the position of the optimum oil palm ripeness at the bunch different positions. This information is essential to complete a measurement procedure to detect oil palm fresh fruit bunch (FFB) maturity so that the detection devices can directly measure the optimal mature position as a representative of the entire FFB characteristics. In this study, the oil palm FFB (Elaeis guineensis Jacq. var. tenera) with the various ripeness stages (4 until 22 weeks after anthesis) were collected and divided from three positions, i.e., proximal, central and distal. Moreover, each fruit in each of these positions was subjected to sample preparation to identify water and oil content. The water and oil content were completed based on the oven test method and the Soxhlet extraction technique, respectively. The optimum ripeness position is determined based on the lowest water content and the highest oil content. Based on the analysis, during the process of oil palm maturation occurs a decrease in water content and an increase in oil content. In addition, the average water content of palm fruit varies greatly depending on its position based on the analysis, i.e., proximal (45.38±5.62%), central (35.30±3.34%) and distal (41.98±2.57%). The average oil content of oil palm fruit in the central position is higher oil content (25.10±1.72%) compared to the proximal (10.00±0.77%) and distal position (13.77±1.22%). We suspect that the chemical content differences of palm fruit in various positions are due to the inequality of the respiration rate and ethylene production throughout FFB. In addition, overall it can be concluded that the fruit in the central FFB position has an optimal ripeness level compared to the proximal and distal position. Thus, the measurement position recommended in evaluating palm maturity is at the central position of FFB.


2017 ◽  
Vol 37 (1) ◽  
pp. 102 ◽  
Author(s):  
Andreas Wahyu Krisdiarto ◽  
Lilik Sutiarso ◽  
Kuncoro Harto Widodo

Oil palm fresh fruit bunch (FFB) handling processes, i.e harvesting, loading, and transporting to the Palm Oil Mill are interrelated activities because each of them contributed to the degradation of oil palm fruit quality. This paper presented studied among factors that together in series interfere FFB quality. FFB quality parameter observed was Free Fatty Acid (FFA) content. Experiment was conducted by measuring FFA content of FFB at each step of handling processes, i.e harvesting, transportation in plantation block, loading into truck, and transportation to the palm oil mill. Interrelationship among factors was built using dynamic modelling. Output of dynamic model simulation showed that there was differences of FFA content among different handling conditions. A slight difference on FFA content was observed between harvesting in mineral land and peatland and among different plant heights. Loading into truck was a handling step that had biggest contribution to quality degradation due to FFB bruise. FFBs laid on the base of truck bin suffered more bruise that resulted in higher FFA content. Manual loading of FFB harvested from mineral soil by throwing to the bottom of truck bin resulted in FFA content of bruised fruit by 5.5%, higher compared to those of the top layer which was 4.5%. Model also showed that FFA content increased due to series handling steps, compared with natural degradation. Proportion of good FFB can be used to control the whole FFA content. Without mixing, bruised FFB produced FFA content of 9.95 %, while mixing bruished and good fruit at a ratio 20 % : 80 % resulted in FFA content of 2.82 %. Increasing bruise fruit proportion from 10 % to 20 % resulted in higher FFA content of fruit harvested on mineral land than those harvested on peat land (0.88 % compare to 0.80 %), and resulted in 0.92 % increment for 3rd maturity level fruit harvested compared to 0.72 % for 1st maturity level harvested fruit. Recommendations related to harvesting were: 1) If the road and truck bin was in bad condition, FFB should be harvested at 1st or 2nd level of maturity; 2) The optimum harvesting-transportation condition for FFB quality was at 1st maturity level in peat land and transported by wood bin truck. While recommendations related to transportation were: 1) The manual loading by throwing to truck bin should be avoided; and 2) In order to maintain FFB quality, loading and transportation delay was better than waiting or queing in oil palm mill. ABSTRAKProses penanganan Tandan Buah Segar (TBS) kelapa sawit, yaitu pemanenan, pemuatan, dan pengangkutan ke pabrik minyak kelapa sawit merupakan kegiatan saling terkait, karena masing-masing berkontribusi terhadap penurunan kualitas. Penelitian ini bertujuan mempelajari keterkaitan antar faktor-faktor yang bersama-sama secara berurutan mempengaruhi kualitas TBS. Parameter kualitas TBS yang diamati adalah kadar Asam Lemak Bebas (ALB). Metode yang digunakan adalah mengukur kadar ALB TBS pada setiap tahap proses penanganan bahan, yaitu pemanenan, pengangkutan di dalam blok kebun, pemuatan ke bak truk, dan pengangkutan ke pabrik minyak kelapa sawit. Keterkaitan antar faktor dibangun dengan model dinamis. Keluaran dari simulasi model dinamis menunjukkan bahwa terdapat perbedaan kadar ALB antar kondisi penanganan TBS yang berbeda. Terdapat sedikit perbedaan kadar ALB antara TBS yang dipanen pada lahan mineral dan lahan gambut dan antara ketinggian pohon yang berbeda. Tahap penanganan TBS yang berkontribusi paling besar kepada penurunan kualitas akibat memar adalah pemuatan ke bak truk. TBS yang dimuat di dasar bak truk mengalami memar lebih banyak sehingga kadar ALB-nya lebih tinggi. Kadar ALB TBS yang dipanen di lahan mineral dan dimuat pada dasar bak truk 5,5 %, sedangkan yang di lapisan atas 4,5 %. Model menunjukkan bahwa kadar ALB meningkat pada penanganan bahan berurutan, berbeda dengan penurunan kualitas secara alami. Proporsi buah utuh dapat digunakan untuk mengendalikan kadar ALB secara keseluruhan. Bila seluruh buah memar, kadar ALB dapat mencapai 9,95 %, sedangkan campuran 20 % buah memar dan 80 % buah utuh, kadar ALB-nya 2,82 %. Peningkatan proporsi buah memar dari 10 % menjadi 20 % untuk buah yang dipanen dari lahan mineral menyebabkan penambahan kadar ALB lebih besar daripada buah yang dipanen dari lahan gambut, yaitu 0,88 % dibanding 0,80 %. Hal yang sama menyebabkan perbedaan kadar ALB 0,92 % untuk buah yang dipanen pada fraksi 3 dan 0,72 % untuk buah dipanen pada fraksi 1. Rekomendasi dari hasil penelitian ini adalah: 1) Pemuatan dengan pelemparan TBS secara manual sebaiknya dihindari; 2) Bila kondisi bak truk dan jalan buruk, sebaiknya TBS dipanen pada fraksi 1 atau 2; 3) Titik optimum kualitas TBS saat panen dan angkut adalah pada fraksi 1 di lahan gambut dan diangkut dengan truk bak kayu, dan 4) Dari sisi kualitas TBS, penundaan pengangkutan lebih menguntungkan daripada menunggu proses (mengantri) di pabrik minyak kelapa sawit (PMKS).


Agriculture ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 1179
Author(s):  
Jia Quan Goh ◽  
Abdul Rashid Mohamed Shariff ◽  
Nazmi Mat Nawi

The quality of palm oil depends on the maturity level of the oil palm fresh fruit bunch (FFB). This research applied an optical spectrometer to collect the reflectance data of 96 FFB from unripe, ripe, and overripe classes for the maturity level classification. The spectrometer scanned the FFB from different parts, including apical, front equatorial, front basil, back equatorial, and back basil. Principal component analysis was carried out to extract principal components from the reflectance data of each of the parts. The extracted principal components were used in an ANOVA test, which found that the reflectance data of the front equatorial showed statistically significant differences between the three maturity groups. Then, the collected reflectance data was subjected to machine learning training and testing by using the K-Nearest Neighbor (KNN) and Support Vector Machine (SVM). The front equatorial achieved the highest accuracy, of 90.6%, by using SVM as classifiers; thus, it was proven to be the most optimal part of FFB that can be utilized for maturity classification. Next, the front equatorial dataset was divided into UV (180–400 nm), blue (450–490 nm), green (500–570 nm), red (630–700 nm), and NIR (800–1100 nm) regions for classification testing. The UV bands showed a 91.7% accuracy. After this, representative bands of 365, 460, 523, 590, 623, 660, 735, and 850 nm were extracted from the front equatorial dataset for further classification testing. The 660 nm band achieved an 89.6% accuracy using KNN as a classifier. Composite models were built from the representative bands. The combination of 365, 460, 735, and 850 nm had the highest accuracy in this research, which was 93.8% with the use of SVM. In conclusion, these research findings showed that the front equatorial has the better ability for maturity classification, whereas the composite model with only four bands has the best accuracy. These findings are useful to the industry for future oil palm FFB classification research.


Author(s):  
Husna Sarirah Husin ◽  
Nurnasuha Amar ◽  
Aznida Abu Bakar Sajak ◽  
Mohd Sallehin Mohd Kassim

2018 ◽  
Vol 15 (1) ◽  
pp. 36
Author(s):  
Minarni Minarni ◽  
Roni Salumbae ◽  
Zilhan Hasbi

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.


Author(s):  
Sebastian Liban Utom ◽  
◽  
Elmy Johana Mohamad ◽  
Hanis Liyana Mohmad Ameran ◽  
Herdawatie Abdul Kadir ◽  
...  

2019 ◽  
Vol 30 (1) ◽  
pp. 141-149
Author(s):  
MA Awal ◽  
SS Tabriz

At present oil palm growers are facing problem to extract crude palm oil in Bangladesh. Processing of palm oil categorized into various forms but basic processing stages are essentially the same including harvesting, sterilization, bunch stripping, digestion, crushing, clarification and drying. Extracting of palm oil is very difficult by traditional method and oil recovery rate is very low. Although mechanical processing is costly but produces good quality Crude Palm Oil (CPO) and oil recovery rate is high. An electric motor operated oil palm crusher was designed and developed and tested in laboratory under the Department of Farm Power and Machinery, Bangladesh Agricultural University, Mymensingh for processing of crude palm oil from fresh fruit bunch. The crusher was designed by using Auto-Cad software. It was fabricated according to design parameters. The major parts of the crusher were screw shaft, cylinder, hopper, hollow bars, pressure case cap, jamnut and frame which were fabricated by mild steel (MS), ball bearing, gear and pinion, line and idle shaft and spring were fabricated by carbon steel (CS) whereas driver and driven pulley were fabricated by cast iron(CI). Crusher was mounted on the frame. A 9 hp electric motor was used as a power source. Crusher was tested after fabrication and 3000 gm fresh fruits were used. About 700 gm crude palm oil, 800 gm oil cake, 1400 gm skum were collected from 2700 gm pretreated fruits. The crushing capacity and crude oil percentage of the crusher was 6.49 kg/hr and 25.93%, respectively. Rotating speed of screw was 40 rpm for smooth running. The weight of crusher was only 70 kg which is easy to operate by single person. The developed oil palm crusher may fulfill the demand of smallholder growers to extract oil from fresh fruit bunches. Progressive Agriculture 30 (1): 141-149, 2019


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