Simulation and Modeling Application in Agricultural Mechanization

Fresh fruit bunches (FFB) consist of fruit be composed grade in few spikelet. Fruit at a spikelet can be distinguished into performed fruit namely internal fruit, middle fruit and outer fruit as soon as each section contain parthenocarpy fruits. This research was conducted for determine composition and content fatty acid of oil at internal fruit, middle, outer and parthenocarpy fruit from oil palm fruit. Samples of fruit came from 3 – 5 spikelet the central of FFB. Result showed that oil content of outer fruit (46.9 + 9.9)% trend higher be compared middle fruit (42.8 + 10.3)% and internal fruit (39.1 + 9.5)%. Parthenocarpy fruits have a low oil content (14.2 + 16.2)% except yellowish fruit trend high relatively oil content. The main components of fatty acid at outer fruit, middle and internal are palmitic acid, oleic, linoleic and stearic with mean value respectively (44.8 – 45.8)%, (37.6 – 38.0)%, (9.9 – 10.9)% and (4.6 – 4.8)%. Oil content at parthenocarpy fruit have amount main component of fatty acid with performed fruit but composition of palmitic acid (40.0 + 5.9)% and oleic (34.6 + 8.4)% lower while linoleic acid (16.9 + 8.5)% and linolenic (1.6 + 1.8)% higher be compared to performed fruit. Simalungun variety has the highest oil content in the part of fruit, with that PPKS 540 and La Mé respectively. PPKS 540 variety has the highest oleic acid content while PPKS 718 has the highest linoleic content.

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Estimation of bodyweight from body measurements and determination of body measurements on Limousin cattle using digital image analysis

Animal Production Science ◽

10.1071/an14943 ◽

2016 ◽

Vol 56 (12) ◽

pp. 2060 ◽

Cited By ~ 3

Author(s):

Serkan Ozkaya ◽

Wojciech Neja ◽

Sylwia Krezel-Czopek ◽

Adam Oler

Keyword(s):

Image Analysis ◽

Body Length ◽

Digital Image ◽

Digital Image Analysis ◽

Digital Camera ◽

Body Measurements ◽

Analysis Software ◽

Body Area ◽

Image Analysis Software

The objective of this study was to predict bodyweight and estimate body measurements of Limousin cattle using digital image analysis (DIA). Body measurements including body length, wither height, chest depth, and hip height of cattle were determined both manually (by measurements stick) and by using DIA. Body area was determined by using DIA. The images of Limousin cattle were taken while cattle were standing in a squeeze chute by a digital camera and analysed by image analysis software to obtain body measurements of each animal. While comparing the actual and predicted body measurements, the accuracy was determined as 98% for wither height, 97% for hip height, 94% for chest depth and 90.6% for body length. Regression analysis between body area and bodyweight yielded an equation with R2 of 61.5%. The regression equation, which included all body traits, resulted in an R2 value of 88.7%. The results indicated that DIA can be used for accurate prediction of body measurements and bodyweight of Limousin cattle.

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OIL CONTENT AND CHEMICAL COMPOSITION IN THE PARTS OF OIL PALM FRUIT FROM 8 IOPRI VARIETIES

Jurnal Penelitian Kelapa Sawit ◽

10.22302/iopri.jur.jpks.v24i2.9 ◽

2016 ◽

Vol 24 (2) ◽

pp. 67-76

Author(s):

Sujadi Sujadi ◽

Hasrul Abdi Hasibuan ◽

Meta Rivani ◽

Abdul Razak Purba

Keyword(s):

Fatty Acid ◽

Palmitic Acid ◽

Oil Palm ◽

Oil Content ◽

Mean Value ◽

Oleic Acid Content ◽

Palm Fruit ◽

Fruit Samples ◽

Main Components ◽

Main Component

Fresh fruit bunches (FFB) consist of fruit be composed grade in few spikelet. Fruit at a spikelet can be distinguished into performed fruit namely internal fruit, middle fruit and outer fruit as soon as each section contain parthenocarpy fruits. This research was conducted for determine composition and content fatty acid of oil at internal fruit, middle, outer and parthenocarpy fruit from oil palm fruit. Samples of fruit came from 3 – 5 spikelet the central of FFB. Result showed that oil content of outer fruit (46.9 + 9.9)% trend higher be compared middle fruit (42.8 + 10.3)% and internal fruit (39.1 + 9.5)%. Parthenocarpy fruits have a low oil content (14.2 + 16.2)% except yellowish fruit trend high relatively oil content. The main components of fatty acid at outer fruit, middle and internal are palmitic acid, oleic, linoleic and stearic with mean value respectively (44.8 – 45.8)%, (37.6 – 38.0)%, (9.9 – 10.9)% and (4.6 – 4.8)%. Oil content at parthenocarpy fruit have amount main component of fatty acid with performed fruit but composition of palmitic acid (40.0 + 5.9)% and oleic (34.6 + 8.4)% lower while linoleic acid (16.9 + 8.5)% and linolenic (1.6 + 1.8)% higher be compared to performed fruit. Simalungun variety has the highest oil content in the part of fruit, with that PPKS 540 and La Mé respectively. PPKS 540 variety has the highest oleic acid content while PPKS 718 has the highest linoleic content.

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Rapid determination of oil content in dried-ground oil palm mesocarp and kernel using near infrared spectroscopy

Journal of Near Infrared Spectroscopy ◽

10.1177/0967033517732679 ◽

2017 ◽

Vol 25 (5) ◽

pp. 338-347 ◽

Cited By ~ 2

Author(s):

Sudarno ◽

Divo D Silalahi ◽

Tauvik Risman ◽

Baiq L Widyastuti ◽

F Davrieux ◽

...

Keyword(s):

Infrared Spectroscopy ◽

Near Infrared Spectroscopy ◽

Oil Palm ◽

Standard Error ◽

Oil Content ◽

Near Infrared ◽

Cross Validation ◽

Calibration Model ◽

Reliable Technique

Near infrared spectroscopy calibrations for rapid oil content determination of dried-ground oil palm mesocarp and kernel were developed. Samples were analyzed, one set using the Soxhlet extraction method for reference analysis and the other set scanned by near infrared spectroscopy instrument for calibration. Successful calibrations were obtained with good accuracy and precision for mesocarp and kernel, based on statistical models. Math treatment and scatter correction had significant effects on the fitting of the calibration model. The best obtained calibration models were demonstrated by multiple correlation coefficient (R2), standard error of calibration, standard error of cross validation, coefficient of determination in cross validation (1-VR) and relative predictive deviation of calibration, which respectively were 0.997, 1.21%, 1.23%, 0.997 and 17.89 for mesocarp and 0.952, 0.47%, 0.53%, 0.94 and 4.00 for kernel. The correlations between reference and predicted values for samples in the validation sets were in agreement with high linearity, high ratio performance to deviation of prediction (≥4.00) and low standard error of prediction samples for both samples. The results demonstrated that near infrared spectroscopy can be used as an alternative and reliable technique to estimate the mesocarp and kernel oil contents in dry matter basis accurately and rapidly.

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Imaging technique for quantification of oil palm fruit ripeness and oil content

European Journal of Lipid Science and Technology ◽

10.1002/ejlt.201000020 ◽

2010 ◽

Vol 112 (8) ◽

pp. 838-843 ◽

Cited By ~ 19

Author(s):

Yew Ai Tan ◽

Kum Wan Low ◽

Chak Khiam Lee ◽

Kum Sang Low

Keyword(s):

Oil Palm ◽

Oil Content ◽

Imaging Technique ◽

Palm Fruit

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A RIPENESS STUDY OF OIL PALM FRESH FRUIT AT THE BUNCH DIFFERENT POSITIONS

Jurnal Keteknikan Pertanian ◽

10.19028/jtep.08.1.9-14 ◽

2020 ◽

Vol 8 (1) ◽

pp. 9-14

Author(s):

Rismen Sinambela

Keyword(s):

Water Content ◽

Oil Palm ◽

Oil Content ◽

Elaeis Guineensis ◽

Soxhlet Extraction ◽

Fresh Fruit ◽

Test Method ◽

Central Position ◽

Fresh Fruit Bunch ◽

Palm Fruit

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.

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Application of Microwave Moisture Sensor for Determination of Oil Palm Fruit Ripeness

Measurement Science Review ◽

10.2478/v10048-010-0002-x ◽

2010 ◽

Vol 10 (1) ◽

Cited By ~ 22

Author(s):

You Yeow ◽

Zulkifly Abbas ◽

Kaida Khalid

Keyword(s):

Oil Palm ◽

Palm Fruit ◽

Moisture Sensor

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Modeling of Oil Palm Fruit Maturity for the Development of an Outdoor Vision System

International Journal of Food Engineering ◽

10.2202/1556-3758.1396 ◽

2008 ◽

Vol 4 (3) ◽

Cited By ~ 5

Author(s):

Muhammad Hudzari Razali ◽

Wan Ishak Wan Ismail ◽

Abd. Rahman Ramli ◽

Md. Nasir Sulaiman

Keyword(s):

Mathematical Model ◽

Oil Palm ◽

Vision System ◽

Linear Regression Analysis ◽

Data Logger ◽

Linear Change ◽

Palm Fruit ◽

Important Indicator ◽

Pixel Value ◽

The Mathematical Model

Color is the most important indicator farmers use to determine the maturity of the oil palm fruit called fresh fruit bunches (FFB) in the manual harvesting process. To automate the harvesting operation, the development of a vision system will replace the human eye for mature FFB recognition. In real plantation environments, variations in the daylight caused the light intensity to change, thus becoming the main issue that affects the automatic recognition process. In this study, the matured FFB was captured using a Sony digital Handycam on the day shift period. At the same time period of daylight intensity, a unit on foot candles (FC) also was simultaneously recorded using an Extech lightmeter data logger. From the linear regression analysis process, the mathematical model shows that there is a linear change between daylight intensity with the pixel value of the components green and blue. For the pixel value of the red component, the value will be linear at a maximum of 255 and at a certain intensity. To validate the mathematical model, this equation is used in the development of software for outdoor recognition processes.

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