Oil Palm Fresh Fruit Bunches Research Articles

Annotated Datasets of Oil Palm Fruit Bunch Piles for Ripeness Grading Using Deep Learning

The quality of palm oil is strongly influenced by the maturity level of the fruit to be processed into palm oil. Many studies have been carried out for detecting and classifying the maturity level of oil palm fruit to improve the quality with the use of computer vision. However, most of these studies use datasets in the form of images of oil palm fresh fruit bunches (FFB) with incomplete categorization according to real conditions in palm oil mills. Therefore, this study introduces a new complete dataset obtained directly from palm oil mills in the form of videos and images with different categories in accordance with the real conditions faced by the grading section of the palm oil mill. The video dataset consists of 45 videos with a single category of FFB videos and 56 videos with a collection of FFB with multiple categories for each video. Videos are collected using a smart phone with a size of 1280 × 720 pixels with .mp4 format. In addition, this dataset has also been annotated and labelled based on the maturity level of oil palm fruit with 6 categories, which are unripe, under-ripe, ripe, overripe, empty bunches and abnormal fruit.

Oil Palm Fresh Fruit Bunch Ripeness Detection Methods: A Systematic Review

The increasing severity of the labour shortage problem in the Malaysian palm oil industry has created a need to explore other avenues for harvesting oil palm fresh fruit bunches (FFBs) such as through autonomous robots’ deployment. However, the first step in using an autonomous system to harvest FFBs is to identify which FFBs have become ripe and are ready to be harvested. In this work, we reviewed previous and current methods of identifying the maturity of fresh fruit bunches as found in the literature. The different methods were then compared in terms of the types of sample data used, sensor modalities, and types of classifiers used with a particular focus on the feasibility of each method for on-field application. From the 51 papers reviewed, which include a total of 11 unique approaches, it was found that the most feasible method for detecting ripe FFBs in the field is a combination of computer vision and deep learning. This system has the advantages of being a noncontact approach that is low cost while also being able to operate in real time with high accuracy.

The Effect Of FFB Prices On The Welfare Of Oil Palm Farmers In Mentawak Village Merangin Regency

This study aims to determine how far the influence of the price of Oil Palm FFB in Mentawak Village, Nalo Tantan District. The research was conducted at the price of fresh fruit bunches (FFB) of oil palm Rp. 1,200.00/kg. The method used is a quantitative research method with simple linear regression using the SPSS version 22 program. The results of this study the regression model obtained is Y=44,554+0,074 X. The regression model obtained at the price of oil palm FFB Rp. 1,200.00/kg is worth positive, so that it is said that the price of oil palm FFB and the welfare of oil palm farmers is positively related. This study suggests that related parties pay more attention to farmers and can provide guidance such as training/counseling to farmers so that they can make derivative products from oil palm plantations. Thus, it is hoped that the farmers will not only benefit from the sale of their agricultural/plantation products but also become entrepreneurs.

Penerapan Asas Kepastian Hukum dalam Peraturan Menteri Pertanian Nomor 01/PERMENTAN/KB/120/1/2018 Tentang Pedoman Penetapan Harga Pembelian Tandan Buah Segar Kelapa Sawit Produksi Pekebun

Smallholder oil palm plantations have made a major contribution to the development of the national palm oil industry. However, the policy of developing oil palm plantations continues to be unfavorable to smallholder oil palm farmers, with one example being the right of farmers to earn income and profits as an illustration of guarantees for agricultural product marketing. To realize these farmers' rights, the government established Regulation of the Minister of Agriculture Number 01/PERMENTAN/KB.120/1/2018 concerning Guidelines for Setting the Purchase Price of Oil Palm Fresh Fruit Bunches Produced by Farmers in lieu of Minister of Agriculture Regulation Number 14/Permentan/OT.140/2/2013 concerning Guidelines for Determining the Purchase Price of Oil Palm Fresh Fruit Bunches Produced by Planters, which is considered unable to provide legal certainty because the content material is incomplete and has multiple interpretations. The purpose of writing this law is to analyze the application of the principle of legal certainty in the Regulation of the Minister of Agriculture, Number 01/PERMENTAN/KB.120/1/2018, concerning Guidelines for Determining the Purchase Price of Oil Palm Fresh Fruit Bunches Produced by Planters. The writing of this law uses a normative-juridical method, namely, by examining and understanding the positivization of the principle of legal certainty in statutory regulations. The application of the principle of legal certainty in the substance of the Regulation of the Minister of Agriculture Number 01/PERMENTAN/KB.120/1/2018 concerning Guidelines for Determining the Purchase Price of Oil Palm Fresh Fruit Bunches Produced by Planters has fulfilled the principle of legal certainty, namely protection for both smallholders and smallholders with plasma patterns as well as self-help patterns through partnerships with plantation institutions. In the cooperation agreement between the company and the planters, through the planters' institution, the regional government is authorized as a supervisor, and the government has also regulated the minimum elements for the parties in the cooperation agreement. The regulation regarding supervision and sanctions in this regulation has also clearly stipulated time limits for the implementation of obligations, so that it will be easier for the Governor to supervise and provide sanctions in the event of a violation. Keywords: Legal Certainty, Smallholders, Oil Palm Plantations.

MONOPOLY POTENTIAL IN PALM OIL FRESH FRUIT LOANS (FFB) SALE AGREEMENTS INDRAGIRI HULU DISTRICT

The problem is how is the monopoly potential in the sale and purchase agreement of coconut fresh fruit bunches (TBS) and how are efforts to overcome the monopoly potential in the sale and purchase agreement of oil palm fresh fruit bunches (FFB) in Batang Cenaku district. The research method is sociological law, with the research location namely Batu Papan Village, Batang Cenaku District, Kab. Indra Giri Hulu (Inhu). The aim of the study was to analyze the monopoly potential in the sale and purchase agreement of oil palm fresh fruit bunches (FFB) and efforts to overcome the monopoly potential in the sale and purchase agreement of oil palm fresh fruit bunches (FFB) in Batu Papan, Batang Cenaku District, Kab. Indra Giri Hulu (Inhu)The results of the research show that there is a potential for monopoly in the sale and purchase agreement of oil palm fresh fruit bunches (FFB) in Batang Cenaku sub-district, where delivery order (DO) holders are unable to compete with single DO holders as sales suppliers to PT Kharisma Agro Lestar (PT KAS) and PT KAS does not make farmers as partners and farmers' recommendations as a condition for establishing a company are obtained by engineering. Efforts to overcome the monopoly potential in the sale and purchase agreement for Fresh Fruit Bunches (FFB) at PT KAS are the issuance of Governor of Riau Regulations regarding partner arrangements and regulation of palm prices, Issuance of seed certification so that results can be competitive, creating an online information system in implementing palm oil purchases and maximizing institutional functions -institutions to further maximize the synergy of oil palm smallholders.

Application of Boiler Fly Ash for Oil Palm Kernel Separation in Claybath

The burning of shells and fiber as boiler fuel in palm oil mills produces waste in the form of ash which is not utilized and managed optimally, resulting in environmental damage. Based on the chemical compounds contained in fly ash, its abundant availability, its cheap price and easy-to-obtain, fly ash can be used as a cheap raw material in claybaths as a substitute for clay and calcium carbonate. This study aims to determine the effective weight of boiler ash in reducing kernel and shell production losses at the kernel processing station. This study used variations in the weight of boiler fly ash, namely 3000 g, 3500 g, 4000 g, 4500 g, and 5000 g which were tested first in the laboratory. The application of boiler ash variations that were close to the norm was tested directly in the claybath. The best weight parameter for using fly ash is found in the weight variation of B5 (5000 g) with a loss of production in the sample of 3.98% or 0.159% of the oil palm fresh fruit bunches. At the time of application, boiler fly ash should be mixed with water at a ratio of 1:2 (fly ash to water) to result the best effect. Key words : Boilers, Clay bath, Fly Ash, Kernel, Shell

Comparative Study of Carotenoids Content in Ripe and Unripe Oil Palm Fresh Fruit Bunches

Currently Elaies Guineensisor oil palm is the most widely planted commodity crop in Malaysiaand hasa very large impact to the country’s economy. At the same time, the industry also produces huge amount of oil palm waste materials such as Unripe FreshFruit Bunche (FFB).Each year million tons of Unripe FFB could not be processed in the mill and were disposed-off and thus posed additional threats to the environment. The objective of this study was to recycle the oil from Unripe FFB and comparedthe carotenoids content with the Ripe FFB. Carotenoids isthe natural chemical compounds which givespalm oil its orange red color. The compound is good for human health as it can strengthen body immunity system and act as antioxidantThe experiment was conductedby collecting fruits from three (3) samples of Ripe FFB and Unripe FFB. The selected fruits were then sterilized, and Crude Palm Oil (CPO) was extracted. The analysis of oil samples was conducted using Near Infrared Spectroscopy Diode Array (NIRS DA) 1650. Result for the carotenoids showed that mean for the Ripe FFB was 968.07 ppm and for the Unripe FFB was927.37 ppm. The Free Fatty Acids (FFA) were 22.08 and 14.47respectively which indicated that the fruits were badly bruised during the processing. This study showed that the carotenoids contentin Unripe FFB is comparable with the Ripe FFB and thus it canbe concluded that Crude Palm Oil (CPO) from Unripe FFB can be used for carotenoids extraction instead of rejected or disposed-off to the environment.

Workload analysis on the operation of a type II pivot trailer on a hand tractor using tire wheels in oil palm plantations

In general, several oil palm fields in Indonesia have different slopes, so that the path on the land is difficult for farmers to pass in the process of transporting palm fresh fruit bunches (FFB). The slope of the land and the difficult path causes a lot of workload incurred by farmers. The pivot II type trailer which is the development of the pivot type trailer is expected to reduce the workload of farmers in transporting the oil palm FFB. The purpose of the study was to analyze the operator’s workload on the operation of a pivot II type trailer using a hand tractor using tires as a drive in oil palm plantations. Analysis of workload when operating a pivot II trailer using the heart rate method on three subjects with various variations in trajectories, turns and trailer loads. The results of this study indicate that the qualitative workload level of operators O1, O2, and O3 in operating a pivot type II trailer on oil palm land, both on flat land, sloping land 10° and sloping land 30° has a workload level of “Light” category. Meanwhile, the operators’ quantitative total energy cost (TEC)’ workload levels for slope 0°, 10°, and 30°, respectively, are 1.31, 1.48, and 1.67 kcal/kg.hour. The operator’s workload level on the pivot II type trailer is better when compared to the initial pivot type trailer before modification.

Menyalurkan Informasi dan Meninjau Gangguan Produktivitas TBS Kebun Sawit Penduduk di Desa Saliki (Kecamatan Muara Badak, Kabupaten Kutai Kartanegara)

The productivity of fresh fruit bunches (FFB) of independent plasma plantations owned by residents of Saliki Village, located in Muara Badak District (Kutai Kartanegara), is only around 1 ton/ha/month. This gain is much smaller than the productivity level of the oil palm plantations managed by the company. In the last two years, the increase in FFB prices has spurred farmers to increase the productivity of their oil palm plantations by investigating the decline in the productivity of their plantations with other more competent parties. The soil analysis findings showed that the macronutrient content of N and K2O was low, and it classified P2O5 as low, a limiting factor for productivity. Early fertilization until 6-8 years is dominant, with compound fertilizer (15N:15P:15K) as the key attribute that implies a non-compliance with the recommended dose. When the age of planting increases, but there is an imbalance of nutrients, it will affect low productivity. The lack of understanding and knowledge of farmers causes this assumption about nutrient content and the use of fertilizers. The implementation method is supported through a comprehensive technical guidance with oil palm FFB farmers in the selected area within 2 sessions. After the field meeting, the researcher recommended the relevant dose of fertilization (kg/tree/year). Through this discussion, the researchers disseminated valuable insights to oil palm farmers in order to stimulate, strengthen references, and identify types of fertilizers that are in line with the nutrients and content in the palm oil fertilization phase in order to improve FFB productivity.

Object Detection Algorithms for Ripeness Classification of Oil Palm Fresh Fruit Bunch

Ripe oil palm fresh fruit bunch allows extraction of high-quality crude palm oil and kernel palm oil. As the fruit ripens, its surface color changes from black (unripe) or dark purple (unripe) to dark red (ripe). Thus, the surface color of the oil

Deteksi Tingkat Kematangan Tandan Buah Segar Kelapa Sawit dengan Algoritme K-Means

Oil extraction rate (OER) of fresh fruit bunches (FFB) of palm oil is depend on the stage of ripeness. The process of detecting the ripeness of oil palm FFB has difficult by manually. Farmers find it difficult to reach the fruit to detect ripeness with the eye, when the palm tree is tall. So farmers need a system that is able to detect the maturity level of oil palm FFB based on color. The K-Means method is capable of clustering based on the closest mean value to the centroid from a number of objects to cluster k. Data obtained from 2 oil palm plantations in East and North Kalimantan. In this study, the clustering of fresh fruit bunches of oil palm has four levels of maturity based on the calculation of the elbow method. The training data used in this study is 80 data. The test image data used in this study is 40 data. There are 36 appropriate data based on the classification method so the accuracy obtained in grouping using the k-means clustering segmentation method is 90%.

Classification of Oil Palm Fresh Fruit Bunches Based on Their Maturity Using Thermal Imaging Technique

The maturity of oil palm Fresh Fruit Bunches (FFB) is considered to be a significant factor that affects the profitability and salability of palm oil FFB. Typical methods of grading FFB consist of physical grading of fresh fruit, which is time-consuming and expensive, and the results are prone to human error. Therefore, this research attempts to formulate a thermal imaging method to indicate the precise maturity of oil palm fruits. A total of 297 oil palm FFBs were collected. The samples were divided into three groups: under-ripe, ripe, and over-ripe. Afterward, all the samples were scanned using a thermal imaging camera to calculate the real temperature of each sample. In order to normalize the measurement, the difference between the average temperature of the palm bunch and the ambient temperature (∆Temp) was considered as the main parameter. The results indicated that the mean ∆Temp of oil palm FFBs decreased consistently from under-ripe to over-ripe. The results of the ANOVA test demonstrated that the observed significance value was less than 0.05 in terms of ∆Temp, so there is a statistically significant difference in the means of all three maturity categories. It can be concluded that ∆Temp is a reliable index to classify the FFBs of oil palm. The classification analysis was conducted using the ∆Temp of the FFBs and its application as an index in Linear Discriminant Analysis (LDA), Mahalanobis Discriminant Analysis (MDA), Artificial Neural Network (ANN), and Kernel Nearest Neighbor (KNN). The highest degrees of overall accuracy (99.1% and 92.5%) were obtained through the ANN method. This study concludes that thermal images can be used as an index of oil palm maturity classification.

Correlation Study between the Organic Compounds and Ripening Stages of Oil Palm Fruitlets Based on the Raman Spectra.

The degree of maturity of oil palm fresh fruit bunches (FFB) at the time of harvest heavily affects oil production, which is expressed in the oil extraction rate (OER). Oil palm harvests must be harvested at their optimum maturity to maximize oil yield if a rapid, non-intrusive, and accurate method is available to determine their level of maturity. This study demonstrates the potential of implementing Raman spectroscopy for determining the maturity of oil palm fruitlets. A ripeness classification algorithm has been developed utilizing machine learning by classifying the components of organic compounds such as β-carotene, amino acid, etc. as parameters to distinguish the ripeness of fruits. In this study, 47 oil palm fruitlets spectra from three different ripeness levels—under ripe, ripe, and over ripe—were examined. To classify the oil palm fruitlets into three maturity categories, the extracted features were put to the test using 31 machine learning models. It was discovered that the Medium, Weighted KNN, and Trilayered Neural Network classifier has a maximum overall accuracy of 90.9% by using four significant features extracted from the peaks as the predictors. To conclude, the Raman spectroscopy method may offer a precise and efficient means to evaluate the maturity level of oil palm fruitlets.

Palm oil plantation transportation management improving using economic information systems and Qm-Windows

Limited information, mainly based on real economy as a tool for determining transportation infrastructure location, is one of the obstacles faced by oil palm plantation companies. This study aims to develop a management information system for transporting the Transportation of Fresh Fruit Bunches (FFB) in oil palm plantations with considering the economic analysis by combination of GIS and Qm-Windows. This research uses the descriptive method. The study was conducted at one of the oil palm plantations in Central Kalimantan. Data were analyzed using the post-classification change detection (PCCD) method and estimated costs using the transportation method with the Qm-Windows program’s help. The results showed that the GIS with Arcgis 10.1 application could compile an inventory information system for oil palm plantation transportation. Cost estimation based on the Qm-Windows application can be used to determine the priority of transportation selection estimation with minimum cost. These applications can be applied as reference considerations for policymaking in managing oil palm FFB transportation management.

ANALISIS PENGARUH SUHU TERHADAP SENSITIVITAS SENSOR PADA HIDUNG ELEKTRONIK UNTUK KEMATANGAN BUAH KELAPA SAWIT

Electronic noses have been developed for decades in many fields. Recently, electronic nose has been used in agriculture to detect the ripeness of fruits because fruits also produce volatile gas during ripening. Oil palm fresh fruit bunches (FFB) is the main source of crude palm oil, its quality depends on the ripeness levels of oil palm FFB. Therefore, electronic detections of oil palm FFB ripeness need to be developed. This study was aimed to investigate the effect of temperature variation on the sensitivity of gas sensors in an electronic nose designed for detecting the ripeness of oil palm FFB. The electronic nose used in this study consisted of 4 sensors which were TGS 2611, TGS 2620, TGS 813 and TGS 822. Samples were peeled fruitlets of ripe oil palm FFB which were heated to temperatures of 30°C, 45°C, and 60°C. Response of each sensor was represented as a trapezoid area of voltage versus time for convenience. The results showed that there was a significant difference in the output voltage of each sensor when the sample temperatures were varied. Fruitlets of oil palm FFB heated at 60°C resulted in higher trapezoid area which mean more volatile gas released. Based on the resulted trapezoid area for each sensor. Sensors of TGS 2611 and TGS 822 are the most sensitive which have higher trapezoid area for the variation of the temperatures.

Marketing Channel Analysis of Oil Palm Fresh Fruit Bunches in Lubuk Barumun District, Padang Lawas Regency

The purpose of the research is to find out marketing channel analysis of oil palm fresh fruit bunches in Lubuk Barumun District, Padang Lawas Regency. The research was conducted in Lubuk Barumun District in Padang Lawas Regency, North Sumatra Province with the consideration that Padang Lawas Regency has potential in developing oil palm plantation areas. The research was carried out from January to February 2021. The sample collection of producer farmers was carried out by purposive sampling with the sample criteria being independent oil palm farmers. From the population of oil palm farmers in Padang Lawas Regency as many as 297 people, a sample of 10 percent was taken, namely 30 farmer respondents. Quantitative analysis is used to determine the Hirschman Herfindahl index on market structure, market behavior based on the price relationship between two markets at the same level and the magnitude of market performance based on marketing margin analysis, profit margin ratio, farmer's share, cost share, and profit share. The results showed that, the number of oil palm farmers is large while the number of sellers or intermediaries is only a few so that the marketing system for fresh fruit bunches of oil palm tends to be imperfect competition because there are many sellers but few buyers (oligopsony). Analysis of the Hirschman Herfindahl index, it is known that the market structure of oil palm fresh fruit bunches in Lubuk Barumun District, Padang Lawas Regency tends to lead to an imperfect competition market (oligopsony) which causes the bargaining position of oil palm fresh fruit bunches farmers to be in poor condition weak, namely as a price taker. The efficiency of an already efficient marketing channel is the one that shows the smallest value of marketing efficiency, namely in channel III (Ep < 5% efficient). Marketing channels I and II have not been efficient (Ep > 5% inefficient). Keywords: Marketing Channel, Oil Palm, Fresh Fruit Bunches .

Wavelength Dependence of Optical Electronic Nose for Ripeness Detection of Oil Palm Fresh Fruits

Electronic noses have been developed as an artificial sense to imitate the human nose based on volatile gases. They have been used in agriculture to monitor and predict fruit qualities such as ripeness and chemical contents. Electronic noses with semiconductor gas sensors have a limitation of volatile gases detected. Therefore, optical electronic noses using an output coupler become an alternative due to the wavelength dependency of the gas types. The ripeness of oil palm fresh fruit bunches (FFBs) is one of the main factors in determining the quality of crude palm oil. Electronic detection is preferable to substitute the manual methods for ripeness detection. This study built an optical electronic nose and analyzed the wavelength dependence on the detection performance. The electronic nose consisted of an infrared LED and a photodiode enclosed in a chamber, a microcontroller, and a sample chamber. We tested four infrared LEDs with 760, 780, 840, and 910 nm wavelengths. The samples were fruitlets taken from oil palm FFBs, previously categorized as unripe, ripe, and overripe. The fruits were grounded, inserted into the sample chamber, and preheated to increase the volatile gas concentration. Trapezoid areas represented the time-varying output voltages for each LED. The results showed that overripe fruits had slightly higher trapezoid areas. LED of 840 nm wavelength obtained higher trapezoid areas. LED of 780 nm was the best candidate for the electronic nose due to linearity in increasing trapezoid areas. The results showed the potential of the optical electronic nose for oil palm fruits.

Wavelength selection of multispectral imaging for oil palm fresh fruit ripeness classification.

Multispectral imaging has been recently proposed for high-speed sorting and grading machine vision of fruits. It is a prospective method applied in yet traditional sorting and grading of oil palm fresh fruit bunches (FFB). The ripeness of oil palm FFBs determines the quality of crude palm oil (CPO). Implementation of multispectral imaging for the task needs wavelength selection from hyperspectral datasets. This study aimed to obtain the optimum wavelengths and use them for oil palm FFB classification based on three ripeness levels. We have selected eight optimum wavelengths using principal component analysis (PCA) regression which represented the ripeness levels.

POTENSI PAJAK PENGHASILAN PEDAGANG PENGUMPUL TANDAN BUAH SEGAR (TBS) KELAPA SAWIT (STUDI DI KPP ABC)

Palm oil collector traders are entities or individuals whose business activities are collecting oil palm plantation products in the form of oil palm fresh fruit bunches (FFB) and selling them to industrial business entities or exporters engaged in the plantation sector. The purpose of the study was to determine the potential income tax, the steps that have been taken and the obstacles, the realization of tax revenue for the collectors of Fresh Fruit Bunches (FFB) of oil palm at the Tax Service Office (KPP) ABC. The research method used is descriptive qualitative. The results of the study show that the potential taxes of palm oil collectors are PPh Article 21, PPh Article 22, PPh Article 23, PPh Article 25/29, Final PPh Article 4 paragraph (2) including the MSME taxation provisions. Steps that have been taken are socialization and appeals to taxpayers. The obstacles are geography, human resources, and awareness of taxpayers. Meanwhile, the realization of tax revenue is quite good and shows an increase, especially in Article 22 Income Tax.

Oil Palm Fruit Ripeness Detection using Deep Learning

To detect the maturity level of oil palm Fresh Fruit Bunches (FFB) generally seen from the loose fruit that fell to the ground. This method is always used when harvesting swit coconuts. Even though this method is not always valid, because many factors cause the fruit to fall from the bunch. The manual harvesting process can result in the quality of palm oil being not optimal. For this reason, technology is needed that can ensure the maturity level of oil palm FFB. This study aims to detect the maturity of oil palm FFB based on digital images by applying a deep learning algorithm so that the maturity level can be classified into three categories, namely: raw, ripe, and rotten. The deep learning algorithm was chosen because there have been many studies that have proven its high level of accuracy. This research method starts from; preparation of data, designing architectural models and convolutional neural network parameters, testing models, testing images, and analyzing results. From the results of the study, it was found that the convolutional neural network algorithm can be applied to detect the maturity level of oil palm FFB with an accuracy value of 92% for test data, and 76% for model testing.