Palm Production Research Articles

Sustainability status of water management in oil palm plantations in peatlands: a case study in Koto Gasib District, Siak Regency, Riau Province

The purpose of this study was to evaluate the sustainability status of water management of oil palm plantations on peatlands and provide recommendations for water management. This research was conducted in Teluk Rimba Village, Koto Gasib District, Siak Regency, Riau Province. The sustainability analysis used was Multidimensional Scaling (MDS). The sustainability status category in this study is based on four basic scales (0-100); 24.9 (poor); 25-49.9 (less); 50-74.9 (enough); and > 75 (good), then a leverage analysis is performed to assess sensitive attributes. The results showed that water management in Koto Gasib District is in a very sustainable status with a value of 84.17. In the environmental dimension, land fertility is the most important aspect of oil palm productivity. In the economic dimension, farming capital and access to marketing are sensitive attributes. The social dimension has the most sensitive attributes. The technology dimension has two sensitive attributes, namely information and the introduction of water management technology as well as oil palm cultivation. The recommendations given are implementing a partnership in water management between private oil palm plantations and smallholder plantations.

Produksi Kelapa Sawit Provinsi Kalimantan Barat dan Faktor-Faktor yang Mempengaruhinya

The palm oil processing industry is one that is believed to be able to help the Indonesian state in increasing per capita income, providing employment, reducing poverty, and as a foreign exchange income. When compared to other vegetable oils like coconut, soybean, or flower oil, palm oil offers advantages sun. This study's goal was to examine the factors impacting the province of West Kalimantan's palm oil production yield between 2015 to 2021. This research uses a scientific techniques and a type of quantitative descriptive research. Secondary sources of data were used in this research. This research's data was obtained between the years of 2015 and 2021 from the websites of the West Kalimantan Province Agricultural Department and the BPS (Central Statistics Administration). In this study, regression with panel data analysis was the analytical technique. The independent factors in this study are land area, labor, and rainfall, while the dependent variable is palm oil production. The outcomes obtained from the panel data regression analysis are land area has a positive effect on oil palm production and rainfall has a positive effect on oil palm production. Meanwhile, labor does not affect palm oil production.

Factors Affecting Oil Palm Productivity in Surat Thani Province

This project is a study of factors affecting oil palm productivity in Surat Thani Province. The objectives were to study the relationship between factors including oil palm prices in Surat Thani Province, the average number of hours of sunshine in Surat Thani, average temperatures in Surat Thani Province, the relative humidity in Surat Thani Province, and oil palm productivity in Surat Thani Province, as well as the factors affecting oil palm productivity in Surat Thani Province. Collected secondary data for the study from January 2016 to December 2020, a total of 60 months, and used multiple regression analysis.The results showed that four independent variables related to oil palm productivity in Surat Thani province were oil palm prices , the average number of hours of sunshine , average temperatures , and relative humidity . That is, the average number of hours of sunshine and average temperatures were in a positive direction, affecting oil palm productivity in Surat Thani Province, which increased with statistical significance at the 0.05 level, The oil palm prices and relative humidity were in a negative direction, affecting oil palm productivity in Surat Thani Province, which decreased with statistical significance at the 0.05 level and has the following form of the multiple regression equation:

An Economics Analysis of Oil Palm Cultivation in East Godavari District of Andhra Pradesh, India

An attempt has been made in this study to examine the economic analysis of oil palm cultivation in East Godavari district of Andhra Pradesh. The specific objective of the study were (i) to identify socio economic profile of the farmers/respondents in different size of farm in study area, (ii) to study cost and return and input output ratio of different size farm group in study area, (iii) to estimate disposal pattern and marketable surplus of oil palm in different size of farm groups, (iv) to work out price spread producers’ share in consumers’ rupee and marketing efficiency in different marketing channels and (v) to find out different problems in production and marketing of oil palm in different size of farm group in study area. The present study was conducted in East Godavari district of Andhra Pradesh. The primary data is collected from the oil palm producers through personal interview method with the help of well-prepared schedule and questionnaire for the production and marketing year 2022-23. The growth rate of area, production and productivity of East Godavari district was worked out by using exponential analysis. The simple mean and average method was used to work out the cost of cultivation, marketable surplus and disposal pattern of oil palm.

Morphological, Physicochemical, and Molecular Evaluation of Twenty-Three Date Palm Males Growing in Aswan Governorate

An essential element of date palm production is the pollen source. The present study was conducted during two successive seasons of 2020 and 2021 to evaluate some males of Aswan date palm. Herein, morphological, physicochemical, and molecular characteristics of 23 date palm males were evaluated to determine the most superior and promising males for pollinating the female ‘Bartamoda’ cultivar. It is obvious that ‘Male No. 22’, recorded almost the highest value for morphological characteristics, pollen viability, crude protein, total amino acids, and mineral content. In contrast, ‘Male No. 5’, showed the lowest content of crude protein, total amino acids, and mineral content compared to the other males that were grown in the rest of the locations in Aswan government. All ISSR primers were highly polymorphic, with a value of 100%, highlighting the necessity of employing such primers when investigating date palm diversification. Two unique bands were among the 43 total bands that were produced. The genetic coefficients with a mean of 61.5% and the first two primary axes were able to explain roughly 52.30% of the genetic variance across the genotypes of date palms. Those results suggested that all genotypes tested are efficient for the fertilization of ‘Bartamoda’ inflorescences and can be used as pollinizer in commercial orchards of this cultivar.

Oil palm boom: its socioeconomic use and abuse

Oil palm cultivation has experienced explosive expansion in recent decades. Although the oil palm boom has serious environmental and socioeconomic consequences, only environmental issues have garnered attention in public discussion and synthesis studies. In this study, we synthesize the literature on the socioeconomic impacts of oil palm expansion across various observation units and spatial and temporal scales, which is of significant relevance to policymakers, researchers, and the wider public. Our review demonstrates that oil palm expansion is a double-edged sword. On the one hand, it has significantly helped both producing and non-producing countries’ economies by facilitating the (re)export of crude palm oil and its byproducts and by creating employment opportunities. This has stimulated rural economies, led to rural poverty reduction, and improved food security and diets for rural households in producer countries. On the other hand, it has increased conflicts and tension between local communities and agro-industrial companies, worsened workers’ conditions, and widened domestic economic inequality between producing and non-producing areas within a given producer country. Monetary quantification of the costs of oil palm’s negative environmental and social impacts indicates that the loss of ecosystem services and social services far outweighs the benefits derived from the increased production of oil palm. The direct income benefits through harvest sales and employment are more evident in the Southeast Asia production frontier, where oil palm cultivation and marketing are relatively advanced and well-integrated into global value chains. The negative outcomes are observed in all oil palm production regions, with more negative effects on food security in the African production frontiers. We propose multiple actionable research and policy recommendations that may jointly lead to inclusive and sustainable socioeconomic (and environmental) outcomes in oil palm cultivation. The socioeconomic consequences of oil palm expansion at the global level, in the African and American production frontiers, and the role of gender in oil palm production systems remain understudied. Hence, studies should be conducted.

Typology of Irrigation Technology Adopters in Oil Palm Production: A Categorical Principal Components and Fuzzy Logic Approach

Oil palm is the second most cultivated oilseed crop in the world after soybeans, with more than 23 million hectares cultivated worldwide; it has become crucial for the economy of many countries. In Colombia, it is one of the most developed agricultural sectors, and every year the sector promotes the development of technologies that lead to greater sustainability of agricultural and food systems and address the challenges and opportunities of agribusiness. In this research, the central focus was the adoption of irrigation technologies, which is limited despite significant efforts and investments in physical and human capital. On many occasions, the typology of farmers has been associated with low technology implementation. Thus, linking the typology of farmers according to certain commonalities or differences is an essential step in exploring the factors that explain the adoption. In addition, the ranking also helps in the understanding of existing adoption constraints, as well as finding opportunities for change. This study aimed to determine the socioeconomic and demographic typology of those who adopt irrigation technologies. The analysis was performed using categorical principal component analysis to reduce dimensionality and fuzzy cluster analysis to classify the groups. As a result, four groups of producers that differ in terms of their demographic and socioeconomic characteristics were obtained, where the groups “population with female leadership” and “diversified population” were the adopters of irrigation technologies. The most outstanding characteristics of these two groups were the profitability of the harvest and the age of the producers. Determining the typology of farmers is a fundamental step in expanding the technology adoption process through agricultural extension services, which represent a way of reaching producers directly. In addition, these results allow decision makers to participate in this dynamic reflectively and intentionally (such as governments, researchers, and technology transferors).

Pengaruh pemberian kalsium terhadap perubahan karakter anatomi pelepah bibit kelapa sawit tercekam kekeringan

One of the environmental limiting factors on the growth and productivity of oil palm is drought stress. Various studies have shown that besides inhibiting the oil palm’s physiological and biochemical processes, severe drought stress also causes morphological changes in the form of oil palm frond fractures. However, research related to calcium’s role in increasing the oil palm seedling’s resistance exposed to drought stress is still limited. This research was conducted to determine the calcium effect and drought stress on the frond anatomical character changes of oil palm seedlings. The study was conducted using a complete randomized block design consisting of two treatments with three replications. The first treatment is drought stress level: field capacity, moderate, and severe drought stress. The second treatment is calcium dose: 0, 50, 100, and 150%. The results showed that drought stress at moderate and severe levels decreased the length and width of epidermal, hypodermis thickness, phloem, and xylem diameter of oil palm frond seedlings. Supplying Ca at 0.08 g increased the cohesiveness and structural strength of frond tissue by increasing the length and width of epidermal tissue and phloem diameter.

Denoising of Hyperspectral Signal from Drone for Ganoderma Disease Detection in Oil Palm

Oil palm is an important crop that generates high income to Malaysia. However, the oil palm is susceptible to Ganoderma infection that reduces the productivity of the oil palm. Conventional ground-based disease detection is laborious and costly. Therefore, airborne remote sensing technology coupled with ground detection provides a more effective control of the disease. Airborne hyperspectral remote sensing utilizes narrow and contiguous bands to assist in detection of diseases in crops. Spectral responses recorded by the camera tend to suffer from interference and these noises could reduce the quality of the data. Therefore, this study presents the application of Savitzky-Golay and wavelet spectral denoising technique to improve the hyperspectral signatures for Ganoderma disease detection in oil palm

Maximizing the oil palm production in coastal area of Sindh, Pakistan: A perfect blend of synthetic fertilizers and organic manure for post-nursery stage of oil palm

Maximizing the oil palm production in coastal area of Sindh, Pakistan: A perfect blend of synthetic fertilizers and organic manure for post-nursery stage of oil palm

A Study of the Effect of Some Natural and Human Factors on Date Palm Cultivation in the Hilla District, Iraq

The current study aimed to study some of the natural and human factors that affect date palm cultivation in the south of Babil Governorate, as the natural factors included the surface, climate, water and soil, and the human factors included labor force, capital, market, fertilization, transportation and marketing. The study includes several areas in the south of Babil Governorate, such as (Al-Hashimiyyah district, Al-Qasim district, Al-Tali’a district, as well as Al-Hamza Al-Gharbi district and Al-Shomali district) as all these areas contain palm trees. The rate of rainfall and wind speed in the study area were based on previously published information. It showed The results of the study indicate the impact of natural and life factors clearly on the decline in the productivity of palm trees through the problem of soil salinity. Also, human factors have the greatest impact on the decline in palm productivity through its role in providing water requirements for palm trees, the lack of number of workers in the agricultural sector and the neglect of farmers, and Thus, the productivity of palm trees is deteriorating in quantity and quality.

Agronomy explains large yield gaps in smallholder oil palm fields

Palm oil production is a major source of income for millions of smallholders in Indonesia. However, actual yield remains low in relation to the attainable yield. While emphasis has been given to planting material as a factor explaining low yield in smallholder fields, the role of agronomic management has received less attention. We assessed the role of agronomic management in explaining low oil palm productivity in independent smallholder fields in Indonesia. We quantified yield gaps and their causes using data on fresh fruit bunch (FFB) yield and management practices collected over two years across 977 fields. The yield gap was estimated for each field as the difference between actual and attainable yield. The latter was estimated using a crop model, local weather and field-specific soil and palm age. Statistical techniques were used to identify factors explaining yield gaps. Average yield represented 42% of the attainable yield, with largest yield gaps occurring in young plantations. Our analyses identified agronomic practices explaining yield gaps, including nutrient management, harvest interval, weed control, and pruning. Improved agronomic management can help smallholders increase yield and profit on existing plantations. There is an opportunity to produce more palm oil on current plantation area via better agronomy, generating a positive economic impact at local to national levels, while reducing pressure to clear new land for cultivation. Research & extension programs should be re-oriented to give more emphasis to agronomic management.

An economic study of date palm production in Aswan governorate

An economic study of date palm production in Aswan governorate

Bagaimana Harga Komoditas Unggulan dan Volume Ekspor Sumatera Selatan sebelum dan saat Pandemi Covid - 19

This research is not only aimed at analyzing whether there are significant differences in the price levels of world rubber and palm oil commodities, and the value of exports in South Sumatra. But also, to find out how the influence of world rubber and palm prices on export levels in South Sumatra. The data in this study are monthly data on world rubber prices, world palm prices, and South Sumatra's export values before the pandemic (January 2018 - February 2020) and data on world rubber prices, world palm prices, and South Sumatra's export values during the pandemic (March 2020 – April 2022). Data analysis techniques in this study used SPSS and Eviews. This study uses SPSS in conducting an independent sample t-test to find out differences in world rubber prices, world palm prices, and South Sumatra's export values before and during the pandemic. Meanwhile, to find out whether there is an effect of world rubber prices and world palm prices on export levels in South Sumatra, a multiple regression test was carried out using Eviews. The results of this study indicate that there are differences in world rubber prices, world palm prices, and South Sumatra's export levels before and during the Covid-19 outbreak. Based on the results of the regression test, world rubber prices have an effect on export levels in South Sumatra, while world palm prices have no significant effect on export levels in South Sumatra. However, world rubber prices and world palm prices simultaneously affect the level of exports in South Sumatra. The government is expected to be able to support the development of downstream rubber and palm oil processing industries in order to increase the added value of rubber and palm products, increase production of rubber and palm oil, and export activities.

Projecting global oil palm expansion under zero-deforestation commitments: Direct and indirect land use change impacts

In the last three decades, global production of oil palm has boomed, which has partly come at the expense of tropical rainforests. Recognizing this, many companies operating in the palm oil industry have committed to eliminate deforestation from their operations, often referred to as zero-deforestation commitments (ZDCs). Here, we estimate that if ZDCs are fully adopted and enforced across all sectors and geographies, the global extent of oil palm plantations may be 11M ha or 40% smaller in 2030 than in a business-as-usual (BAU) scenario that assumes no compliance with ZDCs. As a result of such land-sparing effects, we estimate that 96M ha of forests are saved from conversion, of which, 17% would otherwise have been converted (directly or indirectly) due to expanding oil palm plantations. Overall, these figures suggest that ZDCs have the potential to deliver major environmental benefits if they are fully adopted and enforced.

Elucidating the Mesocarp Drupe Transcriptome of Açai (Euterpe oleracea Mart.): An Amazonian Tree Palm Producer of Bioactive Compounds.

Euterpe oleracea palm, endemic to the Amazon region, is well known for açai, a fruit violet beverage with nutritional and medicinal properties. During E. oleracea fruit ripening, anthocyanin accumulation is not related to sugar production, contrarily to grape and blueberry. Ripened fruits have a high content of anthocyanins, isoprenoids, fibers, and proteins, and are poor in sugars. E. oleracea is proposed as a new genetic model for metabolism partitioning in the fruit. Approximately 255 million single-end-oriented reads were generated on an Ion Proton NGS platform combining fruit cDNA libraries at four ripening stages. The de novo transcriptome assembly was tested using six assemblers and 46 different combinations of parameters, a pre-processing and a post-processing step. The multiple k-mer approach with TransABySS as an assembler and Evidential Gene as a post-processer have shown the best results, with an N50 of 959 bp, a read coverage mean of 70x, a BUSCO complete sequence recovery of 36% and an RBMT of 61%. The fruit transcriptome dataset included 22,486 transcripts representing 18 Mbp, of which a proportion of 87% had significant homology with other plant sequences. Approximately 904 new EST-SSRs were described, and were common and transferable to Phoenix dactylifera and Elaeis guineensis, two other palm trees. The global GO classification of transcripts showed similar categories to that in P. dactylifera and E. guineensis fruit transcriptomes. For an accurate annotation and functional description of metabolism genes, a bioinformatic pipeline was developed to precisely identify orthologs, such as one-to-one orthologs between species, and to infer multigenic family evolution. The phylogenetic inference confirmed an occurrence of duplication events in the Arecaceae lineage and the presence of orphan genes in E. oleracea. Anthocyanin and tocopherol pathways were annotated entirely. Interestingly, the anthocyanin pathway showed a high number of paralogs, similar to in grape, whereas the tocopherol pathway exhibited a low and conserved gene number and the prediction of several splicing forms. The release of this exhaustively annotated molecular dataset of E. oleracea constitutes a valuable tool for further studies in metabolism partitioning and opens new great perspectives to study fruit physiology with açai as a model.

Behavioural Impacts of Workers on Performance: The Case of Malaysian Oil Palm Plantation

Malaysia is the second world’s largest oil palm producer after Indonesia, accounting for about 30% of the total producers. The palm oil industry also contributed significantly to the Malaysian economy as the highest contributor to the national gross domestic product (GDP) for the agriculture sector. As a huge industry in Malaysia, the palm oil industry relies heavily on workers because of the manual activities that require them to execute, like harvesting and collecting fresh fruit bunches (FFB). At the plantation level, dealing with a group of workers can be challenging owing to various issues related to workers’ behaviour such as workers’ efficacy, initiative, motivation, dependability, and cooperativeness. Recognising workers’ behaviour is vital because it will impact how well the plantation performs. Thus, this study aimed to examine the impacts of workers’ behaviour on Malaysian oil palm plantation performance. A structured questionnaire was used during in-depth interviews with 83 Malaysian oil palm plantation executive staff using simple random sampling method. The data were analysed using descriptive analysis, mean ranking analysis, and multiple regression analysis. The results revealed that workers’ efficacy, initiative, motivation, dependability, and cooperativeness significantly impact the performance of Malaysian oil palm plantations. From all five variables, motivation was the most significant predictor identified as the highest contributing factor that impacted the Malaysian oil palm plantation’s performance. The findings showed an important indication that the plantations need to acknowledge and handle their workers’ behaviour to achieve greater performance. The framework of this research can be extended to the oil palm smallholders to capture the overall scenario of the palm oil industry players and their contribution to the Malaysian economy.

Morphological abnormalities in tissue culture-derived date palms (Phoenix dactylifera L.) in Qatar

Recently, the tissue culture (T.C.) propagation has played a major role in the massive expansion of date palm (Phoenix dactylifera L.) plantations by making available a large number of cloned plants. Nevertheless, even if the in vitro propagation is an effective and a rapid way of date palm production, it has been associated with the emergence of some growth problems. Morphological abnormalities have been observed in tissue culture- derived date palm. Dwarfism is the most common abnormality recorded in the Qatari dates plantations. Plants produced by tissue culture in “Nemishi” and “Lulu” are the most sensitive varieties to this problem. Moreover, the phenomenon of pollination failure locally known as “sheiss” was observed with the varieties Khalass and Kheneisi. These off type phenotypes appear in the plants maturity stage and are commonly detected in the field years after planting. Therefore, the detection of these abnormalities, at an early stage, should be performed. Since the genetic variation altered DNA methylation and gene expression are associated with these abnormal phenotypes, the molecular identification is inevitably the solution.

Analyzing the greenhouse gas emissions in the palm oil supply chain in the VUCA world: A blockchain initiative

AbstractAs the world is becoming more VUCA for business operations, organizations are leveraging the competitive advantage through their supply chain practices. The food supply chain is no exception. Being competitive has become imperative in terms of sustainability and accountability of the business process. Therefore, organizations are adopting blockchain to track and trace the information flow to ensure a better business process. Further, to ensure sustainability, analyzing greenhouse gas (GHG) emissions aids firms in achieving a reasonable improvement in the food supply chain. So, the present study collects carbon emissions data for palm oil production. The study evaluates palm oil production in the Sumatra region, Indonesia (Cradle to Port), through predictive modeling. Here, the palm production process is classified as cultivation, harvesting, and shipping. Then, the study evaluates the GHG emissions from the three phases to understand the carbon footprint in palm oil production. Finally, the study uses blockchain to track and trace the GHG emissions in the palm oil supply chain using Hyperledger Fabric self‐executed smart contracts. The study has developed unique contributions in terms of developing predictive modeling, blockchain architecture, and deep learning in palm production to leverage the competitive advantage of the supply chain in the VUCA world for business excellence in the global market.

Palm bunch grading technique using a multi-input and multi-label convolutional neural network

Oil palm bunches, which are the raw materials for several oil palm products, are traded to a crude palm oil (CPO) factory or a middleman. Since high-oil-content palm bunches are desired to produce CPO, the factories and middlemen traditionally have several experts hired for grading FFBs. We have found that colour, shape and size of FFBs are three parameters that need to be considered for classification. Shape and colour data can be collected using RGB and IR sensors, while size data can be collected using IR and weight sensors. In this paper, we propose a deep learning-based model working with three sensors (RGB camera, infrared sensor, and a load cell) for classifying a palm bunch. The classifying framework of the algorithm is a multi-input and multi-label convolutional neural network. The multi-label classifies the 4 grades of FFBs (overripe, ripe, under ripe and unripe). Based on 1,575 images for 14 varieties of palm bunches collected from four trading sites, the sensors were installed, the algorithm was trained, validated, and tested with 70%, 20% and 10% of the overall datasets, respectively. The general images that are preprocessed after training model are applied and compared between original and preprocess images by Gradient-weighted Class Activation Mapping (Grad-CAM). The cross-entropy loss function was applied to investigate the probability error between the target and predicted label during the training process. Based on the testing datasets results, the proposed model achieves an accuracy of 90.26%, precision of 89.86%, recall of 89.54%, and an F1-score of 89.68%.