“Try to Make a Fresh Start”: Dahomean Politicians Rethinking Oil Palm Development in the Late Colonial Period (1957-1960)

This study aims to determine the governance of oil palm downstream development in technopolitan areas of Pelalawan Regency. This research method was carried out qualitatively by analyzing the object of study. First, the development of oil palm down streaming in technopolitan areas, second, the potential for oil palm down streaming in technopolitan areas and third, governance of oil palm downstream development in technopolitan areas. The development of downstream oil palm in technopolitan areas facilitates the development of ideas, innovations, and know-how from the utilization of oil palm derivative products that have a high selling value and downstream oil palm becomes a support for government, academia, business and the community in implementing Good Agricultural Practice (GAP). The development of governance oil palm downstream in Pelalawan Regency is implemented in an integrated, competitive and sustainable approach. The development with such governance makes it possible for every stakeholders and the community (independent farmers) to receive economic, social, and environmental benefits from the development of technopolitan areas in Pelalawan Regency.

The environmental impacts of the palm oil industry are widely recognised. Unsurprisingly, many people, including many conservation pundits, consider oil palm a major evil. What is less widely recognized is the extent to which this industry has benefited people. Oil palm development, if well-planned and managed, can provide improved incomes and employment and generate investments in services and infrastructure. These alternative viewpoints fuel a polarised debate in which oil palm is alternatively seen as a gift from god or a crime against humanity. Stepping outside this rhetorical extremism is necessary if we seek resolution and pragmatic advances. An important question is how to plan, guide and assess oil palm developments to foster the greatest benefits and least harm. Such questions are particularly relevant in a global context in which many voices call for constraining oil palm developments and boycotting palm oil, but also for adhering to sustainable development goals. What opportunities are available to people in tropical forest regions if oil palm developments are prohibited? Broader ethical questions also play out in the contexts of biofuels and food security and of competition among oil crops, especially the crops at higher latitudes (e.g., soy, maize, sunflower, rapeseed, olive), versus the tropical oils (oil palm and coconut). We here explore some of the questions of ethics related to the production and use of palm oil and other vegetable oils. The goal of this article is not to answer these contested questions but rather to highlight some of the nuances that are often omitted in current debates. Judgements will reflect perspectives with tropical producers and temperate consumers framing and assessing the issues differently. Addressing gaps in understanding on ethics of palm oil production, and avoiding double-standards, will help find a shared framework for development involving oil palm and other oil crops. A commitment to ethical consistency, where double standards are recognised and avoided, offers a potential way forward.

Studies were carried out to evaluate the effect of topography on the heavy metal levels of raphia palm tree and oil palm tree wine produced within Awka South and North local government areas using standard analytical procedures and instrumentation. Soil and palm (oil palm tree and raphia palm tree) wine samples produced in the studied upland and lowland areas were wet digested and analyzed for the presence of Pb, Cu, Cd and Zn using atomic absorption spectrophotometer.The lowland soil samples had 0.38±0.08, 6.27±0.40, 0.18±0.05 and 9.55±0.80µg/g as mean levels for Pb, Cu, Cd and Zn respectively. The upland soil samples had 0.70±0.04, 4.89±0.15, 0.06±0.02 and 7.07±0.22 µg/g as the mean levels for Pb, Cu, Cd and Zn respectively. The studied heavy metals were present in the soil sample areas in the following decreasing order; Zn > Cu >Pb >Cd.The mean range of Pb, Cu, Cd and Zn levels in the palm (oil palm tree and raphia palm tree) wine samples produced in the upland areas were 0.04- 0.06, 1.06- 1.91, 0.03- 0.05 and 2.86- 4.04 µg/g respectively. Pb was at toxic level in the oil palm tree wine samples produced in the upland areas.The mean range of Pb, Cu, Cd and Zn levels in the palm (oil palm tree and raphia palm tree) wine samples produced in the lowland areas were 0.05- 0.09, 1.95- 3.23, 0.04- 0.07 and 4.66- 6.51µg/g respectively. Pb, Cu and Cd were at toxic levels in the oil palm tree wine samples produced in the lowland areas. The palm wine samples produced in both the lowland and upland areas contained the investigated heavy metals at statistically significant levels. Because of the near daily consumption of palm wine produced from the oil palm and raphia trees as a drink of leisure by all categories of the people in the society, especially with high volume of production taking place in the lowland areas, it is important that human activities that supports the contamination of the soil with heavy metals, where these wines are produced are checkmated by government and host communities so as to limit the exposure to the heavy metals by palm wine consumers.

ABSTRACTIn the past, oil palm density has been determined by manually counting trees every year in oil palm plantations. The measurement of density provides important data related to palm productivity, fertilizer needed, weed control costs in a circle around each tree, labourers needed, and needs for other activities. Manual counting requires many workers and has potential problems related to accuracy. Remote sensing provides a potential approach for counting oil palm trees. The main objective of this study is to build a robust and user-friendly method that will allow oil palm managers to count oil palm trees using a remote sensing technique. The oil palm trees analysed in this study have different ages and densities. QuickBird imagery was applied with the six pansharpening methods and was compared with panchromatic QuickBird imagery. The black and white imagery from a false colour composite of pansharpening imagery was processed in three ways: (1) oil palm tree detection, (2) delineation of the oil palm area using the red band, and (3) counting oil palm trees and accuracy assessment. For oil palm detection, we used several filters that contained a Sobel edge detector; texture analysis co-occurrence; and dilate, erode, high-pass, and opening filters. The results of this study improved upon the accuracy of several previous research studies that had an accuracy of about 90–95%. The results in this study show (1) modified intensity-hue-saturation (IHS) resolution merge is suitable for 16-year-old oil palm trees and have rather high density with 100% accuracy; (2) colour normalized (Brovey) is suitable for 21-year-old oil palm trees and have low density with 99.5% accuracy; (3) subtractive resolution merge is suitable for 15- and 18-year-old oil palm trees and have a rather high density with 99.8% accuracy; (4) PC spectral sharpening with 99.3% accuracy is suitable for 10-year-old oil palm trees and have low density; and (5) for all study object conditions, colour normalized (Brovey) and wavelet resolution merge are two pansharpening methods that are suitable for oil palm tree extraction and counting with 98.9% and 98.4% accuracy, respectively.

Growing status observation for oil palm trees using Unmanned Aerial Vehicle (UAV) images

This study comprises a review of oil palm development and management across landscapes in the tropics. Seven countries have been selected for detailed analysis using surveys of the current literature, mainly spanning the last fifteen years. Indonesia and Malaysia are the obvious leaders in terms of area planted and levels of production and export, but also in literature generated on social and environmental challenges. In Latin America, Colombia is the dominant producer with oil palm expanding in disparate landscapes with a strong focus on palm oil-based biodiesel; and small-scale growers and companies in Peru and Brazil offer contrasting ways of inserting oil palm into the Amazon. Nigeria and Cameroon represent African nations with traditional groves and old plantations in which foreign ‘land grabs’ to establish new oil palm have recently occurred.The literature surveys have been conducted in English and complemented with literature in local languages (Indonesian, Spanish, Portuguese and French), and where possible have also included fieldwork. Four major themes are used to structure the argument and maintain a comparative approach. They are: 1) the influence of oil palm expansion in economic development and land use change, especially deforestation; 2) the role of government policies and corporate strategies in shaping oil palm development; 3) the business models commonly used, especially plantations and various types of smallholders, either assisted or independent; and 4) ongoing initiatives towards more sustainable and inclusive oil palm production. This study shows that oil palm development is heavily entrenched in local and national political economies and responses for advancing towards more sustainable oil palm have to look beyond oil palm as a sector and a commodity.

Improving conservation outcomes for coral reefs affected by future oil palm development in Papua New Guinea

Global models of biophysical suitability for oil palm consistently rank Brazil as having the greatest potential for expansion, with estimates as high as 238 Mha of suitable lands. In 2010, Brazil launched the Sustainable Palm Oil Production Program (SPOPP) to incentivize oil palm development without deforestation on as much as 30 Mha. Here we examine oil palm expansion before and after the SPOPP’s launch. In Pará, the major oil palm producing state in Brazil, we analyze the extent and change in oil palm cultivation from 2006−2014 using satellite imagery, ground-truthed verification, site-based interviews, and rural environmental (land) registration data. Between 2006−2014, oil palm area (≥9 ha) expanded >200% to ~219 000 ha. Of the ~148 000 ha of oil palm developed, ~91% converted pasturelands while ~8% replaced natural vegetation, including intact and secondary forests. Although >80% of all oil palm parcels rest <0.5 km from intact forests, direct conversion of intact forests declined from ~4% pre-SPOPP (2006−2010) to <1% post-SPOPP (2010−2014).Despite low and declining deforestation rates associated with oil palm expansion in Pará, our results also show a low area of oil palm development overall compared with reported land suitability. To explore potential contributing factors, we conducted semi-structured interviews with researchers, company representatives, and government officials involved in the sector to characterize the perceived factors influencing oil palm development and the role of agro-ecological suitability mapping among them. Interviews indicated that: (1) individual effects of suitability mapping efforts to encourage oil palm expansion on cleared areas, i.e. without deforestation, cannot be disentangled from pre-existing public and private deforestation reduction initiatives; and, (2) socio-economic constraints, e.g. high relative production costs and limited familiarity with this crop, appear to partially explain the major discrepancy between estimated potential suitable areas with realized oil palm development.

The oil palm tree, or scientifically called as Elaeis guineensis is native to West Africa, where it grows in the wild, transformed into a crop that later was introduced to Malaysian industry. The cultivation of oil palm improved rapidly under the agricultural sector causes degradation, particularly when the oil palm plantation goes uncontrolled. Tree plantation identification is very important for plantation management, environmental management, biodiversity monitoring and many other applications. Accurate inventories and monitoring oil palm estates can be a challenge and critical towards the plantation management and plant area expansion. Managing oil palm estate manually can almost be impossible, so do the tree counting. Manual field-based tree counting is time-consuming and high cost. Conventional method for tree counting can be carried out by manually marked on images or carry out field surveying using GPS to collect the positions of oil palm trees and display their position on image. Developing easier, simpler and cheaper method for tree counting is needed. The aim of this study is to analyse oil palm trees using drone-based remote sensing images. The algorithms used in this research study including Gray-Level Co-occurrence Matrix (GLCM), wavelet transform and template matching. The database of oil palm tree been developed with a total of 131 oil palm trees and 161 of non-oil palm trees have been collected. The window size of oil palm tree been analysed where 250 x 250 pixels which GLCM showed the best overall accuracy of 73.10% for both oil palm and non-oil palm. In this specific window, the oil palm crown can be covered and the result given is more accurate compared to other window sizes. The resulting analysis shows that wavelet transform algorithm gives the highest overall accuracy value which is 82.07%. The other eight statistic parameters can also used to modify the GLCM in order to observe the accuracy and identify which give the best classification accuracy. The availability and ubiquity of drone technologies with high resolution images and regular basis monitoring, new techniques in image and pattern recognition using drone-based remote sensing images let the idea of high accuracy oil palm tree detection become a reality.

Field experiment was conducted at Oil Palm Research Institute, Kusi from 2002 to 2007 to as-sess the effect of Phosphate Rock (PR) on soil nutrient dynamics, growth, development and yield of oil palm. The study was carried out on the soils of Nzema series classified as Ferric Acrisols and Typic Hapludult. The oil palm trees selected were 8 year old tenera (DXP ex OPRI). Each plot measured 17.6 m x 17.6 m and had 6 palm trees. There were four treatments arranged in randomized complete block design with four replicates. The treatments included: 1). TSP - OPRI fertilizer recommendation - 222 kg of AS + 222 kg of TSP + 296 kg of MOP/ha/yr (control); 2). PR1 - PR 715 kg + 222 kg of AS + 296 kg of MOP/ha - Yr 1. PR 358 kg + 222 kg of AS + 296 kg of MOP/ ha – Yr 2. PR 358 kg + 222 kg of AS + 296 kg of MOP/ha – Yr 3; 3). PR2 - PR 1428 kg + 222 kg of AS + 296 kg of MOP/ha applied once in every 5 years; 4). PR3 - PR 142.85 kg/ha +222 kg AS/ ha + 296 kg of MOP/ha applied twice in every 5 years. Application of treatments influenced the soil chemical properties to a varying extent. Gradual increase in soil nutrient lev-els were more pronounced in RP treatments than Triple Super Phosphate (TSP) treatment (control). Soil pH increased from extremely acidic (3.73) to acidic (5.43) for treatment PR2. At the end of the study, available P recorded 9.55 mg/kg. The value is slightly below the medium range of available P for oil palm production. Significant increases were recorded by RP treat-ments for exchangeable Ca, Mg, K and ECEC. The results showed that treatment PR2 was effec-tive and gave the highest oil palm yield of 62.8t/ha with TSP recording 53.7t/ha. For sustained levels of soil nutrients, growth, development and yield of oil palm, PR incorporation should be encouraged.Keywords: Phosphate Rock, nutrient dynamics, oil palm, triple super phosphate

Deep learning applications for oil palm tree detection and counting

The amount of carbon sequestration by vegetation can be estimated using vegetation productivity. At present, there is a knowledge gap in oil palm net primary productivity (NPP) at a regional scale. Therefore, in this study NPP of oil palm trees in Peninsular Malaysia was estimated using remote sensing based light use efficiency (LUE) model with inputs from local meteorological data, upscaled leaf area index/fractional photosynthetically active radiation (LAI/fPAR) derived using UK-DMC 2 satellite data and a constant maximum LUE value from the literature. NPP values estimated from the model was then compared and validated with NPP estimated using allometric equations developed by Corley and Tinker (2003), Henson (2003) and Syahrinudin (2005) with diameter at breast height, age and the height of the oil palm trees collected from three estates in Peninsular Malaysia. Results of this study show that oil palm NPP derived using a light use efficiency model increases with respect to the age of oil palm trees, and it stabilises after ten years old. The mean value of oil palm NPP at 118 plots as derived using the LUE model is 968.72 g C m^-2 year^-1 and this is 188% - 273% higher than the NPP derived from the allometric equations. The estimated oil palm NPP of young oil palm trees is lower compared to mature oil palm trees (&lt;10 years old), as young oil palm trees contribute to lower oil palm LAI and therefore fPAR, which is an important variable in the LUE model. In contrast, it is noted that oil palm NPP decreases with respect to the age of oil palm trees as estimated using the allomeric equations. It was found in this study that LUE models could not capture NPP variation of oil palm trees if LAI/fPAR is used. On the other hand, tree height and DBH are found to be important variables that can capture changes in oil palm NPP as a function of age.

One of renewable energy that can be converted into electricity is biomass. Biomass energy or bio energy is the largest source of domestic renewable energy in Indonesia. Since palm oil development is rapidly increasing, Empty Fruit Bunch (EFB) and Mesocarp Fiber (MF) are becoming the highest contributor of oil palm waste. Understanding biomass waste potential is very important for further utilization. Remote sensing technique can be used to detect oil palm trees age based on the canopy density and to estimate the amount of EFB in further analysis. In this research, the percentage of canopy density of oil palm trees/stands depends on their ages and the age is divided into four classes; seeds (<3 years old; <10%), young (3-8 years old; 10-40 %), teenage (9-14 years old; 41-80 %), and mature (15-25 years old; >80 %).

Abstract. Malaysia currently is one of the biggest global producers and exporters of palm oil. The world’s expanding oil palm plantation areas contribute to climate change and in-return, climate is change also affecting the health of oil palms through a range of abiotic and biotic stresses. Current advancements in Precision Agriculture research using UAV gives an advantage to detect the health conditions of oil palm at early stages. Thus, remedial actions can be taken to prolong the life and increase oil palms productivity. This paper explores the use of UAV derived NDVI and CPA of young oil palm to detect the health conditions. NDVI of individual oil palm were extracted using ground masking layer from the dense point clouds and visual on-screen manual editing was done for removing trees other than oil palm in ENVI software. The classified individual crown NDVI were then processed to extract the mean NDVI also conversion to vector to obtain the individual crown outline. Extracted mean NDVI was classified into un-healthy and healthy trees while the CPA was classified into small, medium and big size classes. These classes of NDVI and CPA were analysed using GIS overlay method thus revealing the spatial patterns of individual oil palm trees and its health conditions. Overall, the majority of oil palm trees of the study area are healthy but average performing. However, few oil palm trees detected having health problems which has low NDVI and small CPA. This study demonstrates that biophysical parameters such as the CPA can be used to detect individual young oil palm trees health conditions and problems when combined with vegetation indices such as NDVI.

Does oil palm agriculture help alleviate poverty? A multidimensional counterfactual assessment of oil palm development in Indonesia