Oil Palm Area Research Articles

The Portrait of Agronomic activity of Oil Palm Independent Small Holder in West Kalimantan Province, Indonesia

Indonesia is the largest palm oil producer in the world. One of the provinces with the largest oil palm area in Indonesia is the West Kalimantan Province, which 1,89 million ha. Of this total plantation area, 54,7% (1.456.534 ha) are smallholder plantations. The use of huge area for oil palm cultivation is often associated with global warming because it is considered to source of carbon release from irresponsible cultivation processes. The main problem of oil palm independent smallholder plantations is the low productivity because of does not implementing the sustainable cultivation technologies. This study was conducted to describe the process of oil palm cultivation carried out by oil palm independent small holder in West Kalimantan Province. The research has been conducted through structured interviews in four districts with a purposive sampling method. The results showed that the most sustainable agronomic activities that have been carried out by oil palm farmers are plantations establishment in non-forest estate (APL) and use of certified seeds. Meanwhile, sustainable agronomic activities that have not been carried out by most oil palm farmers include without-burning land clearing, weed and pest-diseases control according to guidelines, and fertilization, castration, pruning, and harvesting rotation as recommended. On average, the productivity of oil palm independent smallholder in West Kalimantan is about 8,36 tons of FFB/ha/year, still below the Indonesian national average of oil palm productivity. These results indicate that most of oil palm independent small holder in West Kalimantan Province need to increase their agronomic capacity so that their productivity can increase.

Oil Palm Plantation and Plant Species Diversity in Kolaka District, Indonesia

Knowledge of the types of plant species in the world continues to progress even though there are still many plant species whose types and benefits are not yet known. These plant species concentrate in an area both in residential areas, pastures, agricultural land, and plantation land. The research aims to identify plant species in mature oil palm plantation areas in Kolaka Regency by selecting Watubangga and Tanggetada subdistricts as survey locations and has been carried out from January to August 2022 by dividing the mature oil palm area into 3 villages in each subdistrict as research samples. The results of the survey and identification were analyzed using the summed dominance ratio formula to determine the level of dominance of plant species in controlling growth facilities. The findings of plant species in mature oil palm plantation areas in Watubangga Subdistrict, Polenga Village (highest-Cyperus rotundus L. 3.0738%, lowest-Solanum torvum Sw. 1.8637%), Kastura Village (highest-Brachiaria miliformis 4.1470%, lowest-Euphorbia hirta L 1.5057%), Kukutio Village (highest-Pennisetum purpureum Schumach 3.8447%, lowest-Chromolaena odorata (L.) King. 1.6317%). Tanggetada Subdistrict, Pundaipa Village (highest-Asystasia coromandeliana Ness 3.8541%, lowest-Cyrtococcum acrescens 1.4968%), Tinggo Village (highest-Imperata cylindrica (L.) P. Beauv. 4.9256%, lowest-Chromolaena odorata (L.) King 1.6079%), Oneeha Village (highest-Pennisetum purpureum Schumach, 3.8447%, lowest-Chromolaena odorata (L.) King. 1.6317%). This finding can be concluded that each area of mature oil palm plantations has several different and varied plant species and there are invasive plants that can eliminate native plants such as Chromolaena odorata (L.) King. and Imperata cylindrica (L.) P. Beauv.

Oil palm contribution to sdgs achievement: A case study in main oil palm producing provinces in Indonesia

The development of oil palm plantations and their production is not only expected to generate foreign exchange for the country, but it is also expected to have a positive impact on the social and economic development of the community, which must be in line with the sustainable development goals (SDGs). The development of oil palm plantations that involves the people through the Nucleus Estate and Smallholder (NES or PIR) Scheme with its various variations has several weaknesses that are detrimental to farmers, causing various conflicts and weaken farmers’ bargaining position, unclear determination of plantation development costs and unclear criteria in determining the quality and price of fresh fruit bunches (FFB) produced by farmers. This study aims to study whether oil palm development is able to improve socio-economic conditions of the people in Indonesia, mainly in main oil palm producing provinces in accordance with the SDGs targets, including no poverty (Goal-1), reduced inequality (Goal-10), and good health and wellbeing (Goal-3). The research was carried out on a national level, especially in oil palm producing provinces in Indonesia. The data used are time series data for the period of 1990 to 2020. The analysis model used is a regression model where oil palm area as an independent variable and the SDGs indicators as dependent variables. The results showed that oil palm development could significantly reduce the number of poor people in both rural and urban areas, had not been able to reduce income inequality even in 4 provinces significantly increased income inequality, and had no effect on improving people’s health and wellbeing based on the human development index.

The Use of Random Forest Regression for Estimating Leaf Nitrogen Content of Oil Palm Based on Sentinel 1-A Imagery

For obtaining a spatial map of the distribution of nitrogen nutrients from oil palm plantations, a quite complex Leaf Sampling Unit (LSU) is required. In addition, sample analysis in the laboratory is time consuming and quite expensive, especially for large plantation areas. Monitoring the nutrition of oil palm plants can be achieved using remote-sensing technology. The main obstacles of using passive sensors in multispectral imagery are cloud cover and shadow noise. This research used C-SAR Sentinel equipped with active sensors that can overcome cloud barriers. A model to estimate leaf nitrogen nutrient status was constructed using random forest regression (RFR) based on multiple polarization (VV-VH) and local incidence angle (LIA) data on Sentinel-1A imagery. A sample of 1116 LSU data from different islands (i.e., Sumatra, Java, and Kalimantan) was used to develop the proposed estimation model. The performance evaluation of the model obtained the averaged MAPE, correctness, and MSE of 9.68%, 90.32% and 11.03%, respectively. Spatial maps of the distribution of nitrogen values in certain oil palm areas can be produced and visualized on the web so that they can be accessed easily and quickly for various purposes of oil palm management such as fertilization planning, recommendations, and monitoring.

Identifying The Potential Sources of Chemical Elements in Drainage and Rivers Using Google Earth Imageries and Posteriori Knowledge

This study attempts to identify the potential sources of the chemical elements in the river and drainage water using in-situ water quality sampling and public domain satellite data. Monitoring the physico-chemicallevel of urban streams and rivers is important to secure sufficient water resources, an indicator to the ecological degradation in urban areas and an indicator of environmental pollution. Nonetheless, identifying the potential sources of chemical pollutants by field observation is constrained by hard labor activities, time, and cost. Having satellite imagery that provides land use activity information would be useful in determining the chemical sources. Therefore, the objective of this paper is to utilize the publicly accessible Google satellite images in identifying the potential sources of the chemical elements' presence in the water that is physically sampled and measured over the selected urban rivers and drainage of Johor Bahru. Three chemical elements were identified, ammonia (NH3), nitrate (NO3-), and phosphate (PO43-). The identification of the chemical sources is conducted based on the interpretation of the satellite-derived information together with the posteriori knowledge, experience, and inputs in an environmental chemistry perspective. The findings revealed that the proportion of land used did not always have a significant impact on the chemical content of the waterways. For ammonia, areas with significant hotspots (aquaculture, wet market) are more significant, although the size of the area is not dominant. The nitrate content, on the other hand, showed quite a distinct pattern linked to oil palm, intensive farming, and industrial or commercial areas. There was no distinct land use pattern associated with phosphatelevel. However, locations with high residential areas were likely to have high phosphate content in their respective waterways or drainage to the onsite investigations with minimal labor works, cost effective, and time efficient.

Assessing the changes in river water quality across a land-use change (forest to oil palm plantation) in peninsular Malaysia using the stable isotopes of water and nitrate

Land conversion from natural forests to plantations (e.g., oil palm) in Southeast Asia is one of the most intensive land-use changes occurring worldwide. To clarify the effects of oil palm plantations on water quality, we conducted multipoint river and stream water sampling in peninsular Malaysia at the end of the rainy season over a 3-year period (2013–2015). We measured the major dissolved ions and stable isotope ratios of water (δ2H-H2O and δ18O-H2O) and nitrate (δ15N-NO3− and δ18O-NO3−) in water from the upper streams in mountainous forests to the midstream areas of two major rivers in peninsular Malaysia. The electrical conductivity increased, and the d-excess value (as an index of the degree of evaporation) decreased with increasing distance from the headwaters, suggesting the effect of evaporative enrichment and the addition of pollutants. We separated the sampling points into four groups (G1–G4) through cluster analysis of the water quality data. From the land use/land cover (LULC) classification maps developed from satellite images and local information, we found that G1 and G2 mainly consisted of sampling points in forested areas, while G3 and G4 were located in oil-palm-affected areas. The concentrations of major ions were higher in the oil palm areas, indicating the effects of fertilizer and limestone (i.e., pH adjustment) applications. The dissolved inorganic nitrogen concentration did not differ among the groups, but the dissolved organic carbon, total dissolved nitrogen, and δ15N-NO3− were higher in the oil palm area than in the forested area. Although the nitrogen concentration was low, even in the oil palm area, the significantly higher δ15N-NO3− in the oil palm area indicated substantial denitrification. This implies that denitrification contributed to the lowering of the NO3− concentration in rivers in the oil palm area, in addition to nutrient uptake by oil palm trees.

Changes in some soil chemical properties in peatland after two years of fire in Kubu Raya, West Kalimantan

Peatland fire that occurred in 2018 are located in Kubu Raya Regency, West Kalimantan. The fire was claimed to cause the changes leading to peatland damage. The initial study based on samples collected in fire period reported that there were some changes of chemical properties leading to peatland damage. The study aimed to evaluate the effect of land fires on changes in some soil chemical properties after two years of fires. Soil samples of fired and unfired peatland were subjected to soil analyses. Soil analyses covered soil pH, organic carbon (C), phosphorus (P), calcium (Ca), magnesium (Mg), potassium (K), iron (Fe), manganese (Mn), copper (Cu), zinc (Zn), and bulk density (BD). The results showed that after two years of peatland fires did not affect the changes of peat soil pH, organic C, P, Ca, Mg, K, Cu, Zn, Mn and BD. One plot of fired peatland showed that the weight of frond and leaf area of oil palm grown on it was not statistically different from those of unfired peatland. The results suggested some chemical properties return to previous equilibrium due to high buffering capacity of peat soil.

Optimization of Open-Access Optical and Radar Satellite Data in Google Earth Engine for Oil Palm Mapping in the Muda River Basin, Malaysia

Continuous oil palm distribution maps are essential for effective agricultural planning and management. Due to the significant cloud cover issue in tropical regions, the identification of oil palm from other crops using only optical satellites is difficult. Based on the Google Earth Engine (GEE), this study aims to evaluate the best combination of open-source optical and microwave satellite data in oil palm mapping by utilizing the C-band Sentinel-1, L-band PALSAR-2, Landsat 8, Sentinel-2, and topographic images, with the Muda River Basin (MRB) as the test site. The results show that the land use land cover maps generated from the combined images have accuracies from 95 to 97%; the best combination goes to Sentinel-1 and Sentinel-2 for the overall classification. Meanwhile, the best combination for oil palm classification is C5 (PALSAR-2 + Landsat 8), with the highest producer accuracy (96%) and consumer accuracy (100%) values. The combination of C-band radar images can improve the classification accuracy of oil palm, but compared with the combination of L-band images, the oil palm area was underestimated. The oil palm area had increased from 2015 to 2020, ranging from 10% to 60% across all combinations. This shows that the selection of optimal images is important for oil palm mapping.

Understanding the spatial distribution and hot spots of collared Bornean elephants in a multi-use landscape

In the Kinabatangan floodplain, Sabah, Malaysian Borneo, oil palm and settlements have reduced and fragmented lowland tropical forests, home to around 200 endangered Bornean elephants (Elephas maximus borneensis). In this region, elephants range within forests, oil palm and community areas. The degree to which elephants are using these areas remains unclear. We used GPS telemetry data from 2010 to 2020 for 14 collared elephants to map their entire known ranges and highly used areas (hot spots) across four land use categories and estimate time spent within these. The use of land use types across elephants varied significantly. Typically, females had strong fidelity to forests, yet many of these forests are threatened with conversion. For the three males, and several females, they heavily used oil palm estates, and this may be due to decreased landscape permeability or foraging opportunities. At the pooled level, the entire range and hot spot extents, constituted 37% and 34% for protected areas, respectively, 8% and 11% for unprotected forests, 53% and 51% for oil palm estates, and 2% for community areas. Protecting all forested habitats and effectively managing areas outside of protected areas is necessary for the long-term survival of this population.

Analysis of deforestation as impact of changes on oil palm land use in Tanah Bumbu Regency, South Kalimantan using satellite remote sensing data

Analysis of deforestation using remote sensing satellite imagery is carried out for monitoring and as an effort to reduce deforestation rates to maintain the ecological function of the forest. One of the causes of deforestation are land clearing and land conversion. Based on BPS data in 2020th, the forest area is decreasing and the area of oil palm is increasing every year. This research was conducted in Tanah Bumbu Regency, the data used were Landsat 7 ETM+ and Landsat 8 OLI/TIRS images. The method used is a guided classification with Support Vector Machine (SVM). Analysis of deforestation uses the results of image processing classification in time series by taking into account the reduction of forest that occurs every year. Based on the results of image classification in 2010th using SVM, forest has an area of 2161.1 km2 and oil palm is 1063.6 km2. Both of these land uses underwent changes in 2020th with forest area experiencing a reduction of 1493.42 km2 and oil palm having an additional area of 865.62 km2. The classification results have an overall accuracy value of above 80% and a kappa accuracy of 78%. The results of the analysis show that there is a relationship between the incidence of deforestation and the expansion of oil palm land. Based on the results of the regression analysis, R2 = 0.95 with a change value of 935.42 km2.

Oil Palm Plantation Land Cover and Age Mapping Using Sentinel-2 Satellite Imagery and Machine Learning Algorithms

Nowadays, there are various techniques and methods used in land cover classification using remote sensing data especially in oil palm monitoring. This study discussed the oil palm mapping using satellite imagery (Sentinel-2) and classification of land cover features using machine learning algorithms such as linear support vector classifier (LSVC), random forests (RF) and deep neural network (DNN). A total 13218 sampling points (80% of the total sampling points used as training samples and 20% applied as testing samples) were randomly selected in the study area which were then classified into six land cover features; water, bare soil, forest, immature oil palm (the age of 2-8 year), mature oil palm (age >8 year) and built-up area. These data were validated by using spectral reflectance, Google Earth Pro and ground checking. The accuracy assessment was conducted by a confusion matrix method. The results showed that classification of land features using DNN with batch size 32 and epoch 100 has the highest accuracy which is 99.35% for overall accuracy and 98.49% kappa accuracy. This study demonstrated various machine learning algorithms that may be used to detect and classify the maturity of oil palm trees, which is vital to record in tree inventories for effective plantation management.

PENGANGKUT PANEN KELAPA SAWIT DARI POHON KE MOBIL PENGANGKUT MENGGUNAKAN ALAT ANGKUT SISTEM CONVEYOR RANTAI

Indonesia is one of the main producers of palm oil, and currently occupies the second position in the world. Indonesia is a country with the largest oil palm area in the world, which is 34.18% of the world's palm oil area. The achievement of the average production of Indonesian palm oil in 2017-2020 was recorded at 176 million tons of fresh fruit bunches (FFB). This study aims to increase effectiveness and efficiency in work productivity. The method used in this research is to do direct spaciousness. The results show the results of the performance of the tool for developing oil palm fruit ideas into cars by looking at the consumption of fuel used in a single transport process. The system works by rotating the gear and shaft that encircles the chain and pulls the oil palm haul board.

Anticoagulant rodenticide use in oil palm plantations in Southeast Asia and hazard assessment to non-target animals.

Anticoagulant rodenticides (ARs) are used worldwide for the control of rodent pests and are the main method of control of rat pest populations in agricultural areas. The main aim of this review is to discuss the risk of ARs to non-target wildlife in oil palm areas in Southeast Asia, mainly Indonesia and Malaysia. We discussed AR use in oil palm areas and toxicities of ARs on target and non-target animals. We also reviewed published literature on wildlife species reported in oil palm areas in Southeast Asia and utilizing this information, we assessed the hazard risk of ARs to non-target wildlife in oil palm plantations. ARs are a secondary exposure hazard to rodent-consuming mammalian carnivores, such as leopard cats and civets, and rodent-consuming raptors, such as barn owls. Consumption of dead poisoned prey puts scavengers, such as water monitors, at high risk for AR exposure. Domestic livestock and granivorous birds are at high risk for AR exposure via primary exposure to toxic bait, while omnivores such as macaques and wild pigs are at moderate risk for both primary and secondary exposure to ARs. The effects of ARs on barn owls have been well studied in the field and in laboratory secondary toxicity studies. Thus, the nest-box occupancy and reproductive parameters of local barn owl populations can be monitored as an indicator of the AR exposure level in the area. CLINICAL TRIALS REGISTRATION: No clinical trials were involved in this study.

The potential of peatland fires estimated from physical properties for several land uses

The construction of drainage channels following the opening of peat ecosystems without proper water management results in rapid decline of water level in peat swamp ecosystems, which potentially causes fires. Peat land fires triggered by intentional or unintentional human negligence and are supported by long dry season. This research aims to examine the potential of peat land fires based on the physical characteristics of peat on the type of use of secondary forest land, shrub land, and oil palm land. The study was conducted on peat ecosystems for one year using survey methods and field observations. The results of study indicate that changes in peat land use from secondary forests to shrubs and oil palm plantations result in changes in some physical characteristics of peat, namely humification level, bulk density, peat thickness, organic matter content, hydraulic conductivity, and soil water content. The depth of the ground water table affects the ground water content. Potential fires occur on oil palm land and on shrub land from July to September, whereas secondary forest land does not have the potential to cause fire. In order to avoid fires in oil palm and shrub land areas, it is necessary to manage water by maintaining the groundwater level above 50 cm.

Clustering of Palm Oil Production Results with K-Means Algorithm in West Aceh Regency

The area and production of oil palm in West Aceh continues to experience a significant increase, because along with the expansion of oil palm plantations in the local area, it is very influential on employment and improving the economy of the community. This study aims to group the results of oil palm production and planted area by applying the data mining technique method with the K-Means Clustering algorithm. The data used in this study in the form of area and palm oil production results were obtained from the West Aceh catalog (BAPPEDA) and the Central Statistics Agency from 2005 to 2020 in 12 sub-districts of West Aceh Regency. The results of the study showed that the high cluster (cluster 1) contained 1 sub-district, namely Kaway XVI, the medium cluster (cluster 0) there were 7 sub-districts namely Bubon, Johan Pahlawan, Panten Reu, Samatiga, Sungai Mas, Woyla Barat, and Woyla Barat, while the cluster low (cluster 2), there are 4 sub-districts, namely Arongan Lambalek, Meureubo, Pante Ceureumen, and Woyla.

Analisis Kelayakan Usaha Perkebunan Kelapa Sawit Rakyat di Desa Tanoh Mayang Kecamatan Teunom Kabupaten Aceh Jaya

Tanoh Mayang Village is one of the villages which has the highest oil palm area compared to other villages in Teunom District of Aceh Jaya Regency. Based on the survey of research sites, the average smallholder oil palm plantation in Tanoh Mayang Village is neglected with low production levels. By the existing issues, the author is interested in conducting research in the location. The purpose of this study is to know whether the smallholder oil palm plantation business in Tanoh Mayang Village is feasible when viewed from technical aspect, marketing aspect, and financial aspect. The location of this research was chosen purposively by a sample of 19 farmers. The data used are primary data and secondary data. The analysis method uses business feasibility analysis, namely examining technical aspect, marketing aspect, and financial aspect. The results of the study indicate which is based on the results of this study indicate that the smallholder oil palm plantation business in Tanoh Mayang Village, Teunom District, Aceh Jaya Regency is feasible. From the technical aspect, it can be known that access to raw materials, labor and business location is profitable for farmers. Besides, from the aspect of marketing, it has been going well and it is feasible. Meanwhile, from the financial aspect, the results of the NPV analysis is Rp. 133,195,811.4, Net B/C is 2.0, IRR is 10.83%, and Payback Period in the 11th year of the 11th month 2nd day 27th. The results of the sensitivity analysis of the four analytical criterias is that the smallholder oil palm plantation business in Tanoh Mayang Village is still feasible to operate even when operating costs increase to 10% while benefit is fixed or when benefit decreases to 10% while the operating cost is fixed.

Spatial patterns and drivers of smallholder oil palm expansion within peat swamp forests of Riau, Indonesia

Protecting the tropical peat swamp forests in Southeast Asia is critical for addressing global sustainability challenges such as climate change and biodiversity loss. However, more than half of these forests have been lost since 1990 due to the rapid expansion of drainage-based agriculture and forestry. Within the oil palm sector, the number of regional smallholder oil palm plantings on peat soils has risen quickly. These activities are challenging to govern and manage, due to their fragmented nature and the numerous farmers involved. It is imperative to understand the spatial distribution and drivers of the smallholder oil palm-related conversion of peat swamp forests. In contrast to existing studies based on farm surveys, we used state-of-art maps of smallholder oil palm plantings, derived from 2019 remote sensing data. Spatial data about socioeconomic and biophysical factors (e.g. mills, roads, water ways, and concessions) was then used to develop logistic regression models to investigate the relative influence of these factors. We show that the spatial patterns of smallholder oil palm plantings are distinct from those of industrial oil palm plantations, revealing the critical roles of roads, especially service roads, residential roads and tracks, in driving smallholder oil palm expansion within peatlands. We found that 90% of smallholder oil palm areas were located within 2 km of roads and 25 km of mills. The mean likelihood of a given land area being converted from peat swamp forests to smallholder oil palm declined rapidly with increasing distance from roads and mills. In addition to roads and mills, land use zones (e.g. the setting of concessions and migration settlements) and other environmental factors (e.g. precipitation and elevation) were identified as important drivers of smallholder oil palm expansion on peatland. Based on these findings, we identify priority regions for the protection of the remaining peat swamp forests in Indonesia and discuss strategies for tackling these sustainability challenges on local and global scales.

Spatial Prioritization for Wildfire Mitigation by Integrating Heterogeneous Spatial Data: A New Multi-Dimensional Approach for Tropical Rainforests

Wildfires drive deforestation that causes various losses. Although many studies have used spatial approaches, a multi-dimensional analysis is required to determine priority areas for mitigation. This study identified priority areas for wildfire mitigation in Indonesia using a multi-dimensional approach including disaster, environmental, historical, and administrative parameters by integrating 20 types of multi-source spatial data. Spatial data were combined to produce susceptibility, carbon stock, and carbon emission models that form the basis for prioritization modelling. The developed priority model was compared with historical deforestation data. Legal aspects were evaluated for oil-palm plantations and mining with respect to their impact on wildfire mitigation. Results showed that 379,516 km2 of forests in Indonesia belong to the high-priority category and most of these are located in Sumatra, Kalimantan, and North Maluku. Historical data suggest that 19.50% of priority areas for wildfire mitigation have experienced deforestation caused by wildfires over the last ten years. Based on legal aspects of land use, 5.2% and 3.9% of high-priority areas for wildfire mitigation are in oil palm and mining areas, respectively. These results can be used to support the determination of high-priority areas for the REDD+ program and the evaluation of land use policies.

Effect of integrated biofertilizers with chemical fertilizers on the oil palm growth and soil microbial diversity

Prolong use of chemical fertilizers has adversely affected the environment and natural microbial diversity in soil and thereby reduced soil fertility and crop quality. The application of biofertilizers containing a combination of beneficial microorganisms in a formulation with a reduced amount of chemical fertilizer was believed to be more effective compared with the stand-alone application of biofertilizers or chemicals. The objective of this study was to investigate the effect of four different treatments on oil palm growth and soil microbial diversity shift located in Chaah, Achijaya, Johor. The treatments comprised of biofertilizers with zero chemical fertilizer content (BF100), biofertilizer amended with 30% of chemical fertilizer (BF70), 100% chemical fertilizer (CF100), and standard organic fertilizer (SF). The results indicated that the application of BF70 produced the highest oil palm height, meristem diameter, number of fronds , leaf area, wet and dry weight of oil palm leaves. Important macronutrients; nitrogen (N) and potassium (K) were highly significant in the oil palms treated with BF70; which were 2.85% and 4994.20 mg L −1 , respectively. While phosphorus (P) recorded 2147.78 mg L −1 with no significant difference compared to other treatments. Application of BF100 indicated the highest soil microbial biodiversity (H' = 3.4723) while BF70 showed a slightly lower H′ that was 3.2444 for bacteria compared to CF100 (2.2372). Whereas, for fungi, BF70 resulted in the highest H’ (2.6662) compared to BF100 (1.9730) and CF100 (2.3799). Therefore, environmentally friendly biofertilizer integrated with a small rate of chemical fertilizer helps in developing better oil palm growth, balanced and sufficient nutrient availability, and maintaining the survivability of beneficial microorganisms in the soil. • Excessive use of chemical fertilizers in agriculture will lead to more environmental problems. • Researchers have emphasized the usage of environmentally friendly biofertilizers that hold vast potential in meeting plant nutrient requirements. • Integration of biofertilizer with a small rate of chemical fertilizer promised an excellent result compared to the usage of biofertilizer alone and 100% chemical fertilizer.

The potential of area under young oil palm plantation on tidal swamps for soybean development

In Indonesia, soybean production during 2011-2020 only met 20-30% of the total need due to the decrease of the harvested area from 660 to 285 thousand ha. To achieve soybean self-sufficiency, the area of young oil palm plantations on tidal lands is potential for soybean development. In 2020, the areas reached 14.9 million ha with a growth rate of 8.68% year−1, meaning that at least every year, there is around 1.29 million ha of new oil palm areas potential for soybean production. Constrain for soybean growth on these lands are shading, low soil pH, and high Al-soil saturation. A solution for the shading problem is planting tolerant soybean varieties such as Dena1, Dena2, Denasa1, Denasa2, Argomulyo, and Dega1. The low soil pH and high Al saturation can be improved by using dolomite until the Al-dd saturation decreases to 20-30%. Soybeans can grow well under oil palm crops until the trees are 4 years old, with a potential production of >1.0 t ha−1, increases LER up to 1.8, and increases farmers’ income until the oil palm starts producing. Good planning and coordination among stakeholders for the input procurement, assistance, and farmers’ readiness would determine the success of soybean development on such lands.