Coconut Plantations Research Articles

Why do Farmers not Use Fertilizer? A Case of Multistorey Cropping System with Abaca under Coconut in Zamboanga Peninsula, Philippines

The Zamboanga Peninsula region significantly contributes to the Philippine coconut production, wherein abaca is also cultivated as an additional crop within coconut plantations. Still, coconut farmers belong to the country’s poverty sector. Abaca plays a significant role in providing an alternative source of income as a perennial intercrop in agroforestry systems like coconut. However, the productivity and sustainability of this farming system are affected by practices such as nutrient management, which is not explicitly known. Using a mixed-methods approach, this study applies a combination of quantitative and qualitative data-gathering techniques to assess the nutrient management practices adopted by the 33 qualified respondents, including challenges encountered and perceptions to abaca under the coconut farming system and fertilizer use. Quantitative data were analyzed using IBM SPSS Statistics version 29, and thematic analysis was utilized for qualitative data. Results indicate that most (88%) of the farmers in the area did not apply fertilizers for their abaca. Yet, they still consider abaca as one of the income-generating crops besides coconut. The lack of financial resources and irregular harvesting operations are significant challenges that hinder fertilizer application. Findings revealed the need to develop low-cost and practical nutrient management technology for abaca under coconut, which shall be complemented with an effective human resource management system of skilled harvesters for the continuous harvesting operation of abaca to translate good crop growth into good yield and income. This will serve as a basis for government institutions and other stakeholders in developing and implementing programs and policies to improve the abaca and coconut industries.

EVALUASI STATUS KESUBURAN TANAH PADA BEBERAPA JENIS PENGGUNAAN LAHAN DI DESA PENGERAGOAN, KECAMATAN PEKUTATAN, KABUPATEN JEMBRANA

This research was carried out in Pengeragoan Village, Pekutatan District, Jembrana Regency, from July to September 2023. The aim of this research was to determine the chemical properties of soil and determine soil fertility status classes and provide direction in land management according to the level of soil fertility status for each type. Land use in Pengeragoan Village, Pekutatan District, Jembrana Regency. The types of land use that exist include coffee plantations, cocoa plantations, coconut plantations, mixed plantations, natural forests, teak forests and rice fields. Sampling was carried out compositely on several existing land use types, namely coffee plantations (Tki), cocoa plantations (Tko), coconut plantations (Tka), mixed plantations (Tc), natural forests (Tha), teak forests (Tj), and rice field (Ts). Determination of soil fertility status is carried out by measuring soil chemical properties parameters, namely soil Cation Exchange Capacity (CEC), Base Saturation (KB), P-total, K-total and C-organic. The research results show that the soil fertility status in several types of land use falls into the criteria of high, medium and low. Natural forest and mixed garden land use types have high soil fertility status. The land use types of coffee plantations, cocoa plantations and teak forests have medium soil fertility status. The land use types of coconut plantations and rice fields have low soil fertility status. The management direction recommended from the results of evaluating soil fertility status and several supporting soil chemical properties for each type of land use is the need to add N and P nutrients to the land use types of coffee plantations, mixed plantations and natural forests. In the types of land use of cocoa plantations, coconut plantations, teak forests and rice fields, it is necessary to add nutrients N, P and organic materials in the form of plant litter and organic fertilizer.

Satellite imagery reveals widespread coconut plantations on Pacific atolls

Abstract Efforts to mitigate tropical deforestation overlook coconut palm (Cocos nucifera L.) plantations on atolls—low island ecosystems that represent the most common landforms in the Pacific basin. Coconut palms have a deep history in the Pacific and were planted extensively over the last two centuries to meet the surging demand for coconut oil exports. But despite wide interest in the global footprint of palm crops, the distribution of coconut palms on Pacific atolls has remained unknown. We applied a supervised machine learning classifier to satellite imagery to produce 2 m resolution vegetation maps of 235 of 266 Pacific atolls. Despite the abandonment of many plantations in recent decades, we find that coconut palms surpass native broadleaf trees in terms of canopy area: coconut presently covers 58.3% of the mapped atolls’ total forested area and 24.1% of their total land area. 51.2% of these coconut canopies occur in monocultures indicative of plantation agriculture and drastic ecological changes. Even among atolls with climates equally suitable for coconut palms, coconut canopy coverage is 32.1 percentage points greater on those that historically exported coconut products, demonstrating the significant and persistent effects of plantations on forest compositions in the tropical Pacific. Coconut palms are most dominant on large, wet islands, reflecting their high rates of water use and thus their potential to deplete critical groundwater resources. The spread of coconut plantations also came at the expense of native vegetation critical for wildlife habitat, nutrient cycling, and soil formation. The severe environmental impacts of coconut plantations urge ecosystem management in a region uniquely exposed to climate change.

Revolutionizing agricultural efficiency with advanced coconut harvesting automation

<span style="vertical-align: inherit;"><span style="vertical-align: inherit;">The precision coconut harvesting system aims to develop an efficient system for accurately detecting coconuts in agricultural landscapes using advanced image processing techniques. Coconut cultivation is vital to many tropical economies and precise monitoring is essential for optimizing yield and resource utilization. Traditional methods of coconut detection are labor-intensive and time-consuming. The proposed computer vision-based approach automates and enhances coconut detection by analyzing high-resolution images of coconut plantations. Pre-processing techniques improve image quality and object detection algorithms such as convolutional neural networks (CNNs) identify coconut clusters. Challenges like lighting variations and background clutter are addressed using feature extraction and pattern recognition. A user-friendly interface visualizes detection results, aiding farmers in timely decision-making. Extensive testing on diverse datasets evaluates system effectiveness. This model aims to advance precision agriculture, enhancing productivity and informing coconut farmers' decision-making processes. Using a CNN model, the accuracy of coconut detection based on its ripeness was 98.8%.</span></span>

Impact of climate and land use on the temporal variability of sand fly density in Sri Lanka: A 2-year longitudinal study.

Leishmaniasis has emerged as an escalating public health problem in Sri Lanka, with reported cases increasing nearly three folds over past decade, from 1,367 in 2014 to 3714 cases in 2023. Phlebotominae sand flies are the vectors of leishmaniasis. Their density is known to be influenced by context-specific climatic and land use patterns. Thus, we aimed to investigate how these factors drive sand fly density across Sri Lanka. We analysed monthly collections of sand flies (n = 38,594) and weather data from ten sentinel sites representing three main geo-climatic zones across Sri Lanka, over 24 months. Site-specific land use data was also recorded. The influence of climate and land use patterns on sand fly density across the sentinel sites were estimated using distributed lag non-linear models and machine learning. We found that climate played a major role on sand fly density compared to land use structure. Increase in rainfall and relative humidity at real time, and ambient temperature and soil temperature with a 2-month lag were associated with a statistically significant increase in sand fly density. The maximum relative risk (RR) observed was 3.76 (95% CI: 1.58-8.96) for rainfall at 120 mm/month, 2.14 (95% CI: 1.04-4.38) for relative humidity at 82% (both at real time). The maximum RR was 2.81 (95% CI: 1.09-7.35) for ambient temperature at 34.5°C, and 11.6 (95% CI, 4.38-30.76) for soil temperature (both at a 2-month lag). The real-time increase in ambient temperature, sunshine hours, and evaporation rate, however, reduced sand fly density homogeneously in all study settings. The high density of chena and coconut plantations, together with low density of dense forests, homesteads, and low human footprint values, positively influenced sand fly density. The findings improve our understanding of the dynamic influence of environment on sand fly densities and spread of leishmaniasis. This knowledge lays a foundation for forecasting of sand fly densities and designing targeted interventions for mitigating the growing burden of leishmaniasis among the most vulnerable populations, particularly in an era of changing climate.

Mapping coconut plantation in Western Agro-Climatic zone using object-based classification and machine learning technique

Coconut (Cocos nucifera), a key crop for over 10 million farming families in India, is vital in the agricultural economies of southern states like Tamil Nadu. However, traditional methods of monitoring coconut plantations are challenging due to the crop's geographical dispersion and seasonal variations. This study focuses on mapping coconut plantations in the Western Agro-Climatic Zone of Tamil Nadu using Object-Based Classification (OBC) and machine learning techniques. A ten-year time series of Landsat 7 optical satellite data (2012-2013 and 2022-2023) was employed, combined with ground truth surveys across the region. The study utilized Support Vector Machine (SVM) and Random Forest (RF) classifiers, with RF demonstrating superior accuracy. The RF classifier achieved an accuracy of 91.7% in 2012-2013 and 90.3% in 2022-2023, outperforming SVM, which hovered around 70%. The research also conducted a change detection analysis, revealing a net increase of 3,270 hectares of coconut plantations over the decade, with the Coimbatore district contributing the most significant growth of 2,560 hectares. This study underscores the effectiveness of integrating OBC and machine learning, mainly RF, for accurate and efficient mapping of coconut plantations using Landsat satellite data.

Exploring the relationship between land characteristics and the sustainable growth of coconut cultivation in Indonesia

This study explores land types as a basis for evaluating the sustainability of coconut plantations in Indonesia, focusing on peatlands and coastal areas that affect productivity and management practices. This research aims to evaluate the sustainability of coconut plantation farming across various land types and identify critical sustainability factors. Carried out in Indragiri Hilir Regency, Riau Province, the study employed a survey methodology and utilized Rap-Coconut Ordination Analysis coupled with Multidimensional Scaling (MDS). The surveyed area encompasses peatlands and coastlands, and a purposive sampling approach, guided by the Slovin Formula, yielded a sample size of 101 coconut farmers. The sustainability assessment covered five dimensions: ecological (7 attributes), social-cultural (4 attributes), economic (4 attributes), technological (6 attributes), and institutional (7 attributes) and 28 attributes. The study assessed the sustainability of coconut farming in Indragiri Hilir Regency, Riau Province. Peatlands showed lower sustainability, while coastline lands demonstrated higher sustainability levels. Key factors affecting sustainability include ecological aspects like fertilizer and pesticide use, socio-cultural elements like family involvement and attitudes towards coconut farming, economic factors like the coconut vending system, technological considerations such as optimal planting spacing and seed quality, and institutional factors like participation in extension programs and access to financial resources.

Phosphorus-Mediated Transition from Vegetative to Reproductive Growth in Dwarf Coconut (Cocos nucifera L.).

Reducing the time before the flowering stage in coconut (Cocos nucifera L.) trees greatly influences yield, yet the mechanisms driving the switch from vegetative to reproductive growth are not well understood, especially the role of phosphorus in this transition. In this study, dwarf coconut plants of the same cultivation age were selected and categorized into the vegetative phase (VP) or the reproductive phase (RP). By examining the phenotypic traits, nutrient variations in the roots and soil, and the transcriptional expression of relevant genes in the roots across both phases, we investigated the potential mechanisms driving the transition from the VP to the RP in coconuts. The shoots of coconuts in the RP were significantly taller compared to those in the VP. Moreover, the phosphorus concentration in the roots of coconuts during the RP was 1.31 times higher than in the VP, which may be linked to the significant upregulation of the PT1 genes AZ11G0219160 and AZ02G0034860 in the roots of coconuts in the RP. In addition, all phosphorus-containing metabolites in the roots during the RP showed a significant increase, particularly those related to long-chain fatty acids and ribonucleotide metabolites. This suggests that coconut roots may facilitate the progression from vegetative to reproductive growth by enhancing phosphorus uptake via PT1s and promoting the synthesis and accumulation of phosphorus-containing metabolites.

Performance Assessment of the Small and Medium-Scale Coconut Weeder Cum Fertilizer Applicator Developed by Rajarata University of Sri Lanka

The enhancement of coconut yield significantly hinges on proper weeding and chemical fertilizer application. In Sri Lanka, several mechanical methods have been introduced for weeding and fertilizer application of coconut, but the traditional manual approach persists most popular, despite being time, labor cost intensive. Moreover, the introduced technologies were suited for large-scale coconut cultivation and could not cope with medium or small-scale. Furthermore, most of them are designed for a single application; weeding or fertilizing. Thus, the Faculty of Agriculture, Rajarata University of Sri Lanka (RUSL), developed a coconut weeder cum fertilizer applicator for medium and small-scale coconut cultivations. However, it has not been properly evaluated and recommended for farmers. Consequently, this study sought to evaluate the performance of the above machine by conducting a comparative performance evaluation with the conventional method. A healthy, well-maintained, proper-spacing coconut plantation was selected from the faculty research unit, and each weeding and fertilizer application method was replicated ten times. In terms of performance parameters: effective field capacity, field efficiency, and weeding efficiency in mechanical and manual methods were 0.172 ha h-1, 61.86%, 66.62%, and 0.048 ha h-1, 55.34%, 60.35%, respectively. Statistical analysis indicates the mechanical method had higher field capacity and efficiency than the manual method, while weeding efficiency was not significantly different (p≤0.05). In addition, the machine had a fertilizer spreading uniformity of around 99.98% when operating at an optimum speed of 1.45 km h-1. Fertilizer application rate and performance index as a weeder were 1.7 kg/min and 1145.86, respectively. Furthermore, the fuel consumption rate of the machine was 0.733 L h-1 and its break-even point was recorded as 2.85 ha yr-1. Consequently, the coconut weeder cum fertilizer applicator proves suitable for medium and small-scale coconut cultivations in Sri Lanka.

Characterization of phytoplasma associated with wilt disease in coconut and approaches for its sensitive diagnostics

Coconut wilt associated with phytoplasma presence is a serious disease that threatens the coconut plantations in South India. Symptoms progress rapidly and cause complete destruction of coconut palm which results in severe economic loss to farmers. Survey in the areas of Thanjavur and Coimbatore districts revealed disease incidence upto 2.5 % and the affected palms exhibited unique symptoms, which differ from the root wilt disease symptoms reported so far. Nested PCR with universal primers and multilocus characterization of tuf and certain rp genes confirmed the presence of phytoplasmas. The 16S rRNA ribosomal gene sequence-based identification assigned the coconut wilt phytoplasma to the ‘Candidatus Phytoplasma asteris’ species. To achieve timely management of the disease and also to check its spread, Loop Mediated Isothermal Amplification (LAMP) and real-time LAMP diagnostics by targeting the 16S rRNA gene, were established for rapid and specific detection of phytoplasma presence. PCR with LAMP outer primers was carried out and sequence analysis confirmed the amplification of the 16S rRNA gene of phytoplasma. LAMP assay positive samples showed the color shift from violet to blue and was further confirmed by the ladder-like bands produced during the amplification. Diseased samples also generated a unique annealing peak at 87 ± 0.5 °C in the real-time LAMP assay. The LAMP protocol devised will be useful for quick and sensitive detection of this phytoplasma and it has potential application to detect phytoplasma presence in suspected coconut palms and to allow screening of nursery seedlings to ensure disease free planting.

The Economic Development of the Malays in the Coconut Planting Sector in Selangor Before 1940

The Economic Development of the Malays in the Coconut Planting Sector in Selangor Before 1940

Kajian Beberapa Status Hara Pada Areal Replanting Tanaman Karet (Hevea brasiliensis) di Kebun Aek Nabara Utara Kecamatan Bilah Hulu

Rubber plants (Hevea brasiliensis) will experience a decrease in production as plants age and the nutrient content in the soil decreases. This study aims to find out the chemical properties of soil on plantations of rubber crops that are converted into palm and coconut crops. The research was conducted from Februari 2023 to Agustus 2024 at the palm coconut plantation of PTPN III Aek Nabara North Garden in Labuhanbatu district and analyzed in the Land Laboratory of the Faculty of Agriculture of the University of Northern Sumatra. The methods used are observation methods, field sampling, and analysis in the laboratory to obtain quantitative data. Observation parameters include soil pH, C-organic, Total Nitrogen, Available P, Cation Interchange Capacity, and Base Fulness. The results of the survey showed that the level of soil fertility at the site of the research was included in the low category. The main limiting factor that causes the low fertility of the soil is the low content of organic material in the soil. In order to improve the fertility status of the ground at the research site for further planting, it is necessary to make efforts such as irrigation and fertilization, as well as the addition of organic materials, to make the availability of nutrients for plants more affordable. Keywords: replanting area, rubber plants, conversion, soil fertility, quantitative data

The Influence Of Total Production, NTP And Grdp On Labor Absorption In The Coconut Plantation Subsector In Riau Province

This research aims to determine the effect of total production, Farmer Exchange Rate (NTP) and Gross Regional Domestic Product (GRDP) on labor absorption in the smallholder coconut plantation subsector in Riau Province in 2012-2023. In this research, multiple linear regression techniques were used using the Ordinary Least Square (OLS) method. The research results show that the simultaneous test (F test) shows that total production, NTP and GRDP together have a significant influence on labor absorption in the coconut plantation subsector in Riau Province in 2012-2023. Meanwhile, the partial regression test (t test) shows that total production has a positive and significant effect on labor absorption, NTP has a positive and significant effect on labor absorption, and GRDP has a negative and insignificant effect on labor absorption. The results of the coefficient of determination (R2) of the independent variable on the dependent variable obtained a value of 0.973238. This means that the contribution of the independent variables (total production, NTP and GRDP) to the dependent variable (demand for employment) is 97.32% and the remaining 2.68% is influenced by other variables outside the regression model in this research.

Evaluation of unmanned aerial vehicle for effective spraying application in coconut plantations

Unmanned aerial vehicle (UAV) pesticide application in recent years owing to its importance such as time saving, reduction in human drudgery and also reduction in pesticides application rate. UAV has a great potential to address the problem involved in manual chemicals spraying in tall crops like coconut plantation where at present operation performed by manual climbing involves lots of drudgery and life risk. The current study aimed to understand the most influencing spraying parameters, such as spray height and spray time of the UAV sprayer on droplet characteristics such as spray droplet size, spray coverage and spray deposition at different layers (spindle, middle and bottom) of coconut tree canopy. The selected spray height (1, 2 and 3 m) and spray time (5, 8 and 11 s) significantly affects (p < 0.05) the droplet size (μm), spray coverage (%) and spray deposition (μl cm−2). In spray droplet size, the treatment T4, T5, T7 and T8 were recorded recommended droplet size of 50–400 μm in all layer of the coconut tree canopy. In spray coverage, the nearest value for recommended spray coverage of 10–20 % was observed for T1 and T5 treatment in all layer of the coconut tree canopy. The maximum penetration efficiency of 34.41 % had achieved at spray height of 2m and spray time of 8s (treatment T5). Based on performance of selected parameter, the spray height of 2 m and spray time of 8 s (treatment T5) was found best for spraying operation using UAV in coconut tree. The results showed the performance of the UAV offers best alternative for spraying operation on coconut tree and also this system will drastically reduce application time, labour requirement and improved the safety of coconut farmers.

Comparative Study of the Coastal Geomorphology of Kajirbhati Sand-Spit Using Google Earth Pro Images (2005, 2011, 2023) and Landsat Satellite Data (2009, 2016, 2023): An Approach Towards the Impact of the Casuarina Plantation

Coastal geomorphology undergoes constant transformation due to a combination of coastal and fluvial processes and human intervention. Remote sensing and GIS tools are invaluable in identifying and studying these changes. Due to the dynamic interaction between land and sea, the coastline requires careful monitoring to detect hotspots and understand the spatial and temporal impacts of climate change on the coastal environment. Remote sensing data offers a comprehensive means of studying coastal landform changes. In a recent study, the focus was to analyze the impact of the Casuarina plantation on the coastal geomorphology of Kajirbhati spit. This involved studying various depositional features such as sand bars, sand spits, dunes, and beaches. The study utilized Google Earth Pro images from 2005, 2011, and 2023 to digitize 13 classes each year, enabling the identification of changing geomorphic classes. These include agriculture, swash zones, dunes on sand spits, berm lines, Casuarina and coconut plantations, estuary, mangroves, mudflats, open land, sea, settlement, and vegetation. The results revealed dramatic changes in land use and land cover classes from 2005 to 2023. In the years from 2011 to 2023, the area of sandspit covered by Casuarina plants expanded rapidly. To analyze the changes, Landsat 5, 8, and 9 data were used to check the intensity of NDVI (Normalized Difference Vegetation Index) in 2009, 2016, and 2023. NDVI is a critical factor in this research. The mean NDVI values for 2009, 2016, and 2023 were -0.002, 0.02, and 0.04 respectively. The changes in higher NDVI values from 2009 to 2023 were -0.10, 0.27, and 0.28, while the lower values were -0.10, -0.10, and -0.07 for the same years. The correlation calculation between the mean NDVI values and the years indicates a strong positive correlation with an R-value of 0.99. Casuarina plants play a crucial role in protecting the coast from strong winds and dynamic sea waves. They help protect mudflats, mangroves, settlements, and estuary land use and cover classes along the coast of Kajirbhati.

AI based early identification and severity detection of nutrient deficiencies in coconut trees

Coconut trees are vital in various agricultural and economic sectors. Their susceptibility to nutrient deficiencies poses a significant threat to growth and productivity. Traditional nutrient assessment methods are time and labour-intensive, relying on manual inspection and chemical testing. There has been no significant research on detecting nutrient deficiencies in coconut trees. Additionally, assessing deficiency, and severity automatically and recommending suitable fertilizers remain unexplored. This research leverages the YOLOv9 model to identify macro and micronutrient deficiencies in coconut trees and proposes an Image Analysis based Severity Detection (IASD), to determine the severity of these deficiencies. Along with these a Severity Index Calculation Model (SICM) is also introduced that calculates the Severity Index (SI) of these deficiencies. For each identified deficiency, the appropriate fertilizer and its application quantity are suggested. Four deep learning models—RetinaNet, Faster Regional Convolutional Neural Network (Faster R-CNN), You Only Look Once version 5 (YOLOv5), and version 9 (YOLOv9) —were compared for the prediction of nutrient deficiencies in coconut trees using a dataset of 5,720 images of nutrient-deficient coconut tree leaves. YOLOv9 outperformed other models with Accuracy, Precision, and Recall values of 80 %, 98.59 %, and 80.37 %, respectively. Manual verification ensured the correctness of IASD and SICM predictions during model creation, providing farmers and agricultural professionals with a precise, automated tool for managing coconut plantations.

Intercropping in Coconut Plantations Regulate Soil Characteristics by Microbial Communities

Intercropping is a commonly employed agricultural technique that offers numerous advantages, such as increasing land productivity, enhancing soil health, and controlling soil-borne pathogens. In this study, Artemisia argyi, Dioscorea esculenta, and Arachis pintoi were intercropped with coconuts and compared with naturally growing weeds (Bidens pilosa), respectively. The regulatory mechanism of intercropping was examined by analyzing the variability in soil properties and microbial community structure across different intercropping modes and soil depths (0–20 cm, 20–40 cm, and 40–60 cm). The results indicate that intercropping can increase the diversity of soil bacteria and fungi. Moreover, as soil depth increases, the changes in microbial communities weaken. Intercropping reduced soil SOM and increased pH, which is directly related to the changes in the abundance of Acidobacteria in the soil. In various intercropping systems, the disparities resulting from intercropping with A. pintoi are particularly pronounced. Specifically, intercropping with A. pintoi leads to an increase in soil potassium and phosphorus levels, as well as an enhancement in the abundance of Bacillus sp., which plays a crucial role in the suppression of plant pathogenic fungi within the soil ecosystem. The results of the correlation analysis and structural equation modeling (SEM) suggest that the impacts of three intercropping systems on microbial composition and soil indicators exhibit considerable variation. However, a common critical factor influencing these effects is the soil phosphorus content. Furthermore, our findings indicate that intercropping resulted in lower soil nitrogen levels, exacerbating nitrogen deficiency and masking its impact on the microbial community composition.

The Rhino Shield for The Coconut Palm: An Automated Protection System for Coconut Tree

This paper will provide the concept and installation of the automated Rhino Beetle Sheild system, which defends coconut plants against attacks by rhinoceros beetles, are presented in this work. The system makes use of chemical sprayers that are managed by an Arduino board, poles, pumps and electrical valves. It is talked about how well the technique works to keep the coconut trees healthy and prevents beetle infestations. The Rhino Beetle Sheilds potential for use in agriculture is demonstrated by experimental results.

Dampak Konversi Lahan Perkebunan Kelapa Lokal menjadi Perkebunan Kelapa Sawit dalam Perspektif Ekonomi Syariah di Desa Kuala Keritang, Indragiri Hilir, Riau

This aims to reveal the Impact of Converting Local Coconut Plantation Land into Oil Palm Plantations in an Islamic Economic Perspective in Kuala Keritang Village, Kec. Keritang, Kab. Indragiri Hilir, Riau. This thesis uses a qualitative approach by collecting data through observation, interviews, and documentation. The background causes the rubber farmers to switch functions to become oil palm farmers in Kuala Kritang Village is that work as a local coconut farmer is carried out every day and requires difficult maintenance while the price is cheap so that the farmer's income is not enough to meet economic needs. While oil palm work is only once every two weeks, it is more expensive than rubber and is sufficient to meet daily needs. The impact on the welfare of the families of local coconut farmers after the conversion to oil palm farmers in Kuala Kritang Village has a positive impact on farmers, their income increases, work is lighter, there is an increase in assets owned, and families feel more prosperous. If viewed from Maqasid Syariah, the impact of converting local coconut plantation land to oil palm for the economy of the people in Kuala Keritang Village is in accordance with Islamic Sharia.

Insects found in different ages of coconut viridis variety in Sri Tiga Village, Banyuasin District, South Sumatra, Indonesia

Abstract. Anggraini E, Sinaga TM, Irsan C, Herlinda S, Muslim A, Hamidson H, Sefrila M, Kurnianingsih A, Aryani D, Antoni M, Ikhsan Z. 2024. Insects found in different ages of coconut viridis variety in Sri Tiga Village, Banyuasin District, South Sumatra, Indonesia. Biodiversitas 25: 2637-2647. Coconut (Cocos nucifera L.) is a high-value export commodity and has promising potential on the global market. The existence of insect species is very important in coconut cultivation. The coexistence of insects and plants is interconnected because plants provide habitat and food sources for insects. However, the correlation between plants and insects still needs to be discovered to many people. Therefore, a comprehensive assessment of insect biodiversity in an environment is important to be carried out. This study revealed the structure of the insect community associated with coconut plants and weeds around coconut trees. Therefore, this is a novel and pioneering study that aims to determine the insects associated with coconut plants. This study was conducted by surveying community-owned coconut plantations in Sri Tiga Village, Sumber Marga Telang Sub-district, Banyuasin District, South Sumatera, Indonesia. The observation was carried out during July and September of 2023. The data-gathering process involved identifying three coconut plantations with varying ages of coconut trees (8, 5, and 2 years old). Data collection was carried out using the purposive sampling method by direct observations and using traps such as insect nets, light traps, and pheromone traps. Collected specimens were identified using a microscope in the Laboratory of Entomology, Department of Plant Pests and Disease, Faculty of Agriculture, Universitas Sriwijaya. The results of this study found 12 insect species in coconut trees, namely Oryctes rhinoceros Linnaeus 1758, Aspidiotus sp., Nipaecoccus nipae Maskell 1893, Aleurocanthus sp., Apis cerana Fabricius 1793, Cotesia congregata Say 1836, Dolichoderus thoracicus Smith 1860, Oecophylla smaragdina Fabricus 1775, Provespa sp., Pteroma pendula de Joannis 1929, Metura sp., Metisa plana Walker 1883. The predominant insect pests identified were Aspidiotus sp., N. nipae, and Aleurocanthus sp. Furthermore, the most predominant insects that served as insect scavengers were Polyrhachis sp. and O. smaragdina. Meanwhile, in the weeds around coconut trees, there were found six insect species, namely Aulacophora lewisii Baly 1866, Eumorphus westwoodi Guérin 1858, Mactrotermes sp., Conocephalus sp., Dianemobius sp., and Tettigidea sp.