Coconut Plantations Research Articles

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.

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.

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.

Impacts of deforestation and land use/land cover change on carbon stock dynamics in Jomoro District, Ghana

Tropical deforestation in the African continent plays a key role in the global carbon cycle and bears significant implications in terms of climate change and sustainable development. Especially in Sub-Saharan Africa, where more than two-thirds of the population rely on forest and woodland resources for their livelihoods, deforestation and land use changes for crop production lead to a substantial loss of ecosystem-level carbon stock. Unfortunately, the impacts of deforestation and land use change can be more critical than in any other region, but these are poorly quantified. We analyse changes in the main carbon pools (above- and below-ground, soil and litter, respectively) after deforestation and land use/land cover change, for the Jomoro District (Ghana), by assessing the initial reference level of carbon stock for primary forest and the subsequent stock changes and dynamics as a consequence of conversion to the secondary forest and to five different tree plantations (rubber, coconut, cocoa, oil palm, and mixed plantations) on a total of 72 plots. Results indicate overall a statistically significant carbon loss across all the land uses/covers and for all the carbon pools compared to the primary forest with the total carbon stock loss ranging between 35% and 85% but with no statistically significant differences observed in the comparison between primary forest and mixed plantations and secondary forest. Results also suggest that above-ground carbon and soil organic carbon are the primary pools contributing to the total carbon stocks but with opposite trends of carbon loss and accumulation. Strategies for sustainable development, policies to reduce emissions from deforestation and forest degradation, carbon stock enhancement (REDD+), and planning for sustainable land use management should carefully consider the type of conversion and carbon stock dynamics behind land use change for a win-win strategy while preserving carbon stocks potential in tropical ecosystems.

Abysmal Hike in Global Cocoa Price and its Implications on Cocoa Plantations in Tamil Nadu - A Critical Analysis

Cocoa belonging to the family Sterculiaceae has its origin in South America and later it had spread to Europe, Africa and Asia. In Tamil Nadu, cocoa is accommodated as an intercrop in arecanut and coconut plantations especially in South India. But over the past few years, the acreage under cocoa showed a steady decline and the area currently hovers around 5,000 ha especially concentrated in Coimbatore, Theni and Kanyakumari districts of the state. Price volatility is the key player in culminating cocoa plantations in the state. But the recent global shortage of cocoa associated with climatic vagaries and biotic stress like swollen shoot virus and black pod disease in the leading cocoa producers of the world has prompted a positive note in the price of cocoa beans in India. Government policies like ban on deforestation and engaging child labourers for farming and underinvestment in cocoa gardens in the West African countries also added hue to the problem. A record high of ten fold increase in price was observed during the last quarter of 2023 and first quarter of 2024. According to the International Cocoa Organization, global cocoa supply will decline by almost 11% over the 2023/2024 season. Global price has a direct impact on cocoa plantations in the state of Tamil Nadu as many cocoa orchards were cleared due to the lack of remunerative price. But the abysmal price hike in the global front has invited the farmers to rejuvenate the abandoned cocoa plantations and bring new area under cultivation in Tamil Nadu as price was the key player in giving up the crop during 2010s by the farmers. Abysmal hike in global cocoa price has brought a ray of hope for the expanding acreage of cocoa in the state of Tamil Nadu.

Molecular Insights into Red Palm Weevil Resistance Mechanisms of Coconut (Cocos nucifera) Leaves.

Red palm weevil (RPW) (Rhynchophorus ferrugineus) threatens most palm species worldwide. This study investigated the molecular responses of coconut (Cocos nucifera) leaves to RPW infestation through metabolomics and transcriptomics analysis. An RPW insect attack model was developed by placing different RPW larval densitiesin coconut plants and measuring the relative chlorophyll content of different leaf positions and physiological indicators of dysfunction after RPW infestation. The metabolomic changes were detected in the leaves of 10, 20, 30, 40, and 50 days after infestation (DAI) using GC-MS. Certain metabolites (glycine, D-pinitol, lauric acid, allylmalonic acid, D-glucaro-1, 4-lactone, protocatechuic acid, alpha, and alpha-trehalose) were found to be possible indicators for distinct stages of infestation using metabolomics analysis. The influence on ABC transporters, glutathione, galactose, and glycolipid metabolism was emphasized by pathway analysis. Differentially expressed genes (DEGs) were identified at 5, 10, 15, and 20 DAI through transcriptomics analysis of infested coconut leaves, with altered expression levels under RPW infestation. The KEGG pathway and GO analysis revealed enrichment in pathways related to metabolism, stress response, and plant-pathogen interactions, shedding light on the intricate mechanisms underlying coconut-RPW interactions. The identified genes may serve as potential markers for tracking RPW infestation progression and could inform strategies for pest control and management.

Carbon Stock Potential of Coconut Plantations in University Campus: A Case Study from Coimbatore, India

The urgent need to mitigate climate change has prompted researchers to explore various avenues for carbon sequestration. One such avenue is the utilization of natural ecosystems like forests and plantations. Coconut plantations in university campuses play a vital role in carbon sequestration in mitigation of climate change. In this case study, we report the potential of coconut plantation from Bharathiar University campus, India. Four plots of 50 m × 50 m were randomly sampled from the coconut plantation in Bharathiar University campus. Carbon stock of the coconut plantation was calculated based on field survey and allometric equations. A total of 171 trees were recorded from the four plots totalling one hectare (ha) area. The total carbon stock determined for the one ha of coconut plantation sampled from Bharathiar University campus was 31.69 tonne/ha and the mean carbon stock per tree was 0.19 ± 0.06 tonne/tree. We have discussed the carbon stock of coconut tree allocation by above-ground and below-ground parts. This case study highlights the importance of coconut plantations in university campuses in support of curbing the atmospheric carbon concentration. We suggest for plantation of coconut trees in university campuses, that can serve not only as carbon sinks but also contribute to fulfilling the sustainable development goals of the nation.

Design of Rain Water Harvesting System for Efficient Water Scarcity and Flood Management in India

Areas experiencing extensive floods during the rainy season and water scarcity in winter require efficient water resource management. Economical water-harvesting structures such as drystone masonry and upstream-wall cement masonry, with heights ranging from 1 to 2.5 meters, are constructed for catchments smaller than 10, 10 to 20, and 20 to 30 hectares, respectively, utilizing locally sourced materials. These constructions offer significant cost-effectiveness for the location, boasting a B:C ratio of 3.5:1. In certain areas of Assam, Garh structures are constructed, featuring large and lengthy embankments on both sides with an open central section for water flow. Within paddy fields, the entire area is partitioned into small square segments, creating small embankments known as "Dara." which store rainwater for cultivation. Across the entire Western Himalayan region, encompassing Jammu, Himachal Pradesh, and Northern Uttaranchal, Guhl serves as a standardized water harvesting technique. Notably, in Akola and Chittoor districts, the establishment of farm ponds has significantly boosted crop and livestock productivity, along with farm income. Additional irrigation has notably enhanced the yield of various rainfed crops such as pigeon pea, chickpea, groundnut, cotton, and vegetables, as well as mango and coconut plants, with improvements ranging from 5 to 72%. With the availability of harvested rainwater for supplemental irrigation, farmers have also planted additional fruit trees, resulting in increased productivity of existing fruit trees, such as mango (39%) in Chittoor district and coconut (51%) in Vellore district. Expanding the number of rainwater harvesting structures could potentially reduce runoff within the basin by up to 60%. The implementation of Doha Models, involving percolation tanks dug along the length of lower-order seasonal streams in Jalna district of Maharashtra, has increased cropping intensity from 129% to 132%. Remarkably, five out of seven crops have demonstrated a relatively higher percentage increase in yields. The optimal productivity of harvested water is achieved when efficient application methods such as micro-irrigation are employed, targeting high-value crops.

Assessing the Impact of King Coconut Husk Ash and Biochar, Combined with Chemical Fertilizer Application, on Enhancing Soil Fertility in Coconut Plantations

Sustainable soil fertility management is crucial for enhancing productivity in coconut plantations. This study investigated the synergistic effects of king coconut husk (KCH) ash, biochar, and chemical fertilizers on soil properties in a coconut plantation over a short period (4 months). Six treatments were applied: control, chemical fertilizers alone (F), fertilizers with ash (FA), fertilizers with biochar (FB), fertilizers with both ash and biochar (FAB), and fertilizers with half ash and biochar (FA1/2B). Strongly alkaline KCH ash contained significantly higher total and available potassium content levels than mildly alkaline biochar. Data indicated that KCH ash significantly enhanced soil available potassium, electrical conductivity, and organic carbon content compared to the control and F treatments over a short-term period. Even though biochar application demonstrated initial improvements in soil moisture content, a longer study duration may be required to evaluate its influence on other soil parameters comprehensively. Highlighting the synergistic benefits of KCH ash and biochar, FA1/2B treatment exhibited the highest combined index score based on physical, biological, and chemical soil indicators, suggesting its potential for optimizing agricultural outcomes. It emerged as the most promising approach, underscoring the value of exploring sustainable soil amendments derived from agricultural waste streams to promote soil fertility and sustainable coconut production.

Agroforestry mapping using multi temporal hybrid CNN+LSTM framework with landsat 8 satellite imagery and google earth engine

Agroforestry is indeed a traditional practice followed in tropical countries like India. About 28.43 million hectare area is used for agroforest cultivation. By 2050 India has the mission of increasing the area under agroforestry to 53 million hectares. In this study, we have made an effort to map the agroforest areas using the geospatial tools and hybrid deep learning techniques. The land utilized for cultivation and various agroforestry activities such as rubber, tea, coconut, and banana plantation were classified as forest canopy by the existing classifiers taking the tree canopy density as a parameter. In light of proposing a solution to the issue, we have put forth a multi temporal hybrid deep learning framework which is a fusion of convolutional neural network, a deep neural net and long short term memory network to classify agroforestry distinguishing it from the forest canopy using remote sensing data. The experimentation was carried out in the southern districts of India, and Landsat 8 imagery was used to classify the agroforestry of the study area that includes tea, banana, rubber, coconut, and crop lands. An efficient multi temporal hybrid deep learning framework was designed to classify the agroforest plantation distinguishing it from crop lands and forest clusters. The experimental results of multi temporal hybrid CNN+LSTM outperformed CNN, LSTM, BiLSTM model reducing the error rate with respective accuracy and kappa score of 98.23% and 0.88. The proposed method provides a benchmark to accurately classify and estimate the LULC, particularly mapping the agroforest plantation for other regions across the country.

Development of Integrated Coconut Agroindustry from a Circular Economy Perspective: A Literature Review

Abstract Indonesia is one of the world’s largest coconut-producing countries. In 2021, the coconut plantation area in Indonesia reached 3,374,347 hectares, resulting in a total production of 2,853,299 tons. Among the total coconut plantation area, 3,361,145 hectares (99.02%) are dedicated to smallholder plantations, involving 6,003,690 farming households. Therefore, coconuts play a significant and vital role in Indonesia. A circular economy approach prioritizes the effective utilization of resources, minimizing waste, and promoting material recycling to establish sustainable systems. The development of an integrated coconut agroindustry that applies circular economy principles by processing all parts of the coconut fruit to produce value-added products and reduce waste generated from the coconut processing process can create an efficient production cycle and minimize negative environmental impacts. In this paper, a comprehensive review of existing literature is conducted, focusing on the advancement of an integrated coconut agroindustry within the framework of a circular economy. Through maximizing the utilization of all parts of the coconut and enhancing value through innovative approaches, the integrated coconut agroindustry has the potential to play a substantial role in fostering economic growth, preserving the environment, and promoting societal well-being.

Analisis Usahatani Tanaman Sela Pada Lahan Perkebunan Kelapa Di Desa Tontalete Kecamatan Kema Kabupaten Minahasa Utara

This research aims to analyze the income of farmers who cultivate land under coconut trees with intercropping. This research uses primary data and secondary data. Primary data is a source of data obtained directly from original sources or not through intermediaries. Meanwhile, secondary data is data sourced from the Tontalete Village office, Kema District, North Minahasa Regency and the Central Statistics Agency (BPS). Sampling was carried out randomly (Simple Random Sampling). The total research sample was 13 corn farmers and 2 chili farmers. The research results were analyzed using farming income analysis. The results of this study show that farmers utilizing coconut plantation land with intercropping in Tontalete Village, Kema District, North Minahasa Regency, obtained an average production cost of corn intercropping respondents amounting to IDR8.445.822,00 per hectare, with revenue of IDR21.868.750,00 per hectare, resulting in an income of IDR13.422.929,00 per hectare. Meanwhile, respondents growing intercropped chili had an average production cost of IDR10.865.342,00 per hectare, with revenue of IDR69.307.857,00 per hectare, and income of IDR58.442.515,00 per hectare over 8 harvesting periods.