Search Results (11)

Xylooligosaccharides (XOS) are functional oligosaccharides with recognized prebiotic properties and growing industrial relevance, typically obtained through enzymatic depolymerization of xylan-rich lignocellulosic substrates. In this study, a recombinant endo-β-1,4-xylanase (XynA) from Clostridium acetobutylicum was employed for XOS production. The xynA gene was cloned into the expression vector pET-21a(+) and heterologously expressed in Escherichia coli BL21(DE3) under induction with isopropyl β-D-1-thiogalactopyranoside (IPTG). The recombinant protein, with an estimated molecular mass of 37.5 kDa, was verified by SDS-PAGE and Western blot analysis. Functional characterization via thin-layer chromatography revealed that XynA efficiently hydrolyzed beechwood xylan and rye arabinoxylan, predominantly yielding xylobiose. Additionally, the enzyme catalyzed the conversion of xylotriose into xylobiose and trace amounts of xylose. Notably, XynA demonstrated hydrolytic activity against autohydrolysed and alkali-pretreated coconut husk biomass, facilitating the release of XOS. These results underscore the potential of C. acetobutylicum XynA as a biocatalyst for the valorization of lignocellulosic residues into high-value oligosaccharides. Full article

The following study investigated the melting behavior of coconut oil as a phase-change material in shell-and-tube and shell-and-coil thermal energy storage systems. The primary objective was to deepen the understanding of PCM melting dynamics under varying boundary conditions, aiming to optimize TES designs for renewable energy applications. This research addresses a gap in understanding how different heat-transfer configurations and boundary conditions affect melting efficiency. Experimental setups included two distinct heat-transfer surfaces in a cylindrical shell—a copper tube and a copper coil—tested under constant wall temperatures (34 °C for the tube, 33 °C for the coil) and constant heat flux (597 W/m² for the coil). Findings reveal that melting under constant heat flux takes approximately twice as long as under constant wall temperatures, underscoring the critical role of heat-transfer conditions in TES performance. The liquid fraction was estimated using two approaches: image-based analysis and the volume-averaged temperature method. The former proved less reliable due to geometric limitations, particularly when the heat-transfer surface was distant from the shell wall. Conversely, the latter yielded higher accuracy, especially in the shell-and-tube setup. Due to the scarcity of correlations for constant heat-flux conditions, the novel contribution of this work is the development of a modified semi-empirical correlation for the shell-and-coil TES system. For this purpose, an existing model, which demonstrated strong alignment with experimental data, was adapted. The findings suggest that slower melting under constant heat flux could benefit applications needing sustained heat release, like solar energy systems. Future work could investigate additional PCMs or novel geometries to further improve TES efficiency and scalability. Full article

In coastal areas, coconuts are a common crop. Everyone from farmers to lawmakers and businesses would benefit from an accurate forecast of coconut production. Internet of Things (IoT) sensors are strategically positioned to continuously monitor the environment and gather production statistics to obtain accurate agricultural output predictions. To effectively estimate coconut prediction, this study presents an enhanced deep learning classifier called Bi-directional Long Short-Term Memory (BILSTM) with the integrated Lévy Flight and Seagull Optimization Algorithm (LFSOA). LASSO feature selection is applied to eliminate the superfluous characteristics in the yield estimation. To further enhance the coconut yield estimate, the optimal set of hyperparameters for BILSTM is tuned by the LFSOA, which helps to avoid the overfitting issue. For the results, the BILSTM is compared against different classifiers such as Recurrent Neural Network (RNN), Random Forest Classifier (RFC), and LSTM. Similarly, LFSOA-based hyperparameter tuning is contrasted with different optimization algorithms. The outputs show that LFSOA-based hyperparameter tuning in BILSTM achieved accuracy, precision, recall, and f1-score of 98.963%, 99.026%, 99.155%, and 95.758%, respectively, which are higher when compared to existing methods. Similarly, the BILSTM-LFSOA accomplished better results in statistical measures, including the Root Mean Square Error (RMSE) of 0.105, Mean Squared Error (MSE) of 0.011, Mean Absolute Error (MAE) of 0.094, and coefficient of determination (R²) of 0.954, respectively. From the overall analysis, the proposed BILSTM-LFSOA improves coconut yield prediction by achieving better results in all the performance measures when compared with existing models. The results of this study are important to many stakeholders, including but not limited to policymakers, farmers, banks, and insurance companies. As coconuts are an important crop in developing countries, accurate coconut yield forecasting will lead to greater financial and food security in these regions. Full article

This study optimized the input processing factors, namely compression force, pressing speed, heating temperature, and heating time, for extracting oil from desiccated coconut medium using a vertical compression process by applying a maximum load of 100 kN. The samples’ pressing height of 100 mm was measured using a vessel chamber of diameter 60 mm with a plunger. The Box–Behnken design was used to generate the factors’ combinations of 27 experimental runs with each input factor set at three levels. The response surface regression technique was used to determine the optimum input factors of the calculated responses: oil yield (%), oil expression efficiency (%), and energy (J). The optimum factors’ levels were the compression force 65 kN, pressing speed 5 mm min⁻¹, heating temperature 80 °C, and heating time 52.5 min. The predicted values of the responses were 48.48%, 78.35%, and 749.58 J. These values were validated based on additional experiments producing 48.18 ± 0.45%, 77.86 ± 0.72%, and 731.36 ± 8.04 J. The percentage error values between the experimental and the predicted values ranged from 0.82 ± 0.65 to 2.43 ± 1.07%, confirming the suitability of the established regression models for estimating the responses. Full article

Coconut palms (Cocos nucifera L.) are globally significant palms with both economic and cultural value. Despite the increasing demand for coconut products, production is decreasing globally due to palm senility, pests, and diseases. It has been estimated that over half of the world’s coconut palms need to be replaced immediately. The coconut industry has acknowledged that conventional propagation methods are unlikely to yield sufficient high-quality planting material. Therefore, coconut tissue culture is considered a potential solution to this problem. By using coconut tissue culture, a large number of plantlets can be obtained in a short period of time. In this study, the quality of explants and the development stage (visible shoot/non-visible shoot) of coconut used for micropropagation were examined. To our knowledge, little research has been undertaken on this aspect of coconut micropropagation. Our results indicated that tender coconut fruit exhibited an advantage over mature fruits. In addition, coconut plumule explants subjected to an extended storage of 15 days demonstrated enhanced development compared to those without storage. Notably, smaller embryos utilized as explants displayed superior callus formation compared to their larger counterparts. Finally, embryos possessing shoots exhibited improved callus initiation, albeit accompanied by a more pronounced browning effect. Further investigations are required to obtain more knowledge about the most suitable conditions for plumule explants that lead to optimal callus initiation. Full article

The aim of this study was to evaluate the economic feasibility of integrating Jamnapari goats into underutilized pasture lands under coconut cultivations managed by the Coconut Research Institute of Sri Lanka. Naturally grown and improved pasture samples were collected from coconut estates in the intermediate zone of Sri Lanka. Samples were taken randomly using a quadrant, and analyzed for dry matter (DM) yield (kg/ha), crude protein (CP), and crude fiber (CF) contents. An economic feasibility analysis was carried out based on average DM yields and respective carrying capacities of pastures and related production and economics data. The mean DM yield of natural and improved pastures ranged from 2141 ± 193 kg/ha to 3314 ± 212 kg/ha and 4231 ± 407 kg/ha to 9152 ± 531 kg/ha, respectively. Accordingly, CP and CF of natural and improved pastures ranged from 6.3 ± 0.2% to 18.5 ± 0.2% and 30.0 ± 0.4% to 33 ± 0.3%, respectively. Estimated Jamnapari goat carrying capacities for natural and improved pastures were 8 heads/ha and 24 heads/ha, respectively, including does, kids, and a buck. At a 15% discount rate for 10 years, the net present value (NPV) for the coconut monoculture system was approximately 0.45 million rupees, and for integrated systems with natural and improved pastures, it was 1.4 and 4.7 million rupees, respectively. This study concluded that, when goats are integrated with improved and natural pastures rather than maintaining a monoculture, the economic feasibility and profitability will be higher. Full article

The demand for edible fats and oils has sparked interest in alternative vegetable oil sources with a focus on health benefits and new industrial applications. Therefore, this study aimed to assess the potential of using underutilized tropical almond (TA) (Terminalia catappa) nut oil as a source of novel dietary lipids. The fatty acid profile of the screw-pressed TA oil was analyzed by a gas chromatography-flame ionization detector. Physicochemical properties, total phenolics, total flavonoids, and antioxidant properties were evaluated and compared with coconut and almond oils extracted under similar conditions. Thermal behavior and shelf life of TA oil were comparatively analyzed using differential scanning calorimetry and Schaal’s oven test respectively. Interestingly the yield of TA oil (48.67 ± 1.76%) was significantly higher than the almond oil (39.0 ± 0.57%). The TA oil contained more than 56% of unsaturated fatty acids, particularly 31.3% oleic and 24.9% linoleic being the predominant fatty acids. Palmitic acid was the predominant (38.9%) saturated fatty acid. The melting and the crystallization temperatures of TA oil were 14.29 °C and (−0.75 °C) respectively while the melting points of almond and coconut oil were −10.63 °C and 24.8 °C. The physicochemical properties including specific gravity, refractive index, peroxide, acid value, and iodine value were comparable with coconut oil, and they were consistent with the CODEX and SLS standards. The estimated shelf life of TA oil was more than nine months. Moreover, TA oil showed significantly higher phenolic content (2.26 ± 0.08 mg GAE/100 g) and flavonoid content (10.46 ± 1.47 mg QE/100 g) than almond and coconut oils. Further, TA oil showed antioxidant activity with an IC₅₀ of 1574.93 ± 3.44 mg/mL for DPPH, 340.28 ± 1.23 mg/mL for ABTS, and a reducing power of 4.68 ± 0.33 mM Trolox eq/100 g in FRAP assays. Hence, TA oil possessed excellent physicochemical and functional properties suitable to be used as a novel, healthy edible oil. Full article

Typhoon Goni crossed several provinces in the Philippines where agriculture has high socioeconomic importance, including the top-3 provinces in terms of planted coconut trees. We have used a computational model to infer coconut tree density from satellite images before and after the typhoon’s passage, and in this way estimate the number of damaged trees. Our area of study around the typhoon’s path covers 15.7 Mha, and includes 47 of the 87 provinces in the Philippines. In validation areas our model predicts coconut tree density with a Mean Absolute Error of 5.9 Trees/ha. In Camarines Sur we estimated that 3.5 M of the 4.6 M existing coconut trees were damaged by the typhoon. Overall we estimated that 14.1 M coconut trees were affected by the typhoon inside our area of study. Our validation images confirm that trees are rarely uprooted and damages are largely due to reduced canopy cover of standing trees. On validation areas, our model was able to detect affected coconut trees with 88.6% accuracy, 75% precision and 90% recall. Our method delivers spatially fine-grained change maps for coconut plantations in the area of study, including unchanged, damaged and new trees. Beyond immediate damage assessment, gradual changes in coconut density may serve as a proxy for future changes in yield. Full article

Performance evaluation of irrigated agriculture is an important tool that assists in decision-making on water management in the river basin, particularly in tropical semiarid regions. This study was carried out using information from the Jaguaribe River basin, located in the Northeast region of Brazil, which has an important restriction in the availability of water resources and high competition for water use. From a set of indicators (production, water, economic, and social), the overall performance index of irrigated agriculture was estimated (ranging from zero to 1.0) for two scenarios: high water scarcity and low water scarcity. The performance index used was based on the mean value of these security criteria normalized with respect to the maximum value of the indicator for the crop obtained in the sub-basin. A low performance index of irrigated agriculture (less than 0.3) has always been associated with inadequacy of more than one security indicator. Crops with significant cultivated areas and, therefore, requiring a high volume of irrigation, such as rice, sugar cane, banana, and green coconut, require technical interventions related to the management of the soil–water–plant system aiming at improving yield with less water. Under conditions of water restrictions, crops with performance indexes higher than 0.3 should be prioritized. The study presented here for Jaguaribe River basin may support public policies related to irrigation and agronomic techniques necessary to improve the performance of agricultural under tropical dry lands. Full article

In this study, we investigated the biomethane potential of cassava peels from the four most common varieties of cassava grown in Inhambane Province in Mozambique, Chinhembue, Cussi, Cizangara and Nhassumbi. Agro-wastes from coconut wood and jambolan wood processing were also analyzed to give a complete analysis of the most significant sources of agro-waste in the province. The macromolecular composition (carbohydrates, lipids and proteins) was determined and used to calculate the theoretical maximum biochemical methane potential (BMP). The results show that cassava fiber and cassava peel, which are considered to be waste, are viable resources for biomethane production. Further, the results show that cassava fiber and cassava peel have a higher biomethane potential compared with sawdust, and are therefore more suitable for biomethane production. A study to investigate the effect of toxic cyanogenic glycosides and lignin on cassava peels, using pre-treatment techniques to enhance biogas yield, should be carried out. An estimate of how much electricity can be generated based on the availability of agro-waste (cassava residues) and the amount of biomethane produced in our laboratory experiment was carried out. The amount of electricity that can be produced is enough to provide a valuable contribution to the production process in small and medium sized enterprises (SMEs) and in the cassava industry, or some other use in the rural setting. Full article

Water use of human depends on daily life activities. Agriculture is the main activity of Thailand. In the present, there are the extension of agriculture, industry, residence, and community which increase water demand. It can cause a problem of water use among urban, industrial and agricultural. Most agricultural in Samut Songkhram Province, Thailand were planting crops such as pomelo, coconut and lychee, which are famous and generate a lot of income for farmers. The quality and quantity of water is an indicator for measure of the quality and yield of agricultural products. The aim of research is to estimate water use through geographic information system, and remote sensing from Landsat8 satellite. This research considers the main parameters which were; estimation of spatial rainfall runoff and quantity of evaporation, infiltration rate of the soil. To evaluate the amount of soil moisture in order to create soil moisture map for planning the utilization and management of water for agriculture. The classification land use was to investigate from Landsat8 which shown currently agricultural area. The result showed the soil moisture which distributes in each area especially the agricultural area. This information can be used by agriculturists and related organizations to plan and make the decision of growing appropriate plants according to the soil moisture for the sustainability of the agriculture. Full article