ICAPS 2020

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Therapeutic potential of Cinnamomum zeylanicum Blum aqueous bark extract on doxorubicin induced cardiotoxicity in Wistar rats
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Sandamali, J.A.N.; Hewawasam, R.P.; Jayatilaka, K.A.P.W.; Mudduwa, L.K.B.
The effectiveness of doxorubicin as an anti-cancer agent is hampered by its’ life-threatening cardiotoxicity induced by oxidative-stress. As Cinnamomum zeylanicum Blum has proven antioxidant activity, the objective of this study was to find out the therapeutic potential of aqueous Cinnamomum bark extract against cardiotoxicity induced by doxorubicin in Wistar rats. Sample size of the study group was determined and an equal number of male and female Wistar rats were randomly selected into five groups. Group 1: normal-control (distilled water for 14 days, normal saline (10 mL/kg) on 11th day); group 2: plant control (2.0 g/kg of freeze dried plant extract for 14 days, normal saline (10 mL/kg); group 3: doxorubicin control (distilled water for 14 days, doxorubicin (18 mg/kg) on 11th day); group 4: freeze dried plant extract (2.0 g/kg) for 14 days, doxorubicin (18 mg/kg) on 11th day; group 5: distilled water for 14 days, dexrazoxane (180 mg/kg) 0.5 h before doxorubicin (18 mg/kg). Animals were sacrificed on the 15th day, blood was drawn for biochemical analysis and heart tissues were collected for estimation of antioxidant parameters and histological assessment of tissue damage. A significant (p ˂ 0.05) elevation in cardiac biomarkers including cardiac troponin I, AST, LDH and NT-proBNP activity were observed in doxorubicin-control group compared to the normal-control. Pretreatment with Cinnamomum bark extract in the doxorubicin treated rats showed a significant reduction (p ˂ 0.05) in above cardiac biomarkers compared to the doxorubicin-control. A significant reduction (p ˂ 0.05) in reduced glutathione, glutathione peroxidase and glutathione reductase was observed in the doxorubicin control group (Group 3) compared to the normal-control. Total antioxidant capacity as well as superoxide dismutase and catalase activity were markedly reduced (p < 0.05) in the doxorubicin control group. However, pretreatment with Cinnamomum extract was capable of significantly increasing (p ˂ 0.05) all of the above antioxidant parameters compared to the rat group which was treated with doxorubicin alone. A significant increase (p ˂ 0.05) in malondialdehyde concentration, which measures the lipid peroxidation and myeloperoxidase activity, which measures the extent of inflammation was observed in the doxorubicin-control compared to the normal-control. The plant-treated group showed a significant decrease (p ˂ 0.05) in malondialdehyde concentration and myeloperoxidase activity compared to the doxorubicincontrol. Histological assessment of tissue damage was scored according to a scale developed by the authors and doxorubicin-treated group showed a significant damage to the myocardium showing the highest score among the five groups. Plant-treated group showed only a minor degree of damage and showed a significant reduction in the score compared to the doxorubicin control. In conclusion, C. zeylanicum Blum bark extract has the potential to significantly reduce doxorubicin induced cardiotoxicity in Wistar rats.
Tourist volume forecasting: An approach with supervised machine learning algorithms
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Basnayake, B.R.P.M .; Chandrasekara, N.V.
The tourism industry generates almost US$4 billion of income and provides direct and indirect employment to a large number of people in the country. Expert knowledge on the travel behaviour of tourists is an important part of planning and aids decision making for all stakeholders including the government and private business organisations. There was a severe drop in tourist arrivals during the civil war and was also apparent after the more recent Easter Sunday bomb attack. The study compared the predictions of different forecasting models on tourist arrivals in Sri Lanka, in an effort to identify the most appropriate model. The supervised machine learning algorithms (MLA) applied were Time Delay Neural Network (TDNN) and Feedforward Neural Network (FFNN) with two different algorithms namely Levenberg-Marquardt (LM) and Scaled Conjugate Gradient (SCG). Recently, MLA has started playing a vital role as an effective forecasting tool. A better model in forecasting was identified using the performance criteria of the Normalized Mean Squared Error (NMSE). As an initial step, monthly data from December 2019 to January 2000 were standardized to maintain the consistency of data. The aforementioned models were trained for 100, 200 and 500 epochs separately, with different numbers of hidden layers and hidden neurons, and detected the model with minimum NMSE for further training. For the selected model from TDNN, subsequently, the transfer functions and time delays were modified. A better model was identified in 500 epochs for the network with 2 hidden layers of 4 and 3 hidden neurons with tansig transfer functions from time delay of 3 (NMSE 0.3537). For the FFNN model, input combinations were recognized using the Pearson correlation coefficient and Spearman's rank correlation coefficient. Among the trained models with the different input combinations, the model with MA3, MA6, MA9, MA12, and MA15, lag 1, lag 2, lag 3, lag 11 and lag 12 indicated the lower NMSE of 0.5244 where Moving Average (MA) indicates current and past values and depends linearly on the output variable and lags being predetermined fixed quantity of passing time. For the FFNN, a better model was identified with the adjustment of parameters. A better model was identified in 100 epochs for the network with 3 hidden layers of 3 hidden neurons in each layer with tansig transfer functions, a learning rate (ɳ) of 0.01, a combination coefficient (μ) of 0.001 and a decreasing factor as 0.1 and increasing factor as 10 of μ (NMSE 0.2234). For the SCG algorithm, the lowest performance measurement value, NMSE was 0.3193. The model had 500 epochs with 3 hidden layers of 3, 2 and 2 hidden neurons respectively, transfer functions with tansig in all hidden layers, a sigma parameter value of 5e (- 5) and a lambda of 5e (-7). The main conclusion is that all the discussed network models capture the actual behaviour of the testing set while the minimum NMSE was identified in the FFNN with the LM algorithm. The findings of the analysis are beneficial, as tourism is a global service industry and a source of foreign exchange earnings and a key employment generation sector for the country.
A review of product based recommender systems used in online shopping platforms
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Boteju, W.P.A.
Online shopping platforms have drastically changed customer behaviour. Customers can make their choices far easier with the help of recommender systems which are an integral part of modern online shopping platforms. As a result of rapid growth in the number of products in the market and due to the complex lifestyle of people, choosing the right product, takes extra time and effort. Therefore, online shopping platforms provide users with recommender systems to help choose shopping items. A recommender system is a software tool used to recommend items of interest to users. Some recommender systems provide personalized recommendations by analysing user persona, personal interests, and requirements. In other words, there are personalized and nonpersonalized recommendation systems, though personalized recommender systems are becoming increasingly popular and the norm. For example, Netflix movie recommender systems, Amazon product recommender system are among many other generic book and music recommendation systems out there. In this study, we review some of the existing personalized recommender systems and analyse its strengths, weaknesses, and vulnerabilities. The basic components of a recommendation system are Items, Users, and Transactions. Apart from that, recommender systems use filtering methods such as collaborative filtering, knowledge-based filtering, constraint-based, content-based and community-based systems. The study investigated around 100 related research papers. There, we found 43 research studies based on a collaborative filtering approach, 31 based on knowledge-based, 8 studies using both methods as a hybrid approach, with the remaining 26 papers using other filtering methods. The acceptance rate of the personalized recommendations made by collaborative filtering is higher because recommendations are made based on user profile similarity and their purchasing behaviour. For example, 60% of movies are chosen by users based on Netflix's recommendations. This shows that collaborative filtering is effective for personalized recommendations. In contrast, the knowledge-based filtering method uses the description of the product and its properties/features with the profile of the user's preferences. For example, the Pandora music streaming service uses knowledge-based filtering for song recommendation and needs very little information to make similar recommendations. However, there are limitations in collaborative filtering and knowledge-based filtering methods. For example, key limitations of collaborative filtering are 'cold start problem', 'sparsity', and 'scalability'. Knowledge-based filtering shows limitations such as 'overspecialization' and 'domain-dependency'. Studies analysing hybrid recommendation methods have indicated better performance, in making recommendations. Further, we investigated some of the privacy issues and vulnerabilities in recommender systems. To our knowledge, only a handful of studies have investigated vulnerabilities of recommender systems. For example, Cyber-attacks can make significant damages to existing recommender systems. One study has simulated 6 inference attacks per user with 90% accuracy. Thus, security and privacy issues of existing recommender systems need to be explored and investigated. The review paper provides some valuable insights about the usability of existing recommender systems and their vulnerabilities. Future work will specifically focus on security issues of recommender systems and investigating novel systems such as GPT-3 empowered recommender systems.
Activation of wood biochar and red brick using natural coconut vinegar
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Malka, U.K.M.; De Silva, R.C.L.; De Silva, D.S.M.; Chandrajith, R.
Number of studies have been carried out to determine the efficiency of strong oxidizers in activating natural raw materials used in low cost water purification processes. However, rural communities find it difficult to acquire most of such chemicals. Therefore, this study was aimed to determine the ability of natural coconut vinegar, which is a common domestic acidic solution, in activating abundantly available potential water purifying materials to reduce calcium (Ca2+) ions from water, further reducing the water hardness. In this study mature barks of Glyricidia (Glyricidia sepium), Gadumba (Trema orientalis) and Ipil Ipil (Leucaena leucocephala) were collected and air dried. These were carbonized (400-450 °C) in a closed vessel (2 hours) to produce biochar. Both biochar and brick particles in the range of 2.0-5.6 mm were selected for the analysis. For the activation these samples were soaked in natural coconut vinegar (biochar/brick: vinegar, 1:2 V/V) for 24 hours and completely dried in an oven (120 °C) for 3 hours. Laboratory scale glass columns (2 cm in diameter) were used to calculate Ca2+ adsorption and retaining capacities. Filtrates were analyzed for Ca2+ using flame photometer. Ca2+ adsorption and retaining capacities of each material were calculated per unit bulk volume of the material. Each test was duplicated, and the average was recorded. Untreated red brick and biochar of Glyricidia, Gadumba, Ipil Ipil showed Ca2+ adsorption capacities of 0.44, 0.30, 0.31, 0.27 mg cm3 and retaining capacities of 0.19, 0.01, 0.02, 0.02 mg cm-3 respectively. Activated red brick and biochar of Glyricidia, Gadumba and Ipil Ipil showed Ca2+ adsorption capacities of 0.76, 0.58, 0.68 and 0.63 mg cm-3 and retaining capacities of 0.25, 0.20, 0.23 and 0.15 mg cm-3 respectively. Increase in Ca2+ adsorption and retaining capacities were observed in all the materials tested after activation with vinegar. Further studies are continued to use the vinegar activated natural materials in a low-cost domestic drinking water purification process.
Effect of film thickness on characteristic properties of thermally evaporated cadmium sulphide thin films
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Lakmal, A.A.I.; Kumarasinghe, R.K.K.G.R.G.; Seneviratne, V.A.; Dassanayake, B.S.
Cadmium sulphide (CdS) thin films are regarded as one of the most promising materials for heterojunction solar cells. Due to its wide bandgap (~ 2.42 eV), CdS thin films have been used as the window material together with several semiconductors such as InP, CdTe, Cu2S, and CuInSe2. For the future development of photonic devices based on above materials comprehensive studies on CdS window layer throughout all aspects such as deposition technique, temperature, duration, and post-heat treatments, etc. are highly required. In this study, CdS thin films were deposited on the cleaned FTO glass substrates using vacuum thermal evaporation technique by varying the deposition duration to have different layer thicknesses. The temperature of the substrates and the chamber pressure were maintained at 175 °C and 2×10-5 torr respectively. The deposition was carried out using CdS powder (Sigma-Aldrich, 99.995%) containing in an alumina boat. Deposited samples were then annealed in vacuum (pressure 3×10-5 torr) at 300 °C for 30 minutes. The bandgap and optical transmittance of the deposited thin films were studied using UV-Visible spectrophotometry. The surface topology analysis of the deposited thin films was carried out using Atomic Force Microscopy (AFM). A photoelectrochemical cell of (CdS/0.1 mol L-1 Na2S2O3/Pt) was used to investigate electrical properties such as short circuit current (JSC), open circuit voltage (VOC), carrier concentration, and majority carrier type of the semiconductor with the aid of I-V measurements and Mott–Schottky measurements. The structural and crystal properties such as preferred orientation, phase distribution, crystallite size, microstrain, and lattice parameters were studied by employing the grazing incident X-ray diffraction. The calculations were done using the profile fit, Rietveld refinement, and Pawley refinement techniques. All the results revealed that there exists a correlation between the film thickness and the above-considered properties of the CdS thin film. The highest bandgap of 2.43 eV and optimum JSC and VOC of 113 µA/cm3 and 341 mV respectively were observed for the photoelectrochemical cell made by 210 nm thick CdS thin film.
Chemical profile of Terminalia chebula fruit collected from different regions of Sri Lanka and commercial samples from Sri Lanka and India
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Suraweera, K.P.C.D.; Wickramarachchi, S.R.; Tennakoon, T.M.S.G.
Terminalia chebula is a valuable medicinal plant used in traditional medicine. The fruit of T. chebula contains a large number of biologically active chemical compounds. Demand for the herbal drugs is increasing every day and maintaining the quality of herbal drugs is very important. Therefore, the objective of this study is qualitative and quantitative comparison of the chemical profiles of T. chebula fruit (without seeds) of commercial samples and authentic samples. Authentic samples of T. chebula were analyzed to see the effect of climatic zone variation on chemical profile and physicochemical parameters. Authentic samples (SLA) were collected from T. chebula plant itself from onsite visit, from Bibila, Buththala, Padhiyathalawa, Gampaha and Colombo and authenticated from the voucher specimen available at Herbarium, Link Natural Products (Pvt) Ltd (LNP). One composite sample was made according to sampling protocol, WHO 1998, from each region for analysis. Commercial samples are a mixture of fruits obtained from several suppliers from different areas. Commercial samples were obtained separately from three different batches of T. chebula commercial stocks from Sri Lanka (SLC) and India (INC) at LNP. Powdered dried fruits were extracted with 70% aqueous methanol and concentrated using rotatory evaporator. Physicochemical parameters were determined according to WHO and European pharmacopoeia methods. Total tannin was determined using Folin-Denis assay. Crude T. chebula fruit extract was separated by thin layer chromatography (TLC) and high performance liquid chromatography (HPLC). Gallic acid content and gallic acid/ellagic acid ratio were calculated using the peak area of HPLC chromatograms. TLC and HPLC showed a large number of compounds in the crude extract of T. chebula fruit. Both showed similar profiles with variations in intensity among the samples. Physicochemical parameters (without water soluble extractive values), total tannin, gallic acid content, gallic acid/ellagic acid ratio are statistically different among SLA samples (P < 0.05). Except physicochemical parameters, other parameters are statistically similar among SLC and INC (P<0.05). Total tannin content (% w/w) of SLA samples was; Padiyathalawa: 33.40 ± 0.17, Buththala: 43.39 ± 0.41, Gampaha: 41.13 ± 0.61, Bibila: 42.31 ± 0.23 and Colombo: 34.12 ± 0.01. Gallic acid content (% w/w) of SLA samples was; Padiyathalawa: 0.49 ± 0.01, Buththala: 0.98 ± 0.01, Gampaha: 1.03 ± 0.02, Bibila: 0.83 ± 0.02 and Colombo: 1.86 ± 0.04. Gallic acid/ellagic acid ratio (% w/w) of SLA samples; Padiyathalawa: 0.15 ± 0.0038, Buththala: 0.18 ± 0.0009, Gampaha: 0.16 ± 0.0003, Bibila: 0.16 ± 0.0041 and Colombo: 0.68 ± 0.0040. Total tannin content, gallic acid content and gallic acid/ellagic acid ratio vary in different batches of commercial samples. Mean of total tannin content (% w/w) of SLC was 49.14 ± 6.09 and INC is 42.79 ± 0.76. Mean of gallic acid content (% w/w) of SLC was 1.13 ± 0.28 and INC is 2.25 ± 0.69. Gallic acid/ellagic acid ratio (% w/w) of SLC was 0.30 ± 0.07 and INC is 0.43 ± 0.05. Chemical composition and quality of T. chebula. dried fruit depend on the geographical location, maturity stage, growth condition and raw material processing condition.
CNN based deep learning model for tomato crop disease detection
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Gunarathna, M.M.; Rathnayaka, R.M.K.T.
Tomato is one of the most commonly cultivated solanaceous short duration vegetable crops, grown in outdoor and indoor conditions, worldwide. However, unfortunately, many diseases affect these crops which have an impact on quality and the quantity of the produce, agricultural productivity, and causes considerable economic losses to the producers and to the contribution to the growth of the agricultural sector. Therefore, continuous monitoring of the crop is required throughout the growing stage to identify the diseases. The most traditional way of identifying diseases is naked eye observation, which is tedious and time-consuming. Today, advances in computer vision paved by deep learning have led to a situation where disease diagnosis is based on automated recognition. The main objective of this study is to develop an accurate tomato disease classification model which eliminates human error when identifying diseases. Due to a variety of similar disease and pathological problems, even experienced agronomists and plant pathologists often fail to recognize the correct disease. This computer vision system will assist agronomists in detecting a variety of tomato crop diseases. The proposed algorithm consists of four main steps; data collection, data pre-processing, CNN model creation, and evaluation of performance metrics. A leaf is a good indicator of the tomato’s health. Therefore, tomato leaf images belonging to 10 different classes with a resolution of 256x256 were collected from the Internet to build, validate, and test the model. Collected images were normalized and image augmentation techniques were applied to increase the size of the training data set in the preprocessing phase. The CNN model of the study was built from scratch using the Keras library, which runs top of the Tensorflow backend. The model comprises four convolutional blocks followed by batch normalization, max pooling, and dropout layers. Two dense and flatten layers were also included at the end. A time-based learning rate scheduler was used with an initial learning rate of 0.001, momentum of 0.5, an epoch of 15 and a batch size of 27. The final model was able to achieve a training accuracy of 94% and a testing accuracy of 92%. This proposed system would encourage tomato cultivators to detect diseases at an early stage and start treatments without relying on experts. In the future, we hope to build an ensemble approach to classify plant diseases with real-time images towards the development of a decision support system.
A method of obtaining a solution of �� +�� ≡ �� (mod ��) when �� is prime and �� is a primitive root modulo ��
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Wijerathna, P.A.S.D.; Ranasinghe, P.G.R.S.; Senavirathna, S.S.M.A.C.
The congruence relation modulo a positive integer identifies two integers if and only if their difference is divisible by that positive integer. The modern theory of congruences was developed by Gauss at the beginning of the 19th century. Several formulations are established in solving congruences of various types. In this study, we introduce a method in solving congruences of the form 𝑎 𝑝𝑥+𝑞𝑦 ≡ 𝑏 (mod 𝑚) for a prime number 𝑚 and integers 𝑎, 𝑏, 𝑝, and 𝑞. Since we do not have a standard generalized method of obtaining a solution for the aforementioned congruence type, some restricted forms of it were studied. In this work, we especially focus on the congruences of prime modulus 𝑚 and 𝑎 is a primitive root modulo 𝑚: If gcd(𝑎, 𝑛) = 1 and 𝜑(𝑛) is the order of 𝑎 modulo 𝑛, then 𝑎 is called a primitive root of the integer 𝑛. Here 𝜑(𝑛) is the Euler’s Phi function (totient function) of 𝑛, that counts the number of integers less than or equal to 𝑛 which are relatively prime to 𝑛. In or method, first, a solution system for 𝑎 𝑝𝑥+𝑞𝑦 ≡ 1 (mod 𝑚) is obtained. That solution system is used with a transformation to obtain a solution of the congruence 𝑎 𝑝𝑥+𝑞𝑦 ≡ 𝑏 (mod 𝑚). We prove that a solution of 𝑎 𝑝𝑥+𝑞𝑦 ≡ 1 (mod 𝑚) can be obtained by (±𝑘𝜑(𝑚) + 𝑥0, ±𝑙𝜑(𝑚) + 𝑦0), where 𝑘 and 𝑙 are non-negative integers. When (𝑥𝑜, 𝑦𝑜) is a solution of 𝑎 𝑝𝑥+𝑞𝑦 ≡ 1 (mod 𝑚) with both 𝑥𝑜, 𝑦𝑜 are not simultaneously zero, the obtained solution is transformed to a solution of 𝑎 𝑝𝑥+𝑞𝑦 ≡ 𝑏 (mod 𝑚) when gcd(𝑝, 𝑞) |𝑏. The former result can be used to obtain a solution for the congruence in the form of 𝑎 𝑝𝑥+𝑞𝑦 ≡ 𝑏 (mod 𝑚) when 𝑚 is prime and 𝑎 is a primitive root modulo 𝑚. In future, we hope to generalize this method when 𝑚 is composite and 𝑎 is not a primitive root modulo 𝑚.
Indole Acetic acid production and pathogen growth control abilities of endophytic fungal assemblages associated with two newly improved Oryza sativa varieties of Sri Lanka
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Pathmanathan, N.; Deshappriya, N.; Manamgoda, D.S.; Sandamali, T.G.I.
Newly improved rice varieties, highly dependent on agrochemicals, have been introduced to meet the increasing food demand in Sri Lanka. Health and environmental problems caused by extensive use of agrochemicals in rice cultivation necessitate investigations on alternative, less harmful methods for maintaining high productivity and disease management. Endophytic fungi (EF) of many crops have been reported to have the ability to enhance plant growth through the synthesis of Indole Acetic Acid (IAA) and to possess mechanisms of fungal pathogen control. Therefore, the present study was carried out to assess the levels of IAA production by the endophytic fungi (EF) isolated from two rice varieties, At 362 and Bg 352 with a view to utilise the high producers of IAA as a means of increasing rice plant growth and productivity. Screening test for growth inhibition of two known rice pathogens, Rhizoctonia solani and Bipolaris oryzae, the causative agents of Sheath blight and Brown spot diseases respectively was carried out to test the possibility of using isolated EF for management of the two pathogens. Healthy plant samples of the selected rice varieties were collected during the Yala and Maha seasons (2019) from Anuradhapura, Kurunegala, Gampaha and Kalutara districts. Endophytic fungi present on leaves, stems and roots were isolated onto 2% Malt Extract Agar medium. Fungal isolates were identified based on morphological characters and ITS gene sequencing. A total of 235 EF isolates belonging to 26 genera were isolated from the two rice varieties. IAA production by these fungal isolates was evaluated using Salkowski’s assay. The effect of the isolated EF on the growth of the two fungal pathogens was tested under in-vitro conditions using the dual culture assay. All experiments were conducted in triplicate and data were statistically analysed using one-way ANOVA and Tukey’s pairwise comparisons. Amongst the tested isolates, Curvularia sp and Aspergillus terreus isolated from Bg 352 produced IAA at significantly high levels of 15.642 µg/mL and 15.117 µg/mL respectively (P < 0.05). Dual culture studies showed that Sarocladium oryzae and Rhizopus microsporus isolated from At 362 inhibited the colony growth of R. solani by 68.5% and 58.7% respectively whilst the growth inhibition of B. oryzae was 38.5% and 43.1% respectively. The preliminary tests of this study indicated that some of the EF associated with the two rice varieties have the ability to produce significantly high levels of the growth promoting phytohormone IAA whilst some others have the means to control the growth of two common rice pathogens and therefore have the potential to be used for increased productivity of rice as well as for the control of the two rice diseases after further testing.
Finding co-rotation resonance in spiral galaxies using localized observable features
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Abdeen, M. S.; Kennefick, D.; Kennefick, J.; O’mara, H.; Bassett, C.
The co-rotation resonance of a spiral galaxy represents a stable region within the galactic structure where the velocity of the disk material and the spiral arm global pattern speeds concur with each other. The cardinal objectives of studying these regions include but are not limited to; checking the validity of theoretical predictions, getting a better understanding about the disk material distribution process and to study the evolution process of galaxies. Often these regions are attributed to galactic scale habitable zones; hence the study is undoubtedly a worthy pursuit. The co-rotation resonance region creates a radius of localized observable features that can be used to locate and study them. The current study focusses on using multiple methods such as spiral arm overlays by measuring pitch angles, arm-inter-arm contrast plots, 2D-fast Fourier transformation plots and 3-D surface intensity plots. Ten nearby galaxies were observed in 3.6 µm, 8 µm and Bband based on the availability and the clarity of image data. It is important to emphasize that the different wavelengths were selected based on their unique characteristic abilities to trace different structural components of the galaxy. B-band usually depicts the newly formed young stars while the 3.6 µm images are sensitive to the old stellar population. 8 µm images denote the gas and dust lanes; hence they are usually ascribed with the location of the underlying density waves. As the initial phase, we create composite images using the different wavelengths and de-project them to a face-on orientation. The standard, Image Reduction and Analysis Facility (IRAF) ellipse fitting tasks are used in the de-projection process while considering the available published de-projection parameters in the NASA/IPAC Extragalactic Database (NED). The arm-inter-arm contrast plots require an additional symmetry enhancement process to better visualize the underlying symmetry. The most probable locations for the co-rotation radii were identified using each method and were compared against previous studies found in the literature. Most of the results are compatible, while there are a few galaxies with notable deviations. Considering each galaxy and the results obtained through each method, the largest sample standard deviation of s = 1.5 kpc is recorded for NGC 1566, while the smallest, s = 0.31 kpc is recorded for NGC 5194. NGC 3031 shows the largest deviation when comparing our results with the values found in the literature. To better understand the deviations, further analysis is required using larger sample sizes and more wavelengths.
Morpho-molecular characterization of Lasiodiplodia and Diaporthe species infecting Solanum melongena L. (brinjal) in Gampaha district
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Koshila, H.V.A.S.; Dias, R.K.S.; Wanigatunge, R.P.; Edirisinghe, P.
Solanum melongena L. (brinjal) is a vegetable belonging to the family Solanaceae and a popular commodity among consumers. Brinjal plants are infected by numerous fungal pathogens causing a wide range of diseases such as anthracnose by Colletotrichum sp., stem and leaf lesions by Phomopsis vexans (anamorph of Diaporthe), and early blight by Alternaria solani which significantly reduce the yield. The objective of this study was to isolate and identify the fungal pathogens associated with leaves of S. melongena in the Gampaha district. Necrotic or prematurely wilted leaves of S. melongena were collected and associated fungi were isolated onto PDA medium. Pathogenicity was confirmed by wounded and non-wounded inoculation of a seven-day old isolate onto healthy S. melongena leaves and the confirmed fungal pathogens were identified using their morphological, cultural characteristics and analysis of the internal transcribed spacer region (ITS1-5.8S-ITS2). Fifteen fungal isolates were isolated from necrotic leaves of S. melongena. Three fungal isolates (Isolates H32A, H32B and U11) were identified to be pathogenic on leaves of S. melongena based on the pathogenicity test. A necrotic leaf spot was initiated at the site of inoculation with isolates H32A and H32B in both wounded and nonwounded inoculations, which later developed into wilting and premature falling of the leaf. Leaf blight was observed with non-wounded inoculation of isolate U11. Morphological characters of isolates H32A and H32B were similar, with fluffy, blackish-grey, septate mycelia and dark brown oval shape spores with a septum in the middle. Both had similar growth rates of 2.25 cm/day. They were morphologically identified as Lasiodiplodia sp. Yellowish grey color pigmentation was observed in the isolate U11 which produced aseptate hyphae but could not be identified by its morphological characteristics. The nucleotide sequence of ITS region confirmed the morphological identification of isolates H32A (MT990527) and H32B (MT990528) as Lasiodiplodia theobromae with 99.81% sequence similarity to L. theobromae (IRNKB244) at NCBI database. Further, isolate U11 (MT990529) showed 99.82% sequence similarity with Diaporthe eugeniae (ASHM304) at NCBI database. L. theobromae is reported to cause fruit rot in brinjal, while Diaporthe sp. has caused stem and leaf lesions. L. theobromae and D. eugeniae were confirmed to be pathogenic on S. melongena L. (brinjal) plants in the Gampaha district and further studies will be conducted to develop an environmentally friendly strategy to manage above mentioned diseases.
Investigation of antihyperglycaemic activity of hexane extract of polyherbal mixture in streptozotocin induced diabetic rats
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Sampath, S.N.T.I.; Jayasinghe, J.M.S.; Attanayake, A.P.; Karunaratne, V.
A homemade Ayurvedic remedy made of cloves of Allium sativum, leaves of Murraya koenigii, seeds of Piper nigrum and dried fruit rinds of Garcinia quaesita is considered as an antidiabetic polyherbal mixture. This polyherbal mixture has been used for the treatment of diabetes mellitus and dyslipidaemia in Sri Lankan traditional medicine. The in-vitro antioxidant and in-vivo acute antihyperglycaemic screening of hexane, ethyl acetate and methanol extracts of the above polyherbal mixture were studied and the hexane extract showed a significant antioxidant and dose dependent antihyperglycaemic activity when compared with the two extracts. Hence, the present study was aimed to further investigate the effect of administration of the hexane extract of polyherbal mixture at the optimum effective therapeutic dose for 30 days on serum glycaemic parameters in streptozotocin induced diabetic rats. Diabetes was induced in male Wistar rats by injecting with streptozotocin at the single dose of 65 mgkg-1 . Group one and two considered as the healthy untreated control, diabetic untreated control rats and received standard animal food and distilled water daily for 30 days (n = 6 /group). Group three and four were diabetic rats and were treated with the hexane extract (25 mgkg-1 ) and glibenclamide (positive control - 0.5 mgkg1 ) daily for 30 days respectively (n = 6 /group). Body weight of treated and control group rats were measured on 1 st, 7th, 14th, 21st and 28th day of the experiment. On the 30th day, all experimental rats were euthanized and blood was collected by cardiac puncture. The antihyperglycaemic activity was evaluated by determining the changes of fasting serum glucose concentration in each group using oral glucose tolerance test on 1 st , 7 th, 14th, 21st and 28th day and analyzed through total oral glucose tolerance curve (TAUC) values. Further, the percentage of glycated haemoglobin (HbA1C) and fasting serum glucose concentration were determined as glycaemic parameters in each group. The body weight was increased in healthy untreated control group and treated groups while the diabetic untreated control group showed a 10% reduction of body weight during the intervention period, indicating the treatment led to control loss of body weight. The oral administration of hexane extract and glibenclamde, lowered the TAUC values by 21% and 35% respectively and these values were statistically significant compared with TAUC value of diabetic untreated group (p < 0.05) on the 28th day of experiment. There was a statistically significant reduction in the HbA1C (27%, 33%) and the fasting serum glucose concentration (23%, 33%) in hexane extract and glibenclamide treated diabetic rats when compared to streptozotocin induced untreated diabetic rats (p < 0.05). The findings of the current study revealed that the hexane extract of the polyherbal mixture is a potential source to develop antidiabetic agent/s and further investigations are warranted to study the cellular antidiabetic mechanisms.
Reduction of experimental error in coconut research by choosing proper data analysis techniques
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Fernando, W.H.H.; Waidyarathn, K.P.; Jayasundara, D.D.M.
Accurate data analysis techniques are essential in field experiments to correctly understand the influence of independent variables on the dependent variable/s. This study compares different statistical techniques used in analyzing longitudinal data (nut yield data collected in multiple years) of a coconut field experiment. Longitudinal studies are necessary for coconut research due to its perennial nature. However, these experiments often have high variability due to the heterogeneity nature of coconut palms, where individual palms display inconsistent temporal behaviour. High variation among the individuals in similarly treated plots makes treatment mean sensitive to those fluctuations ultimately masking the true treatment effect. Even careful planning of the experiment cannot ensure the total elimination of this component. The study highlights the ways in which how this unaccountable variability should be handled to obtain a precise research output. There are many types of statistical techniques used in analyzing data from different experimental designs to achieve optimal research outcomes. This study compares different statistical techniques applied to a randomized complete block design (RCBD), the most frequently used experimental design in coconut research, using a long term coconut fertilizer study. The example illustrates the appropriate types of analyses to meet the precise analysis output by evaluating the model residuals and the Coefficient of Variations (CV). CV, the ratio of the standard deviation to the mean (total average of the design), is a measure of relative variability. In particular ANOVA, Mean Square Error of ANOVA can be used as the standard deviation of the design because Standard Error (SE) of a statistic (usually an estimate of a parameter) represents the standard deviation of its sampling distribution. In this study, Repeated Measures Analysis of Variance (RMANOVA) was used as the classical method. Improved methods used were Linear mixed model and Multivariate Analysis of Variance(MANOVA) with two principal components (representing ≥ 78% variation of the data) as dependent variables. Adequacy of all methods was accepted after checking normality with the Shapiro-Wilk test, homogeneity of variance with Levene’s test, and independence of residuals with the Box-Pierce test. CV resulted from RMANOVA applied on RCBD was 39.2%, while it was 16.51% from the Liner mixed model. The lowest CV (10.04%) resulted from MANOVA with two principal components indicates that it can be more efficiently used to analyze long term experiments of coconuts. The consistency of the results should be studied further with a few more similar kinds of data sets. In addition to the above statistical analysis techniques, Bayesian inference methods will be studied for further improvements in the results.
Framework to select the most suitable production line in an apparel firm in Sri Lanka: use of Analytical Hierarchical Process
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Thalagahage, N.T.H.; Niwunhella, D.H.H.; Wijayanayake, A.
The apparel industry is considered as one of the most labour-intensive industries in the world despite the technological advancements and the amount of automation. Line planning in the garment industry is the process of scheduling and allocating production orders to production lines according to the product setting and due dates of manufacturing completion. Most of the apparel manufacturers in Sri Lanka have switched to lean model production, in which large sewing departments are split into smaller, self-balancing sewing lines. The decisions that address the production line selection process for a particular production order still heavily rely on production planners, based on their experience. These decisions tend to be neither consistent nor scientific because of the lack of interdepartmental connectivity. Little emphasis has been placed on the impact of the planning considerations and ways to apportion certain production orders to the appropriate production system with specific characteristics. This problem is addressed in the research through the development of a multi criteria decision making framework to enable the incorporation of all the parameters to select the best production line for a particular sales order using Analytical Hierarchical Process (AHP). AHP method is adopted for decision making which models multiple, possibly conflicting factors dependent on each other and it makes appropriate trade-offs to recommend well-balanced solutions to different stakeholders. The production line selection criteria identified through expert opinions and literature review were applied in the AHP conceptual model. 23 factors were identified and they were categorized under 5 areas which are characteristics of the product, characteristics of the production order, characteristics of the production line, technical support and quality parameters. In order to build the AHP model, 4 manufacturing firms and 4 senior and middle level managerial industrial experts from each firm were selected and interviewed through AHP questionnaires. After the pairwise comparisons, each criterion was weighted and prioritized. Most of the interviews resulted in high priority for delivery date, technical infrastructure, skills inventory of the line, the efficiency of the line, and cadre requirement while the ability to adopt changeovers, prioritization of machine service, and infrastructure support by the technicians were given low priorities. This interprets that, for any kind of a production order the mostly prioritized criteria are important to be considered. Therefore, focusing on them in line selection would lead to improved planning efficiency. After the criteria comparison, each alternative production line was given a score against the planning criteria and the production lines were ranked in order to select the best production line. Through data analysis, it was found out that the results obtained from different industrial experts representing different apparel manufacturing firms vary from each other depending on individual perspective and policies inherent to the manufacturing firm. However, the framework can relate to any apparel manufacturing firm by allowing Decision Makers to select the valid criteria depending on the Production Order and its related parameters. Also, the framework can be used for other manufacturing industries with few modifications and assumptions. In order to avoid the subjectivity in AHP method, a Linear Programming model can be developed as a future improvement and optimize the production lines selected through AHP ranking.
Farmers’ knowledge, perception, and practices on agrochemical usage in upper Uma Oya and Kumbukkan Oya watersheds in Sri Lanka
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Sumudumali, R.G.I.; Piyathilake, I.D.U.H.; Randika, J.L.P.C.; Jayawardana, J.M.C.K.; Udayakumara, E.P.N.; Gunatilake, S.K.
Pesticides are widely used to reduce pre- and post-harvest losses in cultivations due to the pest infestations. A semi-structured questionnaire survey and key informant interviews were carried out to compare the patterns of pesticide usage, perception and knowledge of farmers in one of the main vegetables growing areas of upper Uma Oya and main field crop cultivated areas of upper Kumbukkan Oya watershed in Sri Lanka. The primary data were collected covering two main seasons (Yala and Maha of 2019/2020) in Uma Oya (n = 61) and Kumbukkan Oya (n = 65) watersheds. The cultivated major crops in Uma Oya watershed area are potato, bean, tomato and cabbage whereas rice, cowpea, and maize are grown in Kumbukkan Oya watershed. According to the results, active ingredients of 26 insecticides, 21 fungicides, 17 herbicides were used by farmers for their cultivations in both sampling areas. The most frequently used pesticides were insecticides (51.2%) followed by fungicides (45.8%) and herbicides (3.0%) in Uma Oya watershed while in Kumbukkan Oya watershed herbicides usage (44.4%) was followed by insecticides (36.0%) and fungicides (19.6%). More than 50% of farmers in Uma Oya watershed mainly used five insecticides namely Abamectin, Carbosulfan, Chlorantraniliprole 20% + Thiamethoxam 20%, Profenofos, three fungicides of Chlorothalonil, Mancozeb, Propineb and only three types of herbicides. More than 80% of the farmers in the Kumbukkan Oya watershed used to utilize herbicides of MCPA 600 g/l and MCPA 400 g/l as major pesticides. Most of these active ingredients used in this study were belong to the World Health Organization hazard classification class “U” which is unlikely to present an acute hazard. Highly used insecticides Abamectin, Carbosulfan, Profenofos MCPA 600 g/l and MCPA belongs to WHO hazard class II (moderately hazardous) chemicals while fungicide Chlorothalonil belongs to hazard class III (slightly hazardous) chemicals. There is no significant difference observed in mixing (χ2 = 2.567, α = 0.05) and selecting the pesticides (χ2 = 0.403, α = 0.05) in both regions. Nearly 67.5% of the respondents applied a mixture of different chemicals because they believe such mixtures save their time (20.6%) and unsure about the pesticide strength of controlling pests and diseases (34.2%). Farmers selected pesticides mainly based on the information provided by the pesticide retail shop owners or dealers (72.2%). Meanwhile, only 7.1% of farmers seek advice from agricultural instructors/extension officers on pest management decisions. Only 31.0% of respondents had training on the correct use of pesticides and such training were conducted by private sector organizations involved in pesticide marketing. Most of the farmers washed their pesticide sprayers in their field (62%) while 23% washed in the irrigation canal and 13% washed in nearby waterways. Eight percent of farmers carelessly disposed of the pesticide leftovers and containers in the open fields. The findings indicated pesticide application in the study areas represents a potential risk for the environment and farmers.
Microfractionation-based approach to screen potential specialized anti-microbial metabolites of Sri Lankan marine sponges
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Gamage, J.B.; Kosgahakumbura, L.N.; Cárdenas, P.; Jayasinghe, R.P.P.K.; Hettiarachchi, C.M.; Gunasekera, S.
The discovery of bioactive specialized metabolites from marine invertebrates has increased significantly during the last two decades. Marine sponges (phylum Porifera) are the existing oldest metazoan group that host rich microbial communities, and are considered as potential sources of future drugs in pharmacological and biomedical industry as they produce an impressive array of anti-inflammatory, immunosuppressive, neurosuppressive, antitumor, antiviral, and antimicrobial compounds. Of the few studies that have been carried out on such products in Sri Lankan marine sponges, the discovery of bioactive peptides has been largely overlooked. Therefore, a study was carried out to screen potential specialized anti-microbial metabolites especially peptides and sterols in Sri Lankan marine sponges with the intention of large scale isolation of targeted bioactive molecules. Bioassay-guided micro fractionation is an efficient method for the rapid screening of a large number of samples using only a small amount of starting material. Aqueous extracts (60% methanol) and organic extracts (Dichloromethane: methanol 9:1) of 20 different sponge species collected in coastal waters in Sri Lanka were micro fractionated into 48 fractions in deep well plates (1 mL per well), using reversed-phase HPLC. A volume of 100 µL from each fraction was tested for antimicrobial activities and the wells with antimicrobial activity were analyzed by LC-MS coupled to a PDA detector to identify the molecular ions of the bioactive compounds. Of all the 40 extracts, 18 extracts produced by Rhabdastrella globostellata, Aciculites sp., Rhabderemia sp., Erylus sp, Aulospongus sp., Manihinea sp., Agelas sp., Phakellia sp., Topsentia sp., four species belonging to order Haplosclerida and one species belonging to order Suberitida showed bioactivity against Staphylococcus aureus (ATCC 25928). Stylissa massa showed bioactivity against Escherichia coli (ATCC 35218) while Aulospongus sp., showed bioactivity against Candida albicans (ATCC 90028). Sponge species were identified using their morphology, spicule arrangement and DNA barcoding. The 5’ end of CO1 and 28S rRNA genes were sequenced for both forward and reverse direction. Sequences were compared using the BLASTn tool with the NCBI database in order to narrow down and identify the possible lowest taxonomic level. The wells that indicated bioactivity contained fractionated extract at ≤ 0.2 mg/mL concentration. Organic extracts of Aciculites sp., Topsentia sp. and the aqueous extract of Erylus sp. were the most active at ≤ 0.05 mg/mL. The targeted masses obtained from LC-MS will be isolated in large scale and the structural characterization of isolated specialized anti-microbial metabolites will be determined using LC-MS and NMR. Furthermore, these micro fractions will be subjected to lymphoma cell toxicity assay to identify potential anticancer compounds.
Diversity of Firmicutes in selected hot water springs of Sri Lanka by 16S metagenomic sequencing
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Samarasinghe, D.G.S.N.; Wanigatunge, R.P.; Magana-Arachchi, D.N.
Thermophiles have the ability to survive in environments with very high temperatures. Hot springs provide unique natural environments for these thermophilic microorganisms. In recent years, hot water springs and thermophilic microorganisms have gained attention due to their industrial and biotechnological importance. Among the thermophilic bacteria, a large number of metabolites can be found in the phylum Firmicutes. Different species of Firmicutes show various ecological optima. Even though Sri Lanka harbors many hot springs, majority of them are not yet explored and require comprehensive studies to unravel the inhabitant microbial diversity, specially the phylum Firmicutes. This study was focused into uncovering the resident thermophilic Firmicutes which could be unculturable and their diversity in four major hot springs namely, Mahapelessa, Wahawa, Maha Oya and Nelumwewa using 16S rRNA metagenomic sequencing. Water samples were collected from the four hot springs in which the surface temperature ranged from 44.2 to 53.8 °C. Further, a water sample from a natural spring located in Digana (26.9 °C) was used as the control. Genomic DNA was extracted from the water samples using modified Boom’s method and was subjected to 16S rRNA metagenomic sequencing (16S V3-V4 region) using Illumina platform. The results were analyzed using GAIA: Metagenomics data analysis software to identify Firmicute bacteria (Operational taxonomic units/ OTU) and to determine their relative abundance. OTU analysis was carried out with a cut-off similarity value at 97%. The relative abundance of Firmicutes in each spring is as follows: Mahapelessa (23.7%), Wahawa (0.8%), Maha Oya (0.9%), Nelumwewa (5.8%) and Digana natural spring (4.2%). The class Clostridia and Bacilli were the most abundant classes observed in hot springs. A total of twenty-one species were affiliated with the phylum Firmicutes, among which 18 species were only detected in hot water springs while the rest of the three species (Clostridium sp., Flintibacter butyricus and Oscillibacter sp.) were only detected in the natural spring. Nine different bacterial species were unique to Mahapelessa hot spring including; Bacillus licheniformis and Bacillus thuringiensis belonging to class Bacilli, Caldanaerocella colombiensis, Desulfotomaculum reducens, Geosporobacter sp., Geosporobacter subterraneus, Pelotomaculum isophthalicicum, Salimesophilobacter vulgaris and Tepidibacter sp. belonging to the class Clostridia. The two bacterial species; Carboxydocella manganica and Faecalibacterium prausnitzii were only recorded from Maha Oya while Clostridium islandicum was reported from Maha Oya and Nelumwewa hot springs. Bacillus pumilus and Sporacetigenium mesophilum were present in Mahapelessa and Wahawa hot springs. Anaerosolibacter carboniphilus was found in both Mahapelessa and Nelumwewa while Anaerobacterium chartisolvens was detected in all hot water springs except Wahawa. Bacillus sp. and Paenibacillus sp. were common in all the hot water springs. When compared to the natural spring, the four hot water springs showed high bacterial species diversity (85%). Results from this study confirm the uniqueness of bacterial species belonging to phylum Firmicutes in hot water springs than in the natural springs. More comprehensive studies on these Firmucutes are needed to identify their potential to be used in industrial and biotechnological applications.
Adulteration detection of Cinnamomum verum with BarHRM technology
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Peiris, M.A.L.M.; Silva, F.H.C.; Wijesinghe, W.R.P.
Sri Lanka is the premier exporter of the true cinnamon (C. verum) in the global market. However, Sri Lankan true cinnamon faces a major threat due to severe competition and adulteration from its substitute cassia (e.g. C. aromaticum). It costs one-third of the price of C. verum but it contains coumarin which is a hepatotoxin at substantial amounts (up to 5%) whereas true cinnamon has only trace amounts (about 0.004%). Therefore, it is paramount to detect adulteration of C. verum from its substitute to protect the reputation of true cinnamon. Chemical and morphological methods can detect the adulteration of C. verum but when it comes to admixtures and value-added products, morphological and chemical methods are not accurate. Hence, the objective of the research was to develop a molecular assay to detect adulteration in commercially available cinnamon products. In this study, DNA sequences of C. verum and C. aromaticum were extracted from the National Center for Biotechnology Information (NCBI) using the keyword “Cinnamomum” and selected barcode region “rbcL”. Gene-specific novel markers were manually designed targeting the identified diagnostic SNP sites. Primer properties were analyzed using NetPrimer software and primers with the best qualities were selected. DNA extraction of cinnamon was done using CTAB method with slight modifications. Real-time PCR and melting curve analysis at 65 ⁰C to 95 ⁰C with a ramping rate of 0.05 ⁰C (Qiagen, Germany) was performed. The melting curve analysis and principal component analysis of the data demonstrated a clear distinction between the two species and results confirm that rbcL gene-specific primers can be used to distinguish C. verum from C. aromaticum. Further, this assay has a great potential to quantify adulterants in commercially available cinnamon samples and extremely valuable for an accurate and rapid adulteration detection of cinnamon value-added products in the global and local market.
Non-Newtonian fluid flow in a long-distance pipe with circular cross section
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Imasha, V.S.; Karunathilaka, N.G.A.
In many chemical and process industries, the fluid should pump through pipes over long distances from a storage to various processing plants. The substantial frictional pressure loss both in the pipeline and in the individual units is a common problem in these applications. Therefore, it is often necessary to calculate the pressure gradient, selection of optimum pipe diameter, and the flow rate. In this work, we develop a mathematical model for the description of the laminar, steady and incompressible fully developed flow of a Non-Newtonian polymer fluid in a circular tube of constant radius. The fluid flow has been studied using the Giesekus fluid model and the radial stress equations. Navier Stokes equations have been used as the governing equations and Giesekus constitutive relation has been used to model the stress tensor. No-slip boundary conditions at the outer wall and non-singularity conditions at the centre have been used to close the system. Nondimensionalized coupled problem has been solved analytically for the velocity field and volumetric flow rate for optimal flow parameters, namely, the Giesekus parameter, Deborah number and pressure gradient. The maximum constant pressure gradient has been calculated and the behavior of the velocity profiles and the corresponding flow rate of the fluid flow has been computed. The simulation results indicate that for fixed Giesekus parameter and Deborah number, an increase of the ratio of relaxation time of the viscoelastic fluid and the shear viscosity increases the velocity. Furthermore, for a fixed ratio of relaxation time and the shear viscosity and fixed Deborah number, a decrease of the Giesekus parameter increases the velocity. Also, it can be concluded that the negative pressure gradient with the maximum value of the Deborah number provides the maximum velocity field and the maximum fluid flow rate.
Linear programming approach to assess an optimal cultivation plan: A case study
(Faculty of Science, University of Kelaniya, Sri Lanka, 2020) Hakmanage, N.M.; Chandrasekara, N.V.; Jayasundara, D.D.M.
An optimal cultivation plan refers to the procedure or action of making the best or most effective use of resources for cultivation in a sustainable manner while maximizing net return. Reaching an efficient cultivation plan and utilization of resources and requirements is often a challenging problem. To utilize resources and requirements such as water, land, manpower, fertilizers and seeds, optimization techniques are used. The objective of this research is to maximize the net return of the cultivation using linear programming technique and allocate the arable land optimally. Linear programming is the most convenient and effective tool to handle the objective function with many constraints. This study was carried out in a rural village located in Dompe divisional secretariat in Gampaha district using 150 farming lands, to determine the land resource allocation for twelve selected crops: bitter gourd, lady's fingers, manioc, potatoes, rambutan, banana, pineapple, beetle, rice, coconut, tea and pepper. The linear programming model is formulated for the optimal land resource allocation of 4477.2 perches. The maximum net return projected by the proposed model is Rs 6,370,512.00 for cultivation seasons. The proposed solution is a 34.96% increase in profit as compared to the actual profit obtained from the cultivations. Crops like rambutan, rice, manioc and pineapple which provides a higher return should be developed and cultivation extended under the supervision of the agricultural expertise or officers. The model suggests that some crops such as lady’s fingers, potatoes, banana and coconut may not be providing comparable returns versus the other selected crops. The results reveal that linear programming approach will significantly improve the net benefits with optimal crop area allocation. The limitation of this study is that it is considered the soil condition is the same for all crops in the study area. Advanced operations research techniques like multi objective nonlinear programming models will be employed for this study in future work.