Proceedings of the 6th National Symposium on Agriculture 2024.Theme of the Symposium "“Resilient Agriculture – A tool for reviving Sri Lankan economy" http://www.digital.lib.esn.ac.lk//handle/1234/15234 2026-04-08T23:53:12Z 2026-04-08T23:53:12Z Sathuja, S. Thirumaran, S. Niroash, G. Sugirtharan, M. http://www.digital.lib.esn.ac.lk//handle/1234/15331 2025-09-06T22:17:19Z 2024-03-06T00:00:00Z

USE OF RAINWATER HARVESTING TANK FOR WATER SUSTAINABILITY: A CASE STUDY IN POTTUVIL AND THIRUKKOVIL DS DIVISIONS OF AMPARA DISTRICT, SRI LANKA Sathuja, S.; Thirumaran, S.; Niroash, G.; Sugirtharan, M. Water sustainability is a global imperative, given the rising demand for freshwater, which constitutes merely 1% of the earth's water and is essential for human use. Sri Lanka's dry zones contend with severe droughts, floods, and saline water intrusion in coastal areas. The aftermath of the 2004 tsunami triggered a water crisis in the Ampara district, prompting collaborative efforts between the government and NGOs to establish a domestic rainwater harvesting system. Although the project was successfully finished, there has been a problem with sustainability in some areas due to a lack of monitoring of the harvesting tanks' use. Therefore, this study was aimed to assess the status of the implemented rainwater harvesting system at the Pottuvil and Thirukkovil DS Divisions in Ampara, employing simple random sampling in Inspector Eatham, Kundumadu, Thandiyadi, and Sangamangramam villages. The data was collected using questionnaires, interviews, and literature studies. The collected data was analyzed using descriptive statistics. Results revealed that only 30% of the 150 respondents utilized rainwater tanks, with a mere 3% using harvested water for drinking and 27% for various domestic purposes. Reduced dependence on rainwater collection was associated with the introduction of a water supply scheme in those areas. In areas with restricted centralized supplies, rainwater collection serves as an alternative, particularly in larger households. A minimal percentage (2%) of respondents had higher education, emphasizing the role of education in effectively implementing rainwater-harvesting systems. Challenges such as tank damage, financial constraints among low-income farmers and inadequate maintenance skills also contributed to the reduced usage of rainwater harvesting tank. The study suggests funding for tank repairs in addition to community awareness campaigns that emphasize the advantages of rainwater harvesting and encourage more involvement. This holistic approach aims to address the multifaceted challenges hindering sustainable water practices in the region.

2024-03-06T00:00:00Z Munasinghe, V.U Liyanage, M.R http://www.digital.lib.esn.ac.lk//handle/1234/15330 2025-09-06T22:17:18Z 2024-03-06T00:00:00Z

A STUDY ON DESIGNING AN AUTOMATED IoT SYSTEM TO AID HYDROPONIC AGRICULTURE FOR DOMESTIC PURPOSE Munasinghe, V.U; Liyanage, M.R The population of the global is predicted to grow daily and reach 9.3 bilion people by the year 2050. Thus, in order to ensure a sufficient supply of food, agricultural productivity needs to be raised. In addition, the cost of food in Sri Lanka rise in July 2022 at a recordbreaking pace of 90.90% compared to the same month the previous year. Traditional farming, hindered by insufficient fertilizers and pesticides, fails to address the heightened demand, further diminishing productivity. The aim of the research is to the design of an automated IoT system for the deepwater culture method of hydroponics for domestic Water Spinach plant purpose. The results obtained were compared with the results obtained from the traditional cultivation method. The MQTT platform is used when cultivation uses the IoT method which is designed for IoT. In addition, Kincony esp32 A8 is used as the hardware and sensors and controllers are connected. The data received from those devices is configured with the Tasmota firmware and sent to the EMQX MQTT broker. Through the integration of Node-Red and the app via broker, this project enables users to acquire realtime cultivation data and exercise control over cultivation process accordingly. After connecting the hydroponics system, the parameters of pH, TDS and temperature were obtained in the form of graphs and the parameters of lights, fan and pump to be controlled were set to work manually. Results showed that reading the accuracy of the sensors temperature, TDS and humidity is, 98.21% for temperature, 95.51% for TDS and 96.45% for humidity. The proposed system aims to provide an efficient, cost-effective, and easy-touse solution for domestic hydroponic agriculture. The system's automation reduces the need for constant manual monitoring, and the remote access feature allows users to monitor and control the system from anywhere.

2024-03-06T00:00:00Z Epitakumbura1, P.D. Chandrasiri, R.S. Amarasinghe, A.A.Y. Dharmasena1, H.A.Y.B. Galahitigama, G.A.H. http://www.digital.lib.esn.ac.lk//handle/1234/15329 2025-09-06T22:17:16Z 2024-03-06T00:00:00Z

SELECTION OF A SUITABLE FERTILIZER MIXTURE FOR HIGH-DENSITY CABBAGE (Brassica oleracea L.) CULTIVATION IN NUWARA ELIYA, SRI LANKA Epitakumbura1, P.D.; Chandrasiri, R.S.; Amarasinghe, A.A.Y.; Dharmasena1, H.A.Y.B.; Galahitigama, G.A.H. Cabbage (Brassica oleracea L.) is a globally significant vegetable crop, particularly in temperate regions like Sri Lanka. The main objective of this study is to identify the most suitable fertilizer mixture for high-density cabbage cultivation in Sri Lanka's Nuwara Eliya area. The experiment consisted of five treatments namely; T2 (Urea + Up country root special mixture (N:P:K:Mg=2:3:4:1), T3 (urea + vegetable top dressing mixture (N:K=3:2) + Calcium nitrate granules), T4 (Urea + vegetable top dressing mixture (N:K=3:2) + Blue granules (N:P:K:Mg=6:6:8:1+trace elements)) and T5 (Urea + Calcium nitrate granules + Blue granules), and the fertilizer recommendations (N:P:K:=6:5:3) from Department of Agriculture was considered as control (T1). ‘Krishna’ F1 Hybrid cabbage variety used for the experiment Randomized complete block design (RCBD) was used as the experimental design with 5 replicates. Plant head weight, height, diameter and compactness of the cabbage heads were measured as yield parameters after harvesting. Data were analyzed by ANOVA and mean separation was done by using Duncan multiple range test (DMRT). According to the results, there was a significant cabbage head weight received in T3 (1.84±0.105 kg) compared to other treatments. Moreover, the higher values for head diameter (18.92±0.419 cm) and head height (16.33±0.306 cm) were observed in T3. According to soil analysis, T3 exhibited the highest reduction in pH by 0.62±0.082. Thus, this study concluded that the urea + vegetable top dressing mixture (N:K=3:2) + Calcium nitrate granules would be a more effective fertilizer mixture for high-density cabbage cultivation in Nuwara Eliya area among the used fertilizer mixtures.

2024-03-06T00:00:00Z Lakshitha, A.A. Liyanage, M.R. Samarakoon2, E.R.J. http://www.digital.lib.esn.ac.lk//handle/1234/15328 2025-09-06T22:18:51Z 2024-03-06T00:00:00Z

DEVELOPMENT OF IMAGE PROCESSING ALGORITHM TO DETECT CROP MATURITY OF SCOTCH BONNET PEPPER (Capsicum chinense) Lakshitha, A.A.; Liyanage, M.R.; Samarakoon2, E.R.J. Sri Lanka is a luxuriant tropical land with the potential for the cultivation and hence agriculture is considered as one of the best prospect sectors of the country. To maximize the yield from the crops, a proper classification of harvest which aids in determining the storage conditions and the export quality is essential. Deep learning technologies facilitate crop recognition by enabling a computer to automatically detect a crop and determine its ripeness level. This study introduces a real-time image processing algorithm utilizing Convolutional Neural Networks (CNNs) to identify the maturity stages of scotch bonnet peppers. The algorithm is designed to classify the scotch bonnet peppers into three maturity stages as unripe, moderately ripe, and ripe, by training the CNN aid of dataset of labelled images of scotch bonnet peppers at different maturity stages. Training the CNN through backpropagation minimizes categorical cross-entropy loss, resulting in a testing accuracy of 89.04% and training accuracy of 91.6%. These results underscore the algorithm's real-time effectiveness in discerning the maturity stage of scotch bonnet peppers. For scotch bonnet peppers, the algorithm holds significant potential to substantially reduce postharvest losses and cut production costs tied to exporting top-quality produce. Precisely discerning the maturity stages of scotch bonnet peppers ensures the delivery of high-quality products to consumers, concurrently optimizing storage conditions and export quality. The real-time image processing algorithm, developed using CNNs and Python, proves to be an efficient approach for detecting the maturity stage of scotch bonnet peppers and the approach can be extended to diverse crops, establishing its versatility in the agricultural sector.

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