SLIIT Conference and Symposium Proceedings
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All SLIIT faculties annually conduct international conferences and symposiums. Publications from these events are included in this collection.
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Publication Open Access Paddy Disease Identification and Impact Calculation Using Machine Learning(SLIIT Business School, 2023-12-14) Sandeepanie, N; Rathnayake, S; Gunasinghe, ARice is a crucial staple crop globally, providing over half of humanity's caloric intake. It supports the livelihoods of small-scale farmers and landless laborers worldwide. With the growing population, there is a high demand for rice production. Sri Lanka is renowned for its high- quality rice and has a long history of paddy cultivation. However, not all the country's 708,000 hectares of land dedicated to paddy cultivation are utilized due to water scarcity and unstable terrain. The objective of this paper is to explore the ways of enhancing the quality of the paddy crop during its vegetative phase by early identification of diseases through the utilization of emerging technologies. The vegetative phase constitutes a critical stage in the growth of paddy, exerting significant influence on the overall yield, resistance to pests and diseases, nutrient assimilation, and the environmental implications of agricultural practices. The primary emphasis of this paper is to identify diseases to which paddy crops are susceptible during the vegetative phase and subsequently present avisual representation of their locations on a map, serving as the output for end-users. Early identification of paddy diseases is crucial for effective crop management and high yields. These diseases, caused by different pathogens, can significantly hinder plant growth and productivity if not detected and treated promptly. Identifying them early allows farmers and experts to take timely and targeted actions, like applying suitable fungicides or implementing cultural practices, to control their spread and minimize crop damage.Publication Open Access In Silico Identification of Abiotic Stress-Responsive Candidate Genes in Rice and Their Allelic Differences Between At 354 and Bg 352(Faculty of Humanities and Sciences, SLIIT, 2023-11-01) Rathnayake, S; Kottearachchi, N; Lankika, S. P. C.Rice (Oryza sativa L) feeds more than half of the world’s population. One of the main elements that harm yield globally is abiotic stress. Therefore, it is important to develop abiotic stress tolerant rice varieties in order to increase rice productivity and to extend the cultivation. The lack of knowledge of the genetic mechanisms underlying abiotic stress tolerance is the primary issue with the traditional breeding technique. Hence, studying genes responsible for abiotic stress mechanisms is important to accelerate breeding by molecular marker - based detection techniques. Aiming at finding the candidate genes for abiotic stress tolerance ,two rice genome sequences of At 354 and Bg 352 varieties given by National Research Council, Sri Lanka -16 -16 project were analyzed. At 354 has some abiotic stress tolerance (salt) traits and Bg 352 has some susceptible traits. Next-generation sequencing-derived genome sequences were used to identify SNPs and Indels in the At 354 and Bg 352 varieties with reference to Oryza sativa japonica group cultivar Nipponbare. The STRING Database was used to extract the most correlated genes with abiotic stress. The allelic differences among Nipponbare, At 354 and Bg 352 sequences were detected from Multiple Sequence Alignment by using the Rice Annotation Project database, UGENE software and MEGA 11 software. The mutations of the genes were validated if they were present in another germplasm in the NCBI database. Altogether 100 genes were used to examine, and 166 mutations were observed including 163 SNPs and 3 Indels while 09 genes were validated due to their presence in other rice accessions. The amino acid sequences of the validated sequences were determined by Expasy Translate tool. The Swiss model database and ProtParam tool were used to predict the protein structures and their parameters, which showed some structural differences among tested alleles. These mutant alleles further need to be assessed against abiotic stress and varietal turnover in order to use them in rice improving breeding programs to be used in abiotic stress-prone ecosystems.Publication Open Access Disease Identification and Mapping using CNN in Paddy Fields(Faculty of Humanities and Sciences, SLIIT, 2023-11-01) Sandeepanie, W.D.N; Rathnayake, S; Gunasinghe, ARice, a globally vital staple crop, sustains over half of the world’s caloric needs while supporting the livelihoods of small-scale farmers and landless laborers. The escalating global population has led to an increased demand for rice production. Sri Lanka, renowned for its premium rice quality, has a rich history of paddy cultivation. However, a substantial portion of the country’s 708,000 hectares of paddy land remains underutilized due to water scarcity and unstable terrain. The objective of this project is to enhance paddy crop quality during the critical vegetative phase by employing machine learning and web development for early disease identification. The vegetative phase significantly influences overall yield, resistance to pests and diseases, nutrient assimilation, and environmental sustainability in agriculture. This project primarily focuses on early disease identification during this phase and presents the findings through a user-friendly map interface. Early identification of paddy diseases is vital for effective crop management and high yields. These diseases, caused by various pathogens, can severely impede plant growth and productivity if not promptly detected and treated. Identifying them early enables farmers and experts to take timely, targeted actions such as applying suitable fungicides or implementing cultural practices to control their spread and minimize crop damage. A logical map, displaying disease spread percentages, will gauge the impact of infections on paddy plants. The reliability of this mapping process hinges on model accuracy, which was rigorously validated using multiple metrics to ensure its effectiveness.Publication Open Access From Off-time to Offline: Recognising Right to Disconnect under the Sri Lankan Labour Law System(Faculty of Humanities and Sciences, SLIIT, 2023-11-01) Rathnayake, SThis study aims to interrogate the possibility of acknowledging the Right to Disconnect (RTD) under the labour laws of Sri Lanka. RTD which emerged as a response to the increasing demand for online and hybrid work, recognises employees’ right to remain disconnected or disengaged from any work-related activities such as answering phone calls or responding to emails after working hours. Research on RTD has focused on its practical implications for building a healthy and sustainable work force, but less has been said about its incorporation to domestic legal environments, especially in developing countries. The present study therefore critically reviews the Sri Lankan labour laws and the labour laws in other jurisdictions that have acknowledged RTD, to understand the potential of acknowledging this right in Sri Lanka. Through its data analysis this study revealed that, despite the existence of legal measures that ensure employees’ Right to relax and leisure (RRL), a little to no focus has been given to the new working environments such as online and hybrid work, and the rights that would emerge from them. While highlighting the best practices relating to RTD from other jurisdictions, this study also examines the legal dilemmas that may thwart such attempts of recognising this right in Sri Lanka. Thus, it highlights the need to update Sri Lankan labour laws to match the contemporary labour market while strengthening labour tribunals to play an active role which will be essential to acknowledge novel rights such as RTD under Sri Lankan labour laws.