Potassium (K) nutrition in pineapple grown on tropical peat can be problematic due to high precipitation which encourages leaching losses. Non-destructive tools that can assess K deficiency and the accompanying changes in biophysical and biochemical properties within pineapple is a good strategy to employ. In this study, we assessed the biophysical changes in pineapple (var. MD2) in response to different K rates by using a hyperspectral approach. K deficiency was detected at 171 days after planting. Shortage of K also exhibited a shift in red edge towards shorter wavelengths between 500-700 nm. In addition, spectral ranges of 430-680 nm, as well as 680-752 nm were found to be most effective in differentiating spectral response to varying K rates. Three vegetation indices, i.e. Normalized Pigment Chlorophyll Index (NPCI), Plant Senescence Index (PSRI) and Red-edge Vegetation Index (RVSI) were found to best describe K treatment effects on pineapple canopy reflectance. This study could be extended further to include pineapple varieties other than MD2, and also key nutrients, such as N and P, for better fertilizer management in peat-grown pineapple.
{"title":"Use of Selected Spectral Ratios to Assess the Response of Pineapple to Potassium Nutrition","authors":"S. K. Balasundram, Y. Chong","doi":"10.24191/JSST.V1I1.11","DOIUrl":"https://doi.org/10.24191/JSST.V1I1.11","url":null,"abstract":"Potassium (K) nutrition in pineapple grown on tropical peat can be problematic due to high precipitation which encourages leaching losses. Non-destructive tools that can assess K deficiency and the accompanying changes in biophysical and biochemical properties within pineapple is a good strategy to employ. In this study, we assessed the biophysical changes in pineapple (var. MD2) in response to different K rates by using a hyperspectral approach. K deficiency was detected at 171 days after planting. Shortage of K also exhibited a shift in red edge towards shorter wavelengths between 500-700 nm. In addition, spectral ranges of 430-680 nm, as well as 680-752 nm were found to be most effective in differentiating spectral response to varying K rates. Three vegetation indices, i.e. Normalized Pigment Chlorophyll Index (NPCI), Plant Senescence Index (PSRI) and Red-edge Vegetation Index (RVSI) were found to best describe K treatment effects on pineapple canopy reflectance. This study could be extended further to include pineapple varieties other than MD2, and also key nutrients, such as N and P, for better fertilizer management in peat-grown pineapple.","PeriodicalId":17117,"journal":{"name":"Journal of Smart Science and Technology","volume":"20 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89248219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
N. A. Rahim, A. Bohari, A. Adnan, N. Khalil, A. Olanipekun
There is a growing global concern about the adverse effects of today's rapid economic growth and development, which impact the environment and deplete energy supply. A green roof may lower a building's energy consumption and minimise air pollution by reducing dust particles in the air. The primary impediment to green roof implementation in Malaysia lacks local knowledge and unskilled green roof specialists. As a result, there is a shortage of green roof installers and specialised firms in the country. This article discusses the problems and solutions of adopting green roofs in building projects based on construction industry experience in Sarawak. A survey utilising a questionnaire is used to obtain data for this research. The paper revealed the possible challenges of adopting a green roof for the construction industry. The study is critical in order to adopt green roof technology quickly in Malaysia.
{"title":"Challenges and Way Forward for Implementing Green Roof in Construction Industry in Sarawak, Malaysia","authors":"N. A. Rahim, A. Bohari, A. Adnan, N. Khalil, A. Olanipekun","doi":"10.24191/JSST.V1I1.13","DOIUrl":"https://doi.org/10.24191/JSST.V1I1.13","url":null,"abstract":"There is a growing global concern about the adverse effects of today's rapid economic growth and development, which impact the environment and deplete energy supply. A green roof may lower a building's energy consumption and minimise air pollution by reducing dust particles in the air. The primary impediment to green roof implementation in Malaysia lacks local knowledge and unskilled green roof specialists. As a result, there is a shortage of green roof installers and specialised firms in the country. This article discusses the problems and solutions of adopting green roofs in building projects based on construction industry experience in Sarawak. A survey utilising a questionnaire is used to obtain data for this research. The paper revealed the possible challenges of adopting a green roof for the construction industry. The study is critical in order to adopt green roof technology quickly in Malaysia.","PeriodicalId":17117,"journal":{"name":"Journal of Smart Science and Technology","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89575531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xavier Chee Wezen, Cl Wen, Li Ping, Yeong Kah Ho, K. Qing, Christopher Ha, Hwang Siaw San
Clathrin-mediated endocytosis (CME) is a normal biological process where cellular contents are transported into the cells. However, this process is often hijacked by different viruses to enter host cells and cause infections. Recently, two proteins that regulate CME – AAK1 and GAK – have been proposed as potential therapeutic targets for designing broad-spectrum antiviral drugs. In this work, we curated two compound datasets containing 83 AAK1 inhibitors and 196 GAK inhibitors each. Subsequently, machine learning methods, namely Random Forest, Elastic Net and Sequential Minimal Optimization, were used to construct Quantitative Structure Activity Relationship (QSAR) models to predict small molecule inhibitors of AAK1 and GAK. To ensure predictivity, these models were evaluated by using Leave-One-Out (LOO) cross validation and with an external test set. In all cases, our QSAR models achieved a q2LOO in range of 0.64 to 0.84 (Root Mean Squared Error; RMSE = 0.41 to 0.52) and a q2ext in range of 0.57 to 0.92 (RMSE = 0.36 to 0.61). Besides, our QSAR models were evaluated by using additional QSAR performance metrics and y-randomization test. Finally, by using a concensus scoring approach, nine chemical compounds from the Drugbank compound library were predicted as AAK1/GAK dual-target inhibitors. The electrostatic potential maps for the nine compounds were generated and compared against two known dual-target inhibitors, sunitinib and baricitinib. Our work provides the rationale to validate these nine compounds experimentally against the protein targets AAK1 and GAK.
{"title":"Predicting AAK1/GAK Dual-Target Inhibitor against SARS-CoV-2 Viral Entry into Host Cells: An in silico Approach","authors":"Xavier Chee Wezen, Cl Wen, Li Ping, Yeong Kah Ho, K. Qing, Christopher Ha, Hwang Siaw San","doi":"10.24191/JSST.V1I1.14","DOIUrl":"https://doi.org/10.24191/JSST.V1I1.14","url":null,"abstract":"Clathrin-mediated endocytosis (CME) is a normal biological process where cellular contents are transported into the cells. However, this process is often hijacked by different viruses to enter host cells and cause infections. Recently, two proteins that regulate CME – AAK1 and GAK – have been proposed as potential therapeutic targets for designing broad-spectrum antiviral drugs. In this work, we curated two compound datasets containing 83 AAK1 inhibitors and 196 GAK inhibitors each. Subsequently, machine learning methods, namely Random Forest, Elastic Net and Sequential Minimal Optimization, were used to construct Quantitative Structure Activity Relationship (QSAR) models to predict small molecule inhibitors of AAK1 and GAK. To ensure predictivity, these models were evaluated by using Leave-One-Out (LOO) cross validation and with an external test set. In all cases, our QSAR models achieved a q2LOO in range of 0.64 to 0.84 (Root Mean Squared Error; RMSE = 0.41 to 0.52) and a q2ext in range of 0.57 to 0.92 (RMSE = 0.36 to 0.61). Besides, our QSAR models were evaluated by using additional QSAR performance metrics and y-randomization test. Finally, by using a concensus scoring approach, nine chemical compounds from the Drugbank compound library were predicted as AAK1/GAK dual-target inhibitors. The electrostatic potential maps for the nine compounds were generated and compared against two known dual-target inhibitors, sunitinib and baricitinib. Our work provides the rationale to validate these nine compounds experimentally against the protein targets AAK1 and GAK.","PeriodicalId":17117,"journal":{"name":"Journal of Smart Science and Technology","volume":"19 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84333291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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