Article
Agriculture, Multidisciplinary
Nur A. Husin, Siti Khairunniza-Bejo, Ahmad F. Abdullah, Muhamad S. M. Kassim, Desa Ahmad
Summary: The study aimed to identify suitable parameters and monitoring time frames for the detection of oil palm tree diseases based on temporal laser scanning data. The results indicate that crown strata number 17 (850 cm from the top) and crown area are the most suitable parameters, and BSR can be detected by comparing the 4-month scan or the second 2-month scan, aiding in the prevention of crop losses.
PRECISION AGRICULTURE
(2022)
Article
Agronomy
Izrahayu Che Hashim, Abdul Rashid Mohamed Shariff, Siti Khairunniza Bejo, Farrah Melissa Muharam, Khairulmazmi Ahmad
Summary: This study utilized ALOS PALSAR-2 image with dual polarization to classify oil palm trees infected by G. boninense, showing that both MLP and RF machine learning classifiers had robust success rates. The HV backscatter variable was found to have a significant impact on classification accuracy for BSR disease prediction.
Article
Agriculture, Multidisciplinary
Julie Flood, Paul D. Bridge, Carmel A. Pilotti
Summary: This manuscript aims to provide a comprehensive review of the current knowledge on basal stem rot caused by Ganoderma boninense in South Asia and Oceania, by bringing together reports from different regions. The authors identify key issues that still need to be addressed in order to achieve a comprehensive understanding of this disease and its processes.
ANNALS OF APPLIED BIOLOGY
(2022)
Article
Plant Sciences
Latiffah Zakaria
Summary: Basal stem rot of oil palm caused by Ganoderma boninense is a serious disease in Southeast Asia, leading to significant economic losses. The disease has expanded its range to infect younger palm trees, including those as young as 1 year old. In addition to coastal areas, the disease has also spread to inland areas with peat soils. The management of the disease includes cultural practices, chemical control, and the use of biocontrol agents or fertilizers, while research on resistant oil palm varieties is still in the early stages.
Review
Plant Sciences
Nur Aliyah Jazuli, Assis Kamu, Khim Phin Chong, Darmesah Gabda, Affendy Hassan, Idris Abu Seman, Chong Mun Ho
Summary: Oil palm has been growing on a large scale and contributes significantly to the GDP of producing countries. However, the threat of diseases like Ganoderma basal stem rot is deteriorating oil palm plantations. Researchers are studying the progression of this disease to find suitable solutions.
Article
Plant Sciences
Arthy Surendran, Yasmeen Siddiqui, Khairulmazmi Ahmad, Rozi Fernanda
Summary: The study found that certain phenolic compounds have a significant effect on controlling the growth of Ganoderma boninense in oil palm wood, reducing wood mass loss. Treatment with benzoic acid resulted in lower degradation rates of lignin and cellulose, while maintaining the integrity of wood anatomy.
Article
Biochemistry & Molecular Biology
Fook-Hwa Lim, Omar Abd Rasid, Abu Seman Idris, Abdul Wahab Mohd As'wad, Ganesan Vadamalai, Ghulam Kadir Ahmad Parveez, Mui-Yun Wong
Summary: This study successfully isolated and characterized the full-length cDNA encoding ERG11 from G. boninense and investigated its gene expression during interaction with oil palm. These findings provide important molecular insights for understanding and controlling oil palm BSR disease.
MOLECULAR BIOLOGY REPORTS
(2022)
Review
Agronomy
Sugenendran Supramani, Nur Ardiyana Rejab, Zul Ilham, Wan Abd Al Qadr Imad Wan-Mohtar, Soumya Ghosh
Summary: This paper reviews the economic implications of oil palm infectious diseases and discusses the control methods, including biological, chemical, and mechanical approaches. The study finds that there is currently no effective method to combat one specific infection and highlights the need for future research.
EUROPEAN JOURNAL OF PLANT PATHOLOGY
(2022)
Article
Microbiology
Jakarat Anothai, Thanunchanok Chairin
Summary: This study investigated the microbial community difference in the rhizosphere soil of asymptomatic and symptomatic oil palm trees and found no significant difference in soil physicochemical properties and species richness. However, the abundance of phyla Actinobacteria and Firmicutes was significantly higher in the rhizosphere soil of asymptomatic oil palm trees, which are known to be related to disease suppression.
ARCHIVES OF MICROBIOLOGY
(2022)
Article
Agriculture, Multidisciplinary
Ong Win Kent, Tan Weng Chun, Tay Lee Choo, Lai Weng Kin
Summary: This study introduces an enhanced approach for early symptom detection of basal stem rot (BSR) disease in densely populated oil palm tree areas. The proposed method, utilizing a modified U-Net architecture and an image postprocessing method called the overlapped contour separation (OVCS) algorithm, demonstrates superior segmentation performance and accurate identification of tree boundaries.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2023)
Article
Environmental Sciences
Mohd Sharul Aikal Baharim, Nor Aizam Adnan, Fazly Amri Mohd, Ainon Nisa Othman, Haris Abdul Rahim, Mohamad Haris Abd Azis, Idris Abu Seman, Mohamad Anuar Izzuddin, Nur Amanina Shahabuddin, Abd Aziz Nordiana
Summary: This research aims to introduce technologies and methods for detecting Basal Stem Rot disease in oil palm plantations, utilizing advanced technologies for remote study and highlighting important techniques and methods for disease detection.
GEOCARTO INTERNATIONAL
(2022)
Article
Agronomy
Izrahayu Che Hashim, Abdul Rashid Mohamed Shariff, Siti Khairunniza Bejo, Farrah Melissa Muharam, Khairulmazmi Ahmad
Summary: Basal stem rot (BSR) disease caused by the aggressive fungal attack of Ganoderma boninense has significant impacts on oil palm crops in Malaysia and Indonesia. This study utilized thermal imagery to classify non-infected and BSR-infected trees, with machine learning classifiers like naive Bayes, multilayer perceptron, and random forest. The research found that using the ROS approach with temperature features provided a high accuracy in predicting BSR disease.
Article
Plant Sciences
V Pomies, N. Turnbull, S. Le Squin, I Syahputra, E. Suryana, T. Durand-Gasselin, B. Cochard, F. Bakry
Summary: This study confirms and details the process of sexual polyploidization in oil palm and identifies three phenotypical traits to assess the ploidy level of giant oil palms in the field.
Article
Plant Sciences
Zain Nurazah, Abu Seman Idris, Amiruddin Mohd Din, Mohamad Arif Abd Manaf, Abrizah Othman, Umi Salamah Ramli
Summary: This study compared the metabolic profiles of natural Ganoderma-infected and healthy control oil palm root samples, revealing differential metabolites associated with BSR in oil palm roots. Systematic metabolic pathway analysis identified the significant involvement of amino acid metabolism, carbohydrate metabolism, and biosynthesis of other secondary metabolites in response to BSR disease.
PHYSIOLOGICAL AND MOLECULAR PLANT PATHOLOGY
(2021)
Article
Multidisciplinary Sciences
Aqilah Yusoff, Fatin Humairah M. Ashaari, Muhammad Asyraff Abd Samad, Anis Farhan Fatimi Ab Wahab, Izwan Bharudin
Summary: Basal Stem Rot disease caused by Ganoderma boninense poses a huge threat to oil palm plantations in Malaysia, and chemical fungicides have limited effectiveness. This study identified locally isolated bacteria with strong antagonistic effects against G. boninense, potentially useful as biological control agents in preventing the spread of the disease.
Article
Agronomy
Abdusslam A. Houma, Md Rowshon Kamal, Md Abdul Mojid, Ahmad Fikri B. Abdullah, A. Wayayok
Summary: This study assessed the impacts of climate, irrigation practices, and weed control measures on lowland rice yield using the FAO-AquaCrop model. The model predicted an increase in yield under future climate scenarios, while also showing reduced yield under water stress and poor weed control. Projections suggest that proper weed control and water management practices will likely increase yield under changing climate conditions in the future.
AGRICULTURAL WATER MANAGEMENT
(2021)
Article
Agriculture, Multidisciplinary
Nur A. Husin, Siti Khairunniza-Bejo, Ahmad F. Abdullah, Muhamad S. M. Kassim, Desa Ahmad
Summary: The study aimed to identify suitable parameters and monitoring time frames for the detection of oil palm tree diseases based on temporal laser scanning data. The results indicate that crown strata number 17 (850 cm from the top) and crown area are the most suitable parameters, and BSR can be detected by comparing the 4-month scan or the second 2-month scan, aiding in the prevention of crop losses.
PRECISION AGRICULTURE
(2022)
Article
Environmental Sciences
Mohd Shahkhirat Norizan, Aimrun Wayayok, Ahmad Fikri Abdullah, Muhammad Razif Mahadi, Yahya Abd Karim
Summary: This study established an irrigation management zone (IMZ) covering 23.4 ha using GIS software and the Kriging method, based on soil sampling and analysis. The IMZ was classified into three areas (A, B, C) according to the available water-holding capacity (AWHC) values, showing differences in irrigation depth requirements between 2016 and 2017.
Article
Green & Sustainable Science & Technology
Mourtadha Sarhan Sachit, Helmi Zulhaidi Mohd Shafri, Ahmad Fikri Abdullah, Azmin Shakrine Mohd Rafie
Summary: This study proposes a method to assess the temporal complementarity of wind and solar resources in Iraq. It reveals significant synergy patterns in the southwestern regions and some eastern parts of the country. The highest complementarity is observed in March and December. Though typical temporal complementarity that eliminates power fluctuations hasn't been found, the synergistic properties can help reduce reliance on storage systems.
Review
Green & Sustainable Science & Technology
Fatimah Md Yusoff, Ahmad Fikri Abdullah, Ahmad Zaharin Aris, Wahidah Ahmad Dini Umi
Summary: The COVID-19 pandemic has both positive and negative impacts on aquatic ecosystems and environments. While reduced human activities led to improved water quality, the surge of plastics and biomedical wastes during the pandemic increased the risk of aquatic pollution, negatively affecting fisheries and aquaculture industries.
Article
Chemistry, Multidisciplinary
Khaled Yousef Almansi, Abdul Rashid Mohamed Shariff, Ahmad Fikri Abdullah, Sharifah Norkhadijah Syed Ismail
Summary: Palestinian healthcare institutions struggle with effective service delivery during crises, with spatial distribution and accessibility to healthcare facilities in Gaza being inadequate due to decades of conflicts. This study utilized machine learning methods to identify suitable hospital locations, demonstrating high correlation and prediction accuracy, suggesting reliability of machine learning techniques in assessing optimal hospital site locations.
APPLIED SCIENCES-BASEL
(2021)
Article
Chemistry, Multidisciplinary
Nur Atirah Muhadi, Ahmad Fikri Abdullah, Siti Khairunniza Bejo, Muhammad Razif Mahadi, Ana Mijic
Summary: The study introduced a semantic segmentation approach based on convolutional neural networks for water region identification, evaluating the performance of two deep learning algorithms with DeepLabv3+ outperforming SegNet. Using LiDAR data to extract water level markers and overlaying them with image segmentation results for water level estimation, the high Spearman's rank-order correlation coefficient indicates a strong relationship between estimated and observed water levels.
APPLIED SCIENCES-BASEL
(2021)
Review
Environmental Sciences
Habibu Ismail, Md Rowshon Kamal, Md Abdul Mojid, Ahmad Fikri Bin Abdullah, Lai Sai Hin
Summary: This paper reviews the loss methods in the HEC-HMS model for streamflow simulation under climate change. The result of the review shows that despite the simplicity and accuracy of the loss methods in HEC-HMS, their application in climate change studies is still limited and has not been studied in Malaysia.
INTERNATIONAL JOURNAL OF HYDROLOGY SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Multidisciplinary
Hamidreza Maskani Jifroudi, Shattri B. Mansor, Biswajeet Pradhan, Alfian Abdul Halin, Noordin Ahmad, Ahmad Fikri Bin Abdullah
Summary: This study proposes a rule-based algorithm called DB-creator to automatically create building footprints. Experimental results show that the constructed footprints based on LiDAR analysis are highly accurate with slight internal variations.
Article
Green & Sustainable Science & Technology
Khaled Yousef Almansi, Abdul Rashid Mohamed Shariff, Bahareh Kalantar, Ahmad Fikri Abdullah, Sharifah Norkhadijah Syed Ismail, Naonori Ueda
Summary: This study focuses on the suitable site identification for constructing a hospital in Malacca, Malaysia. The MLP model showed high correlation and reliability, achieving a prediction accuracy of 80%. The findings suggest that the MLP model is a promising approach for hospital location suitability.
Article
Agronomy
Siti Nurul Afiah Mohd Johari, Siti Khairunniza-Bejo, Abdul Rashid Mohamed Shariff, Nur Azuan Husin, Mohamed Mazmira Mohd Masri, Noorhazwani Kamarudin
Summary: This study used unmanned aerial vehicles (UAVs) to quickly detect the severity levels of infestation in oil palm plantations. Different combinations of vegetation indices were used for classification, and the results showed that the best combination accurately classified the severity levels. The weighted KNN model was found to be the best for classification. This technique is crucial for early detection of infestation severity and saves time in preparing and implementing control measures.
Article
Computer Science, Information Systems
Yu Hong Haw, Yan Chai Hum, Joon Huang Chuah, Wingates Voon, Siti Khairunniza-Bejo, Nur Azuan Husin, Por Lip Yee, Khin Wee Lai
Summary: The palm oil industry in Malaysia is facing significant economic loss due to Basal Stem Rot, a disease caused by the fungus Ganoderma Boninense. Early detection of the disease is difficult, as infected trees often show no symptoms during the early stage. To improve detection, Terrestrial Laser Scanning technology was used to obtain canopy images of oil palm trees, which were pre-processed and used to train deep learning models. The best performing model, the fine-tuned DenseNet121, achieved a Macro F1-score of 0.798. However, overfitting was observed in the fine-tuned models due to dataset limitations. Future work should focus on increasing sample size and exploring other CNN architectures.
Article
Multidisciplinary Sciences
Nuraddeen Mukhtar Nasidi, Aimrun. Wayayok, Ahmad Fikri Abdullah, Muhamad Saufi Mohd Kassim
Summary: Increased greenhouse gas emissions affect precipitation, leading to various hazards. This study used multi-model ensembles to project precipitation in the coming decades, finding higher daily precipitation in Cameron Highlands under certain scenarios. The concentration index indicates significant variability in precipitation, with varied spatial distribution patterns in the future.
SN APPLIED SCIENCES
(2021)
Article
Environmental Sciences
Nuraddeen Mukhtar Nasidi, Aimrun Wayayok, Ahmad Fikri Abdullah, Muhamad Saufi Mohd Kassim
Summary: This study projected the spatial and temporal rainfall erosivity factor using ensemble Global Circulation Models (GCMs) and found a significant increase in erosivity due to climate change. The availability of water resources is also expected to be influenced, necessitating appropriate conservation strategies.
MODELING EARTH SYSTEMS AND ENVIRONMENT
(2021)