Erdy Sulino Mohd Muslim Tan
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Preferred name
Erdy Sulino Mohd Muslim Tan
Official Name
Erdy Sulino, Mohd Muslim Tan
Alternative Name
Mohd Muslim Tan, Erdy Sulino
Mohd Muslim Tan, E. S.
Tan, Erdy S.M.
Main Affiliation
Scopus Author ID
57210106471
Researcher ID
GEQ-7073-2022

Research Output

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Analysis of Soil Nutrient (NPK) Test Value - Relative yield Relationship for Harumanis Mango using Modification Arcsine-Log Calibration Curve.

2023-01-01 , Erdy Sulino Mohd Muslim Tan , Markom M.A.B. , Allan Melvin Andrew , Abu Hassan Abdullah , Norasmadi Abdul Rahim , Fathinul Syahir Ahmad Sa'ad , Imaduddin Helmi Wan Nordin , Abidin M.A.Z. , Jamil S.H.F.S.A. , Yogesh C.K.

The cultivation of Harumanis mango (Mangifera indica) is of significant agricultural importance, especially in tropical regions like Malaysia, where it is renowned for its exceptional taste and quality. Maximizing mango yield and maintaining fruit quality are vital aspects of successful cultivation, relying on optimal soil nutrient management, particularly nitrogen (N), phosphorus (P), and potassium (K). In this research, the soil nutrient test value - relative yield relationship for Harumanis mango is investigated using a modification arcsine-log calibration curve. Traditional linear calibration curves may not fully capture the nonlinearities observed in crop responses, potentially leading to inaccurate nutrient requirements for optimal yield. By employing the innovative modification arcsine-log calibration curve, a more precise and robust relationship between soil nutrient test values and relative mango yield is established. Soil samples are collected from mango orchards, and NPK levels are measured using standardized laboratory techniques, alongside corresponding relative mango yields. This study advances precision agriculture by offering precise soil nutrient recommendations for mango farmers. Utilizing calibrated curves improves mango yield, minimizes nutrient waste, and encourages sustainable farming. In conclusion, the modified arcsine-log calibration curve reveals vital insights for optimal Harumanis mango production, benefiting the industry and sustainability.

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Nutrient Requirements and Growth Response of Harumanis Mango (Mangiferaindica L.) during Vegetative Shoot Growth Stages: A Mitscherlich Law Analysis

2023-01-01 , Erdy Sulino Mohd Muslim Tan , Markom M.A.B. , Allan Melvin Andrew , Abu Hassan Abdullah , Norasmadi Abdul Rahim , Fathinul Syahir Ahmad Sa'ad , Imaduddin Helmi Wan Nordin , Abidin M.A.Z. , Jamil S.H.F.S.A. , Yogesh C.

This study investigates the nutrient requirements of Harumanis mango (Mangifera indica L) during different vegetative shoot growth stages by analyzing the soil nutrient test value-relative growth relationships. The research utilizes the Mitscherlich Law to model the response of mango yield in relation to varying nutrient levels. The data came from experimental plots, and the results show the asymptotic behavior of mango yield for three essential nutrients: nitrogen (N), phosphorus (P), and potassium (K). For vegetative shoot growth1, the asymptotic yield was estimated at 665.5 with a decline rate of -3.39 concerning N, -2.17 concerning P, and -1.35 concerning K. The coefficient of determination (R2) was 0.934, indicating a high goodness of fit for the model. Similar trends were observed for vegetative shoot growth2 and 3, where the asymptotic yields and nutrient decline rates varied accordingly. This study provides crucial insights into Harumanis mango nutrient needs across growth stages, aiding orchard management for sustainable yields. Applying the Mitscherlich Law enhances our understanding of how nutrients affect mango growth. These findings support targeted fertilization, boosting productivity and orchard efficiency. Future research can explore more growth factors and long-term nutrient impacts.

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Fuzzy logic based prediction of micronutrients demand for harumanis mango growth cycles

2021-12-01 , Wan Mohd Nooriman Wan Yahya , Abu Hassan Abdullah , Norasmadi Abdul Rahim , Erdy Sulino Mohd Muslim Tan

Harumanis is a famous green eating mango cultivar that has been commercially cultivated in Malaysia's state of Perlis. A variety of nutrients are found in soil, all of which are necessary for plant growth. Micronutrients such as Nitrogen (N), Phosphorus (P), and Potassium (K) are essential for Harumanis mango (Mangifera Indica) to growth. The importance of soil fertility in achieving high plant productivity and quality cannot be overstated. It should be used in a moderate amount and in a balanced manner. Predicting appropriate nutrients and the right timing to satisfy the tree's demands is critical. The aim of this study is to create a fuzzy logic-based system to analyse the results of soil tests for nitrogen (N), phosphorus (P), and potassium (K) in the Harumanis mango orchard. The interpreted data are used to estimate N-P-K nutrient levels and indicate the optimal fertilizer solution and application timing for each Harumanis growth stages. The system utilizes Fuzzy Logic Control (FLC) to predict the nutrients demand for Harumanis mango growth. Results shows the system able to calculate and predict values of required N-P-K fertilizer for optimal growth. Thus, assist farmers in predicting the proper amount of N-P-K to apply to Harumanis mango soil.

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A Review: Deep Learning Classification Performance of Normal and COVID-19 Chest X-ray Images

2021-11-25 , Marni Azira Markom , Taha S.M. , Abdul Hamid Adom , Abdul Syafiq Abdull Sukor , Aimi Salihah Abdul Nasir , Haniza Yazid , Erdy Sulino Mohd Muslim Tan , Arni Munira Markom

COVID19 chest X-ray has been used as supplementary tools to support COVID19 severity level diagnosis. However, there are challenges that required to face by researchers around the world in order to implement these chest X-ray samples to be very helpful to detect the disease. Here, this paper presents a review of COVID19 chest X-ray classification using deep learning approach. This study is conducted to discuss the source of images and deep learning models as well as its performances. At the end of this paper, the challenges and future work on COVID19 chest X-ray are discussed and proposed.

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