Abdullah Al Masum, born on November 30, 1997, in Cox’s Bazar, Bangladesh, serves as a Lecturer in the Department of Agricultural Mechanization at Habiganj Agricultural University. He holds a Master of Science in Farm Power and Machinery and a Bachelor of Science in Agricultural Engineering, both earned from Bangladesh Agricultural University. With a robust academic background and a focus on innovation, his work is dedicated to advancing agricultural practices through the integration of modern technologies. He has made significant contributions to agricultural automation and precision farming, including the development of automated real-time grading systems for potatoes using machine vision technology. His research also extends to the application of hyperspectral techniques for soil nutrient determination, underscoring his commitment to sustainable soil management practices. He has professional experience as a Research Assistant on a project aimed at addressing agricultural sustainability and mechanization challenges. His work reflects a broader ambition to enhance resource efficiency and foster sustainable development within the agricultural sector. As an educator and researcher, He is committed to inspiring his students to embrace innovative solutions to agricultural challenges. His academic and professional objectives focus on contributing to national agricultural development, promoting sustainable practices, and establishing himself as a global authority in smart agriculture, mechanization, and renewable energy technologies.

Research Articles

1. Habibullah Siddiki, Bondhon Chakrabarti, Abdullah Al Masum, & Mamunur Rashid (2024). Minimizing Chemical Fertilizer Usage and Improving Soil Nutrient and Microbial Activity Through Organic Strategies in Rice Production. Advances in Biotechnology & Microbiology, 18(4), 555992. DOI: 10.19080/AIBM.2024.17.555992
2. Most. Sapna Khatun, Abdullah Al Masum, Md. Hamidul Islam, Muhammad Ashik-E-Rabbani, Anisur Rahman*(2024), Short wave-near infrared spectroscopy for predicting soluble solid content in intact mango with variable selection algorithms and chemometric model, Journal of Food Composition and Analysis 136 (2024) 106745, https://doi.org/10.1016/j.jfca.2024.106745

Conference Proceedings

1. Oral Presentation on “Oral Presentation on “Hyperspectral Imaging Technique for Quantification of Total Nitrogen in Soil” at 3rd Annual Paper Meet 2022, Agricultural Engineering Division, The Institute of Engineers, Bangladesh.
2. Oral Presentation on “Automated Real-Time Mango Grading Based on Size Using Machine Vision Technique” at International Conference on Advanced Agricultural Research-2024 (ICAAR-2024), Sylhet Agricultural University, Sylhet-3100, Bangladesh.

Posters

1. Poster Presentation on “Hyperspectral Imaging Technique for Quantification of Total Nitrogen in Soil” at 3rd Annual Paper Meet 2022, Agricultural Engineering Division, The Institute of Engineers, Bangladesh.

Projects

• Title: Automated Real-Time Grading System for Potato Using Machine Vision Technology
• Project ID: 2021/1470/BAU
• Project Duration: 1.5 years
• Funding Agencies: Bangladesh Agricultural University Research System (BAURES)
• Role: Research Assistant