Dr. Seyed Ahmad Mireei samireei@iut.ac.ir Office Department of Biosystems Engineering, College of Agriculture, Isfahan University of Technology, Isfahan, Iran. P.O. Box: 84156-83111. Phone +98 31 3391 3408 Fax +98 31 3391 3471 Positions Associate Professor of Biosystems Engineering Research Interests Nondestructive quality evaluation of agricultural products Postharvest technology Sensors and testing technology Dr. Seyed Ahmad Mireei type: Journal Title Conference / Journal Date Comparative classification of spectrally overlapping Allium seed genotypes using Vis-NIR spectroscopy and hyperspectral imaging with chemometric, machine, and deep learning models Scientific Reports 2026-05 The effect of UAV sprayer operational characteristics on spray deposition within the target area Smart Agricultural Technology 2025-12 Chick embryo development assessment and fertility detection using pixel-wise hyperspectral image analysis and deep learning POULTRY SCIENCE 2025-11 Use of Vis-NIR reflectance spectroscopy for estimating soil phosphorus sorption parameters at the watershed scale SOIL and TILLAGE RESEARCH 2025-05 A free-space dielectric system with X-band coaxial-to-waveguide adapters for nondestructive fertility detection in unincubated chicken eggs: Optimizing spectrum, orientation, features, and classifiers COMPUTERS AND ELECTRONICS IN AGRICULTURE 2025-04 Spatial analysis of hyperspectral images for detecting adulteration levels in bon-sorkh (Allium jesdianum L.) seeds: Application of voting classifiers Smart Agricultural Technology 2025-01 Novel feature extraction in laser light backscattering imaging for real-time monitoring of quince moisture content during hot-air drying JOURNAL OF FOOD ENGINEERING 2025-01 Early monitoring of drought stress in safflower (Carthamus tinctorius L.) using hyperspectral imaging: a comparison of machine learning tools and feature selection approaches Plant Stress 2024-12 Microwave spectroscopy in a free-space arrangement for nondestructive quality assessment of chicken eggs: Comparing different measurement modes and feature selection approaches FOOD CHEMISTRY 2024-11 Using visible and near infrared spectroscopy and machine learning for estimating total petroleum hydrocarbons in contaminated soils JOURNAL OF NEAR INFRARED SPECTROSCOPY 2024-10
