B
Brajesh Kumar Panda
Researcher at Indian Institute of Technology Kharagpur
Publications - 20
Citations - 224
Brajesh Kumar Panda is an academic researcher from Indian Institute of Technology Kharagpur. The author has contributed to research in topics: Computer science & Hyperspectral imaging. The author has an hindex of 6, co-authored 15 publications receiving 115 citations. Previous affiliations of Brajesh Kumar Panda include University of South Australia & Lethbridge College.
Papers
More filters
Popping and Puffing of Cereal Grains: A Review
TL;DR: A brief review of popping characteristics of different cere al grains and popping methods in response to high popping yield and great er volume expansion ratio can be found in this article, where a wide range of cereals and millets such as rice, wheat, corn, sorghum, ragi, foxtail m illet are used for popping.
Journal ArticleDOI
Rapid Assessment of Quality Change and Insect Infestation in Stored Wheat Grain Using FT-NIR Spectroscopy and Chemometrics
TL;DR: In this article, the authors developed a rapid and non-destructive FT-NIR spectroscopic method for the determination of insect infestation by analyzing the quality changes in grain due to infestation.
Journal ArticleDOI
Prediction of Sitophilus granarius infestation in stored wheat grain using multivariate chemometrics & fuzzy logic-based electronic nose analysis
TL;DR: The findings of this study will open up a convenient, rapid yet nondestructive approach for quality determination of insect infested wheat grains at various stages during the storage.
Journal ArticleDOI
Research advancements in optical imaging and spectroscopic techniques for nondestructive detection of mold infection and mycotoxins in cereal grains and nuts
Gayatri Mishra,Brajesh Kumar Panda,Wilmer Ariza Ramirez,Hye-Won Jung,Chandra B. Singh,Chandra B. Singh,Sang-Heon Lee,Ivan Lee +7 more
TL;DR: In this article, a review summarizes the recent application of rapid and nondestructive optical imaging and spectroscopic techniques, including digital color imaging, X-ray imaging, near-infrared spectroscopy, fluorescent, multispectral, and hyperspectral imaging.
Journal ArticleDOI
Sensor array optimization and determination of Rhyzopertha dominica infestation in wheat using hybrid neuro-fuzzy-assisted electronic nose analysis
TL;DR: In this article, the E-nose consists of 18 metal oxide semiconductor (MOS) sensors and the resistance of all the sensors changes in response to the volatile organic compounds generated from the insect-infested wheat grains.