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Jitendra Paliwal

Jitendra Paliwal

D-Index & Metrics

Engineering and Technology

D-Index
44
Citations
5749
World Ranking
5953
National Ranking
237

Overview

Jitendra Paliwal is affiliated with the University of Manitoba in Canada and has produced extensive research within the field of Agricultural and Biological Sciences. Their work encompasses a range of subfields including Plant Science, Food Science, Nutrition and Dietetics, Analytical Chemistry, and Biomedical Engineering.

Their research topics prominently cover Food composition and properties, Spectroscopy and Chemometric Analyses, Proteins in Food Systems, Smart Agriculture and AI, Advanced Chemical Sensor Technologies, Food Drying and Modeling, as well as Magnetic and Electromagnetic Effects.

Several recent papers highlight Paliwal's contributions in these areas:

  • Effects of extrusion conditions and nitrogen injection on physical, mechanical, and microstructural properties of red lentil puffed snacks (2020), Food and Bioproducts Processing
  • Digital Twins: A novel traceability concept for post-harvest handling (2022), Smart Agricultural Technology
  • Recent applications of novel laser techniques for enhancing agricultural production (2021), Laser Physics
  • Image-to-Image Translation-Based Data Augmentation for Improving Crop/Weed Classification Models for Precision Agriculture Applications (2022), Algorithms
  • Non-Destructive Estimation of Physicochemical Properties and Detection of Ripeness Level of Apples Using Machine Vision (2022), International Journal of Fruit Science

Paliwal frequently coauthors with several researchers, notably Mohammad Nadimi, Muhammad Mudassir Arif Chaudhry, Chyngyz Erkinbaev, Filiz Köksel, and Digvir S. Jayas, reflecting a collaborative research environment.

The primary publication venues where Paliwal's works appear include Foods, Powder Technology, Food and Bioprocess Technology, Journal of Stored Products Research, and Comprehensive Reviews in Food Science and Food Safety.

Best Publications

  • Detection of insect-damaged wheat kernels using near-infrared hyperspectral imaging

    C.B. Singh;D.S. Jayas;J. Paliwal;N.D.G. White

  • Hyperspectral imaging to classify and monitor quality of agricultural materials

    S. Mahesh;D.S. Jayas;J. Paliwal;N.D.G. White

  • Feasibility of near-infrared hyperspectral imaging to differentiate Canadian wheat classes

    S. Mahesh;A. Manickavasagan;D.S. Jayas;J. Paliwal

  • Identification of insect-damaged wheat kernels using short-wave near-infrared hyperspectral and digital colour imaging

    Chandra B. Singh;Digvir S. Jayas;Jitendra Paliwal;Noel D. G. White

  • Near-infrared spectroscopy and imaging in food quality and safety

    Wenbo Wang;Jitendra Paliwal

  • Cereal Grain and Dockage Identification using Machine Vision

    J Paliwal;N.S Visen;D.S Jayas;N.D.G White

  • Comparison of Partial Least Squares Regression (PLSR) and Principal Components Regression (PCR) Methods for Protein and Hardness Predictions using the Near-Infrared (NIR) Hyperspectral Images of Bulk Samples of Canadian Wheat

    S. Mahesh;D. S. Jayas;J. Paliwal;N. D. G. White

  • Multi-layer neural networks for image analysis of agricultural products

    D.S. Jayas;J. Paliwal;N.S. Visen

  • Classification of cereal grains using wavelet, morphological, colour, and textural features of non-touching kernel images

    R. Choudhary;J. Paliwal;D.S. Jayas

  • AE—Automation and Emerging Technologies: Evaluation of Neural Network Architectures for Cereal Grain Classification using Morphological Features

    J. Paliwal;N.S. Visen;D.S. Jayas

  • Identification of wheat classes using wavelet features from near infrared hyperspectral images of bulk samples.

    R. Choudhary;S. Mahesh;J. Paliwal;D.S. Jayas

  • Image Analysis of Bulk Grain Samples Using Neural Networks

    Neeraj Singh Visen;Jitendra Paliwal;Digvir Jayas;N.D.G. White

  • Fungal Detection in Wheat Using Near-Infrared Hyperspectral Imaging

    C. B. Singh;D. S. Jayas;J. Paliwal;N. D. G. White

  • Automatic classification of non-touching cereal grains in digital images using limited morphological and color features

    H. K. Mebatsion;J. Paliwal;D. S. Jayas

  • GRAIN KERNEL IDENTIFICATION USING KERNEL SIGNATURE

    J. Paliwal;N. S. Shashidhar;D. S. Jayas

  • Fungal Damage Detection in Wheat Using Short-Wave Near-Infrared Hyperspectral and Digital Colour Imaging

    C.B. Singh;D.S. Jayas;J. Paliwal;N.D.G. White

  • AE—Automation and Emerging Technologies: Identification and Segmentation of Occluding Groups of Grain Kernels in a Grain Sample Image

    N.S. Visen;N.S. Shashidhar;J. Paliwal;D.S. Jayas

  • Evaluation of variations in the shape of grain types using principal components analysis of the elliptic Fourier descriptors

    H. K. Mebatsion;J. Paliwal;D. S. Jayas

  • AE—Automation and Emerging Technologies: Specialist Neural Networks for Cereal Grain Classification

    N.S. Visen;J. Paliwal;D.S. Jayas;N.D.G. White

  • Computational Fluid Dynamics in Drying Process Modelling—a Technical Review

    Rani Puthukulangara Ramachandran;Mohsen Akbarzadeh;Jitendra Paliwal;Stefan Cenkowski

  • Pathogenetic process monitoring and early detection of pear black spot disease caused by Alternaria alternata using hyperspectral imaging

    Ting-tiao Pan;Erkinbaev Chyngyz;Da-Wen Sun;Jitendra Paliwal

  • Applications of Thermal Imaging in Agriculture - A Review

    Annamalai Manickavasagan;Digvir S. Jayas;Agri-Food Canada;Jitendra Paliwal

Frequent Co-Authors

Digvir S. Jayas
Digvir S. Jayas University of Manitoba
Joe LoVetri
Joe LoVetri University of Manitoba
Da-Wen Sun
Da-Wen Sun University College Dublin
Hongbin Pu
Hongbin Pu South China University of Technology
Surendranath P. Suman
Surendranath P. Suman University of Kentucky
Suresh Neethirajan
Suresh Neethirajan Dalhousie University

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