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Application notes and research

A guide to validating NIR methods, method notes for materials we've already modelled, and the peer-reviewed NIR studies behind metaspeQ.

Guides

Application notes

Publications

Research anchor

Prof. Rajib Bandyopadhyay

Director, Ayudyog Private Limited · Professor, Jadavpur University · 35 years as a professor

26 peer-reviewed NIR papers, 2016–2025, all co-authored by Prof. Bandyopadhyay

metaspeQ's calibration methods come from this body of work: NIR spectroscopy and chemometrics for tea, spices, herbal raw materials, pulses and fish. Each reference links to the paper's public DOI page. Names in bold are Prof. Bandyopadhyay.

Journal articles

  1. Sengupta, R., Bag, A. K., Tudu, B. and Bandyopadhyay, R. (2025). Convolutional Neural Network Based Deep Learning Approach of Polyphenol Content Prediction for Fresh Tea Leaves Using NIR Spectroscopy. SN Computer Science, 7(1). doi.org/10.1007/s42979-025-04627-5
  2. Rahaman, S. H., Banerjee, S., Ali, S. B., Tudu, B., Das, N., Naskar, S., Ghorai, S., Chatterjee, A., Bandyopadhyay, R. and Tudu, B. (2025). Regression based prediction of piperine content in black pepper using near infrared spectroscopy. Journal of Near Infrared Spectroscopy, 33(3-4), 64–76. doi.org/10.1177/09670335251369047
  3. Sing, D., Banerjee, S., Mallik, R., Yonzone, U. A., Hazarika, A. K., Majumdar, K. and Bandyopadhyay, R. (2024). Rapid and non-destructive quality estimation of cinchona, andrographis paniculata, and black pepper using a portable NIR spectroscopy measuring device. Microchemical Journal, 199, 109949. doi.org/10.1016/j.microc.2024.109949
  4. Naskar, S., Sing, D., Banerjee, S., Shcherbakova, A., Bandyopadhyay, A., Kar, A., Haldar, P. K., Sharma, N., Mukherjee, P. K. and Bandyopadhyay, R. (2024). Rapid quality assessment and traceability of ginger powder from Northeast India and Indian market based on near infrared spectroscopic fingerprinting. Phytochemical Analysis, 36(2), 369–376. doi.org/10.1002/pca.3397
  5. Kar, S., Tudu, B. and Bandyopadhyay, R. (2024). Statistical machine learning techniques applied to NIR spectral data for rapid detection of sudan dye-I in turmeric powders with optimized pre-processing and wavelength selection. Journal of Food Science and Technology, 61(10), 1955–1964. doi.org/10.1007/s13197-024-05971-9
  6. Sing, D., Banerjee, S., Jana, S. N., Mallik, R., Dastidar, S. G., Majumdar, K., Bandyopadhyay, A., Bandyopadhyay, R. and Mukherjee, P. K. (2021). Estimation of Andrographolides and Gradation of Andrographis paniculata Leaves Using Near Infrared Spectroscopy Together With Support Vector Machine. Frontiers in Pharmacology, 12. doi.org/10.3389/fphar.2021.629833
  7. Kar, S., Tudu, B., Jana, A. and Bandyopadhyay, R. (2019). FT-NIR spectroscopy coupled with multivariate analysis for detection of starch adulteration in turmeric powder. Food Additives & Contaminants: Part A, 36(6), 863–875. doi.org/10.1080/19440049.2019.1600746
  8. Chanda, S., Hazarika, A. K., Choudhury, N., Islam, S. A., Manna, R., Sabhapondit, S., Tudu, B. and Bandyopadhyay, R. (2019). Support vector machine regression on selected wavelength regions for quantitative analysis of caffeine in tea leaves by near infrared spectroscopy. Journal of Chemometrics, 33(10). doi.org/10.1002/cem.3172
  9. Hazarika, A. K., Chanda, S., Sabhapondit, S., Sanyal, S., Tamuly, P., Tasrin, S., Sing, D., Naskar, H., Tudu, B. and Bandyopadhyay, R. (2018). On-site estimation of total polyphenol in fresh tea leaf using near-infrared spectroscopy. NIR news, 29(1), 9–14. doi.org/10.1177/0960336017750326
  10. Hazarika, A. K., Chanda, S., Sabhapondit, S., Sanyal, S., Tamuly, P., Tasrin, S., Sing, D., Tudu, B. and Bandyopadhyay, R. (2018). Quality assessment of fresh tea leaves by estimating total polyphenols using near infrared spectroscopy. Journal of Food Science and Technology, 55(12), 4867–4876. doi.org/10.1007/s13197-018-3421-6
  11. Kar, S., Tudu, B., Bag, A. K. and Bandyopadhyay, R. (2017). Application of Near-Infrared Spectroscopy for the Detection of Metanil Yellow in Turmeric Powder. Food Analytical Methods, 11(5), 1291–1302. doi.org/10.1007/s12161-017-1106-9

Conference papers and book chapters

  1. Kow, T., Nandy, S., Debabhuti, N., Firdoushi, S., Sharma, P., Bandyopadhyay, R. and Tudu, B. (2024). Discrimination of Different Varieties of Large Indian Cardamom Using NIR Spectroscopy. Springer Proceedings in Information and Communication Technologies, 559–566. doi.org/10.1007/978-981-97-5157-0_46
  2. Sengupta, R., Bag, A. K., Tudu, B. and Bandyopadhyay, R. (2024). Machine Learning Approach of Polyphenol Content Prediction for Fresh Tea Leaves Using NIR Spectroscopy. Springer Proceedings in Information and Communication Technologies, 483–494. doi.org/10.1007/978-981-97-5157-0_39
  3. Giri, A., Sing, D., Dastidar, S. G., Halder, P. K., Sharma, N., Mukherjee, P. K. and Bandyopadhyay, R. (2023). Application of NIR Spectroscopy with Chemometrics for Discrimination of Indian Black Pepper Berries. Lecture Notes in Electrical Engineering, 475–482. doi.org/10.1007/978-981-19-6913-3_32
  4. Nag, S., Das, D., Bhowmik, S., Tudu, B., Bandyopadhyay, R. and Roy, R. B. (2022). An assessment of Metanil Yellow Adulteration in Pigeon Pea using NIR Spectroscopy. 2022 2nd International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET), 1–3. doi.org/10.1109/icefeet51821.2022.9848090
  5. Banerjee, S., Ghatak, B., Naskar, H., Ghosh, S., Dhara, M., Ali, S. B., Das, N., Tudu, B. and Bandyopadhyay, R. (2022). Discrimination of Thymoquinone Using Near Infrared Spectroscopy Technique. 2022 2nd International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET), 1–2. doi.org/10.1109/icefeet51821.2022.9847893
  6. Das, D., Nag, S., Naskar, H., Hazarika, A. K., Roy, R. B., Sabhapondit, S., Tudu, B. and Bandyopadhyay, R. (2020). Discrimination of Various Clones of Black Tea Using NIR Spectroscopy. 2020 International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET), 1–3. doi.org/10.1109/icefeet49149.2020.9186954
  7. Nag, S., Das, D., Naskar, H., Roy, R. B., Tudu, B. and Bandyopadhyay, R. (2020). Estimation of Theophylline in Black Tea Using NIR Spectroscopy. 2020 International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET), 1–3. doi.org/10.1109/icefeet49149.2020.9186994
  8. Dei, J., Naskar, H., Dasgupta, S., Nag, S., Behera, B. K., Tudu, B., Roy, R. B. and Bandyopadhyay, R. (2020). Fish Freshness Assessment using NIR spectroscopy. 2020 International Conference on Emerging Frontiers in Electrical and Electronic Technologies (ICEFEET), 1–3. doi.org/10.1109/icefeet49149.2020.9187016
  9. Sing, D., Mallik, R., Dastidar, S. G., Bandyopadhyay, R., Banerjee, S., Jana, S. N. and Mukherjee, P. K. (2020). Prediction of Andrographolide Content in Andrographis paniculata Using NIR Spectroscopy. 2020 IEEE Applied Signal Processing Conference (ASPCON), 335–338. doi.org/10.1109/aspcon49795.2020.9276668
  10. Kar, S., Tudu, B. and Bandyopadhyay, R. (2019). Identification and Classification of Sudan Dye I Adulterants in Turmeric Powder by Nir Spectroscopy and Support Vector Machine. 2019 IEEE International Symposium on Olfaction and Electronic Nose (ISOEN). doi.org/10.1109/isoen.2019.8823529
  11. Kar, S., Tudu, B. and Bandyopadhyay, R. (2018). Comparison of Different Pre-processing Techniques towards Discrimination of Turmeric Powders using Near-infrared Spectra and Exploratory Data Analysis. 2018 IEEE Applied Signal Processing Conference (ASPCON), 193–197. doi.org/10.1109/aspcon.2018.8748565
  12. Kar, S., Naskar, H., Tudu, B. and Bandyopadhyay, R. (2018). Comparison of Multivariable Techniques for Brand Classification of Turmeric Powders by Near-infrared (NIR) Spectroscopy. 2018 Fourth International Conference on Research in Computational Intelligence and Communication Networks (ICRCICN), 98–102. doi.org/10.1109/icrcicn.2018.8718705
  13. De, A., Chanda, S., Tudu, B., Bandyopadhyay, R., Hazarika, A. K., Sabhapondit, S., Baruah, B. D., Tamuly, P. and Bhattachryya, N. (2017). Wavelength Selection for Prediction of Polyphenol Content in Inward Tea Leaves Using NIR. 2017 IEEE 7th International Advance Computing Conference (IACC), 184–187. doi.org/10.1109/iacc.2017.0050
  14. Kar, S., Tudu, B., Bandyopadhyay, R. and Bag, A. K. (2016). Discrimination of turmeric brands by means of near infrared (NIR) spectroscopy combined with chemometrics. 2016 International Conference on Intelligent Control Power and Instrumentation (ICICPI), 74–78. doi.org/10.1109/icicpi.2016.7859677
  15. Chanda, S., De, A., Tudu, B., Bandyopadhyay, R., Hazarika, A. K., Sabhapondit, S., Baruah, B., Tamuly, P. and Bhattachryya, N. (2016). Prediction of polyphenol content in tea leaves using NIR spectroscopy. 2016 International Conference on Intelligent Control Power and Instrumentation (ICICPI). doi.org/10.1109/icicpi.2016.7859672

Bibliographic details from Crossref. Some papers are open access; others may need a journal subscription.

Webinars

The NIR-Sight webinar series, hosted by metaspeQ ahead of the 9th Asian NIR Symposium (ANS-2024), is on our YouTube channel.