an official journal of: published by:
Editor in Chief: RAFFAELLO COSSU


  • Namrata Mhaddolkar - Waste Processing Technology and Waste Management (AVAW) , Montanuniversitat Leoben , Austria
  • Gerald Koinig - Waste Processing Technology and Waste Management (AVAW) , Montanuniversitat Leoben , Austria
  • Daniel Vollprecht - Waste Processing Technology and Waste Management (AVAW) , Montanuniversität Leoben , Austria

DOI 10.31025/2611-4135/2022.15216

Released under CC BY-NC-ND

Copyright: © 2021 CISA Publisher

Editorial History

  • Received: 18 Dec 2021
  • Revised: 05 Sep 2022
  • Accepted: 05 Sep 2022
  • Available online: 14 Sep 2022


Biobased plastics are often seen to be an environmentally friendly alternative to conventional plastics, with their share, though being less now, is gradually increasing. This necessitates that the waste management of these possibly eco-friendly materials is also at par with their growth. Near-infrared (NIR) sorting is an effective waste sorting technology and is already widely used for conventional plastics. Thus, it would be imperative to analyse whether this effective existing infrastructure could also be successfully used to sort bioplastic. In the present study, the lab-scale NIR sensor-based sorting system in Montanuniversität Leoben was used to analyse polylactic acid (PLA) in three sets of experiments. First, the spectra of 7 conventional plastics were compared to that of virgin PLA and it was found that PLA has a distinct spectrum and should ideally be detected from a mixed plastic fraction. Second, it was assessed whether different grades and thicknesses of virgin PLA samples produced different spectra and it was found that there is a slight difference in the intensities without any wavelength shift of the recognizable peaks. Lastly, the detection of 10 PLA product samples was tested using the NIR recipe of a virgin PLA. It was observed that the samples were successfully detected and blown out as PLA for all the conducted trials. Additionally, it was also seen that an appropriate backlight setting is important to be able to correctly sort the transparent PLA products in the used chute-type sorter.



Alaerts, L., Augustinus, M., & van Acker, K. (2018). Impact of Bio-Based Plastics on Current Recycling of Plastics. Sustainability, 10(5), 1487.
DOI 10.3390/su10051487

Amigo, J. M., Babamoradi, H., & Elcoroaristizabal, S. (2015). Hyperspectral image analysis. A tutorial. Analytica Chimica Acta, 896, 34–51.
DOI 10.1016/j.aca.2015.09.030

biofutura. (2021, May 27). CPLA Material Bio Futura - Sustainable.

Bonifazi, G [Giuseppe], Gasbarrone, R., & Serranti, S [Silvia] (2021). Detecting CONTAMINANTS IN POST-CONSUMER PLASTIC PACKAGING WASTE BY A NIR HYPERSPECTRAL IMAGING-BASED CASCADE DETECTION APPROACH. Detritus, Volume 15- June 2021.
DOI 10.31025/2611-4135/2021.14086

Briassoulis, D., Pikasi, A., & Hiskakis, M. (2020). Recirculation potential of post-consumer /industrial bio-based plastics through mechanical recycling - Techno-economic sustainability criteria and indicators. Polymer Degradation and Stability, 109217.
DOI 10.1016/j.polymdegradstab.2020.109217

Calabrò, P. S., & Grosso, M. (2018). Bioplastics and waste management. Waste Management (New York, N.Y.), 78, 800–801.
DOI 10.1016/j.wasman.2018.06.054

Cao, J., & Sharma, S. (2013). Near-Infrared Spectroscopy for Anticounterfeiting Innovative Fibers. ISRN Textiles, 2013, 1–4.
DOI 10.1155/2013/649407

Chen, X., Kroell, N., Li, K., Feil, A., & Pretz, T. (2021). Influences of bioplastic polylactic acid on near-infrared-based sorting of conventional plastic. Waste Management & Research : The Journal of the International Solid Wastes and Public Cleansing Association, ISWA, 734242X211003969.
DOI 10.1177/0734242X211003969

DIRECTIVE 2008/98/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL of 19 November 2008 on waste and repealing certain Directives 1 (2008).

Friedrich, K [Karl], Koinig, G [Gerald], Fritz, T., Pomberger, R., & Vollprecht, D [Daniel] (2022). Sensor-based and Robot Sorting Processes and their Role in Achieving European Recycling Goals - A Review. Academic Journal of Polymer Science, 5(4), 1–18.
DOI 10.19080/AJOP.2021.05.555668

Friedrich, K [Karl], Koinig, G [Gerald], Pomberger, R., & Vollprecht, D [Daniel] (2022). Qualitative analysis of post-consumer and post-industrial waste via near-infrared, visual and induction identification with experimental sensor-based sorting setup. MethodsX, 9, 101686.
DOI 10.1016/j.mex.2022.101686

Gere, D., & Czigany, T. (2019). Recycling of Mixed Poly(Ethylene-terephthalate) and Poly(Lactic Acid). MATEC Web of Conferences, 253, 2005.
DOI 10.1051/matecconf/201925302005

Ghasemzadeh-Barvarz, M., Rodrigue, D., & Duchesne, C. (2014). Multivariate image analysis for inspection of multilayer films. Polymer Testing, 40, 196–206.
DOI 10.1016/j.polymertesting.2014.09.011

Hahladakis, J. N., & Iacovidou, E. (2018). Closing the loop on plastic packaging materials: What is quality and how does it affect their circularity? The Science of the Total Environment, 630, 1394–1400.
DOI 10.1016/j.scitotenv.2018.02.330

Hahladakis, J. N., & Iacovidou, E. (2019). An overview of the challenges and trade-offs in closing the loop of post-consumer plastic waste (PCPW): Focus on recycling. Journal of Hazardous Materials, 380, 120887.
DOI 10.1016/j.jhazmat.2019.120887

Helena Wedin, C. Gupta, Pailak Mzikian, F. Englund, R. Hornbuckle, Vittoria Troppenz, Lucijan Kobal, M. Costi, D. Ellams, & S. Olsson (2017). Title : Can automated NIR technology be a way to improve the sorting quality of textile waste ? In

Koinig, G [G.], Friedrich, K [K.], Rutrecht, B [B.], Oreski, G., Barretta, C [C.], & Vollprecht, D [D.] (2022). Influence of reflective materials, emitter intensity and foil thickness on the variability of near-infrared spectra of 2D plastic packaging materials. Waste Management (New York, N.Y.), 144, 543–551.
DOI 10.1016/j.wasman.2021.12.019

Koinig, G [Gerald], Rutrecht, B [Bettina], Friedrich, K [Karl], Barretta, C [Chiara], & Vollprecht, D [Daniel] (2022). Latent Recycling Potential of Multilayer Films in Austrian Waste Management. Polymers, 14(8), 1553.
DOI 10.3390/polym14081553

Kotu, V., & Deshpande, B [Bala]. (2018). Chapter 8 - Model Evaluation. In V. Kotu & B. Deshpande (Eds.), Data science: Concepts and practice / Vijay Kotu, Bala Deshpande (pp. 263–279). Morgan Kaufmann.
DOI 10.1016/B978-0-12-814761-0.00008-3

Lorber, K., Kreindl, G., Erdin, E., & Sarptaş, H. (2015). Waste Management Options for Biobased Polymeric Composites. In

Manley, M. (2014). Near-infrared spectroscopy and hyperspectral imaging: Non-destructive analysis of biological materials. Chemical Society Reviews, 43(24), 8200–8214.
DOI 10.1039/C4CS00062E

Masoumi, H., Safavi, S. M., & Khani, Z. (2012). Identification and classification of plastic resins using near infrared reflectance spectroscopy. International Journal of Mechanical and Industrial Engineering, 6, 213–220

Müller, G., Hanecker, E., Blasius, K., Seidemann, C., Tempel, L., Sadocco, P., Pozo, B. F., Boulougouris, G., Lozo, B., Jamnicki, S., & Bobu, E. (2014). End-of-life Solutions for Fibre and Bio-based Packaging Materials in Europe. Packaging Technology and Science, 27(1), 1–15.
DOI 10.1002/pts.2006

Neo, E. R. K., Yeo, Z., Low, J. S. C., Goodship, V., & Debattista, K. (2022). A review on chemometric techniques with infrared, Raman and laser-induced breakdown spectroscopy for sorting plastic waste in the recycling industry. Resources, Conservation and Recycling, 180, 106217.
DOI 10.1016/j.resconrec.2022.106217

Niaounakis, M. (2019). Recycling of biopolymers – The patent perspective. European Polymer Journal, 114, 464–475.
DOI 10.1016/j.eurpolymj.2019.02.027

Pieszczek, L., & Daszykowski, M. (2019). Improvement of recyclable plastic waste detection – A novel strategy for the construction of rigorous classifiers based on the hyperspectral images. Chemometrics and Intelligent Laboratory Systems, 187, 28–40.
DOI 10.1016/j.chemolab.2019.02.009

Rani, M., Marchesi, C., Federici, S., Rovelli, G., Alessandri, I., Vassalini, I., Ducoli, S., Borgese, L., Zacco, A., Bilo, F., Bontempi, E., & Depero, L. E. (2019). Miniaturized Near-Infrared (MicroNIR) Spectrometer in Plastic Waste Sorting. Materials (Basel, Switzerland), 12(17).
DOI 10.3390/ma12172740

Rodarmel, C., & Shan, J. (2002). Principal Component Analysis for Hyperspectral Image Classification. Surveying and Land Information Systems, 62(2), 115-000.

Saito, T., & Rehmsmeier, M. (2015). The precision-recall plot is more informative than the ROC plot when evaluating binary classifiers on imbalanced datasets. PLOS ONE, 10(3), e0118432.
DOI 10.1371/journal.pone.0118432

Serranti, S [Silvia], & Bonifazi, G [Giuseppe]. (2018). 2 - Techniques for separation of plastic wastes. In F. P. Torgal, J. M. Khatib, F. Colangelo, & R. Tuladhar (Eds.), Woodhead Publishing series in civil and structural engineering. Use of recycled plastics in eco-efficient concrete (pp. 9–37). Woodhead Publishing.
DOI 10.1016/B978-0-08-102676-2.00002-5

Ulrici, A., Serranti, S [S.], Ferrari, C., Cesare, D., Foca, G., & Bonifazi, G [G.] (2013). Efficient chemometric strategies for PET–PLA discrimination in recycling plants using hyperspectral imaging. Chemometrics and Intelligent Laboratory Systems, 122, 31–39.
DOI 10.1016/j.chemolab.2013.01.001

Wu, X., Li, J., Yao, L., & Xu, Z. (2020). Auto-sorting commonly recovered plastics from waste household appliances and electronics using near-infrared spectroscopy. Journal of Cleaner Production, 246, 118732.
DOI 10.1016/j.jclepro.2019.118732

Zheng, Y., Bai, J., Xu, J., Li, X., & Zhang, Y. (2018). A discrimination model in waste plastics sorting using NIR hyperspectral imaging system. Waste Management (New York, N.Y.), 72, 87–98.
DOI 10.1016/j.wasman.2017.10.015

Zhu, S., Chen, H., Wang, M., Guo, X., Lei, Y., & Jin, G. (2019). Plastic solid waste identification system based on near infrared spectroscopy in combination with support vector machine. Advanced Industrial and Engineering Polymer Research, 2(2), 77–81.
DOI 10.1016/j.aiepr.2019.04.001