Skip to main content
Log in

Design, Construction, and Testing of an Automated NIR In-line Analysis System for Potatoes. Part II. Development and Testing of the Automated Semi-industrial System with In-line NIR for the Characterization of Potatoes

  • Published:
Potato Research Aims and scope Submit manuscript

Abstract

An automated semi-industrial system with in-line near-infrared reflectance (NIR) for the characterization of the chemical composition of potatoes was designed and constructed, and its performance was tested. The system consisted of the following subsystems: sample crate manipulator, weighing unit for the gross sample weight, potato washing machines with a washing water recycling system, belt for visual inspection of the potatoes, unit for measuring the underwater weight (UWW), industrial rotary saw blade rasp for pulping the potatoes equipped with a sulfite dosage system for inhibiting enzymatic browning of the pulped potatoes, and industrial NIR system for the measurement of the potato composition. The whole system was controlled and operated by a programmable logic controller and process personal computer system. The system was able to process 12 potato samples per hour. Measurements were done to establish the sample carry-over in the system. The carry-over was proven to be well below the maximum acceptable level of 2%. The UWW values established with the automatic system corresponded very well with the UWW data obtained by manual weighting. The day-to-day reproducibility of the UWW system was tested with golf balls. These balls have about the same specific gravity and size as potatoes. The day-to-day reproducibility coefficient of variation of the UWW unit was 0.4%. As a principle of proof, two tentative partial least squares calibration models, one for the starch concentration and one for the coagulating protein concentration in the potato samples, were calculated, applying leaving one out cross-validation. Both models were very promising. The by NIR-predicted starch concentrations showed to be at least as good or even better than the by UWW-obtained starch concentrations. The average difference between the by NIR-predicted and the chemically measured starch concentration was 0.0 ± 0.3% (w/w). For the coagulating protein concentration, the average difference between the by NIR-predicted and the chemically measured concentration was 0.00 ± 0.06% (w/w). In future years, potatoes of a wider range of varieties, growing locations, and growing seasons have to be added to the present tentative model, in order to get a robust NIR model.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

Abbreviations

CVR :

Coefficient of variation in reproducibility

FT-NIR:

Fourier transform near-infrared reflectance

MSC:

Multiple scatter correction

NIR:

Near-infrared reflectance

PC:

Principle component

PLC:

Programmable logic controller

PLS:

Partial least squares regression

PLS2:

A partial least square regression procedure

r 2 :

Squared correlation coefficient

rpm:

Rotations per minute

STDRANGE:

Standard deviation in the sample set

STDREF:

Standard deviation of the reference analysis

STDRATIO:

Ratio between the standard deviation in the sample set and the standard deviation in the reference analysis (STDRANGE/STDREF)

UWW:

Underwater weight

References

  • Brunt K, Drost WC (2003) Determination of potato quality by NIR. In: Revealing secrets of the process. Proceedings of the Fifth European Symposium on Near InfraRed (NIR) Spectroscopy, 15–17 Sep 2003. Kolding, Denmark, pp 51–59

  • Brunt, K, Drost WC (2010) Design, construction and testing of an automated NIR in-line analysis system for potatoes. Part I. Off-line NIR feasibility study for the characterization of the potato composition. Potato Res 53(1):25–39

    Google Scholar 

  • Diller M (2002) Untersuchungen zur NIRS-methodenentwicklung für Kartoffeln aus dem Organischen Landbau unter Berücksichtung von Jahrgangs- und Sorteneinflüssen. Dissertation. Rheinischen Friedrich-Wilhelms-Universität Bonn

  • Dull GG, Birth GS, Leffler RG (1989) Use of near infrared analysis for the non-destructive measurement of dry matter in potatoes. Am Potato 66:215–225

    Article  Google Scholar 

  • Fernandez-Ahumada E, Garrido-Varo A, Guerrero-Ginel AE, Wubbels A, van der Sluis C, van der Meer JM (2006) Understanding factors affecting near infrared analysis of potato constituents. J Near Infrared Spectrosc 14:27–35

    Article  CAS  Google Scholar 

  • Haase NU (2003/2004) Estimation of dry matter and starch concentration in potatoes by determination of under-water weight and near infrared spectroscopy. Potato Res 46:117–127

    Article  Google Scholar 

  • Haase NU (2006) Rapid estimation of potato tuber quality by near-infrared spectroscopy. Starch 58:1–5

    Article  Google Scholar 

  • Hartmann R (1998) Entwicklung und Anwendung einer NIR-spektrometrischen Methode zur Differentzierung von Kartoffelqualitäten im Organischen Landbau. Dissertation, Rheinischen Friedrich-Wilhems-Universitat Bonn

  • ISO 6493 (2000) Animal feeding stuffs—Determination of starch—Polarimetric method

  • Mehrübeoglu M, Coté GL (1997) Determination of total reducing sugars in potato samples using near infrared spectroscopy. Cer Foods World 42:409–413

    Google Scholar 

  • Naes T, Isaksson T, Fearn T, Davies T (2002) Chapter 10.3 Multiplicative scatter correction (MSC) and Chapter 13.4 Cross-validation. In: A user-friendly guide to multivariate calibration and classification, 1st edn. NIR Publications, Chichester, pp 114–119 and 160–162

  • Scanlon MG, Pritchard MK, Adams LR (1999) Quality evaluation of processing potatoes by near infrared reflectance. J Sci Food Agric 79:763–771

    Article  CAS  Google Scholar 

Download references

Acknowledgement

This project is co-financed by the Northern Netherlands Provinces, SNN EZ/KOMPAS, and the Ministry of LNV. The authors also acknowledge Steve Revett from Eurofins Laboratory Ltd, Wolverhampton, England, for his valuable corrections in English language of the manuscript.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kommer Brunt.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Brunt, K., Smits, B. & Holthuis, H. Design, Construction, and Testing of an Automated NIR In-line Analysis System for Potatoes. Part II. Development and Testing of the Automated Semi-industrial System with In-line NIR for the Characterization of Potatoes. Potato Res. 53, 41–60 (2010). https://doi.org/10.1007/s11540-010-9148-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11540-010-9148-z

Keywords

Navigation