Research Article
Pushing HSI to the Limit for the Quantification of Peanut Traces in Bulk Powder Foods
Pilar Barreiro*, Belén Diezma, Teresa R. Cuadrado Dominguez, Inés María López-Calleja, Lourdes Lleó, Ana Herrero-Langreo, Puneet Mishra, Satyabrata Ghosh, Eva Cristina Correa, Teresa García, Nathalie Gorretta, SitiNurHidayah Mohamad, Pablo Delgado Sánchez, Facundo Ruiz, Christophe B.Y. Cordell, Douglas N. Rutled, Jean Michel Roger, Rosario Martínde Santos and Margarita Ruiz-Altisent
Corresponding Author: Pilar Barreiro, LPF_TAGRALIA Departamento de Ingeniería Agroforestal, UPM CEI Moncloa, Madrid, España
Received: March 1, 2018; Revised: June 26, 2018; Accepted: March 26, 2018
Citation: Barreiro P, Diezma B, Dominguez TRC, Calleja IML, LleóL, et al., (2018) Pushing HSI to the Limit for the Quantification of Peanut Traces in Bulk Powder Foods. Food Nutr Current Res, 1(2): 56-60.
Copyrights: ©2018Barreiro P, Diezma B, Dominguez TRC, Calleja IML, Lleó L, et al.This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Share :
  • 2695

    Views & Citations
  • 1695

    Likes & Shares

CEI Moncloa as the Origin of this Interdisciplinary Research


The CEI_Moncloa was a proposal coordinated by the Complutense University of Madrid (UCM) and the Technical University of Madrid (UPM), approved in 2011, in which 13 institutions have been integrated.It houses around 10,000 researchers, 10% of the national scientific production and approximately 80,000 students (75% of the UCM and 25% of the UPM), including the Agri-Food and Health Cluster. It is situated in the so-called Agroalimentary Corridor, which groups together the activities that all these groups carry out in the production of agricultural and livestock products, and their subsequent processing for the creation of safe, healthy and nutritious foodand feed.In this context we have been committed to finding synergistic and stable relations among research groups and as a consequence of a think tank set up to do this, there has been a steady scientific production since the first published works in 2014 (Figure 1). Detection Limit of the Reference Measurement

The main outcome of the think tank was the realisation that there was a need (both in biomedicine and the Agrofood industry) for low-cost real-time non-destructive methods for detecting peanut traces in powdered food ingredients such as flour, milk and cocoa. According to IUPAC[1], "trace" means any element having an average concentration of less than about 100 parts per million atoms (ppm) or less than 100 ug g-1. One of the relevant issues for the development of a new procedure is the need of a reliable reference procedure which should be at least one order of magnitude more sensitive than the proposed one. In this research the reference procedure was developed (prior to CEI_Moncloa) by the UCM research group (TRADETBIO) and consisted of both PCR and real-time PCR [1,2] for the quantification of peanut traces with 0.1 ppm resolution.


On the other hand, the spatial resolution of the Hyper Spectral images (HSI) images proposed by UPM (LPF_Tagralia) was identified as the cornerstone for the detection of peanut traces, therefore at the very initial steps the optimal configuration of HIS was set as to characterize particles of 70um size.


Selection of Wavelength Range

VIS and NIR spectroscopy and HIS have been evaluated in consecutive trials [3-9] using IRMM[i]-481e originating from Jumbo Runners, USA to guarantee the highest variability among peanut origins and treatments. The main conclusion being that VIS is sensitive to peanut variability, and does not provide sufficient specificity regarding milk and flour, based on results validated with commercial peanut samples (Figure 2). On the other hand, NIR spectroscopic imaging provides characteristic bands for peanut detection: 950 nm arising from O-H bond, 1212 nm arising from 2nd overtone of the C-H stretch of CH2group and 1450 nm arising from the 1st overtone of the O-H stretch, while HIS measurements at 70 µm resolution has shown the feasibility to detect up to 100 ppm (0.01 %) of peanut traces in any of the proposed powder foods (Figure 3).



Detecting peanut traces is relevant when it is sufficiently specific. Therefore, it is mandatory to avoid both false positives and false negatives. To this end, 49 commercial samples of cereals, legumes, oilseeds and nutswere obtained from local market of Madrid, Spain. All samples were ground with precautions to avoid cross-contamination. After grinding, all powdered food sampleswere sifted by passing through a sieve of 212 um, since diffuse reflectanceproperties are dependent on the size of particles, non-uniformity in size can cause scatter effects in the spectra. In this case the wavelength range proposed included all NIR data, except for the bands with highest sensitivity to peanuts. The result (see procedure in Figure 5a), attained for calibration and external validation [10,11] showed that the greatest challenge was in isolating peanuts from pine nuts. Figure 4b provides an indication or the most relevant wavelength bands for specificity. 

Calibration Transfer, Transcontinental Approach

Finally, it was necessary to determine whether our results were reproducible irrespective of the instrumental platform, a hypothesis which was dismissed after initial trials at the transcontinental level [12]. Therefore the development of calibration transfer techniques is required, and this step is still ongoing. Figure 5b summarizes some pros and cons of NIR spectroscopic techniques for the specific identification and quantification of peanut traces in powdered foods.

Prospective of Use for the Agro-Food Industry

The main conclusion of nearly a decade of research is that low-cost non-destructive NIR multispectral equipment associated with corresponding chemometric approaches should be commercially available in the near future, as derived from our AECOC[1] award in 2016. This technology can be complemented with real-time PCR when required with a highly significant reduction in cost, since it will only be used for contamination levels below 100ppm (0.01 %).



This research was financially supported by IDEAS and INDIA4EU2 project of Erasmus Mundus and PICATA of the MoncloaCampusof International Excellence (UCM-UPM, 2012).

  1. Maria Lopez-Calleja I, de la Cruz S, Gonzalez I, Garcia T, Martin R (2014) Survey of undeclared allergenic pistachio (Pistaciavera) in commercial foods by hydrolysis probe real-time PCR. Food Control 39: 49-55.
  2. Maria Lopez-Calleja I, de la Cruz S, Pegels N, Gonzalez I, Garcia T, et al. (2013) High resolution TaqMan real-time PCR approach to detect hazelnut DNA encoding for ITS rDNA in foods. Food Chem 141: 1872-1880.
  3. Mishra P, Barreiro Elorza P, Roger JM, Diezma Iglesias B, HerreroLangreo A, et al. (2014) Detection of peanut traces in wheat flour through NIR hyperspectral imaging spectroscopy. Hyperspectral imaging conference. Ricoh arena, Coventry, United Kingdom.
  4. Mishra P, Roger J-M, Barreiro Elorza P, Diezma Iglesias B, HerreroLangreo A, LleóGarcía L, et al. (2014) Application of Improved Direct Calibration for Hyperspectral image processing: Detecting peanut traces in wheat flour. Food Analysis Congress, Barcelona, Spain.
  5. Mishra P, Herrero-Langreo A, Barreiro P, Roger JM, Diezma B, et al. (2015) Detection and quantification of peanut traces in wheat flour by near infrared hyperspectral imaging spectroscopy using principal-component analysis. J Infrared Spectroscopy 23: 15-22.
  6. [Mishra P, HerreroLangreo A, Barreiro Elorza P, Roger J-M, Diezma Iglesias B, et al. (2015) Hyperspectral to multispectral imaging for detection of tree nuts and peanut traces in wheat flour. J Spectral Imaging 4: 1-9.
  7. Mohamad SNH, Ghosh S, Mishra P, Barreiro Elorza P, Diezma Iglesias B. (2015) Star dust memories, or how to detect allergen traces in powder foods. VII Congreso de EstudiantesUniversitarios de Ciencia, Tecnología e IngenieríaAgronómica. Madrid, Spain.
  8. Ghosh S, Domínguez TRC, Diezma B, Lleó L, Barreiro P, et al. (2015) VIS/NIR spectral signature for the identification of peanut contamination of powder foods. AgricEngInt J 17: 310-329.
  9. Cuadrado Dominguez TR, Ghosh S, Barreiro P, Lleo Garcia L, Diezma B, et al. (2014) VIS-NIR spectroscopy for the detection of peanuts traces in powder food. In: Tellez FA, Rodriguez AM, Sancho IM, Robinson MV, RuizAltisent M, Ballesteros FR, Hernando ECC, eds. VII CongresoIbérico de Agroingenieria y CienciasHorticolas: Innovar y Producirpara el Futuro Innovating and Producing for the Future. Madrid, Spain.
  10. Mishra P, Cordella CBY, Rutledge DN, Barreiro P, Roger JM, et al. (2016) Application of independent components analysis with the JADE algorithm and NIR hyperspectral imaging for revealing food adulteration. J Food Eng 168: 7-15.
  11. Ghosh S, Mishra P, Mohamad SNH, Martin de Santos R, Diezma Iglesias B, et al. (2016) Discrimination of peanuts from bulk cereals and nuts by near infrared reflectance spectroscopy. BiosystemsEng 151: 178-186.
  12. Cuadrado Dominguez TR, Barreiro Elorza P, LleóGarcía L, Ruiz F, et al. (2016) Prospective of NIR Calibration transfer need for detecting peanut traces in powder foods: a transcontinental approach. 4th CIGR International Conference of Agricultural Engineering (CIGR-AgEng2016). Aahrus University, Denmark.