000130597 001__ 130597
000130597 005__ 20240319081011.0
000130597 0247_ $$2doi$$a10.1039/d2ay01046a
000130597 0248_ $$2sideral$$a130341
000130597 037__ $$aART-2022-130341
000130597 041__ $$aeng
000130597 100__ $$0(orcid)0000-0001-5254-4403$$aLopez Molinero, Angel$$uUniversidad de Zaragoza
000130597 245__ $$aA mobile phone digital image method designed for efficient durum wheat flour characterization
000130597 260__ $$c2022
000130597 5060_ $$aAccess copy available to the general public$$fUnrestricted
000130597 5203_ $$aThe characterization and counting of foreign bodies and impurities in flour and semolina from wheat are decisive analytical parameters of safety and quality which should be evaluated in the context of efficiency and low cost. Moreover, their recognition and counting are required by the regulatory and quality norms of the sector. International standards such as UNI 10941:2001 could be applied but this has subjective interpretation. In this paper, a new analytical semi-automatic method based on digital images is assessed and proposed. The main features of the method are based on the use of representative sample images that could be taken under controlled illumination conditions with a smartphone. The images were then analyzed using a macro-script adapted to the free software Fiji-ImageJ for image processing. By changing the image color format to grey and its contrast, a threshold intensity, or cutoff, was selected to distinguish foreign bodies from the rest of the product. And the number of particles was counted. Finally, four different fractions of components in the product were recognized which characterized the type of product. The estimated processing time was less than 60 s. The method has been validated against 14 reference samples that were previously studied using the standard UNI 10941:2001. These samples presented low, medium and high particle content, as well as different background colors of the matrix product, from white to yellow. The results were obtained with an average of 6 ROIs taken in different locations of the same digital image. Figures of merit of the procedure such as the biases presented relative differences of less than +/- 20%, against reference values in the worst case. The reproducibility of the measurements, examining different locations, is better than 30-40% RSD. Likewise, the reproducibility in the same ROI but with short scans in the threshold of selection produced response ranges of less than 30% RSD. These parameters are consistent with those prevalent in the sector and this type of product.
000130597 536__ $$9info:eu-repo/grantAgreement/ES/DGA/E25-20R$$9info:eu-repo/grantAgreement/ES/MICINN/PID2019-105408GB-I00
000130597 540__ $$9info:eu-repo/semantics/openAccess$$aAll rights reserved$$uhttp://www.europeana.eu/rights/rr-f/
000130597 590__ $$a3.1$$b2022
000130597 591__ $$aCHEMISTRY, ANALYTICAL$$b35 / 86 = 0.407$$c2022$$dQ2$$eT2
000130597 591__ $$aSPECTROSCOPY$$b12 / 41 = 0.293$$c2022$$dQ2$$eT1
000130597 592__ $$a0.535$$b2022
000130597 591__ $$aFOOD SCIENCE & TECHNOLOGY$$b69 / 142 = 0.486$$c2022$$dQ2$$eT2
000130597 593__ $$aAnalytical Chemistry$$c2022$$dQ2
000130597 593__ $$aEngineering (miscellaneous)$$c2022$$dQ2
000130597 594__ $$a5.5$$b2022
000130597 593__ $$aChemical Engineering (miscellaneous)$$c2022$$dQ2
000130597 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/acceptedVersion
000130597 7102_ $$12009$$2750$$aUniversidad de Zaragoza$$bDpto. Química Analítica$$cÁrea Química Analítica
000130597 773__ $$g14, 35 (2022), 3416 [7 pp.]$$pAnal. methods$$tANALYTICAL METHODS$$x1759-9660
000130597 8564_ $$s371370$$uhttps://zaguan.unizar.es/record/130597/files/texto_completo.pdf$$yPostprint
000130597 8564_ $$s390163$$uhttps://zaguan.unizar.es/record/130597/files/texto_completo.jpg?subformat=icon$$xicon$$yPostprint
000130597 909CO $$ooai:zaguan.unizar.es:130597$$particulos$$pdriver
000130597 951__ $$a2024-03-18-15:07:46
000130597 980__ $$aARTICLE