Applying Infrared Technique as a Nondestructive Method To Assess Wheat Grain Hardness

Ayman Ibrahim; Adrienne Csúr Varga; Márton Jolánkai; Ferenc Safranyik

doi:doi:10.11648/j.ijsqa.20180403.16

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Applying Infrared Technique as a Nondestructive Method To Assess Wheat Grain Hardness

Ayman Ibrahim, Adrienne Csúr Varga, Márton Jolánkai, Ferenc Safranyik

Published in International Journal of Science and Qualitative Analysis (Volume 4, Issue 3)

Received: 15 May 2018 Accepted: 29 May 2018 Published: 28 June 2018

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Abstract

Hardness, of wheat grains, is one of the most important quality characteristics used in wheat classification and determination of its marketing value. So, the key objective of this investigation applies a non-destructive method like infrared technique as an alternative method of destructive methods to assess hardness of wheat grains. The hardness characteristic was measured by two destructive methods Single-Kernel Characterization System (SKCS) and Instron Universal Testing Machine (IUTM), as reference values. Infrared technique was used to develop NIR calibration and validation model using the partial least squares (PLS) regression to assess wheat grain hardness. The best calibration and validation model for assess hardness of wheat grains were observed throughout the reference method Instron Universal Testing Machine (IUTM) within the wavelength range 950 to 1650 nm with 6 principal components (PCs) and pretreatment by Savitzky-Golay second derivative (S.G. 2^nd). Where, the optimum PLS was recorded at the lowest standard error of prediction (SEP) 3.92 N with the maximum value of coefficient of prediction (R^2P ≈ 0.91) and sufficient value of the relative prediction deviation (RPD ≈ 3.35). The accuracy of the prediction model was sufficient to use NIRS technique as a nondestructive method to estimate hardness of wheat grains for different varieties of the wheat.

Published in	International Journal of Science and Qualitative Analysis (Volume 4, Issue 3)
DOI	10.11648/j.ijsqa.20180403.16
Page(s)	100-107
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2018. Published by Science Publishing Group

Keywords

Wheat Quality, Hardness, Near Infrared (NIR), Partial Least Squares (PLS) Regression

References

[1]	Koga, S., Böcker, U., Uhlen, A. K., Hoel, B., Moldestad, A., 2016. Investigating environmental factors that cause extreme gluten quality deficiency in winter wheat. Acta Agriculturae Scandinavica Section B: Soil and Plant Science 66(3), 237-246.
[2]	Nakamura, K., Taniguchi, Y., Taira, M., Ito, H., 2012. Investigation of soft wheat flour quality factors associated with sponge cake sensory tenderness. Cereal Chemistry 89(2), 79-83.
[3]	Salmanowicz, B. P., Adamski, T., Surma, M., Kaczmarek, Z., Karolina, K., Kuczyńska, A., Banaszak, Z., Ługowska, B., Majcher, M., Obuchowski, W., 2012. The relationship between grain hardness, dough mixing parameters and bread-making quality in winter wheat. International Journal of Molecular Sciences 13, 4186-4201.
[4]	Pasha, I., Anjum, F. M., Morris, C. F., 2010. Grain Hardness: A Major Determinant of Wheat Quality. Food Science Technology International 16(6), 511- 522.
[5]	Faměra, O., Hrušková, M., Novotná, D., 2004. Evaluation of methods for wheat grain hardness determination. Plant soil environment 50(11), 489-493.
[6]	Wan, Y. N., 2002. Kernel handling performance of an automatic grain quality inspection system. Transactions of the American Society of Agricultural Engineers 45(2), 369-377.
[7]	Gaines, C. S., Finney, P. F., Fleege, L. M., Andrews, L. C., 1996. Predicting a hardness measurement using the single-kernel characterization system. Cereal Chemistry 73(2), 278-283.
[8]	Chen, F., Yu, Y., Xia, X., He, Z., 2007. Prevalence of a novel puroindoline b allele in Yunnan endemic wheats (Triticum aestivum ssp. Yunnanense King). Euphytica 156, 39-46.
[9]	Martin, J. M., Meyer, F. D., Morris, C. F., Giroux, M. J., 2007. Pilot scale milling characteristics of transgenic isolines of a hard wheat overexpressing puroindolines. Crop Science 47, 497-504.
[10]	Cane, K., Spackman, M., Eagles, H., 2004. Puroindoline genes and their effects on grain quality traits in southern Australian wheat cultivars. Australian Journal of Agricultural Research 55, 89-95.
[11]	Anjum, F. M., Walker, C. E., 1991. Review on the significance of starch and protein to wheat kernel hardness. Journal of the Science of Food and Agriculture 56, 1-13.
[12]	Shewry, P., 2009. Review paper: Wheat. Journal of Experimental Botany 60(6), 1537-1553.
[13]	Morris, C. F., Bettge, A. D., Pitts, M. J., King, G. E., Pecka, K., McCluskey, P. J., 2008. Compressive strength of wheat endosperm: comparison of endosperm bricksto the single kernel characterization system. Cereal Chemistry 85(3), 359-365.
[14]	Campbell, K. G., Bergman, C. J., Gualberto, D. G., Anderson, J. A., Giroux, M. J., Hareland, G., Fulcher, R. G., Sorrels, M. E., Finney, P. L., 1999. Quantitative trait loci associated with kernel traits in soft and hard wheat cross. Crop Science 39, 1184-1195.
[15]	Pomeranz, Y., Williams, P. C., 1990. Wheat hardness: its genetic, structural, and biochemical background, measurement, and significance. In: Dickinson. E and Stainsby. G. (eds). Advances in Cereal Science and Technology. Elsevier Applied Science publishsers Ltd., London. Chapter 8.
[16]	Hansen, A., Poll, L., 1997. Raavarekvalitet: Frugt, Groensager, Kartofler og Korn. Copenhagen: DSR Forlag. Cited by [4].
[17]	Kent, N. L., Evers, A. D., 1994. Technology of Cereals, 4th edn. Oxford: Pergamon Press.
[18]	Morris, C. F., 2002. Puroindolines: The molecular genetic basis of wheat grain hardness. Plant Molecular Biology 48, 633-647.
[19]	Dobraszczyk, B. J., Whitworth, M. B., Vincent, J. F. V., Khan, A. A., 2002. Single kernel wheat hardness and fracture properties in relation to density and the modelling of fracture in wheat endosperm. Journal of Cereal Science 35, 245-263.
[20]	Turnbull, K. M., Rahman, S., 2002. Endosperm texture in wheat. Journal of Cereal Science 36, 327-337.
[21]	Sirisomboon, P., Kitchaiya, P., Pholpho, T., Mahuttanyavanitch, W., 2007. Physical and mechanical properties of Jatropha curcas L. fruits, nuts and kernels. Journal of Food Engineering 97, 201-207.
[22]	Blandino, M., Marinaccio, F., Vaccino, P., Reyneri, A., 2015. Nitrogen Fertilization Strategies Suitable to Achieve the Quality Requirements of Wheat for Biscuit Production. Agronomy Journal 107(4), 1584-1594.
[23]	Gooding, M. J., Devis, W. P., 1997. Wheat production and utilization. CAB International, Wallingford.
[24]	Dupont, F. M., Altenbach, S. B., 2003. Molecular and biochemical impacts of environmental factors on wheat grain development and protein synthesis. Journal of Cereal Science 38, 133-146.
[25]	Johansson, E., Prieto-Linde, M. L., Svensson, G., 2004. Influence of nitrogen application rate and timing on grain protein composition and gluten strength in Swedish wheat cultivars. Journal of Plant Nutrition and Soil Science 167, 345-350.
[26]	Cobb, N. A., 1896. The hardness of the gram m the principal varieties of wheat. Agricultural Gazette of NSW 7, 279-299.
[27]	Greenaway, W. T., 1969. A Wheat Hardness Index. Cereal Sci. Today 14, 4-7.
[28]	Stenvert, N. L., 1974. Grinding resistance. A simple measure of wheat hardness. Flour Anim. Feed Milling 7, 24-27.
[29]	Chung, C. J., Clark, S. J., Lindholm, M. C., McGinty, R. J., Watson, C. A., 1977. The pearlograph technique for measuring wheat hardness. Transactions of the ASAE 18, 185.
[30]	Williams, P. C., Sobering, D. C., 1986. Attempts at standardization of hardness testing of wheat. II. The near infrared method. Cereal Foods World 31, 417-420.
[31]	Norris, K. H., Hruschka, W. R., Bean, M. M., Slaughter, D. C., 1989. A definition of wheat hardness using near infrared reflectance spec-troscopy. Cereal Foods World 34, 696-705.
[32]	AACC, 2000. Approved methods of the American Association of Cereal Chemists, 10th Ed. Methods 14-15A, 39-70A, 55-30 and 55-31. The Association: St. Paul, MN.
[33]	Osborne B. G., Turnbull K. M., Anderssen R. S., Rahman S., Sharp P. J., Appels, R., 2001. The hardness locus of Australian wheat lines. Australian Journal of Agricultural Research 52, 1275-1286.
[34]	Miller, B. S., Afework, S., Pomeranz, Y., Bruinsma, B. L., Booth, G. D., 1982. Measuring the hardness of wheat. Cereal Foods World 27, 61-64.
[35]	Ohm, J. B., Chung, O. K., Deyoe, C. W., 1998. Single-kernel characteristics of hard winter wheats in relation to milling and baking quality. Cereal Chemistry 75(1), 156-161.
[36]	Randall, P. G., Krieg, H. M., McGILL, A. E. J., 1992. Calibration companson between South African and Federal Grain Inspection Service and European calibrations. S. Afr. J. Food Sci. Nutr., 4, 33-35.
[37]	Williams, P. C., 1979. Screening wheat for protein and hardness by near infrared reflectance spectroscopy. Cereal Chemistry 56, 169-172.
[38]	Delwiche, S. R., 1993. Measurement of single-kernel wheat hardness usmg near infrared transmittance. Trans. ASAE. 36, 1431-1437.
[39]	Manley, M., 1995. Wheat hardness by near infrared (NIR) spectroscopy: New insights. Ph. D. Seale-Hayne Faculty of Agriculture, Food and Land Use. University of Plymouth, United Kingdom.
[40]	Maghirang, E. B., Dowell, F. E., 2003. Hardness measurement of bulk wheat by single-kernel visible and near-infrared reflectance spectroscopy. Cereal Chemistry 80(3), 316-322.
[41]	Mohsenin, N. N., 1986. Physical Properties of Plant and Animal Materials. Gordon and Breach Science Publishers, New York.
[42]	Martin, C. R., Rousser, R., Brabec, D. L., 1993. Development of a single-kernel wheat characterization system. Trans ASAE. 36(5), 1399-1404.
[43]	Williams, P. C., Norris, K., 2001. Near-infrared technology in the agricultural and food industries. American Association of Cereal Chemists, St Paul, MN, 296p.
[44]	Williams, P. C., Sobering, D. C., 1996. How do we do it: a brief summary of the methods we use in developing near infrared calibrations. In: Davies, A. M. C., Williams, P. C. (Eds.), Near Infrared Spectroscopy: The Future Waves. NIR Publications, Chichester, 185–188.
[45]	Beman, J. M., Arrigo, K. R., Matson, P. A., 2005. Agricultural runoff fuels large phytoplankton blooms in vulnerable areas of the ocean. Nature (434), 211-214.
[46]	Orloff, S., Wright, S., Ottman, M., 2012. Nitrogen Management Impacts On Wheat Yield And Protein. Proceedings, California Alfalfa and Grains Symposium, Sacramento, CA, December, 11-12. http://alfalfa.ucdavis.edu
[47]	Ibrahim, A., Csúr-Varga, A., Jolánkai, M., Mansour, H., Hamed, A., 2018. Monitoring some quality attributes of different wheat varieties by infrared technology. Agricultural Engineering International: CIGR Journal 20(1), 1-10.
[48]	Miller, C. E., 2001. Chemical principles of near infrared technology. In: Near Infrared Technology in the Agricultural and Food Industries. St. Paul, Minnesota, USA: American Association of Cereal Chemists, Inc.
[49]	Siesler, H. W., 2002. Introduction. In: Near Infrared Spectroscopy: Principles, Instruments, Applications. pp. 1-10. Weinheim, Germany: Wiley-VCH Verlag GmbH.
[50]	Nicolaï, B. M., Beullens, K., Bobelyn, E., Peirs, A., Saeys, W., Theron, K. I., Lammertyn, J., 2007. Nondestructive measurement of fruit and vegetable quality by means of NIR spectroscopy: a review. Postharvest Biology and Technology 46, 99-118.
[51]	Shenk, J. S., Workman, J. J., Westerhaus, M. O., 2007. Application of NIR spectroscopy to agricultural product. In E. W. Ciurczak, and D. A. Burns (Eds.), Handbook of near-infrared analysis (3rd ed.). 347-386.
[52]	Stuart, B. H., 2004. Infrared Spectroscopy: Fundamentals and Applications. 1st ed. Hoboken, NJ: Wiley and Sons.
[53]	Wold, S., Sjostrom, M., Eriksson, L., 2001. PLS-regression: a basic tool of chemometrics. Chemometr Intell Lab 58, 109-130.

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APA Style

Ayman Ibrahim, Adrienne Csúr Varga, Márton Jolánkai, Ferenc Safranyik. (2018). Applying Infrared Technique as a Nondestructive Method To Assess Wheat Grain Hardness. International Journal of Science and Qualitative Analysis, 4(3), 100-107. https://doi.org/10.11648/j.ijsqa.20180403.16

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ACS Style

Ayman Ibrahim; Adrienne Csúr Varga; Márton Jolánkai; Ferenc Safranyik. Applying Infrared Technique as a Nondestructive Method To Assess Wheat Grain Hardness. Int. J. Sci. Qual. Anal. 2018, 4(3), 100-107. doi: 10.11648/j.ijsqa.20180403.16

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AMA Style

Ayman Ibrahim, Adrienne Csúr Varga, Márton Jolánkai, Ferenc Safranyik. Applying Infrared Technique as a Nondestructive Method To Assess Wheat Grain Hardness. Int J Sci Qual Anal. 2018;4(3):100-107. doi: 10.11648/j.ijsqa.20180403.16

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@article{10.11648/j.ijsqa.20180403.16,
  author = {Ayman Ibrahim and Adrienne Csúr Varga and Márton Jolánkai and Ferenc Safranyik},
  title = {Applying Infrared Technique as a Nondestructive Method To Assess Wheat Grain Hardness},
  journal = {International Journal of Science and Qualitative Analysis},
  volume = {4},
  number = {3},
  pages = {100-107},
  doi = {10.11648/j.ijsqa.20180403.16},
  url = {https://doi.org/10.11648/j.ijsqa.20180403.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsqa.20180403.16},
  abstract = {Hardness, of wheat grains, is one of the most important quality characteristics used in wheat classification and determination of its marketing value. So, the key objective of this investigation applies a non-destructive method like infrared technique as an alternative method of destructive methods to assess hardness of wheat grains. The hardness characteristic was measured by two destructive methods Single-Kernel Characterization System (SKCS) and Instron Universal Testing Machine (IUTM), as reference values. Infrared technique was used to develop NIR calibration and validation model using the partial least squares (PLS) regression to assess wheat grain hardness. The best calibration and validation model for assess hardness of wheat grains were observed throughout the reference method Instron Universal Testing Machine (IUTM) within the wavelength range 950 to 1650 nm with 6 principal components (PCs) and pretreatment by Savitzky-Golay second derivative (S.G. 2nd). Where, the optimum PLS was recorded at the lowest standard error of prediction (SEP) 3.92 N with the maximum value of coefficient of prediction (R2P ≈ 0.91) and sufficient value of the relative prediction deviation (RPD ≈ 3.35). The accuracy of the prediction model was sufficient to use NIRS technique as a nondestructive method to estimate hardness of wheat grains for different varieties of the wheat.},
 year = {2018}
}

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TY  - JOUR
T1  - Applying Infrared Technique as a Nondestructive Method To Assess Wheat Grain Hardness
AU  - Ayman Ibrahim
AU  - Adrienne Csúr Varga
AU  - Márton Jolánkai
AU  - Ferenc Safranyik
Y1  - 2018/06/28
PY  - 2018
N1  - https://doi.org/10.11648/j.ijsqa.20180403.16
DO  - 10.11648/j.ijsqa.20180403.16
T2  - International Journal of Science and Qualitative Analysis
JF  - International Journal of Science and Qualitative Analysis
JO  - International Journal of Science and Qualitative Analysis
SP  - 100
EP  - 107
PB  - Science Publishing Group
SN  - 2469-8164
UR  - https://doi.org/10.11648/j.ijsqa.20180403.16
AB  - Hardness, of wheat grains, is one of the most important quality characteristics used in wheat classification and determination of its marketing value. So, the key objective of this investigation applies a non-destructive method like infrared technique as an alternative method of destructive methods to assess hardness of wheat grains. The hardness characteristic was measured by two destructive methods Single-Kernel Characterization System (SKCS) and Instron Universal Testing Machine (IUTM), as reference values. Infrared technique was used to develop NIR calibration and validation model using the partial least squares (PLS) regression to assess wheat grain hardness. The best calibration and validation model for assess hardness of wheat grains were observed throughout the reference method Instron Universal Testing Machine (IUTM) within the wavelength range 950 to 1650 nm with 6 principal components (PCs) and pretreatment by Savitzky-Golay second derivative (S.G. 2nd). Where, the optimum PLS was recorded at the lowest standard error of prediction (SEP) 3.92 N with the maximum value of coefficient of prediction (R2P ≈ 0.91) and sufficient value of the relative prediction deviation (RPD ≈ 3.35). The accuracy of the prediction model was sufficient to use NIRS technique as a nondestructive method to estimate hardness of wheat grains for different varieties of the wheat.
VL  - 4
IS  - 3
ER  -

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Author Information

Ayman Ibrahim

Department of Agricultural Bio-Engineering Systems, Agricultural Engineering Research Institute (AEnRI), Agricultural Research Center (ARC), Dokki, Giza, Egypt
Adrienne Csúr Varga

Crop Production Institute, Szent Istvan University, G?d?ll?, Hungary
Márton Jolánkai

Crop Production Institute, Szent Istvan University, G?d?ll?, Hungary
Ferenc Safranyik

Department of Mechanics and Technical Drawing, Faculty of Mechanical Engineering, Szent István University, G?d?ll?, Hungary

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Ayman Ibrahim, Adrienne Csúr Varga, Márton Jolánkai, Ferenc Safranyik. (2018). Applying Infrared Technique as a Nondestructive Method To Assess Wheat Grain Hardness. International Journal of Science and Qualitative Analysis, 4(3), 100-107. https://doi.org/10.11648/j.ijsqa.20180403.16

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ACS Style

Ayman Ibrahim; Adrienne Csúr Varga; Márton Jolánkai; Ferenc Safranyik. Applying Infrared Technique as a Nondestructive Method To Assess Wheat Grain Hardness. Int. J. Sci. Qual. Anal. 2018, 4(3), 100-107. doi: 10.11648/j.ijsqa.20180403.16

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AMA Style

Ayman Ibrahim, Adrienne Csúr Varga, Márton Jolánkai, Ferenc Safranyik. Applying Infrared Technique as a Nondestructive Method To Assess Wheat Grain Hardness. Int J Sci Qual Anal. 2018;4(3):100-107. doi: 10.11648/j.ijsqa.20180403.16

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@article{10.11648/j.ijsqa.20180403.16,
  author = {Ayman Ibrahim and Adrienne Csúr Varga and Márton Jolánkai and Ferenc Safranyik},
  title = {Applying Infrared Technique as a Nondestructive Method To Assess Wheat Grain Hardness},
  journal = {International Journal of Science and Qualitative Analysis},
  volume = {4},
  number = {3},
  pages = {100-107},
  doi = {10.11648/j.ijsqa.20180403.16},
  url = {https://doi.org/10.11648/j.ijsqa.20180403.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijsqa.20180403.16},
  abstract = {Hardness, of wheat grains, is one of the most important quality characteristics used in wheat classification and determination of its marketing value. So, the key objective of this investigation applies a non-destructive method like infrared technique as an alternative method of destructive methods to assess hardness of wheat grains. The hardness characteristic was measured by two destructive methods Single-Kernel Characterization System (SKCS) and Instron Universal Testing Machine (IUTM), as reference values. Infrared technique was used to develop NIR calibration and validation model using the partial least squares (PLS) regression to assess wheat grain hardness. The best calibration and validation model for assess hardness of wheat grains were observed throughout the reference method Instron Universal Testing Machine (IUTM) within the wavelength range 950 to 1650 nm with 6 principal components (PCs) and pretreatment by Savitzky-Golay second derivative (S.G. 2nd). Where, the optimum PLS was recorded at the lowest standard error of prediction (SEP) 3.92 N with the maximum value of coefficient of prediction (R2P ≈ 0.91) and sufficient value of the relative prediction deviation (RPD ≈ 3.35). The accuracy of the prediction model was sufficient to use NIRS technique as a nondestructive method to estimate hardness of wheat grains for different varieties of the wheat.},
 year = {2018}
}

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TY  - JOUR
T1  - Applying Infrared Technique as a Nondestructive Method To Assess Wheat Grain Hardness
AU  - Ayman Ibrahim
AU  - Adrienne Csúr Varga
AU  - Márton Jolánkai
AU  - Ferenc Safranyik
Y1  - 2018/06/28
PY  - 2018
N1  - https://doi.org/10.11648/j.ijsqa.20180403.16
DO  - 10.11648/j.ijsqa.20180403.16
T2  - International Journal of Science and Qualitative Analysis
JF  - International Journal of Science and Qualitative Analysis
JO  - International Journal of Science and Qualitative Analysis
SP  - 100
EP  - 107
PB  - Science Publishing Group
SN  - 2469-8164
UR  - https://doi.org/10.11648/j.ijsqa.20180403.16
AB  - Hardness, of wheat grains, is one of the most important quality characteristics used in wheat classification and determination of its marketing value. So, the key objective of this investigation applies a non-destructive method like infrared technique as an alternative method of destructive methods to assess hardness of wheat grains. The hardness characteristic was measured by two destructive methods Single-Kernel Characterization System (SKCS) and Instron Universal Testing Machine (IUTM), as reference values. Infrared technique was used to develop NIR calibration and validation model using the partial least squares (PLS) regression to assess wheat grain hardness. The best calibration and validation model for assess hardness of wheat grains were observed throughout the reference method Instron Universal Testing Machine (IUTM) within the wavelength range 950 to 1650 nm with 6 principal components (PCs) and pretreatment by Savitzky-Golay second derivative (S.G. 2nd). Where, the optimum PLS was recorded at the lowest standard error of prediction (SEP) 3.92 N with the maximum value of coefficient of prediction (R2P ≈ 0.91) and sufficient value of the relative prediction deviation (RPD ≈ 3.35). The accuracy of the prediction model was sufficient to use NIRS technique as a nondestructive method to estimate hardness of wheat grains for different varieties of the wheat.
VL  - 4
IS  - 3
ER  -

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