Research Article
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Establishing Near Infra Red Spectroscopy (NIR) Calibration for Starch Analysis in Corn Grain

Year 2019, Volume: 12 Issue: 1, 7 - 14, 31.03.2019
https://doi.org/10.30607/kvj.459701

Abstract

This
study has been carried out to calibrate the starch values of 320 corn samples
taken from Soil Products Offices (TMO) in seven different geographical regions
of by using an NIR instrument. The corn samples used in the study were selected
from the regions where corn production is intensive in Turkey and brought to
the laboratory. The corn samples brought to the laboratory were milled and then
spectra were formed. Subsequently, the starch values were determined in the
laboratory with the use of wet chemical analysis methods. The calibration
values generated were R= 0.6410; R2 = 0.4109 Standard Deviation =
4.4208, R = 0.5854 from the validation set; R2 = 0.3427 Standard
Deviation = 4.5662. The calibration interval in the study was 44.53 and 45.72,
respectively. This study has concluded that more samples representing the 7
different regions in Turkey for the starch contents of corn are needed in order
to generate scientifically reliable results with the FT-NIR device.  

References

  • Anonymous. http://www.kanatlıbilgi.com.tr ; Accessien date : 08.03.2016.
  • AOAC (2005) Official method of Analysis. 18th Edition, Association of Officiating Analytical Chemists, Washington DC.
  • Baye TM, Pearson TC, Settles AMM. (2006). Development of a calibration to predict maize seed composition using single kernel near infrared spectroscopy, Journal of Ceracel Science. 43:236-243
  • Blanco M, Peguero A (2012). A new and simple PLS calibration method for NIR spectroscopy. API determination in intact solid formulations, Jounal of The Royal Socicety of Chemistry. 4:1507-15012.
  • Bokobza L (1998). Near Infrared Spectroscopy. J Near Spectrosc, 6, 3-7.
  • Burgers AP (2009). Development of rapid methods to determine the quality of corn for ethanol production. A thesis submitted to the graduate faculty in partial fulfillment of the requirements for the degree of master of scıence. Iowa State University, USA.
  • Cen H, He Y (2007). Theory and application of near infrared reflectance spectroscopy in determination of food quality. Trends in Food Science & Technology, 18(2): 72-83.
  • Campbell MR, Mannis SR, Port HA, Zimmerman AM, Glover DV (1999). Prediction of starch amylose content versus total grain amylose content in corn by near-infrared transmittance spectroscopy. Cereal Chem. 76:552-557.
  • Dryden GMcL (2008).Animal Nutrition Science.Textbook. Cambridge University Press. Cambridge.UK.
  • Foley WJ, Mcilwee A, Lawler I, Aragones L, Woolnough AP, Berding N (1998). Ecological applications of near infrared reflectance spectroscopy – a tool for rapid, cost-effective prediction of the composition of plant and animal tissues and aspects of animal performance. Oecologia. 116: 293-305.
  • Fu N (2011). Research on NIR Calibration Model of Corn Starch ContentBased on Subset Selecting and a Series of PLS Method. Journal of Anhui Agricultural Science. 36.
  • Givens DI, De Boever JI, Deaville ER (1997). The principles, practices and some future applications of near infrared spectroscopy for predicting the nutritive value of foods for animals and humans. Nutr. Res. Rev. 10(1): 83-114.
  • González-Martin I, Hernández-Hierro JM, Bustamante-Rangel M, Barros-Ferreiro N (2006). Near-infrared spectroscopy (NIRS) reflectance technology for the determination of tocopherols in alfalfa. Analytical and Bioanalytical Chemistry. 386: 1553-1158.
  • Gümüştaş Ö, Bayram İ (2018). Determination of acid detergent fiber (ADF) in corn grain by using NIR technology. 5th International Conference on Sustainable Agriculture and Environment (5th ICSAE)October 08-10, 2018, Hammamet, Tunusia
  • Güngör T, Başalan M, Aydoğan İ (2008). Kırıkkale yöresinde üretilen bazı kaba yemlerde besin madde miktarları ve metabolize olabilir enerji düzeylerinin belirlenmesi. Ankara Üniv Vet Fak Dergisi. 55, 111-115.
  • Hódsági M, Gergely S, Gelencsér T, Salgó A (2012). Investigations of native and resistant starches and their mixtures using near-infrared spectroscopy. Food and Bioproc. Tech. 5(1): 401-417.
  • Irudayaraj J, Yang H, Sakhamuri S (2002). Differentiation and detection of microorganism using Fourier transform infrared photoacustic spectroscopy. J Mol Struct 606: 181–188.
  • Jarvis CE, Walker JRL (1993). Simultaneous, rapid, spectrophotometric determination of total starch, amylose and amylopectin. J. Sci. Food Agric. 63:53-57.
  • Jiang HY, Zhu YJ, Wei LM, Dai JR, Song TM, Yan Yl, Chen SJ (2007). Analysis of protein, starch and oil content of single intact kernels by near infrared reflectance spectroscopy (NIRS) in maize (Zea mays L.). Plant Breading. 126(5): 492-497.
  • Lahumı S, Lee S, Lee W, Kim Ms, Mo C, Bae H, Cho B (2014). Detection of Starch Adulteration in Onion Powder by FT-NIR and FT-IR Spectroscopy. Journal of Agricultural and Foof Chemstry. 62:9246-9251.
  • Lardy G (2013). Feeding Corn to Beef Cattle, North Dakota State University Fargo, North Dakota USA.
  • Lu G, Huang H, Zhang D (2006). Prediction of sweetpatoto starch physiochemical quality and pasting properties using near-infrared reflectance spectroscopy. Journal of Food Chemisty. 94:632-639.
  • Mark H, Workman J (2003). Statistics in Spectroscopy 2nd Edition, Elsevier, Amsterdam.
  • Melchinger AE, Schmidt GA, Geiger HH (1986). Evaluation of near infra-red reflectance spectroscopy for predicting grain and stover quality traits in maize. Plant Breed. 97, 20–29.
  • Osborne BG, Fearn T (1983). Collaborative evaluation of universal calibrations for the measurement of protein and moisture in flour by near infrared reflectance. Int J Food Sci Tech 18 (4): 453-460.
  • Osborne BG, Fearn T (1986). Near-infrared spectroscopy in food analysis. Longman Scientific and Technical. Harlow, U.K.
  • Özcan S (2009) Modern dünyanın vazgeçilmez bitkisi mısır: genetiği değiştirilmiş transgenik mısırın tarımsal üretime katkısı. Tür Bilimsel Derlemeler Dergisi. 2(2):01-34.
  • Panero PS, Panero FS, Panero JS, Silva HEB (2013). Apllication of Extended Multiplicative ASignal Correction to Short-Wavelength near Infrared Specta of Moisture in Marzipan. Journal of Data Analysis and Information Processing. 1:30-34.
  • Paulsen M, Pordesımo LO, Singh M, Ye B (2003). Mazie Starch Yield Calibrations with Near Infrared Reflactance. Biosystem Engineering. 85(4):455-460.
  • Paulsen MR, Singh M (2004). Calibration of a Near-infrared Transmission Grain Analyser for Extractable Starch in Maize. Biosystem Engineering. 89(1):79-83.
  • Plumier BM, Danao MC, Singh V, Rausch KD (2013). Analysis and Prediction of Unreacted Starch Content Corn Using FT-NIR Spectroscopy. American Society of Agricuştural and Biological Engineers. 56:1877-1884.
  • Sohn M, Himmelsbach DS, Morrison WH, Akin DE, Barton FE (2006). Partial Least Squares Regression Calibration for Determining Wax Content in Processed Flax Fiber by Near-Infrared Spectroscopy. Society for Applied Spectroscopy. 60:437-440.
  • Shenk JS, Workman JJ, Westerhans MO (2003). Application of NIRS to agricultural products. Handb. Near-Infrared Anal.Pages 347-386.
  • Tallada JG, Palacıos-Rojas N, Armstrong PR (2009). Prediction of maize seed attributes using a rapid single kernel nearinfrared instrument. Journal of Cereal Science. 50:381-387.
  • Via BK, Zhou C, Acquah G, Jıang W, Eckhardt L (2014). Near Infrared Spectroscopy Calibration for Wood Chemistry: Which Chemometric Technique Is Best for Prediction and Interpretation. MDPI(Multidisciplinary Digital Publishing Institute). 14: 13532-13547.
  • Wehling RI, Jackson DS, Hooper DG, Ghaedian AR (1993). Prediction of Wet-Milling Starch Yield from Corn by Near-Infrared Spectroscopy. Journal of Cereal Science. 70(6): 720-723.
  • Wolfrum E, Rooney W, Stefenıak T, Rooney W, Dighe N, Bean B, Dahlberg J (2013). Multivariate Calibration Models for Sorghum Composition using Near-Infrared Spectroscopy. NREL is a national laboratory of the U.S. Department of Energy, Office of EnergyEfficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, Technical Report. Denver USA.
  • Zhao N, Wu Z, Zhang Q, Shi X, Ma Q, Qiau Y (2015). Optimization of Parameter Selection for Partial Least Squares ModelDevelopment. Journal of Nature. 5:11647-11655.
  • Zhong J, Qin X (2016). Rapid Quantitavie Analysis of Corn Starch Adulteration in Konjac Glucomannan by Chemometrics-Assited FT-NIR Spectroscopy. 9:61-67.

Mısır Tahılında Nişasta Analizi İçin Near Infra Red Spectroscopy (NIR) Kalibrasyonu Oluşturulması

Year 2019, Volume: 12 Issue: 1, 7 - 14, 31.03.2019
https://doi.org/10.30607/kvj.459701

Abstract

Bu araştırma Türkiye'nin yedi
farklı coğrafi bölgesindeki TMO ofislerinden getirilen toplam 320 adet mısır
numunesindeki nişasta değerlerinin NIR cihazı kullanılarak kalibrasyonunu
yapmak amacıyla gerçekleştirilmiştir. Araştırmada kullanılan mısır numuneleri
Türkiye’de mısır üretiminin yoğun olarak yapıldığı bölgelerden seçilmiştir ve
laboratuvara getirilmiştir. Laboratuvara getirilen mısır numunelerinin
öğütülmesi işlemi yapılmış, daha sonra spektraları oluşturulmuştur. Akabinde,
laboratuarda yaş kimyasal analiz yöntemiyle nişasta değerleri bulunmuştur.
Oluşturulan kalibrasyon setinin R=0.6410; R2= 0.4109 Standart Sapma
= 4.4208 şeklinde değerleri alınmış, validasyon setinden ise R=0.5854; R2=
0.3427 Standart Sapma = 4.5662 değerleri elde edilmiştir. Araştırmada,
kalibrasyon aralığı 44.53 bulunurken, validasyon aralığı ise 45.72. olarak
bulunmuştur. Sonuç olarak bu araştırma ile Türkiye’nin 7 farklı bölgesini
temsil edebilecek mısır örneklerindeki nişasta miktarı FT-NIR cihazı
kullanılarak elde edilen kalibrasyonların bilimsel açıdan daha doğru sonuçlar
vermesi için daha fazla miktarda numune ile çalışmaların yapılması gerektiğine
kanaat getirilmiştir.

References

  • Anonymous. http://www.kanatlıbilgi.com.tr ; Accessien date : 08.03.2016.
  • AOAC (2005) Official method of Analysis. 18th Edition, Association of Officiating Analytical Chemists, Washington DC.
  • Baye TM, Pearson TC, Settles AMM. (2006). Development of a calibration to predict maize seed composition using single kernel near infrared spectroscopy, Journal of Ceracel Science. 43:236-243
  • Blanco M, Peguero A (2012). A new and simple PLS calibration method for NIR spectroscopy. API determination in intact solid formulations, Jounal of The Royal Socicety of Chemistry. 4:1507-15012.
  • Bokobza L (1998). Near Infrared Spectroscopy. J Near Spectrosc, 6, 3-7.
  • Burgers AP (2009). Development of rapid methods to determine the quality of corn for ethanol production. A thesis submitted to the graduate faculty in partial fulfillment of the requirements for the degree of master of scıence. Iowa State University, USA.
  • Cen H, He Y (2007). Theory and application of near infrared reflectance spectroscopy in determination of food quality. Trends in Food Science & Technology, 18(2): 72-83.
  • Campbell MR, Mannis SR, Port HA, Zimmerman AM, Glover DV (1999). Prediction of starch amylose content versus total grain amylose content in corn by near-infrared transmittance spectroscopy. Cereal Chem. 76:552-557.
  • Dryden GMcL (2008).Animal Nutrition Science.Textbook. Cambridge University Press. Cambridge.UK.
  • Foley WJ, Mcilwee A, Lawler I, Aragones L, Woolnough AP, Berding N (1998). Ecological applications of near infrared reflectance spectroscopy – a tool for rapid, cost-effective prediction of the composition of plant and animal tissues and aspects of animal performance. Oecologia. 116: 293-305.
  • Fu N (2011). Research on NIR Calibration Model of Corn Starch ContentBased on Subset Selecting and a Series of PLS Method. Journal of Anhui Agricultural Science. 36.
  • Givens DI, De Boever JI, Deaville ER (1997). The principles, practices and some future applications of near infrared spectroscopy for predicting the nutritive value of foods for animals and humans. Nutr. Res. Rev. 10(1): 83-114.
  • González-Martin I, Hernández-Hierro JM, Bustamante-Rangel M, Barros-Ferreiro N (2006). Near-infrared spectroscopy (NIRS) reflectance technology for the determination of tocopherols in alfalfa. Analytical and Bioanalytical Chemistry. 386: 1553-1158.
  • Gümüştaş Ö, Bayram İ (2018). Determination of acid detergent fiber (ADF) in corn grain by using NIR technology. 5th International Conference on Sustainable Agriculture and Environment (5th ICSAE)October 08-10, 2018, Hammamet, Tunusia
  • Güngör T, Başalan M, Aydoğan İ (2008). Kırıkkale yöresinde üretilen bazı kaba yemlerde besin madde miktarları ve metabolize olabilir enerji düzeylerinin belirlenmesi. Ankara Üniv Vet Fak Dergisi. 55, 111-115.
  • Hódsági M, Gergely S, Gelencsér T, Salgó A (2012). Investigations of native and resistant starches and their mixtures using near-infrared spectroscopy. Food and Bioproc. Tech. 5(1): 401-417.
  • Irudayaraj J, Yang H, Sakhamuri S (2002). Differentiation and detection of microorganism using Fourier transform infrared photoacustic spectroscopy. J Mol Struct 606: 181–188.
  • Jarvis CE, Walker JRL (1993). Simultaneous, rapid, spectrophotometric determination of total starch, amylose and amylopectin. J. Sci. Food Agric. 63:53-57.
  • Jiang HY, Zhu YJ, Wei LM, Dai JR, Song TM, Yan Yl, Chen SJ (2007). Analysis of protein, starch and oil content of single intact kernels by near infrared reflectance spectroscopy (NIRS) in maize (Zea mays L.). Plant Breading. 126(5): 492-497.
  • Lahumı S, Lee S, Lee W, Kim Ms, Mo C, Bae H, Cho B (2014). Detection of Starch Adulteration in Onion Powder by FT-NIR and FT-IR Spectroscopy. Journal of Agricultural and Foof Chemstry. 62:9246-9251.
  • Lardy G (2013). Feeding Corn to Beef Cattle, North Dakota State University Fargo, North Dakota USA.
  • Lu G, Huang H, Zhang D (2006). Prediction of sweetpatoto starch physiochemical quality and pasting properties using near-infrared reflectance spectroscopy. Journal of Food Chemisty. 94:632-639.
  • Mark H, Workman J (2003). Statistics in Spectroscopy 2nd Edition, Elsevier, Amsterdam.
  • Melchinger AE, Schmidt GA, Geiger HH (1986). Evaluation of near infra-red reflectance spectroscopy for predicting grain and stover quality traits in maize. Plant Breed. 97, 20–29.
  • Osborne BG, Fearn T (1983). Collaborative evaluation of universal calibrations for the measurement of protein and moisture in flour by near infrared reflectance. Int J Food Sci Tech 18 (4): 453-460.
  • Osborne BG, Fearn T (1986). Near-infrared spectroscopy in food analysis. Longman Scientific and Technical. Harlow, U.K.
  • Özcan S (2009) Modern dünyanın vazgeçilmez bitkisi mısır: genetiği değiştirilmiş transgenik mısırın tarımsal üretime katkısı. Tür Bilimsel Derlemeler Dergisi. 2(2):01-34.
  • Panero PS, Panero FS, Panero JS, Silva HEB (2013). Apllication of Extended Multiplicative ASignal Correction to Short-Wavelength near Infrared Specta of Moisture in Marzipan. Journal of Data Analysis and Information Processing. 1:30-34.
  • Paulsen M, Pordesımo LO, Singh M, Ye B (2003). Mazie Starch Yield Calibrations with Near Infrared Reflactance. Biosystem Engineering. 85(4):455-460.
  • Paulsen MR, Singh M (2004). Calibration of a Near-infrared Transmission Grain Analyser for Extractable Starch in Maize. Biosystem Engineering. 89(1):79-83.
  • Plumier BM, Danao MC, Singh V, Rausch KD (2013). Analysis and Prediction of Unreacted Starch Content Corn Using FT-NIR Spectroscopy. American Society of Agricuştural and Biological Engineers. 56:1877-1884.
  • Sohn M, Himmelsbach DS, Morrison WH, Akin DE, Barton FE (2006). Partial Least Squares Regression Calibration for Determining Wax Content in Processed Flax Fiber by Near-Infrared Spectroscopy. Society for Applied Spectroscopy. 60:437-440.
  • Shenk JS, Workman JJ, Westerhans MO (2003). Application of NIRS to agricultural products. Handb. Near-Infrared Anal.Pages 347-386.
  • Tallada JG, Palacıos-Rojas N, Armstrong PR (2009). Prediction of maize seed attributes using a rapid single kernel nearinfrared instrument. Journal of Cereal Science. 50:381-387.
  • Via BK, Zhou C, Acquah G, Jıang W, Eckhardt L (2014). Near Infrared Spectroscopy Calibration for Wood Chemistry: Which Chemometric Technique Is Best for Prediction and Interpretation. MDPI(Multidisciplinary Digital Publishing Institute). 14: 13532-13547.
  • Wehling RI, Jackson DS, Hooper DG, Ghaedian AR (1993). Prediction of Wet-Milling Starch Yield from Corn by Near-Infrared Spectroscopy. Journal of Cereal Science. 70(6): 720-723.
  • Wolfrum E, Rooney W, Stefenıak T, Rooney W, Dighe N, Bean B, Dahlberg J (2013). Multivariate Calibration Models for Sorghum Composition using Near-Infrared Spectroscopy. NREL is a national laboratory of the U.S. Department of Energy, Office of EnergyEfficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, Technical Report. Denver USA.
  • Zhao N, Wu Z, Zhang Q, Shi X, Ma Q, Qiau Y (2015). Optimization of Parameter Selection for Partial Least Squares ModelDevelopment. Journal of Nature. 5:11647-11655.
  • Zhong J, Qin X (2016). Rapid Quantitavie Analysis of Corn Starch Adulteration in Konjac Glucomannan by Chemometrics-Assited FT-NIR Spectroscopy. 9:61-67.
There are 39 citations in total.

Details

Primary Language English
Journal Section RESEARCH ARTICLE
Authors

Ercan Tomas This is me 0000-0002-6368-3801

İsmail Bayram 0000-0002-9993-7092

Publication Date March 31, 2019
Acceptance Date November 13, 2018
Published in Issue Year 2019 Volume: 12 Issue: 1

Cite

APA Tomas, E., & Bayram, İ. (2019). Establishing Near Infra Red Spectroscopy (NIR) Calibration for Starch Analysis in Corn Grain. Kocatepe Veterinary Journal, 12(1), 7-14. https://doi.org/10.30607/kvj.459701
AMA Tomas E, Bayram İ. Establishing Near Infra Red Spectroscopy (NIR) Calibration for Starch Analysis in Corn Grain. kvj. March 2019;12(1):7-14. doi:10.30607/kvj.459701
Chicago Tomas, Ercan, and İsmail Bayram. “Establishing Near Infra Red Spectroscopy (NIR) Calibration for Starch Analysis in Corn Grain”. Kocatepe Veterinary Journal 12, no. 1 (March 2019): 7-14. https://doi.org/10.30607/kvj.459701.
EndNote Tomas E, Bayram İ (March 1, 2019) Establishing Near Infra Red Spectroscopy (NIR) Calibration for Starch Analysis in Corn Grain. Kocatepe Veterinary Journal 12 1 7–14.
IEEE E. Tomas and İ. Bayram, “Establishing Near Infra Red Spectroscopy (NIR) Calibration for Starch Analysis in Corn Grain”, kvj, vol. 12, no. 1, pp. 7–14, 2019, doi: 10.30607/kvj.459701.
ISNAD Tomas, Ercan - Bayram, İsmail. “Establishing Near Infra Red Spectroscopy (NIR) Calibration for Starch Analysis in Corn Grain”. Kocatepe Veterinary Journal 12/1 (March 2019), 7-14. https://doi.org/10.30607/kvj.459701.
JAMA Tomas E, Bayram İ. Establishing Near Infra Red Spectroscopy (NIR) Calibration for Starch Analysis in Corn Grain. kvj. 2019;12:7–14.
MLA Tomas, Ercan and İsmail Bayram. “Establishing Near Infra Red Spectroscopy (NIR) Calibration for Starch Analysis in Corn Grain”. Kocatepe Veterinary Journal, vol. 12, no. 1, 2019, pp. 7-14, doi:10.30607/kvj.459701.
Vancouver Tomas E, Bayram İ. Establishing Near Infra Red Spectroscopy (NIR) Calibration for Starch Analysis in Corn Grain. kvj. 2019;12(1):7-14.

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