Abstract
The objective of this study is to compare different calibration models that could be used in the analysis of protein,
oil, carbohydrate and ash contents in maize flour by NIRS. A total of 138 samples were used from 115 hybrids and
23 inbreds in the study as material. Based on reference analysis results, different estimation models were developed
using Partial Least Squares Regression (PLSR) and Multiple Linear Regression (MLR) methods. Validation
procedure of these models (n=110) were accomplished using samples from different genotypes (n=28). In both of
the developed models, the highest accuracy was attained for protein content (r=0.990 for MLR and r=0.987 for
PLSR). For the other traits analyzed, although MLR model yielded better results based on mathematical
evaluations (rMLR=0.801, rPLSR=0.755 for carbohydrate, rMLR=0.823, rPLSR=0.723 for oil, rMLR=0.926 and
rPLSR=0.810 for ash), external validation suggested PLSR model provide a lower error rate than MLR. Results
suggested that protein content could be successfully estimated, whereas, for some other traits, such as carbohydrate
and oil ratios, it seems that there is still need for more studies before getting accurate measurements using NIR
methods. Profile analysis regarding the wavelengths potent in the models showed that the estimation power
declined when the regression coefficients of the wavelengths included in the model were low. Among the analyzed
traits, ash and oil contents seemed to be related with more spectral regions within the scanned spectra than protein
and carbohydrate.
Keywords
References
- AOAC (1990). Methods of the Association of Official Analytical Chemists, Vol. II. 15th ed. Method No. 920.85. Arlington Virginia USA AOAC p. 780
- Bailleres H, Davrieux F & Ham-Pichavant F (2002). Near infrared analysis as a tool for rapid screening of some major wood characteristics in an eucalyptus breeding program. Annals of Forest Science 59: 479–490
- Başlar M & Ertugay M F (2011). Determination of protein and gluten quality-related parameters of wheat flour using near-infrared reflectance spectroscopy (NIRS). Turkish Journal of Agricultural and Forestry 35:139-144
- Baye T M, Pearson T C & Mark Settles A (2006). Development of a calibration to predict maize seed composition using single kernel near infrared spectroscopy. Journal of Cereal Science 43: 236– 243
- Berardo N, Brenna O V, Amato A, Valotia P, Pisacanea V & Mottoa M (2004). Carotenoids concentration among maize genotypes measured by near infrared reflectance spectroscopy (NIRS). Innovative Food Science and Emerging Technologies 5: 393-398
- Buchanan B R, Baxter M A, Chen T-S, Qin X-Z & Robinson P A (1996). Use of Near-Infrared Spectroscopy to evaluate an active in a film coated tablet. Pharmaceutical Research 13: 616-621
- Cozzolino D, Delucchi I, Kholi M & Vázquez D (2006). Use of near infrared reflectance spectroscopy to evaluate quality characteristics in whole-wheat grain. Agricultura Técnica 66: 370- 375
- CWS Manual (2003). Sensologic Calibration Workshop Version 2.02, Sensologic Gmbh, Germany Deaville E R & Flinn P C (2000). (eds D.I. Givens, E. Owen, R.F.E. Axford and H.M. Omed) NearInfrared (NIR) Spectroscopy: an Alternative Approach for the Estimation of Forage Quality and Voluntary Intake, Forage Evaluation in Ruminant Nutrition, 301-320
- Diller M (2002). Investigations for the Development of a NIRS-method for Potatoes in Organic Farming with Special Reference to the Influence of the Year and the Potato Line (in German). PhD Thesis. Rheinische Friedrich-Wilhelms-Universitat, Bonn, Germany
- Fülöp A & Hancsok J (2009). Comparison of calibration models based on near infrared spectroscopy data for the determination of plant oil properties. Chemical Engineering Transactions 17: 445-450
- Gerhardt P, Murray R G E, Wood W A & Krieg N R (1994). Methods for General and Molecular Bacteriology, ASM, Washington DC. ISBN 1- 55581-048-9, p 518
- ICC (1980). ICC Standard No: 105/1. Method for the Determination of Crude Protein in Cereals and Cereal Products for Food and for Feed. Standard Methods of the International Association for Cereal Chemistry (ICC). Verlag Moritz Schafer. Detmold
- ICC (2000). Determination of Ash in Cereal and Cereal Products. Standard Methods of the International Association for Cereal Chemistry (ICC), ICC Standard No: 104/1. Verlag Moritz Schafer. Detmold Jiang H Y, Zhu Y J, Wei L M, Dai J R, Song T M, Yan
- Y L & Chen S J (2007). Analysis of protein, starch and oil content of single intact kernels by near infrared reflectance spectroscopy (NIRS) in maize (Zea mays L.). Plant Breeding 126:492-497
- Kahrıman F & Egesel C Ö (2011). Development of a calibration model to estimate quality traits in wheat flour using NIR (Near Infrared Reflectance) spectroscopy. Research Journal of Agricultural Sciences 43:392-400
- Martens H & Naes T (1992). Multivariate Calibration. J. Wiley and Sons, Chichester, UK.pp:25
- Orman B A & Schumann R A (1991). Comparison of near-infrared spectroscopy calibration methods for the prediction of protein, oil, and starch in maize grain. Journal of Agricultural Food and Chemisty 39: 883-886
- Osborne B G (2000). Near-infrared spectroscopy in food analysis, In: Encyclopedia in analystical Cehemistiry (Ed: R. A. Meyers), John Wiley Sons
- Pandorf J A & deMan J M (1990). Determination of oil content of seeds by NIR: Influence of fatty acid composition on wavelength selection. Journal of American Oil Chemistry Society 67:473-482
- Pasquini C (2003) Near infrared spectroscopy: Fundamentals, practical aspects and analytical applications Journal of the Brazilian Chemical Society 14:198–219.
- Rasco B A, Miller C E & King T L (1991). Utilization of NIR spectroscopy to estimate the proximate composition of trout muscle with minimal sample pretreatment. Journal of Agricultural Food and Chemistry 39: 67-72
- Rodriguez-Otero J L, Hermida M & Centeno J (1997). Analysis of dairy products by near-infrared spectroscopy: A review. Journal of Agricultural Food and Chemisty 45:2815-2819
- Sandorfy C, Buchet R & Lachenal G (2007). Principles of molecular vibrations for near-infrared spectroscopy. In Near-Infrared Spectroscopy in Food Science and Technology; Ozaki, Y., McClure, W. F., Christy, A. A., Eds.; John Wiley and Sons, Inc.: Hoboken, NJ, pp 11-46
- SAS Institute (1999). SAS V8 User Manual. SAS Institue Cary NC Shenk J S, Workman J J & Westerhaus M O (1992). Application of NIR spectroscopy to agricultural products. In: Burns, D.A., Ciurczak, E.W. (Eds.), Handbook of Near-infrared Analysis, vol. 13. Practical Spectroscopy Series, Marcel Dekker, New York, pp. 383–431
- Siesler H W, Ozaki Y, Kawata S & Heise H M (2002). Near-Infrared Spectroscopy. Principles, Instruments, Applications. Wiley-VCH, Weinheim Spielbauer G, Armstrong P, Baier J W, Allen W B,
- Richardson K, Shen B & Settles A M (2009).
- High-throughput near-infrared reflectance spectroscopy for predicting quantitative and qualitative composition phenotypes of individual maize kernels. Cereal Chemistry 86(5): 556-564
- Tallada J G, Palacios-Rojas N & Armstrong P R (2009). Prediction of maize seed attributes using a rapid single kernel near infrared instrument. Journal of Cereal Science 50:381–387 Wehling R L, Jackson D S, Hooper D G & Ghaedian A
- R (1993). Prediction of wet-milling starch yield from corn by near-infrared spectroscopy. Cereal Chemisty 70:720-723
- Welle R, Greten W, Müler T, Weber G & Wehrmann H (2005). Application of near infrared spectroscopy on-combine in corn grain breeding. Journal of Near Infrared Spectroscopy 13:69-75
Abstract
Bu çalışmada mısır ununda protein, yağ, karbonhidrat ve kül oranının NIRS ile tespitinde kullanılabilecek farklı kalibrasyon modellerinin karşılaştırılması amaçlanmıştır. Çalışmada 115 hibrit genotip ve 23 adet saf hatta ait toplam 138 örnek materyal olarak kullanılmıştır. Referans analizlerden elde edilen sonuçlara göre Kısmi En Küçük Kareler Regresyonu (PLSR) ve Çoklu Doğrusal Regresyon (MLR) yöntemleri kullanılarak farklı tahmin modelleri oluşturulmuştur. Oluşturulan modellerin (n=110) validasyon işlemi farklı genotipler (n=28) kullanılarak gerçekleştirilmiştir. Oluşturulan modellerin her ikisinde de en yüksek doğruluk protein oranında (rMLR=0.990 ve rPLSR=0.987) tespit edilmiştir. Diğer özellikler için MLR modeli PLSR modelinden (karbonhidrat için rMLR=0.801, rPLSR=0.755; yağ için rMLR=0.823, rPLSR=0.723; kül için rMLR=0.926, rPLSR=0.810) matematiksel modellere göre daha iyi sonuç vermiş olmasına karşın, dış validasyon işleminde PLSR modelinde yapılan tahminlerin MLR modeline göre hata payının düşük olduğu görülmüştür. Sonuçlar, NIR yöntemi ile protein oranının başarılı şekilde tahminlenebileceğini, karbonhidrat ve yağ gibi diğer özellikler için ise daha fazla çalışmalara ihtiyaç olduğunu ortaya koymuştur. Modellerde etkili olan dalga boylarına ait profil analizi, modele dahil edilen dalga boylarının regresyon katsıyaları düşük olduğunda tahmin gücünün de zayıf olduğunu göstermiştir. Ayrıca, kül ve yağ oranının, protein ve karbonhidrat oranına göre tarama yapılan bölgede daha fazla sayıda spektral bölge ile ilişkili olduğu belirlenmiştir.
Keywords
References
- AOAC (1990). Methods of the Association of Official Analytical Chemists, Vol. II. 15th ed. Method No. 920.85. Arlington Virginia USA AOAC p. 780
- Bailleres H, Davrieux F & Ham-Pichavant F (2002). Near infrared analysis as a tool for rapid screening of some major wood characteristics in an eucalyptus breeding program. Annals of Forest Science 59: 479–490
- Başlar M & Ertugay M F (2011). Determination of protein and gluten quality-related parameters of wheat flour using near-infrared reflectance spectroscopy (NIRS). Turkish Journal of Agricultural and Forestry 35:139-144
- Baye T M, Pearson T C & Mark Settles A (2006). Development of a calibration to predict maize seed composition using single kernel near infrared spectroscopy. Journal of Cereal Science 43: 236– 243
- Berardo N, Brenna O V, Amato A, Valotia P, Pisacanea V & Mottoa M (2004). Carotenoids concentration among maize genotypes measured by near infrared reflectance spectroscopy (NIRS). Innovative Food Science and Emerging Technologies 5: 393-398
- Buchanan B R, Baxter M A, Chen T-S, Qin X-Z & Robinson P A (1996). Use of Near-Infrared Spectroscopy to evaluate an active in a film coated tablet. Pharmaceutical Research 13: 616-621
- Cozzolino D, Delucchi I, Kholi M & Vázquez D (2006). Use of near infrared reflectance spectroscopy to evaluate quality characteristics in whole-wheat grain. Agricultura Técnica 66: 370- 375
- CWS Manual (2003). Sensologic Calibration Workshop Version 2.02, Sensologic Gmbh, Germany Deaville E R & Flinn P C (2000). (eds D.I. Givens, E. Owen, R.F.E. Axford and H.M. Omed) NearInfrared (NIR) Spectroscopy: an Alternative Approach for the Estimation of Forage Quality and Voluntary Intake, Forage Evaluation in Ruminant Nutrition, 301-320
- Diller M (2002). Investigations for the Development of a NIRS-method for Potatoes in Organic Farming with Special Reference to the Influence of the Year and the Potato Line (in German). PhD Thesis. Rheinische Friedrich-Wilhelms-Universitat, Bonn, Germany
- Fülöp A & Hancsok J (2009). Comparison of calibration models based on near infrared spectroscopy data for the determination of plant oil properties. Chemical Engineering Transactions 17: 445-450
- Gerhardt P, Murray R G E, Wood W A & Krieg N R (1994). Methods for General and Molecular Bacteriology, ASM, Washington DC. ISBN 1- 55581-048-9, p 518
- ICC (1980). ICC Standard No: 105/1. Method for the Determination of Crude Protein in Cereals and Cereal Products for Food and for Feed. Standard Methods of the International Association for Cereal Chemistry (ICC). Verlag Moritz Schafer. Detmold
- ICC (2000). Determination of Ash in Cereal and Cereal Products. Standard Methods of the International Association for Cereal Chemistry (ICC), ICC Standard No: 104/1. Verlag Moritz Schafer. Detmold Jiang H Y, Zhu Y J, Wei L M, Dai J R, Song T M, Yan
- Y L & Chen S J (2007). Analysis of protein, starch and oil content of single intact kernels by near infrared reflectance spectroscopy (NIRS) in maize (Zea mays L.). Plant Breeding 126:492-497
- Kahrıman F & Egesel C Ö (2011). Development of a calibration model to estimate quality traits in wheat flour using NIR (Near Infrared Reflectance) spectroscopy. Research Journal of Agricultural Sciences 43:392-400
- Martens H & Naes T (1992). Multivariate Calibration. J. Wiley and Sons, Chichester, UK.pp:25
- Orman B A & Schumann R A (1991). Comparison of near-infrared spectroscopy calibration methods for the prediction of protein, oil, and starch in maize grain. Journal of Agricultural Food and Chemisty 39: 883-886
- Osborne B G (2000). Near-infrared spectroscopy in food analysis, In: Encyclopedia in analystical Cehemistiry (Ed: R. A. Meyers), John Wiley Sons
- Pandorf J A & deMan J M (1990). Determination of oil content of seeds by NIR: Influence of fatty acid composition on wavelength selection. Journal of American Oil Chemistry Society 67:473-482
- Pasquini C (2003) Near infrared spectroscopy: Fundamentals, practical aspects and analytical applications Journal of the Brazilian Chemical Society 14:198–219.
- Rasco B A, Miller C E & King T L (1991). Utilization of NIR spectroscopy to estimate the proximate composition of trout muscle with minimal sample pretreatment. Journal of Agricultural Food and Chemistry 39: 67-72
- Rodriguez-Otero J L, Hermida M & Centeno J (1997). Analysis of dairy products by near-infrared spectroscopy: A review. Journal of Agricultural Food and Chemisty 45:2815-2819
- Sandorfy C, Buchet R & Lachenal G (2007). Principles of molecular vibrations for near-infrared spectroscopy. In Near-Infrared Spectroscopy in Food Science and Technology; Ozaki, Y., McClure, W. F., Christy, A. A., Eds.; John Wiley and Sons, Inc.: Hoboken, NJ, pp 11-46
- SAS Institute (1999). SAS V8 User Manual. SAS Institue Cary NC Shenk J S, Workman J J & Westerhaus M O (1992). Application of NIR spectroscopy to agricultural products. In: Burns, D.A., Ciurczak, E.W. (Eds.), Handbook of Near-infrared Analysis, vol. 13. Practical Spectroscopy Series, Marcel Dekker, New York, pp. 383–431
- Siesler H W, Ozaki Y, Kawata S & Heise H M (2002). Near-Infrared Spectroscopy. Principles, Instruments, Applications. Wiley-VCH, Weinheim Spielbauer G, Armstrong P, Baier J W, Allen W B,
- Richardson K, Shen B & Settles A M (2009).
- High-throughput near-infrared reflectance spectroscopy for predicting quantitative and qualitative composition phenotypes of individual maize kernels. Cereal Chemistry 86(5): 556-564
- Tallada J G, Palacios-Rojas N & Armstrong P R (2009). Prediction of maize seed attributes using a rapid single kernel near infrared instrument. Journal of Cereal Science 50:381–387 Wehling R L, Jackson D S, Hooper D G & Ghaedian A
- R (1993). Prediction of wet-milling starch yield from corn by near-infrared spectroscopy. Cereal Chemisty 70:720-723
- Welle R, Greten W, Müler T, Weber G & Wehrmann H (2005). Application of near infrared spectroscopy on-combine in corn grain breeding. Journal of Near Infrared Spectroscopy 13:69-75
Details
| Primary Language | English |
|---|---|
| Journal Section | Makaleler |
| Authors | |
| Publication Date | March 4, 2012 |
| Submission Date | February 28, 2012 |
| Published in Issue | Year 2012 Volume: 18 Issue: 1 |
Journal of Agricultural Sciences is published open access journal. All articles are published under the terms of the Creative Commons Attribution License (CC BY).