Application of Near Infrared Transmission for the Determination of Ash in Wheat Flour

ORIGINAL SCIENTIFIC PAPER 233

Rezica SUDAR 1( ) Zorica JURKOVIĆ 1 Marica GALONJA 1 Irena TURK 2 Marija ARAMBAŠIĆ 3

Summary Near infrared transmission (NIT) spectroscopy was investigated for applicability as a rapid screening tool to evaluate ash content in wheat fl our. Ash content in fl our samples was determined also by reference method. One hundred thirteen wheat fl our samples with ash content of 0.367-0.964% were collected from the Belje,d.d., PC Mlin and PPK Valpovo, and used for this study. Infratec 1241 Grain Analyzer Flour Module that comes with ready-to- use calibrations, was used to obtain transmission spectra of wheat fl our. All measured ash values obtained by NIT method were within calibration limits (0.00-1.10) of the instrument. Simple linear regression analyses showed high signifi cant correlation between the NIT and the reference method (r=0.953). Th e NIT results were not accurate enough for all fl our types when compared to the results obtained by the reference method. Only the results for fl our types 400 and 550 indicate suffi cient accuracy for fl our type evaluation. Considering its advantages over standard methods, including its recalibration, NIT could represent a good tool for evaluation of all fl our types in the future, as it is used for protein and moisture determination in wheat grain today.

Key words wheat fl our, ash, near infrared transmission, regression

1 Agricultural institute Osijek, Južno predgrađe 17, 31000 Osijek, Croatia e-mail: [email protected] 2 Belje,d.d., PC Mlin, Darda, Croatia 3 PPK Valpovo, Valpovo, Croatia Received: January 15, 2007 | Accepted: March 30, 2007

Agriculturae Conspectus Scientifi cus | Vol. 72 (2007) No. 3 (233-238) 234 Rezica SUDAR, Zorica JURKOVIĆ, Marica GALONJA, Irena TURK, Marija ARAMBAŠIĆ

Introduction Material and methods Ash content is an important constituent for wheat fl our One hundred thirteen wheat fl our samples from regu- quality and it is an indicator of fl our purity. Th e ash is lar manufacture were collected from mills: Belje,d.d., PC not evenly distributed throughout the kernel being more Mlin and PPK Valpovo. Ash content was determined using concentrated in the brain (6%) than in the endosperm two diff erent methods, the NIT method and the refer- portion (0.4%) of the grain. Th e milling process, even at ence method. Th e NIT-method of ash was applied on Foss the optimum conditions, can not completely separate the Tecator “Infratec 1241 Grain Analyzer Flour Module”. For starchy endosperm from the bran, so a small amount of spectrophotometric methods, it is essential to have proper fi ne bran particles escapes separation and passes through calibration for reliable analysis. Th e instrument utilizes a to the fl our streams contaminating them. Ash content in- calibration provided by the manufacturer. Th e measure- dicates how completely and effi ciently the endosperm has ment is based on the fact that the main constituents in the been separated from the bran. Th is measurement is criti- grain absorb electromagnetic radiation in the spectrum area cal to the fl our milling process and is used to monitor the from 850 nm to 1050 nm. Th e monochromatic light beam proper functioning of various milling stages (Singh et al., is transmitted via an optical fi ber to the sample cell, where 1998; Mousia et al., 2004). Ash content refers to the min- it passes through the sample and reaches the detector. Th e eral residue of fl our, and is determined by oven method detector signal is then amplifi ed and further processed by burning (ICC, 1990). It is standard but time-consuming the embedded computer. Th e Infratec 1241 Flour Module method. A quick method for the ash determination has grain analyzer is very simple to operate. Th e sample cup is always been required by the milling industry. fi lled with fl our at the fi lling station. An application model Near infrared transmission (NIT) spectroscopy is an an- is chosen from the user menu aft er which the sample cups alytical technique that is rapid, requires very little labor and drops in the hoper. Th e instrument makes a reference scan does not require chemicals or create chemical waste. Th e before the conveyor start. Th e conveyor then transports the technique has extensive application for the analysis of con- sample cup until it drops into the shaft . Th e lower shut- stituents of agricultural crops (Williams, 1975; Delwiche, ter holds the sample cup right in front of detector where 1995; Delwiche et al.,1998; Jurković et al., 2003; Font et al., the scan is made. Results appear within a minute on the 2005, 2006; Kayes et al., 2005), feed (Aastveit and Marum, large display. Th ey can be printed on an optional printer 1993; Locher et al., 2005) and food (Scotter, 1997; Cen and or can be dumped to an external computer for further data He, 2006). Near infrared spectroscopy analysis, like all processing (Foss Tecator, 2002; 2002a). other spectrophotometric methods, is an indirect method According to the reference method (ICC, 1990) ash was and must therefore be calibrated. Th e calibration is con- defi ned as the quantity of mineral matter which remains ducted using referent analytical values of the calibration as incombustible residue of the tested substance. Burning samples, recording their spectrum and complex statistical to ashes was carried out at 900 °C, and is completed when evaluation of all data. Th e calibration is essential for the the cool residue was white or nearly white. Th e ash quan- method effi ciency; therefore, a large number of samples, tity in wheat fl our expressed to dry matter and the mois- comprising a broad range of values for the parameters ture content of the fl our has to be determined separately of interest, should be used. Th e instrumentation used in (ICC, 1976). near infrared spectroscopy can vary in method of radia- Several statistic parameters were used to test calibration dispersion, wavelength range, detection system and tion and prediction equations: Standard error of predic- chemo metric equation used to predict constituent con- tion (SEP) - variability in the diff erence between predicted centration (Delwiche et al., 1998). NIT method measures values and reference values; Coeffi cient of determination only the fraction of electromagnetic radiation that passes (R2) - proportion of variability in the reference data ac- through the sample. Although small, that fraction is suf- counted for by the regression equation; Correlation coeffi cient for supplying information about the sample quality fi cient (r) - degree to which predicted and reference values (Conradi, 2001). In the last few years Flour module was an are correlated; Bias (D) - the mean diff erence between the optional equipment to the Infratec 1241 Grain Analyzer predicted and the reference values. which has been developed for protein, moisture and ash content in fi ne milled fl our and semolina. Statistical analyses were conducted using statistical- graphic system “Statistica” version 6.0 (StatSoft soft- Th e aim of this study was to test the application for deter- ware). mination of ash content in wheat fl our using NIT instrument Infratec 1241 Grain Analyzer Flour Module with ready-to-use calibrations. Results and discussion Th e ash content measurements are still used in the milling industry worldwide as an indicator for fl our purity.

Agric. conspec. sci. Vol. 72 (2007) No. 3 Application of Near Infrared Transmission for the Determination of Ash in Wheat Flour 235

Table1. Ash content (%) determined by reference and NIT method, and diff erence between the methods (bias)

No. Ash %/DM Bias No. Ash %/DM Bias No. Ash %/DM Bias flour Reference NIT flour Reference NIT flour Reference NIT method method method method method method 1 0.367 0.397 0.030 39 0.543 0.553 0.010 77 0.767 0.727 -0.040 2 0.384 0.412 0.028 40 0.544 0.583 0.039 78 0.773 0.817 0.044 3 0.394 0.390 -0.004 41 0.548 0.560 0.012 79 0.786 0.733 -0.053 4 0.394 0.410 0.016 42 0.548 0.583 0.035 80 0.790 0.730 -0.060 5 0.403 0.428 0.025 43 0.555 0.553 -0.002 81 0.804 0.702 -0.102 6 0.431 0.412 -0.019 44 0.555 0.587 0.032 82 0.806 0.725 -0.081 7 0.450 0.490 0.040 45 0.557 0.480 -0.077 83 0.818 0.743 -0.075 8 0.468 0.503 0.035 46 0.558 0.517 -0.041 84 0.821 0.790 -0.031 9 0.480 0.563 0.083 47 0.559 0.553 -0.006 85 0.824 0.753 -0.071 10 0.485 0.470 -0.015 48 0.559 0.567 0.008 86 0.825 0.783 -0.042 11 0.485 0.543 0.058 49 0.559 0.563 0.004 87 0.836 0.753 -0.083 12 0.487 0.480 0.007 50 0.561 0.530 -0.031 88 0.837 0.757 -0.080 13 0.489 0.560 0.071 51 0.562 0.580 0.018 89 0.840 0.740 -0.100 14 0.490 0.410 0.080 52 0.563 0.587 0.024 90 0.841 0.817 -0.024 15 0.493 0.533 0.040 53 0.564 0.537 -0.027 91 0.842 0.730 -0.112 16 0.495 0.570 0.075 54 0.566 0.550 -0.016 92 0.857 0.783 -0.074 17 0.496 0.553 0.057 55 0.568 0.563 -0.005 93 0.858 0.850 -0.008 18 0.496 0.553 0.057 56 0.570 0.572 0.002 94 0.860 0.802 -0.058 19 0.497 0.570 0.073 57 0.571 0.575 0.004 95 0.863 0.890 -0.027 20 0.498 0.567 0.069 58 0.571 0.553 -0.018 96 0.872 0.813 -0.059 21 0.498 0.550 0.052 59 0.572 0.572 -0.000 97 0.877 0.767 -0.110 22 0.502 0.530 0.028 60 0.574 0.572 -0.002 98 0.878 0.860 -0.018 23 0.503 0.560 0.057 61 0.574 0.537 -0.037 99 0.878 0.847 -0.031 24 0.505 0.567 0.062 62 0.574 0.570 -0.004 100 0.880 0.827 -0.053 25 0.505 0.560 0.055 63 0.581 0.585 0.004 101 0.890 0.847 -0.043 26 0.505 0.510 -0.005 64 0.582 0.575 -0.007 102 0.890 0.785 -0.105 27 0.506 0.560 0.054 65 0.582 0.597 -0.015 103 0.890 0.840 -0.050 28 0.513 0.573 0.060 66 0.587 0.580 -0.007 104 0.891 0.910 0.019 29 0.519 0.567 0.048 67 0.600 0.582 -0.018 105 0.898 0.857 -0.041 30 0.524 0.480 -0.044 68 0.606 0.560 -0.046 106 0.909 0.870 -0.039 31 0.527 0.557 0.030 69 0.632 0.540 -0.092 107 0.913 0.890 -0.023 32 0.529 0.527 -0.002 70 0.638 0.590 -0.048 108 0.918 0.847 -0.071 33 0.530 0.577 0.047 71 0.640 0.540 -0.100 109 0.938 0.883 -0.055 34 0.536 0.543 0.007 72 0.648 0.520 -0.128 110 0.938 0.815 -0.123 35 0.537 0.560 0.023 73 0.680 0.620 -0.060 111 0.951 0.892 -0.059 36 0.539 0.547 0.008 74 0.709 0.685 -0.024 112 0.961 0.917 -0.044 37 0.539 0.530 -0.009 75 0.718 0.677 -0.041 113 0.964 0.857 -0.107 38 0.541 0.550 0.009 76 0.733 0.520 -0.213

However, currently, there is a tendency to replace the ash 0.917%. Figure 1 illustrates mean ash value and standard content analysis with other methods (Kim and Flores, 1999; error of reference and NIT methods. Standard errors of Sing et al., 1998; Ugarčić-Hardi et al., 2001) being more ash value obtained by NIT (0.013) were lower than by ref- rapid, sensitive and inexpensive, for the determination of erence method (0.016). Th e data presented in Table 1 were the bran content in the fl our. An alternative, not yet fully analyzed by t-test. T-test for dependent samples indicated examined method for the ash measurement is near infra- that signifi cant diff erence in mean ash value was obtained red transmission. by reference and NIT methods (p=0.003). Value of bias Th e ash content determined in an tested wheat fl our ranged from -0.213% to 0.083% (Table 1), indicating that sample by the reference and the NIT methods is present- calibration had limited predictive ability. ed in Table 1. Th e overall range of total ash content de- Linear regression for the relationship between ash con- termined by the reference method varied from 0.367% to tent obtained by the two methods is presented in Figure 2. 0.964% on a dry weight basis. Th e ready-to use ash cali- Th e R2 value (0,910) indicated that 91% of ash variability in brations on Infratec Grain Analyzer Flour Module covers fl our samples was explained by equation (Fig 2). Th e cor- the complete range up to 1.10% ash content. All measured relation coeffi cient showed high positive signifi cant cor- ash values obtained by NIT method were within calibra- relation between investigated methods. A standard error tion limits of the instrument and ranged from 0.397% to of prediction (SEP) was 0.054 that is 8,37% of the mean

Agric. conspec. sci. Vol. 72 (2007) No. 3 236 Rezica SUDAR, Zorica JURKOVIĆ, Marica GALONJA, Irena TURK, Marija ARAMBAŠIĆ

0,68 reference value for ash content. Th is value was relatively Mean high according to Williams (1987) who recommended that 0,67 ±SE ±1,96*SE the SEP should not be more than 3% of the mean reference value for that analyte. 0,66 Wheat fl our off ered a range of special types of fl our, diff erent for their granulation, protein quantity and qual- 0,65 ity as well as mineral substance quantity. Th e quantity of ash helps classifying the fl our in types. Assortment ac- 0,64 cording to our regulation (NN 78, 2005) includes wheat s % Ash fl our of 400, 550, 700, 850, 1100 and 1600 type. Tested 0,63 fl our samples were distributed according to the regulation (Table 2). Th e number of samples represents types of fl our, 0,62 mostly utilized for end-usage. Th e results of the mean ash content for fl our type, illustrated in Table 3 showed the 0,61 diff erence in the ash content between reference and NIT method. Values of bias ranged from 0.017% to -0.083% 0,60 indicated that tested calibration had suffi cient accuracy 12 only for fl our type 400 and 550. Th ese fl our types had bias Reference method NIT method <0.020%. Th is diff erence refers to the upper limit for which Figure 1. duplicate measurements may diff er in reference method. Box- Whisker plot of ash content obtained by the reference and For other investigated fl our samples, calibration was not the NIT methods confi dent. As presented in Figure 3, samples in range up to 0.600 % indicated that the Infratec instrument 1,0 Ash%(NIT mehtod)= 0,119 + 0,792 * Ash%(Reference method) had a tendency to underestimate ash content. Correlation: r =0,954 Th erefore, according to ash content obtained 0,9 by NIT method, samples did not inhere ade- quate fl our types. 0,8 Th ese results indicate that current calibration should be corrected (bias, slope and inter- 0,7 cept corrections) on Infratec Grain Analyzer Flour module for ash content determination 0,6 in wheat fl our, aiming to obtain confi dent and accurate predicted value. s NTmethod) (NIT % Ash 0,5

0,4 Figure 2. 95% confidence Relationship between ash content obtained 0,3 by the reference and the NIT methods 0,3 0,4 0,5 0,6 0,7 0,8 0,9 1,0 Ash % (Reference method)

Table 2. Distribution of samples according to the Table 3. Mean value of ash content for fl our types and regulation (Narodne Novine, 78/2005) diff erence between the methods (Bias)

Ash %/ DM Number Wheat flour Ash %/ DM Flour types Ash %/DM Bias (in samples) type (regulation) Reference method NIT method 0.367-0.450 7 T-400 to 0.45 T-400 0.403 0.420 0.017 0.451-0.600 60 T-550 0.50 - 0.60 T-550 0.535 0.551 0.016 0.601-0.750 9 T-700 0.65 - 0.75 T-700 0.667 0.584 -0.083 0.751-0.900 29 T-850 0.80 - 0.90 T-850 0.845 0.792 -0.053 0.901-0.964 8 T-1100 1.05 - 1.15 T-1100 0.937 0.872 -0.065 All types 0.645 0.630 -0.015

Agric. conspec. sci. Vol. 72 (2007) No. 3 Application of Near Infrared Transmission for the Determination of Ash in Wheat Flour 237

1,0

Mean ±SE ±1,96*SE 0,9

0,8

0,7 s % Ash

0,6

0,5

0,4 Figure 3. Box-Whisker plot of ash content obtained by 0,3 reference and NIT method in flour types T-400 T-700 T-1100 T-550 N T-850 N T-550 T-850 T-400 N T-700 N T-1100 N Flour type by reference method Flour type by NIT method

Conclusion Font R., del Rio M., de Haro A. (2006). Th e use of near-infrared spectroscopy (NIRS) in the study of seed quality components Th e results of this study indicate that tested application in plant breeding programs. Ind Crop Prod 24: 307-313 for determination of ash content in wheat fl our on NIT Foss Tecator AB (2002). User manual Infratec 1241 Grain instrument Infratec 1241 Grain Analyzer Flour Module Analyzer ISW 3.0., Foss Tecator, Sweden could be used as a nondestructive, accurate and rapid Foss Tecator AB (2002a). Flour module User manual 1001 0787/ method for routine determination of ash in wheat fl our Rev.1.0. Foss Tecator, Sweden types 400 and 550. Considering its advantages over stand- ICC (1976). Determination of the moisture content of cereals and ard methods, including its recalibration, NIT represents cereal Products (Practical method). ICC Standard No. 110/1, International association for cereal science and technology, a good candidate for evaluation of all fl our types in the Viena, Austria future, as it is used for protein and moisture determina- ICC (1990). Determination of ash in cereals and cereal Products. tion in wheat grain now days. ICC Standard No. 104/1, International association for cereal science and technology, Viena, Austria Jurković Z., Sudar R., Galonja M., Šimić G., Horvat D., Drezner References G. (2003). Measuring sedimentation value in whole wheat Aastveit A.H., Marum P. (1993). Near-infrared refl ectance grain with near-infrared transmission. In: Proceedings of spectroscopy: Diff erent strategies for local calibrations in international congress Flour-bread’01, 4th Croatian congress analyses of forage quality. Appl Spectrosc 47 (4): 463-469. of Cereal technologists, November 19-22, Opatija, Croatia, pp 109-114 Cen H., He Y. (2006). Th eory and application of near infrared refl ectance spectroscopy in determination of food quality. Kayes S.E., Shimizu N., Barton F.E. II, Ohtbuso K. (2005). Near- Trends Food Sci Tech (article in press): 1-12. infrared transmission and refl ectance spectroscopy for the determination of dietary fi ber in barley cultivars. Crop Sci 45: Conradi K. (2001). Near infrared transmittance for measuring the 2307-2311 moisture content of grains. OIML Bulletin 42: 17-20 Kim Y.S., Flores R.A. (1999). Determination of bran Delwiche S.R. (1995). Single wheat kernel analysis by Near- contamination in wheat fl ours using ash content, color, and infrared transmittance: protein content. Cereal Chem bran speck counts. Cereal Chem 76: 957-961 72(1):11-16 Locher F., Heuwinkel H., Gutser R., Schmidhalter U. (2005). Th e Delwiche S.R., Graybosch R.A., Peterson C.J. (1998). Predicting legume content in multispecies mixtures as estimated with protein composition, biochemical properties and dough- near infrared refl ectance spectroscopy. Agron J 97: 18-25 handling properties of hard red winter wheat fl our by near- infrared refl ectance. Cereal Chem 75(4), 412-416 Mousia Z., Edherly S., Pandiella S.S., Webb C. (2004). Eff ect of wheat pearling on fl our quality. Food Res Int 37: 449–459 Delwiche S.R. Pierce R.O., Chung O.K. Seabourn W. (1998). Protein content of wheat by near infrared spectroscopy of Pravilnik o žitaricama, mlinskim i pekarskim proizvodima, whole grain: Collaborative study. J AOAC Int 81 (3): 587-603 tjestenini, tijestu i proizvodima od tijesta. (2005). Narodne novine 78: 4293-4300 Font R., Wittkop B., Badani A.G., del Rio M., Friedt W., Luhs W., de Haro A. (2005). Th e measurements of acid detergent fi bre Singh N., Singh H., Bakshi M.S. (1998). Determining the in rapeseed by visible and near-infrared spectroscopy. Plant distribution of ash in wheat using debranning and breeding 124: 410-412 conductivity. Food Chem 62: 169–172

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