ROŚLINY OLEISTE OILSEED CROPS 37:

ROŚLINY OLEISTE OILSEED CROPS 37: 97 117 2016 Krzysztof Michalski, Jan Krzymański Plant Breeding and Acclimatization Institute National Research Institute, Branch Office in Poznan Author for correspondence K. Michalski, e-mail: km@nico.ihar.poznan.pl The possibility of the use of NIR spectrometer to measure the extremely low content of glucosinolates in seeds during the breeding and maintenance of double low oilseed rape varieties Możliwości użycia spektrometru NIR do pomiaru ekstremalnie niskiej zawartości glukozynolanów w nasionach w czasie hodowli i utrzymywaniu odmian rzepaku podwójnie ulepszonego Key words: total of glucosinolates, alkenyl glucosinolates, indolyl glucosinolates, gluconapin, glucobrassicanapin, progoitrin, napoleiferin, brassicin, 4OH-brassicin, NIRS measurement done on intact seed Abstract The basic factor to obtain reliable results by Near Infrared Spectrometry (NIRS) is a good robust calibration. Two calibration methods were investigated. The more universal method called LOCAL was compared to classical PCA method called GLOBAL. LOCAL method is based on a large database from which the calibration set is chosen on the basis of the spectra similarity. This is done during each measurement. The data base for LOCAL method was collected from seed analyses of varieties and strains bred in Poland during last 15 years. GLOBAL method uses constant calibration based on a set of samples with composition similar to this expected in samples which will be measured. Calibration equations for this method were calculated by Principal Component Analysis (PCA). The results obtained by GLOBAL method for the content of both the total and individual glucosinolates in intact seeds were more similar to the results of the chemical analyses than the results obtained with LOCAL method. Glucosinolate content in seeds of double low rapeseed is so low that when the LOCAL method is searching for calibration set from the database, their spectra are dominated by the spectra of the major seed components, such as fat, protein, fiber or moisture. It is impossible to obtain proper calibration for extremely low glucosinolate content. NIRS method with GLOBAL calibration allowed getting results in satisfactory accordance with the results of the chemical analysis for the total of the glucosinolates, the total of the alkenyl glucosinolates, progoitrin, gluconapin. The measurements of the glucosinolates whose content was even smaller, such as glucobrassicanapin, napoliferin or brassicin, show too big an error. Słowa kluczowe: suma glukozynolanów, glukozynolany alkenowe, glukozynolany indolowe, glukonapina, glukobrassicanapina, progoitryna, brazycyna, 4OH-brazycyna, pomiar NIRS na nienaruszonych nasionach

98 Krzysztof Michalski Streszczenie Dla hodowli odmian rzepaku o bardzo niskiej zawartości glukozynolanów potrzebne są szybkie i tanie metody ich analizy. Do tego celu najlepiej wykorzystać metodę analizy instrumentalnej, np. NIRS (Near Infrared Spectrometry). Podstawą do otrzymania wiarygodnych wyników tą metodą jest dobre równanie kalibracyjne. Istnieje kilka metod kalibracji wykorzystujących regresję liniową wielokrotną, analizę głównych składowych albo sieci neuronowe. W pracy przebadano dwie metody, nazywane LOCAL oraz GLOBAL. Pomiaru NIRS dokonywano na nienaruszonych nasionach. Metoda LOCAL jest bardziej uniwersalna. Opiera się ona na dużej bazie danych oraz wybieraniu z niej przy każdym pomiarze zestawu kalibracyjnego na podstawie podobieństwa widm. Baza danych dla metody LOCAL została zebrana na podstawie wyników analiz nasion odmian i rodów hodowlanych badanych w Polsce w ciągu ostatnich 15 lat. Metoda GLOBAL używa stałej kalibracji opartej na zestawie próbek o składzie podobnym do oczekiwanego w próbkach, które będą mierzone. Równania kalibracyjne dla metody GLOBAL zostały obliczone metodą analizy składników głównych (Principal Component Analysis PCA) przy użyciu zestawu kalibracyjnego próbek rzepaku podwójnie ulepszonego o mocno obniżonej i zróżnicowanej zawartości glukozynolanów. Wyniki otrzymane metodą GLOBAL dały pomiary zawartości tak sumy, jak i poszczególnych glukozynolanów, bardziej zgodne z wynikami analiz chemicznych niż pomiary metodą LOCAL, która okazała się nieprzydatna w hodowli rzepaku o ekstremalnie niskiej zawartości glukozynolanów. Zawartość glukozynolanów w nasionach polskiego rzepaku podwójnie ulepszonego jest tak niska, że metoda kalibracji LOCAL szukając w bazie danych do zestawu kalibracyjnego, dokonuje fałszywych wyborów. Widma glukozynolanów są bowiem zdominowane przez widma głównych komponentów nasion, takich jak tłuszcz, białko, włókno lub wilgotność. Metoda NIRS z kalibracją GLOBAL daje wyniki zadowalająco zgodne z wynikami analizy chemicznej dla następujących składników: sumy glukozynolanów, sumy glukozynolanów alkenylowych, progoitryny, gluconapiny. Natomiast pomiar składników zawartych w jeszcze mniejszej ilości, takich jak glukobrassicanapina, napoliferyna czy brazycyna jest obarczony zbyt dużym błędem. Introduction Upper limit for glucosinolate content in double low rapeseed according Polish standard is the lowest in the world. The limit only up to 15 micromoles of glucosinolates per gram of seeds (about 0.6%) is accepted (Polskie Normy PN- 90/R-66151). This applies to the total of the alkenyl and indolyl glucosinolates. This standard was determined on the basis of the results of Polish nutritional experiments (Rakowska et al. 1979, 1981, 1984). So low glucosinolate content provides good weight gains and reproduction of animals despite still increased the thyroid gland. Therefore, further reduction of glucosinolate contents is very desirable (European Food Safety Authority 2008). Breeding works for further lowering of glucosinolate content needs fast and cheap, and accurate methods for its analysis. Breeding or maintenance of variety of oilseed rape of double low quality (zero erucic and very low in glucosinolate content) requires a large number of accurate chemical analyses in order to control the content and composition of glucosinolates in seeds. This condition is more important in the breeding of new varieties of oilseed

The possibility of the use of NIR spectrometer 99 rape for even more reduced glucosinolate content. Such analyses are expensive and time consuming. The sample of seeds used in chemical analysis is destroyed. Therefore, attempts were made to replace the chemical analyses with spectrometry measurements done on intact seed in the near-infrared (NIRS). The advantages of the NIRS measurement are as follows: at the time of one measurement several components can be determined simultaneously depending on the spectrometer calibration (Starr et al. 1985, Michalski and Kołodziej 2000, Petiscoa et al. 2010). tested sample of seeds is not destroyed and can be sown to obtain the next generation of plants. It is very important because this procedure speeds up the breeding of new varieties. The disadvantage of the NIR methods is that they are based on correlations between the NIR spectra and the contents of the glucosinolates in the measured samples of seeds. These correlations can be affected by many factors, such as: weather conditions during plant growing, mineral nutrition or chemical treatment, seed moisture content (Byczyńska et al. 1970, 1981, Piętka et al. 2001, 2002, 2003, 2005, 2007, Byczyńska et al. 1970, 1981). Different complicated calibration methods are used to get more stable and repeatable results. The accuracy of the calibration depends on: precision of chemical analysis of seeds samples used as calibration set, the accuracy of the spectrum measurement, statistical methods used to calculate the calibration equation, the number of seed samples used for calibration and validation, the chemical variability in composition of seed samples used for calibration and validation, the size of measured sample and its chemical homogeneity. The accuracy and repeatability of the results of chemical analysis and of NIRS measurement has a decisive influence on the progress of breeding works. Heritability and breeding effectiveness decreases with an increase of error in the estimation of selected trait or component (Allard 1960, 1968). The literature that has been concerned with the glucosinolate content measurements in seeds of rapeseed using NIRS method relates to a natural much higher contents of these compounds or to canola standard (Biston et al. 1988, Daun et al. 1994, Font et al. 2004, Hom et al. 2007, Michalski et al. 1987, Montes et al. 2007, Petiscoa et al. 2010, Renard et al. 1987, Velasco and Becker 1998, Velasco and Mollers 1999, Welle et al. 2007, Zhang et al. 2013). The official definition of canola is: Seeds of the genus Brassica (Brassica napus, Brassica rapa or Brassica juncea) from which the oil shall contain less than 2% erucic acid in its fatty acid profile and the solid component shall contain less than 30 micromoles of any one or any mixture of 3-butenyl glucosinolate, 4-pentenyl glucosinolate, 2-hydroxy-3- butenyl glucosinolate, and 2-hydroxy-4-pentenyl glucosinolate per gram of air-dry, oil-free matter (canola standard of Canola Council 2012). Polish standard is lower

100 Krzysztof Michalski than for canola and IHAR target in rapeseed breeding is also much lower. It was necessary to check usability of NIRS-spectroscopy and its exactness in rapeseed with this very low glucosinolate contents. The basis to obtain reliable results by NIRS method is a good robust calibration model. For calibration purposes couple mathematical methods (multiple regression, principal component analysis (PCA), neural network) were developed (Mahalanobis 1936, Martens and Naes 1989, 1991, Shenk and Westerhaus 1997). In the study a classical PCA method called GLOBAL (static equation) was investigated and compared with more flexible and universal method called LOCAL (dynamic method) (Shenk and Westerhaus 1997, WinISI 4). These two methods of calibrating the NIR spectrometer were examined to find the method giving the most accurate results of glucosinolate estimation in seeds of oilseed rape also with extremely low glucosinolate content (Spasibionek et al. 2016) Materials Materials and methods NIRS measurements and chemical analyses used 100 samples of air dry seeds (moisture content about 5.7%) collected from the field trial with breeding strains of double low oilseed rape (zero erucic and with very low content of glucosinolates). The field trial was performed in the growing period 2012/13 on the field of Plant Breeding Company Strzelce, in Borowo Station (Wielkopolska, N 52 o 07, E 16 o 47'). The randomized complete blocks design with 4 replications was used. The size of the four-row plots was 12 m 2 for harvest. 25 objects were examined in the trial: 23 inbred lines from research works conducted in Plant Breeding and Acclimatization Institute Division Poznań and two check varieties: Chagall (open pollinated cultivar) and Monolit (Doubled Haploid cultivar). 16 inbred lines were taken from the breeding conducted with the use of chemical mutagenesis. The aim of breeding was to increase the content of oleic acid and to reduce the linolenic acid content in seed oil (Byczyńska et al. 1996, Spasibionek 2002, 2005, 2006, 2013, Spasibionek et al. 1999, 2000, 2003, 2011). Another set of 7 inbred lines was taken from the recombination breeding which used the natural variability obtained by recurrent selection. Crosses were made between many different varieties and breeding lines of double low oilseed rape. The purpose was to decrease to minimum glucosinolate content in seeds (Krzymański 1968, 1970, 1970a, Krzymański et al. 1999, Piętka et al. 2001, 2002, 2003, 2005, 2007, EFSA 2008) and to increase the content of oleic acid in seed oil (Krzymański et al. 1983, 2004, Piętka et al. 2003). The inbred lines described above are extremely low in the glucosinolate content (total alkenyl glucosinolate range 1,88 to 3,25 μm/g of seeds).

The possibility of the use of NIR spectrometer 101 The glucosinolate contents and their variabilities for examined seed samples were shown in Table 1. All tested seed samples met the Polish requirements of double low rapeseeds. The most differentiated glucosinolate contents were for alkenyl glucosinolates. The variability of the content of indolyl glucosinolates was significantly lower. The contents of glucobrassicanapin, napoleiferin and brassicin were very low (about 0.02 percent). Table 1. Statistics of database used for LOCAL calibration Statystyczny opis bazy danych użytej do kalibracji metodą LOCAL Gluconapin Glucobrassicanapin Progoitrin Napoleiferin Glucobrassicin 4OHglucobrassicin Glucosinolate total Alkenyl glucosinolate total Mean Średnia 2.48 0.44 4.35 0.06 0.19 4.15 11.67 6.64 Standard error Błąd standardowy 0.03 0.01 0.07 0.00 0.00 0.03 0.11 0.11 Mediane Mediana 2.10 0.30 3.50 0.00 0.10 4.10 10.70 5.60 Mode Tryb 2.30 0.30 2.50 0.00 0.10 4.20 8.50 0.00 Standard deviation Odchylenie standardowe 1.54 0.41 3.49 0.10 0.18 1.34 5.19 5.16 Sample variation Wariancja próby 2.37 0.17 12.15 0.01 0.03 1.81 26.98 26.66 Kurtosis Kurtoza 9.41 25.79 13.70 187.49 61.49 1.53 9.49 10.02 Scenes Skośność 2.20 3.61 2.78 10.05 5.25 0.64 2.22 2.27 Range Zakres 15.50 5.10 34.60 2.40 3.00 11.90 47.00 48.70 Minimum 0.20 0.00 0.00 0.00 0.00 0.00 3.40 0.00 Maximum 15.70 5.10 34.60 2.40 3.00 11.90 50.40 48.70 Sample number Liczba prób 2359 2359 2359 2359 2359 2359 2359 2359 Methods of analyses Chemical analyses The glucosinolate analyses in rapeseed were accomplished by gas liquid chromatography of trimethylsilyl derivatives of desulfated glucosinolates according to Raney method (Raney et al. 1990, Michalski et al. 1995). The method was standardized with BC 190 reference material and gives results comparable with the results of high-pressure liquid chromatography method (HPLC) (Wathelet 1987 PN-EN ISO 9167-1:1999).

102 Krzysztof Michalski NIRS measurements The reflectance spectra, Log (1/R), of the samples were recorded on a NIRS spectrometer model 6500 (Foss NIRSystems, Silver Springs, MD) with a spectral range of 400 2.498 nm and 2-nm wavelength increments. Spectrometer was equipped with spinning sample module. Samples were measured using ring cup cuvette. Sample volume was 8 ml. Sample cell construction of NIRS-spectrometers allows usually to measure about 4 5 ml volume of seed sample although small samples or single seed were also estimated (Velasco 1999a, Hom 2007, Zhang 2013). The increased volume of a sample and its rotation allows obtaining better and more exact results. NIRS GLOBAL calibration GLOBAL method is a static model. It uses constant calibration based on a set of samples with chemical composition similar to those expected in samples which will be measured. This calibration remains unchanged until a calibration update is made. Calibration equations for GLOBAL were calculated by Modified Principal Component Analysis (PCA) method using the calibration set of samples of double low rapeseed (Burns 2007, Martens 1989, 1991, WinISI 4, Font et al. 2004, Mahalanobis 1936). Equations were made for individual glucosinolates, total of alkenyl glucosinolates, total of indolyl glucosinolates and total of both glucosinolates. NIRS LOCAL calibration LOCAL calibrations are dynamic in contrast to GLOBAL calibrations. LOCAL method can be used for different products in one model. LOCAL method is based on a large database and from which a calibration set is chosen on the basis of the similarity of the spectra to the measured one by applying Mahalanobis distance method (Mahalanobis 1936). The prediction is based on those of the spectra that most closely resemble the examined unknown sample. It can also better cope with non-linear dependencies (Burns 2007, Martens and Naes 1989, Martens 1990, 1991, Shenk and Westerhaus 1996, 1997, WinIsi 4, patent US 5798526). The database containing 2359 seed samples spectra was collected and used for LOCAL method calibration (Tab. 1 and Fig. 1). The content of total glucosinolates ranged from 4 to 50 μm/g of seed The database consists of mainly winter and summer rapeseed samples but there were present black and white mustard samples as well (20%). Statistical methods Statistical analysis of the field trial was conducted by method of the twofactor analysis with testing the significances of differences between objects. Analysis ToolPak (Microsoft Office Exel) was used for statistical calculations. Measurements and chemical analyses of seeds were done on two average seed samples per each plot. More details can be found in paper by Spasibionek et al. 2016.

The possibility of the use of NIR spectrometer 103 Fig. 1. Histogram of total glucosinolate content in database for LOCAL calibration Histogram rozkładu sumy glukozynolanów w bazie danych dla kalibracji LOCAL Statistical analyses of variance and regression for chemical analyses and for NIRS-measurements were conducted for totals and individual glucosinolate contents in seeds. These analyses were made to compare two studied glucosinolate estimation methods. Standard deviations for glucosinolate determinations (errors) were calculated as the square roots of the mean squares for error. The repeatability of results for objects means were presented as heritability (internal correlation coefficient in the analysis of variance for the trial (h 2 ) calculated according to Allard (1960, 1968). The repeatability (heritability) has been calculated for the selection based on the means for objects. Results and discussion The first attempts of NIRS application to the analysis of the glucosinolate content in Brassica seeds have been carried out by Starr (Starr et al. 1985) and then by other researchers (Biston et al. 1988, Daun et al. 1994, Kumar et al. 2010). Typically, applications for glucosinolates were based on measurements made on different models of spectrophotometers measuring NIR spectrum covering the 1100 2500 nm or 400-range. Described methods have been developed for higher glucosinolate contents and higher of this trait than those with which we are dealing in Polish breeding of new varieties or in the maintenance of the varieties. Therefore, we investigated two

104 Krzysztof Michalski NIRS calibration methods by checking their repeatability and conformity of the results with the results of the chemical analyses. Comparison of NIRS measurements with results of chemical analyses Tables 2, 3 and 4 contain chemical description of rapeseed samples used in research. Tables show the statistical parameters of glucosinolate content estimated with both chemical analyses and NIRS measurements using two different calibration methods: GLOBAL and LOCAL. Table 2. Statistical description of results of chemical analyses of glucosinolate contents in the set of examined seed samples (μm/g of seed) Opis statystyczny wyników analizy chemicznej zawartości glukozynolanów w zbiorze badanych próbek nasion rzepaku (μm/g nasion) Component Komponent Mean Średnia Median Mediana Variance Wariancja Range Zakres Minimum Maximum Gluconapin 2.296 2.3 1.1343 4.6 0.7 5.3 Glucobrassicanapin 0.668 0.7 0.1378 1.7 0.1 1.8 Progoitrin 3.969 3.9 5.7525 9,0 0.5 9.5 Napoleiferin 0.071 0.1 0.0041 0.2 0 0.2 Brassicin 0.140 0.1 0.0099 0.4 0 0.4 4OH-brassicin 4.432 4.3 0.5628 3.5 2.7 6.2 Glucosinolate total 11.592 11.8 15.7987 15.2 4.7 19.9 Alkenyl glucosinolate total 7.018 7.0 13.9718 14.5 1.3 15.8 Indolyl glucosinolate total 4.572 4.5 0.6271 3.8 2.8 6.6 The results of the glucosinolate content measurements using the two NIRS calibration methods were compared with the results of the chemical analyses. These comparisons were shown in the Table 4 containing regression equations and determination coefficients. These comparisons for gluconapin, progoitrin, 4OHbrassicin, and total of glucosinolate, total of alkenyl glucosinolate and total of indolyl glucosinolate were shown also graphically in Figures 2 5. These drawings contain also the regression equations and the coefficients of determination (R 2 ).

The possibility of the use of NIR spectrometer 105 Table 3. Statistical description of results of glucosinolate measurements with GLOBAL method in the set of examined seed samples (μm/g of seed) Opis statystyczny wyników analizy glukozynolanów za pomocą metody GLOBAL badanych próbek nasion (μm/g nasion) Component Komponent Mean Średnia Median Mediana Variance Wariancja Range Zakres Minimum Maximum Gluconapin 2.8643 2.9431 1.0882 4.5391 0.8118 5.3509 Glucobrassicanapin 0.5999 0.6039 0.0544 0.9317 0.1446 1.0763 Progoitrin 4.5592 4.6715 6.9949 10.8727-0.3510 10.5216 Napoleiferin 0.1229 0.1234 0.0005 0.0937 0.0802 0.1739 Brassicin 0.2043 0.2054 0.0002 0.0763 0.1637 0.2401 4OHbrassicin 4.3682 4.3041 0.2264 2.1223 3.2712 5.3935 Glucosinolate total 12.6138 12.8351 17.3756 17.2052 4.8669 22.0721 Alkenyl glucosinolate total 7.9809 8.0720 16.0538 17.0348 0.6588 17.6936 Indolyl glucosinolate total 4.5725 4.5094 0.2300 2.1548 3.4544 5.6092 Table 4. Statistical description of results of glucosinolate measurements with LOCAL method in the set of examined seed samples (μm/g of seed) Opis statystyczny wyników analizy glukozynolanów za pomocą metody LOCAL badanych próbek nasion (μm/g nasion) Component Komponent Mean Średnia Median Mediana Variance Wariancja Range Zakres Minimum Maximum Gluconapin 2.3955 2.3575 0.3878 3.5150 0.3010 3.8160 Glucobrassicanapin 0.2832 0.3110 0.0270 0.8400-0.1080 0.7320 Progoitrin 3.7887 3.8100 1.5927 7.1820 0.0000 7.1820 Napoleiferin 0.0679 0.0715 0.0009 0.1600-0.0170 0.1430 Brassicin 0.1447 0.1475 0.0071 0.4010-0.1100 0.2910 4OHbrassicin 3.4559 3.4640 0.7376 6.0150 0.0000 6.0150 Glucosinolate total 10.3024 10.2330 4.7808 16.7410-0.4710 16.2700 Alkenyl glucosinolate total 7.3071 7.3390 3.7046 9.2180 2.0690 11.2870 Indolyl glucosinolate total 3.6006 3.5965 0.7906 6.1460 0.0370 6.1830

106 Krzysztof Michalski Table 5. Regression equations (Slope and Intercept) and determination coefficients (R 2 ) between chemical analyses and NIRS measurements with GLOBAL and LOCAL calibrations Równania regresji (nachylenie i stała) oraz współczynniki determinacji (R 2 ) obliczone dla wyników analizy referencyjnej i pomiarów za pomocą NIRS dla kalibracji GLOBAL i LOCAL Component Komponent GLOBAL LOCAL Slope Intercept R 2 Slope Intercept R 2 Gluconapin 0.885 0.830 0.817 0.214 1.903 0.134 Glucobrassicanapin 0.395 0.335 0.396 0.171 0.168 0.149 Progoitrin 1.039 0.443 0.888 0.146 3.206 0.077 Napoleiferin 0.242 0.105 0.460-0.042 0.070 0.008 Brassicin 0.013 0.202 0.010 0.119 0.161 0.019 4OHbrassicin 0.227 3.361 0.128 0.006 3.427 0.0001 Total of glucosinolates 0.973 1.330 0.861 0.193 8.055 0.124 Total of alkenyl glucosinolates 1.009 0.893 0.887 0.177 6.064 0.080 Total of indolyl glucosinolates 0.149 3.890 0.060-0.057 3.862 0.002 R 2 in bold were significant at p = 0.01 R 2 wytłuszczone istotne na poziomie p = 0,01 Table 6. Correlation (r) and regression (b) coefficients between results of chemical analyses and results of NIRS measurements on glucosinolate contents in seeds of double low rapeseed Współczynniki korelacji i regresji pomiędzy wynikami referencyjnymi i wynikami analizy metodą NIRS zawartości glukozynolanów w rzepaku podwójnie ulepszonym Component Komponent GLOBAL LOCAL r b r b Gluconapin 0.9042 0.8857 0.3667 0.2144 Glucobrassicanapin 0.6298 0.3958 0.3869 0.1712 Progoitrin 0.9427 1.0395 0.2789 0.1468 Napoleiferin 0.6787 0.2425-0.0922-0.0422 Brassicin 0.1034 0.0139-0.1411-0.1194 4OHbrassicin 0.3582 0.2272 0.0055 0.0064 Total of glucosinolates 0.9282 0.9734 0.3524 0.1939 Total of alkenyl glucosinolates 0.9421 1.0099 0.2834 0.1774 Total of indolyl glucosinolates 0.2464 0.1493-0.0510-0.0572 Regression coefficients with reliable value for breeding purposes printed with bold letters Współczynniki regresji o wartościach wystarczających dla potrzeb hodowlanych podano wytłuszczoną czcionką

The possibility of the use of NIR spectrometer 107 Fig. 2. The comparison of the NIRS measurements results (y) with chemical analyses (x) for gluconapin Porównanie wyników pomiaru za pomocą analizy w NIRS (y) z wynikami analizy referencyjnej (x) dla glukonapiny

108 Krzysztof Michalski Fig. 3. The comparison of the NIRS measurements results (y) with chemical analyses (x) for progoitrin Porównanie wyników pomiaru za pomocą analizy w NIRS (y) z wynikami analizy referencyjnej (x) dla progoitryny

The possibility of the use of NIR spectrometer 109 Fig. 4. The comparison of the NIRS measurements results (y) with chemical analyses (x) for total of glucosinolate Porównanie wyników pomiaru za pomocą analizy w NIRS (y) z wynikami analizy referencyjnej (x) dla sumy glukozynolanów

110 Krzysztof Michalski Fig. 5. The comparison of the NIRS measurements results (y) with chemical analyses (x) for total of alkenyl glucosinolate Porównanie wyników pomiaru za pomocą analizy w NIRS (y) z wynikami analizy referencyjnej (x) dla sumy glukozynolanów alkenowych

The possibility of the use of NIR spectrometer 111 The compatibility between results obtained with chemical analyses and results obtained using LOCAL calibration was not acceptable and much worse than in the case of GLOBAL calibration. Compatibility was also dependent on the genetic variability of the examined components of seed samples. The best compliance was for alkyl glucosinolates, the worst for indolyl glucosinolates. Very low compliances were observed for the constituents present to a very very small degree (napoleiferin, brassicin, glucobrassicanapin bellow 0.02 per cent). NIRS measurement using GLOBAL calibration can be used successfully for estimation of gluconapin, progoitrin, total glucosinolate and total alkenyl glucosinolate for breeding works purposes. Repeatability and accuracy of NIRS measurement for seeds collected from field trial Variance analyses were performed for glucosinolate contents in seeds which were collected from field trial. These analyses were calculated for the three methods of glucosinolate estimation. Some parameters from these calculations have been shown in Table 7. This Table contains: Standard deviations for object means (s ob ), Snedecor coefficient (F), Probability that mean values for object do not differ (p), Repeatability (heritability) for object means (h 2 ), Standard deviation for single estimation (Stand. dev. of analyze). The examined set of strains was very significantly differentiated for the content of all individual glucosinolates and their totals in spite of their very low content in seeds. The statistical significance of variability was the highest for alkenyl glucosinolates. Indol glucosinolates were less variable and their heritability values point to a lower proportion of genetic variability. Fig. 6 shows how the determination coefficients depended on the variability of examined glucosinolates. In case of very low glucosinolate contents and low variability the coefficients decrease very quickly.

112 Krzysztof Michalski Table 7. Statistical parameters from variance analyses for glucosinolates contents in seeds from field trial estimated with two methods Parametry statystyczne otrzymane z analizy wariancji dla zawartości glukozynolanów w nasionach z doświadczenia polowego estymowane dwoma metodami Component Komponent Method Metoda s. ob F p h 2 Stand.dev. of analyze Gluconapin A B 1.065 0.966 49.094 15.980 5.38E -34 3.99E -20 0.9796 0.9374 0.3039 0.4833 Glucobrassicanapin A B 0.365 0.210 48.525 11.450 3.21E -35 3.85E -16 0.9794 0.9127 0.1048 0.1244 Progoitrin A B 2.372 2.447 56.977 15.083 1.48E -37 2.06E -19 0.9824 0.9337 0.6284 1.2600 Napoleiferin A B 0.061 0.020 20.953 10.178 1.38E -23 8.10E -15 0.9523 0.9017 0.0265 0.0128 Brassicin A B 0.097 0.011 41.364 7.724 6.30E -33 6.45E -12 0.9758 0.8705 0.0303 0.0076 4OHbrassicin A B 0.497 0.403 2.551 7.559 0.00120 1.06E -11 0.6080 0.8677 0.6223 0.2929 Glucosinolate total A B 3.863 3.851 35.715 14.843 7.57E -31 3.25E -19 0.9720 0.9326 1.2928 1.9990 Alkenyl glucosinolate total A B 3.516 3.704 41.493 15.118 5.69E -33 1.94E -19 0.9759 0.9339 1.0917 1.9053 Indolyl glucosinolate total A 0.550 3.031 0.00015 0.6700 0.6318 B 0.403 7.188 3.29E -11 0.8609 0.3009 A results of chemical analyses wyniki analizy referencyjnej B results for NIRS measurements with GLOBAL calibration wyniki estymacji metodą NIRS kalibracja GLOBAL Fig. 6. Results of comparisons of NIRS GLOBAL measurements with results of chemical analyses for individual glucosinolates and their totals (y = values of determination coefficients (R 2 ), x = the standard deviations for the object means (s ob ) Rezultat porównania wyników otrzymanych metodą NIRS kalibracja GLOBAL z wynikami referencyjnymi dla poszczególnych glukozynolanów oraz ich sum (y = wartości współczynników determinacji (R 2 ), x = odchylenia standardowe dla średnich obiektowych (s ob )

The possibility of the use of NIR spectrometer 113 Errors of estimations for contents of individual glucosinolates or for their totals were similar for chemical analyses and for NIRS estimations with GLOBAL calibrations. Conclusions 1. The results obtained by GLOBAL method for the content of both the total and individual glucosinolates were more in line with the results of the chemical analyses than results obtained with LOCAL method. GLOBAL method can be used with some limitations in oilseed rape breeding obtaining varieties with extremely low glucosinolate content LOCAL method is not suitable in this case. 2. Glucosinolate content in seeds of double low rapeseed according to Polish standard is so low (from below 0.6% for total of glucosinolate to below 0.01% for some individual glucosinolates) that when LOCAL method is searching for calibration set from the database, the spectra of the major seed components dominate the spectra of glucosinolate. It is probably the reason that LOCAL method is not suitable in the case of breeding oilseed rape for extremely low glucosinolate content in seed (much below Polish standard for double low quality). 3. NIRS method with GLOBAL calibration allowed getting the results with sufficient compliance to chemical analysis for the following components: the total of the glucosinolates, the total of the alkenyl glucosinolates, progoitrin and gluconapin. 4. Probably selection algorithm for calibration set in LOCAL method prefers spectra of major components (like protein, fat, fibre, polyphenols) and relatively less variable glucosinolate spectra are neglected in selection process. LOCAL calibration equations are much less representative and correct than equations obtained by GLOBAL method. Acknowledgments Authors wish to thank MSC Teresa Piętka and Dr Sc Stanislaw Spasibionek for sharing seeds from the field trial.

114 Krzysztof Michalski References Allard R.W. 1968. Principles of Plant Breeding Wiley & Sons London. Podstawy hodowli roślin. PWRiL Warszawa. Biston R., Dardenne P., Cwikowski M., Marlier M., Severin M., Wathelet J-P. 1988. Fast Analysis of Rapeseed Glucosinolates by Near Infrared Reflectance Spectroscopy. JAOCS, 65 (10): 1599-1600. Burns D.A., Ciurczak E.W. 2007. Handbook of Near-Infrared Analysis, Third Edition, CRC Press. Byczyńska B., Krzymański J. 1981. Materiały hodowlane rzepaku ozimego o zmienionym składzie glikozynolanów. Biuletyn IHAR, 146: 63-69. Byczyńska B., Krzymański J., Wiązecka K. 1970. Zawartość izotiocyjanianów i oksazolidyntionów w nasionach rzepaku ozimego w czasie ich formowania i dojrzewania. Hodowla Roślin, Aklimatyzacja i Nasiennictwo, 14/6: 547-551. Canola Council of Canada, http://www.canolacouncil.org/oil-and-meal/what-is-canola/(accessed 05.12. 2012). Canola Council of Canada http://www.canolacouncil.org/oil-and-meal/what-is-canola/the-history-ofcanola/ (accessed 05.12.2012a) Daun J.K., Clear K.M., Williams P. 1994. Comparison of Three Whole Seed Near-Infrared Analyzers for Measuring Quality Components of Canola Seed. JAOCS, 71 (10): 1063-1068. Davis J.B., Hall M.H., Eckert J.W., Corsini J.A., Auld D.L. 1991. Comparison of near-infrared reflectance analyzes with GC analyzes of glucosinolate concentration in rapeseed. EUCARPIA Cruciferae Newsletter, 14-15: 120-121. European Food Safety Autority. 2008. Glucosinolates as undesirable substances in animal feed, Scientific Panel on Contaminants in the Food Chain (Question N EFSA-Q-2003-061), Adopted on 27 November 2007. The EFSA Journal, 590: 1-76. Font R., Del Río M., Fernández J.M., De Haro-Bailón A. 2004. Use of near-infrared spectroscopy for screening the individual and total glucosinolate contents in Indian Mustard seed (Brassica juncea L. Czern. & Coss.). J. Agric. Food Chem., 52: 3563 3569. Hom N.H., Becker H.C., Möllers C. 2007. Non-destructive analysis of rapeseed quality by NIRS of small seed samples and single seeds. Euphytica, 153: 27-34. ISO Norm 9167-1, 1992. Rapeseed: Determination of Glucosinolate Content. Part 1: Method Using High-performance Liquid Chromatography. Krzymański J. 1970. Genetyczne możliwości ulepszania składu chemicznego nasion rzepaku ozimego (Possibilities of chemical composition improvement of winter rapeseed on genetic way). Hodowla Roślin Aklim. Nas., 14/2: 95-133. Krzymański J. 1970. Inheritance of thioglucoside content by rapeseed (Brassica napus) Proc. Journess Internationales sur le Colza, Paris, 26-30.05.1970, p. 212-218. Krzymański J. 1968. Variation in thioglucosides in rapeseed meal (Brassica napus). Meeting of Associate Committees of the National Research Council on Plant Breeding. Canada, Winnipeg 20.02.1968. Krzymanski J., Pietka T., Michalski K., Krotka K. 1999. Study on winter oilseed rape (Brassica napus L.) very low in aliphatic glucosinolate content. Proceedings of 10th International Rapeseed Congress Canberra, Australia, 26-29.9.1999. http://gcirc.org/fileadmin/documents/bulletins/b16/b16% 2017 Krzym64-71.pdf.

The possibility of the use of NIR spectrometer 115 Kumar S., Chauhan J.S., Kumar A. 2010. Screening for erucid acid and glucosinolate content in rapeseed-mustard seeds using near infrared reflectance spectroscopy. J. Food Sci. Technol. Dec., 47 (6): 690-692. Mahalanobis, Prasanta Chandra 1936. On the generalized distance in statistics. Proceedings of the National Institute of Sciences of India, 2 (1): 49-55. Retrieved 2012-05-03. Martens H., Naes T. 1989. Multivariate calibration. John Wiley & Sons, New York, USA. Martens H., Naes T. 1990. Multivariate calibration. John Willey and Sons New York, USA. Martens H., Naes T. 1991. Multivariate calibration. John Willey and Sons New York, USA. Michalski K., Kołodziej K. 2000. Application of NIR spectrometry for analysis of basic chemical constituents of rapeseed seeds. Rośliny Oleiste Oilseed Crops, XXI (3): 801-806. Michalski K., Krzymański J., Byczyńska B. 1987. Determination of glucosinolate in intact seeds of winter rape (B. napus) by near infrared reflectance method Proceedings of 7 th International Rapeseed Congress, 1541-1546. Michalski K., Kolodziej K. Measurement of glucosinolate content in intact seeds of rapeseed with NIR reflectance spectrometry: http://gcirc.org/fileadmin/documents/bulletins/b18/ B18%2036 Poster.pdf. Michalski K., Kołodziej K., Krzymański J. 1995. Quantitative analysis of glucosinolates in seeds of oilseed rape effect of sample preparation on analitycal results. Proc. 9 th International Rapeseed Congress, Cambridge, UK, 4-7 VII, 3: 911-913. Montes J.M., Paul C., Melchinger A.E. 2007. Quality assessment of rapeseed accessions by means of near-infrared spectroscopy on combine harvesters. Plant Breeding, 126: 329-330. Patent US 5798526. A Method of analyzing an unknown material 25-08-1988. Petisco C., García-Criado B., Vázquez-de-Aldana B.R., de Haro A., García-Ciudad A. 2010. Measurement of quality parameters in intact seeds of Brassica species using visible and nearinfrared spectroscopy. Industrial Crops and Products, 32: 139-146. Piętka T., Krótka K., Krzymański J. 2001. Badania nad zdolnością kombinacyjną w odniesieniu do zawartości glukozynolanów w pokoleniach F 1 i F 2 mieszańców liniowo-odmianowych rzepaku ozimego (Brassica napus L.). (Study on combining ability in respect of glucosinolate content in F 1 and F 2 generations of winter rape hybrid (Brassica napus L.)). Rośliny Oleiste Oilseed Crops, 22/2: 303-314. Piętka T., Krótka K., Krzymański J. 2002. Study on general combining ability in F 1 and F 2 generations of winter oilseed rape hybrid in respect of glucosinolates content. (Badanie ogólnej zdolności kombinacyjnej w pokoleniach F1 i F2 mieszańców rzepaku ozimego w odniesieniu do zawartości glukozynolanów). Bulletin GCIRC, http://195.101.21/publications/b18. Piętka T., Krótka K., Krzymański J. 2003. Ogólna zdolność kombinacyjna i odziedziczalność zawartości glukozynolanów w nasionach rzepaku ozimego (General combinig ability and heritability of glucosinolate contents of winter oilseed rape (Brassica napus L.) seeds). Biuletyn IHAR, 226/227/2: 405-414. Piętka T., Krótka K., Krzymański J. 2005. Zdolność kombinacyjna i heterozja zawartości glukozynolanów w nasionach rzepaku ozimego z pokoleń F 1 i F 2, oznaczone metodą krzyżowań diallelicznych pomiędzy liniami podwojonych haploidów (Combining ability and heterosis in glucosinolate content in seeds of winter rapeseed (Brassica napus L.) estimated with diallel crossings between doubled haploid lines). Rośliny Oleiste Oilseed Crops, XXVI/2: 311-324. Piętka T., Krótka K., Krzymański J., Cegielska-Taras T. 2007. Heritability, combinig ability and heterosis in glucosinolate content in seed of winter rape (Brassica napus L.) estimated with diallel crosing between double haploid lines in Sustainable Development in Cruciferous Oilseed

116 Krzysztof Michalski Crops Production. Proc. 12 th International Rapeseed Congress, Wuhan, China, 26-30.03.2007, 1: 73-76. Polska Norma: PN-90/R-66151 Rośliny przemysłowe oleiste. Ziarno rzepaku i rzepiku podwójnie ulepszonego (Industrial plants: double low oilseed rape and turnip rape). Polska Norma: PN-EN ISO 9167-1:1999. Nasiona rzepaku Oznaczanie zawartości glukozynolanów Metoda z zastosowaniem wysokociśnieniowej chromatografii cieczowej (Rapeseed: Method of determination of glucosinolate content using high-performance liquid chromatography). Quinsac A., Ribaillier D. 1985. Quantitative analysis of glucosinolates in rapeseed seeds. Optimization of desulphatation. In: Advances in the Production and Utilization of Cruciferous with Special Emphasis to Oilseed Rape. World crops: Production, Utilization, Description. H. Sorensen (Ed.). Kluwer Academic Publishers, Dordrecht, 11: 85-96. Rakowska M., Twarkowska J., Byczyńska B., Neuman M., Krzymański J. 1979. Effect of glucosinolate content in the seeds of cultivars on the growth, protein efficiency ratio and reproduction of rats. Biuletyn IHAR. EUCARPIA Fodder Crops Section Meeting, 1/55: 334-349. Rakowska M., Twarkowska J., Słomiński B., Neuman M., Krzymański J. 1984. Próba oceny żywieniowej nowych rodów rzepaku o obniżonej zawartości glikozynolanów we wczesnych stadiach selekcji hodowlanej (Nutritional assessment test of new oilseed rape strains with reduced content of glucosinolate in the early stages of the breeding selection). Hodowla Roślin Aklimatyzacja i Nasiennictwo 28/2: 181-193. Rakowska M., Twarkowska J., Szkiłłądź W., Neumann M., Krzymański J. 1981. Porównanie współczynników wydajności wzrostowej białka (PER) śruty z nowych form hodowlanych rzepaku ozimego o obniżonej zawartości glukozynolanów (Comparison of protein eficiency ratios (PER) of meals from new forms oilseed rape with low glucosinolate content). Hodowla Roślin, Aklimatyzacja i Nasiennictwo, 25, 3/4: 163-181. Raney J.P., McGregor D.I. 1990. Determination of glucosinolate content by gas liquid chromatography of trimethylsilyl derivatives of desulfated glucosinolates. Proceedings of the Oil Crops Network, Shanghai, China, April 21-23. Renard M., Bernard C., Deschamps M., Furtoss V., Lila M., Quinsac A., Regnier J.M., Riballier D. 1987. Glucosinolate analysis in whole rapeseed by near infrared reflectance spectroscopy Glucosinolates. In: Rapeseeds: Analytical aspects. Ed. J.P. Wathelet-Martinus Nijhof, 173-176. Shenk J.S., Westerhaus M.O. 1997. Investigation of a LOCAL calibration procedure for near infrared instruments. Journal of Near Infrared Spectroscopy, 5: 223-232. Shenk J.S., Westerhaus M.O. 1996. Calibration the ISI way. In: Near Infrared Spectroscopy: The Future Waves. A.M.C. Davies & P.C. Williams (Eds.). NIR Publications, Chichester, 198-202. Spasibionek S., Piętka T., Krótka K., Krzymański J. 2016. Możliwości dalszego obniżania zawartości glukozynolanów w nasionach rzepaku podwójnie ulepszonego (Brassica napus L.). (The possibilities for further reducing the glucosinolate contents in seeds of double low rapeseed (Brassica napus L.)). Rośliny Oleiste Oilseed Crops, 36: 21-36. Starr C., Suttle J., Morgan A.G., Smith D.B. 1985. A comparison of sample preparation and calibration techniques for the estimation of nitrogen, oil and glucosinolate content of rapeseed by near infrared spectroscopy. The Journal of Agricultural Science, 104/2: 317-323. Velasco L., Becker H.C. 1998. Analysis of total glucosinolate content and individual glucosinolates in Brassica spp. by near-infrared reflectance spectroscopy. Plant Breeding, 117: 97-102. Velasco L., Mollers C. 1999. Analysis of individual glucosinolates in Brassica spp by Near Infrared Reflectance Spectroscopy. Proceedings of 10th International Rapeseed Congress, Canberra, Australia, 26-29.9.1999.

The possibility of the use of NIR spectrometer 117 Velasco L., Mollers C., Becker H. 1999a. Screening for quality traits in single seeds of rapeseed by near infrared reflectance spectroscopy. Proceedings of 10th International Rapeseed Congress, Canberra, Australia, 26-29.9.1999. Welle R., Zähle K., Hildebrand C., Kräling K., Greten W. 2007. Application of near infrared spectroscopy on-combine for canola breeding. J. Near Infrared Spectrosc., 15: 317-325. 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: Near Infrared Spectroscopy: The Future Waves. A.M.C. Davies & P.C. Williams (Eds). NIR Publications, Chichester. 185-188. WinISI 4 Calibration development software www.winisi.com/product_winisi4.htm.