Contribution to technological nutritional and toxicological characterization of two varieties of rice grown in Portugal: amylose, amino acids and arsenic

Contribution to technological nutritional and toxicological characterization of two varieties of rice grown in Portugal: amylose, amino acids and arsenic Contribuição para a caracterização tecnológica, nutricional e toxicológica de duas espécies de arroz cultivado em Portugal: amilose, aminoácidos e arsénio Ana Margarida Cabral de Pinho Orientada por: Professor Doutor Duarte Torres Co-orientada por: Mestre Carla Mota Trabalho de investigação 1.º Ciclo em Ciências da Nutrição Faculdade de Ciências da Nutrição e Alimentação da Universidade do Porto Porto, 2012 i Acknowledgments I am grateful to all members of the Chemistry Laboratory on INSA, for all the support but especially to Dr. Carla Mota, for helping me in my practical and theoretical work and also to Dr. Isabel Castanheira for all the clues and suggestions. I would also like to thanks Prof. Dr. Duarte Torres for discussion time availability and orientation. Another acknowledgment goes to Dr. Inês Coelho and Dr. Sandra Gueifão, who kindly provide me the arsenic data for this work. ii Índice Acknowledgments ............................................................................................... i Abbreviations and symbols ................................................................................. iii Abstract .............................................................................................................. v Resumo ............................................................................................................. vi Keywords ........................................................................................................... vii Palavras-chave .................................................................................................. vii Introduction ......................................................................................................... 1 Objectives ........................................................................................................... 3 Material and methods ......................................................................................... 3 Sample collection and preparation ...................................................................... 3 Reagents, standards and analytical procedures ................................................. 4 Statistical analysis and modes of expressions of results .................................... 7 Results................................................................................................................ 7 Discussion .......................................................................................................... 9 Conclusions ...................................................................................................... 14 References ....................................................................................................... 16 Appendix Index ................................................................................................. 21 iii Abbreviations and symbols Abbreviations AA Amino Acid AC Amylose Content AAS Amino Acid Scores Ala Alanine AOAC American Organization of Analytical Chemists Arg Arginine AAA Aromatic Amino Acid Asp Aspartic acid BCAA Branched Chain Amino Acid Con A Concanavalin A CV Coefficient of Variation DAD Photodiode Array Detector dw dry weight EAA Essential Amino Acid ex. Example FAO Food and Agriculture Organization Glu Glutamic acid Gly Glycine His Histidine ICP/MS Inductively coupled plasma mass spectrometry Ile Isoleucine iv Leu Leucine LOD Limits of Detection LOQ Limits of Quantification Lys Lysine NEAA Non-Essential Amino Acids OECD Organisation for Economic Cooperation and Development PDCAAS Protein Digestibility Corrected Amino Acid Score Pro Proline PTFE polytetrafluoroethylene Ser Serine SAA Sulfuric Amino Acid Thr Threonine TP Total Protein USDA United States Department Of Agriculture UPLC Ultra performance Liquid Chromatography Val Valine WHO World Health Organization Symbols As Arsenic R 2: Correlation Coefficient v Abstract Recent data shows that Portugal has a rice consume of 15.8 kg/capita/year, the largest in Europe. Due to this importance in Portuguese diet, the present work aims to contribute to its technological characterization, through amylose content (AC) quantification; nutritional characterization, namely, total protein (TP) and amino acid (AA) quantification; and toxicological characterization through arsenic (As) quantification. Another goal of this work is to study the compositional differences between rice varieties, year and place of harvest. A modified Concanavalin A (Con A) was used to quantify the amylose content, the Kjeldahl method to estimate the TP, the Ultra Performance Liquid Chromatography (UPLC) the AA and the Inductively coupled plasma mass spectrometry (ICP/MS) the arsenic content. Analyzed rice showed high AC (31.4%). With respect to protein quality, lysine (Lys) was considered the rice limiting AA, with protein digestibility corrected amino acid scores (PDCAAS) lower than 1. As mean level was 0.31 mg/kg and range from 0.13 to 0.70 mg/kg, which although is below than 1 mg/kg, the assumed safe level for food, it is considered a high level. In this study, a very weak correlation between As levels and AA content was demonstrated. Apart from the AA, only AC differed significantly depending on rice variety. Crop place showed to be the major source of variation in AA content. vi Resumo Dados recentes mostram que Portugal teve um consumo de arroz de 15,8 kg/capita/ano, o maior da Europa. Devido a esta importância do arroz na dieta portuguesa, o presente trabalho pretende ser um contributo para a sua caracterização tecnologia, através da determinação do conteúdo em amilose; caracterização nutricional, usando a Proteína Total (PT) e a quantificação em Aminoácidos (AA); e caracterização toxicológica, através da quantificação de arsénio. Paralelamente, outro objetivo foi verificar se existem diferenças significativas dentro da variedade de arroz, ano e local de colheita para os componentes analisados. A amilose, PT, AA e arsénio foram quantificados através de um método baseado numa concavalina A modificada, método de Kjeldahl, cromatografia líquida de ultra performance e espectrometria de massa acoplado a plasma indutivo, respectivamente. O arroz analisado tinha um alto conteúdo em amilose (31,4%). A Lys foi considerada o AA limitante no arroz, por terem um Score de Aminoácidos Corrigido pela Digestibilidade Proteica (SAACDP) inferior a 1. O valor médio obtido para o Arsénio foi de 0,31 mg / kg e varia de 0,13 a 0,70 mg / kg, que, embora seja inferior ao nível estabelecido como seguro para alimentos, é considerado um nível elevado. Há uma correlação muito fraca entre os níveis de arsénio e conteúdo AA. Excluindo os Aminoácidos, o conteúdo em amilose foi o único a diferir significativamente entre a variedade de arroz. O local de colheita mostrou ser a variável que mais influencia o teor de AA do arroz. vii Keywords Portuguese rice; amylose content; essential amino acids, protein quality, arsenic, Palavras-chave Arroz português; conteúdo em amilose; aminoácidos essenciais, qualidade proteica, arsénio 6 The LOD and LOQ will be acceptable if: 10 x LOD - LOQ have a positive value. Linearity was calculated by the equipment according to the formula: h g =i+hk+ilmimℎom Arsenic For hydrolysis by microwave, 0.5000 g of samples were weighed in a polytetrafluoroethylene (PTFE) vessel. At least one of them should be the blank (vessel with all reagents but without sample) and the other should be the SRM (FAPAS 07134 – rice). Then, 4 ml HNO 3, 3 ml H 2 O e 1 ml H 2 O 2 were added into the cup rotor microwave and the vessels were put inside. The rotor was placed in the microwave, and the specific program was selected [(10 min, 180 ºC, 850 W); (5 min, 180 ºC, 0 W); (6 min, 210 ºC, 1100 W); (5 min, 210 ºC, 0 W); (6 min, 90 ºC, 650 W)]. Next, samples were transferred to 50 ml flasks and filled with ultrapure water. Analysis by ICP-MS To correct isobaric interferences the 75 As isotope was selected and then the following correction equations were applied in the software itself and according to matrix studied interferences: 75 As= 75 M-3.13220* 77 ArCl and 77 ArCl= 77 M0.826* 82 Se. The working range for rice is 0.25 - 50 µg/L and the calibration curve was made according to Table 1 (Appendix 3). A dilute solution of 500 µg/L was daily prepared from commercial standard solutions. From this solution dilutions were made in a volumetric flask or using micropipettes, according to Table 2 (Appendix 3). The samples (such as patterns) were placed in an autosampler in disposable tubes 10-50 mL. For each tube, two readings were made and then the mean value was accepted. 7 Statistical analysis and modes of expressions of results All samples were analyzed in duplicate. Moisture was expressed in g/100 g and AC and TP in % of dw (mean ± standard deviation). The amount of each AA was expressed as mg/g of rice (mean ± standard deviation). As content (mean ± standard deviation) was expressed in mg/kg of dw. Normal distribution was previously check using One-Sample Shapiro Wilk Test. Differences between groups were determined using hypothesis tests, namely, the Independent Samples Mann-Whitney U Test for variety and crop place and the Independent Samples Kruskal-Wallis Test for year crop, both at the probability level α=0.05. The correlation between As and AA content was assessed using the Pearson’s Correlation Coefficient. Data analysis was performed using Microsoft Excel 2010 and Statistical Package for Social Sciences 15.0 software for Windows. Results Amylose The mean AC in analyzed rice was 31.4 ± 7.1 %. (Table 2, Appendix 1). AC mean values were higher in Indica rice samples (36.4 ± 6.6), 2009 crop samples (36.8 ± 7.2) and Ribatejo crop samples (33.6% ± 6.8%). Significant difference in AC between rice varieties was found. Total proteins TP content was 7.1 ± 1.0% (Table 2, Appendix 1). Between varieties the highest value belongs to Indica with 7.7 ± 1.2%. Among crop year both 2009 and 2011 had 7.8% and Sado crop had the greatest value of 8.2 ± 0.8%. Nevertheless, no significant differences were found between varieties, regions or crop year. 8 Amino acids The EAA and NEAA detected by UPLC are presented in Table 3 and 4 (Appendix 1), respectively, in mg/g dw and are presented in this section as % of TP dw. Analysed samples Non-Essential Amino Acids (NEAA) represents 65.5 ± 8.9% of TP while EAA contributes to 37.1 ± 4.5%. Regarding EAA, Aromatic AA (AAA) were the ones found in larger amount (11.32 ± 1.80 % of rice´s TP) followed by the Branched Chain AA (BCAA), Leucine (Leu), Valine (Val) and Isoleucine (Ile) with mean percentages 7.58 ± 0.95 %, 4.51 ± 0.60 % and 3.29 ± 0.46 %, respectively. Histidine (His) represents 2.78 ± 0.53 % and Threonine (Thr), 2.71 ± 0.37 %. Lower values were calculated for Sulfuric AA (SAA), 2.32 ± 0.30 %, and Lysine (Lys), 2.56 ± 0.67%. His, Lys, AAA, TEAA, Arg, Gly and Pro content was significantly different between varieties and crop year. Between crop regions, only Try, Val, Asp and Ala were not significantly different. With respect to PDCAAS, Lys was found to limit the nutritional quality of rice protein. (Table 5, Appendix 1). Data obtained a CV was lower than 8.5% for all AA, except Lys (the most limiting AA) with higher CV (~ 18%). Regarding methods parameters, all z-score values fall into -2 and 2, except Asp (2.2). LOD, ranged from 0.04 (Pro and Val) to 0.21 mg/g protein (Lys and Tyr), while the LOQ ranged from 0.12 (Val) to 0.74 mg/g protein (Lys). LOD and LOQ were in acceptable range. As shown in Table 6 (Appendix 1), the coefficient of correlation (R 2 ) for these amino acids was from 0.9932 (Cys) to 0.9997 (Ile and Try). 9 Arsenic Rice sample 2, 6, 8 and 9 were not available for As quantification. Analyzed samples showed mean As levels of 0.31 ± 0.20 mg/kg, ranging from 0.13 to 0.70 mg/kg (Table 2, Appendix 1). No significant differences were confirmed between varieties, regions or crop year. Pearson correlation test shows a 0.024 correlation between As and TAA content (Table 7, Appendix 1). Higher Pearson correlation belong to AAA (-0.204) and minimum value to Ser (0.015). Discussion Amylose In the current study a significant higher AC in Indica variety (36.3%) was shown (p < 0.05). That should result in more firm and separated grains when cooked, than the Japonica variety with AC close to 28.6%. This data is in agreement with the bibliography indicating that amylose/amylopectin ratio content of the grain is influenced by the rice variety. (16) AC is a key determinant for cooking, processing and eating quality. According to International Rice Research Institute (IRRI), the AC defines two kinds of rice: “waxy” or “nonwaxy” rice. (36, 37) The first one has an AC that does not exceed 2% and is used mainly in candy, children's food and cereals. Nonwaxy rice may be classified, in terms of AC (%) as low (10-20%), intermediate (20-25%) and high (>25%) and is used according to textural and pasting properties for cooking. (15) According to this definition, both analyzed Indica and Japonica varieties had high AC. Juliano (1993) analyzed 31 samples of Portuguese rice and concluded that its AC range varies from low to intermediate (19-21%). (17) The same study also refers that preferred AC type in Portugal was the low one. Literature also showed that, worldwide, Indica variety range from 10 intermediate to high and Japonica from low to intermediate AC and preferences varies locally. (38) The rice starch has some special features such as small grains and wide size range of AC, which allows multiple industrial applications. (39) As culinary methods and consequently their commercial value depends on rice´s AC, its measurement is an important quality parameter for starch processing. Total protein In the analyzed rice samples TP content was 7.14% (ranging from 5.93 to 9.97%). These values are close to the previous cited study conducted by Juliano (1993), where TP content of Portuguese rice was 6.8%, ranging between 5 and 8%. (17) This author also analyzed a total 233 samples of milled rice from Europe and their protein mean value was 8.0% (5.7-14.8%). Samples analyzed in the current study also showed similar TP values when compared to the one reported by the Organisation for Economic Cooperation and Development (OECD) report (6.3 – 7.1 %). (40) No significant differences in TP content were found between varieties, regions or crop year. Protein is the major functional and structural component of all cells in the body. Thus an adequate supply of dietary protein is essential to maintain cellular integrity and function, and for health and reproduction. (35, 41) Average requirement for protein in healthy adults is set in 0.66 g/kg. (35) Thus, for a 70 kg person, about 46 g of protein is required. A 100 g dose of rice covers 4.5% (2.2 g) of protein needs, accounting with 88% of its proteins digestibility. Amino acids AA content From all analysed AA, Glu was in higer concentration in all samples, which is 11 in agreement with the literature, as well as the verified biggest proportion of NEAA compared to EAA. (19, 40, 42) In this study, the amount and proportion of AA in rice´s protein were generally quite similar to the ones found in the literature. (40, 43) Many studies have demonstrated that different rice varieties may have very different nutrient contents, including TP and AA. (2, 44) In agreement with that, AA content of His, Lys, AAA, TEAA, Arg, Gly and Pro was significantly different between the analyzed rice varieties. However, crop local showed to be the major source for differences in AA content. No studies were found with updated information concerning the influence of crop year and crop region on AA content. CV shows us the data variability from the average. Thus, the smaller the CV is, the more homogeneous the data gets. Data obtained a low CV (<25%), which indicates a data set reasonably homogeneous. In order to estimate rice protein quality, the relative content of 17 AA were calculated by UPLC, which permits a very high-resolution separations performance in a short period of time with little organic solvent consumption. (45) Up to date, this accurate methodology has never been use for estimate AA in milled rice. The present study includes some parameters to test the UPLC reliability. Z-score correspond to the difference between the values obtained and the SD of the CRM. According to obtained data, Z-score values were excellent, except for Asp. LOD is the minimum analyte concentration that can be detected by the UPLC while the LOQ the lowest concentration of analyte that can be determined with a reasonable degree of precision and accuracy. This LOQ correspond to the lower concentration of the calibration standard, thus the first point of the curve. Assessed LOD and LOQ were in acceptable range. The linear range of the system 12 was excellent, showing a direct proportionality of the detector signal vs solute concentration. These results demonstrated that the detection conditions were feasible and could be applied to a quantitative analysis of amino acids. PDCAAS The most limiting AA are: Lys, Ile and SAA. These AA have health implications. For example, deficiency of Lys in a rice based diet may lead to defective bone development, anemia, and body weight loss. (46) Similar to other cereals, rice samples proteins have Lys as the most cited limiting AA. (1, 19, 40, 47) Even so, the highest concentrations of Lys and SAA than in others cereals grains contributes to rice´s higher complete balance of AA among other cereals, such as wheat or corn. (40) I le is also important for hemoglobin formation and help in maintaining normal blood glucose level and SAA has its main importance contributing to control of oxidative status. (48, 49) AA requirement per day in the human body are well demonstrated, as well as their importance and role for human nutrition, especially EAA as they act as precursors of many coenzymes, hormones, nucleic acids, and other molecules essential for life and consequently their deficiency disturbs nitrogen equilibrium, growth, nutrition, fertility, and life span. (40, 41, 50, 51) The PDCAAS estimate if the effectiveness that dietary absorbed nitrogen is capable of meet the indispensable AA requirement at the safe level of protein intake. (35) Thus the PDCAAS may predict the biological value of proteins, because besides being dependent on the AA balance, by life stages, it also accounts with food protein´s true digestibility. (35) Generally, a diet based on a single staple food plant, like rice, do not ensure an optimal growth because the diet does not provide enough of the limiting AA, essential substrates for protein synthesis. That’s why rice doesn’t contain high 13 biological value proteins. The nutritional quality of rice protein can be increased when combined, for example, with pulse’s proteins, that have different but complementary limiting AA (limiting in Met but rich in Lys). (35) This kind of complementary information is not always in food compositions database because not enough information is available on AA content. The Eurofir and the United States Department of Agriculture (USDA) food composition databases show there is little information about starch and AA content on rice. But despite being more aware about the EAA question, many people and even nutritionists and dietitian intuitively do not have the protein digestibility in consideration. This kind of information would be enriching if extended to all food databases, especially when food protein digestibility and EAA are concerned because, in some pathological status, like severe disease states, catabolic or infectious status or even in liver disease, the plenitude of each AA and TP intake may be difficult to achieve. (41, 51) Although there is the need to compile more documentation on nutritional properties, many studies have demonstrated that different cultivars of the same species may have different nutrient contents, so, this data would also be important to be included on food databases, resulting in better streamlined recommendations. (19) Arsenic Arsenic content Analyzed samples shows 0.31 mg/kg dw mean values, ranging from 0.13 to 0.70 mg/kg (Table 2, Appendix 1). These values fit on Willian et al. (2007) study that report an As concentration range from 0.01 to 0.82 mg/kg in market samples of rice grains. (52) However, results are the double than the ones reported by Rahman (2011) for European rice (0.15 mg/kg, ranging from 0.13 to 0.20 14 mg/kg) (26) and also exceeds the Zavala and Duxbury (2008) worldwide ‘‘normal’’ range (0.08–0.20 mg/kg). (53) At the moment, there is no EU regulations upon As levels in foods. (54) However, 1 mg/kg is often cited in the literature as being a safe level for As in foods. (55, 56) The studied rice samples have lower values, so they may be considered safe. Still, we can be worried about the sample with the highest As value (0.70 mg/kg dw), probably, due to As accumulation in irrigated soils. (57) As is naturally the 12 th most abundant element in the human body but, besides being so present in human body, pollution associated with this toxic element may represents a serious threat to human health .(28), (58), (59, 60) It is well recognized that consumption of As, even at low levels, leads to carcinogenesis. (61, 62) As continuous intake can also lead to gastrointestinal symptoms, bone marrow depression, hemolysis, hepatomegaly, melanosis, polyneuropathy and encephalopathy severe disturbances of the cardiovascular and central nervous systems, and even death. (21, 41) Arsenic correlation with amino acids In recent studies total AA content in rice was negatively correlated with As accumulation. There are strong suspicious about increasing grain As accumulation results in modification and degradation of protein, subsequently leading to inhibition of AA synthesis. (29) However, in the present study, Pearson´s correlation between As and AA showed, in mean, a very weak and non-significant correlation. Conclusions This study demonstrated that Indica variety had significantly higher AC than Japonica. This kind information is useful because AC determines rice suitability for particular end-uses. This is an important information to small and big-scale 15 catering services, where small details, like knowing the optimal water-rice ratio for each kind of amylose content is relevant. (17) Despite the increasing globalization of food, local ingredients will still be kept in all countries. In this regard, each country should have in the food composition table the most current and complete data as possible. Thus, the present study can be considered as a contribution to the Portuguese Food Composition DataBase (PFCDB), in the way that neither the amylose nor AA are included on this food database. With this supplementary information, nutritionists, dietists and other health professionals will be capable to guide their patients in a more reliable way and be sure that, for ex., their intake in EAA are the necessary. Besides, I believe that, with a solid nutrition background and complete food composition databases, national guidelines gets easier to establish. Worldwide the good management of this information might also be assumed as a challenge of reduce malnutrition, especially when EAA are concerned. Rice is considered one of the few foods without relevant antinutritional substances, which result in higher digestibility, biological value and protein efficiency rate. (63) Those characteristics makes it a good source of wellbalanced AA and provides hypoallergenic proteins, which provides an opportunity for industry to create specific products, based on this cereal, for celiac people and children. (64) However, besides its nutrition importance, rice may be a dangerous exposure to arsenic, especially for children. (64) Analyzed rice show potential high As levels contribution to the diet. So, for these reasons, As in specific foods and food products made with this cereal must be monitored. 1 Appendix A - Tables Table 2 Rice nutritional information (Values are presented as Mean ± standard deviation) Moisture * Amylose ** Total Protein ** Arsenic *** Indica 13.25 ± 0.46 a 36.38 ± 6.57 a 7.67 ± 1.22 a 0.29 ± 0.15 a Japonica 12.79 ± 0.49 a 28.57 ± 4.49 b 7.29 ± 0.56 a 0.19 ± 0.23 a 2009 13.32 ± 0.42 a 36.79 ± 7.17 a 7.77 ± 1.32 a 0.30 ± 0.16 a 2010 12.90 ± 0.54 a 30.53 ± 3.13 a 7.08 ± 0.46 a 0.18 ± 0.25 a 2011 12.63 ± 0.32 a 27.97 ± 6.81 a 7.75 ± 0.32 a 0.26 ± 0.06 a Ribatejo 13.11 ± 0.32 a 33.57 ± 6.81 a 7.14 ± 0.32 a 0.19 ± 0.06 a Sado 12.96 ± 0.42 a 32.27 ± 6.88 a 8.16 ± 0.84 a 0.34 ± 0.16 a Total mean 12.40 ± 0.54 31.44 ± 7.14 7.14 ± 1.04 0.31 ± 0.20 Min 11.80 18.36 5.93 0.13 Máx 13.96 52.93 9.97 0.70 * g/100g; ** %dw; *** mg kg-1 dw Values followed by the same letter for the same variable are not significant different (p<0.05) Table 1 Rice samples characterization Variety Crop place Crop year Number (n) Indica Ribatejo 2009 6 Ribatejo 2010 1 Sado 2009 3 Sado 2011 1 Japonica Ribatejo 2010 5 Sado 2010 1 Sado 2011 2 2 Table 3 Essential amino acid concentration (mg/g) comparision between diferente varieties, crop year and place (average ± standard deviation) n His ILe Leu Lys SAA AAA Thr Val TOTAL EAA Indca 11 2.04 ± 0.07 a 2.36 ± 0.11 a 5.42 ± 0.17 a 1.89 ± 0.28 a 1.59 ± 0.10 a 8.12 ± 0.54 a 1.91 ± 0.10 a 3.20 ± 0.18 a 26.53 ± 1.65 a Japonica 4 1.54 ± 0.24 b 2.03 ± 0.18 a 4.65 ± 0.14 a 1.42 ± 0.33 b 1.43 ± 0.13 a 6.58 ± 0.48 b 1.69 ± 0.08 a 2.81 ± 0.17 a 22.15 ± 1.49 b 2009 9 2.05 ± 0.07 a 2.40 ± 0.12 a 5.53 ± 0.18 a 1.93 ± 0.30 a 1.59 ± 0.11 a 8.18 ± 0.56 a 1.94 ± 0.10 a 3.26 ± 0.19 a 26.88 ± 1.74 a 2010 7 1.45 ± 0.25 b 1.98 ± 0.16 a 4.50 ± 0.13 a 1.29 ± 0.36 b 1.43 ± 0.10 a 6.29 ± 0.43 b 1.65 ± 0.06 a 2.73 ± 0.13 a 21.33 ± 1.25 b 2011 3 2.04 ± 0.12 c 2.14 ± 0.18 a 5.01 ± 0.19 a 1.95 ± 0.11 c 1.58 ± 0.12 a 7.92 ± 0.44 c 1.78 ± 0.12 a 2.96 ± 0.25 a 25.38 ± 1.65 c Ribatejo 8 1.73 ± 0.07 a 2.04 ± 0.11 a 4.69 ± 0.17 a 1.51 ± 0.31 a 1.44 ± 0.09 a 6.79 ± 0.43 a 1.68 ± 0.09 a 2.81 ± 0.16 a 22.70 ± 1.25 a Sado 7 2.01 ± 0.27 b 2.48 ± 0.19 b 5.71 ± 0.16 b 2.02 ± 0.26 b 1.67 ± 0.13 b 8.56 ± 0.61 a 2.03 ± 0.09 a 3.37 ± 0.21 a 27.86 ± 2.05 b Mean 0 1.84 ± 0.16 2.20 ± 0.15 5.07 ± 0.16 1.72 ± 0.28 1.53 ± 0.11 7.49 ± 0.50 1.81 ± 0.09 3.02 ± 0.19 24.69 ± 1.58 Values followed by the same letter for the same variable are not significant different (p<0.05) 3 Table 4 Non Essential amino acid concentration (mg/g) comparison between from different varieties, crop year and place (average ± standard deviation) n Ser Arg Gly Glu Asp Ala Pro TOTAL NEAA Indca 11 3.39 ± 0.17 a 6.17 ± 0.24 a 3.19 ± 0.12 a 13.20 ± 0.57 a 5.52 ± 0.37 a 3.48 ± 0.14 a 2.92 ± 0.11 a 37.86 ± 1.73 a Japonica 4 2.98 ± 0.14 a 5.22 ± 0.28 b 2.74 ± 0.16 b 11.71 ± 0.39 a 5.19 ± 0.24 a 3.12 ± 0.07 a 2.46 ± 0.06 b 33.42 ± 1.12 a 2009 9 3.46 ± 0.18 a 6.25 ± 0.24 a 3.22 ± 0.12 a 13.56 ± 0.59 a 5.69 ± 0.38 a 3.56 ± 0.15 a 2.96 ± 0.12 a 38.69 ± 1.79 a 2010 7 2.87 ± 0.12 b 5.01 ± 0.25 b 2.66 ± 0.17 a 11.16 ± 0.46 a 5.03 ± 0.24 a 3.03 ± 0.08 a 2.39 ± 0.05 b 32.16 ± 1.11 a 2011 3 3.22 ± 0.14 c 6.00 ± 0.27 c 3.08 ± 0.09 a 12.40 ± 0.32 a 4.98 ± 0.28 a 3.21 ± 0.07 a 2.69 ± 0.06 c 35.58 ± 1.23 a Ribatejo 8 2.96 ± 0.16 a 5.29 ± 0.24 a 2.78 ± 0.15 a 11.52 ± 0.53 a 5.03 ± 0.30 a 3.10 ± 0.11 a 2.51 ± 0.09 a 33.19 ± 1.44 a Sado 7 3.62 ± 0.14 b 6.55 ± 0.26 b 3.36 ± 0.11 b 14.15 ± 0.44 b 5.86 ± 0.34 a 3.67 ± 0.10 a 3.05 ± 0.07 b 40.26 ± 1.47 b Mean 0 3.21 ± 0.15 5.78 ± 0.25 3.00 ± 0.13 12.53 ± 0.47 5.33 ± 0.31 3.31 ± 0.10 2.71 ± 0.08 35.88 ± 1.41 Values followed by the same letter for the same variable are not significant different (p<0.05) 4 Table 5 Rice Protein Digestibility Corrected Amino Acid Score by variables« His ILe Leu Lys SAA AAA Thr Val Rice protein Indica 1.81 1.02 1.19 0.56 0.96 2.82 1.08 1.06 0.56 Japónica 1.40 0.92 1.08 0.43 0.89 2.35 1.00 0.99 0.43 2009 1.80 1.03 1.21 0.56 0.94 2.82 1.09 1.08 0.56 2010 1.36 0.93 1.06 0.40 0.87 2.53 1.00 0.96 0.40 2011 1.77 0.92 1.10 0.56 0.93 2.70 1.00 0.99 0.56 Ribatejo 1.71 0.97 1.13 0.50 0.91 2.67 1.03 1.01 0.50 Sado 1.65 1.01 1.19 0.55 0.94 2.80 1.08 1.06 0.55 Mean 1.64 0.98 1.14 0.50 0.93 2.62 1.05 1.03 0.50 5 Table 6 Amino acid correlation coefficient and method parameters AA CV (%) Method parameters Zscore LOD (mg/g protein) LOQ (mg/g protein) R 2 Ala 3.35 0.32 0.09 0.16 0.9989 Arg 4.31 0.63 0.18 0.55 0.9975 Asp 5.86 2.11 0.15 0.44 0.9964 Cys 17.88 0.62 0.17 0.52 0.9932 Glu 4.00 0.83 0.15 0.52 0.9973 Gly 4.42 1.04 0.15 0.46 0.9988 His 7.83 0.96 0.15 0.46 0.9980 Ile 6.44 0.35 0.05 0.14 0.9997 Leu 3.21 0.84 0.07 0.20 0.9984 Lys 17.22 0.91 0.21 0.74 0.9935 Met 6.65 0.84 0.11 0.33 0.9989 Phe 5.22 -0.20 0.17 0.51 0.9968 Pro 3.21 0.44 0.04 0.13 0.9996 Ser 4.78 -0.46 0.05 0.13 0.9994 Thr 4.91 0.23 0.06 0.18 0.9994 Tyr 8.43 0.31 0.21 0.65 0.9967 Val 5.89 0.37 0.04 0.12 0.9996 Mean 6.68 0.12 0.37 0.9978 CV (%): Coefficient of variation; LOD: Limit of Detection; LOQ: Limit of Quantitation; R2: Correlation Coefficient 6 T able7 Pearson Correlation As-AA His Ile Leu Lys SAA AAA Thr Val TEAA Ser Arg Gly Glu Asp Ala Pro TNEAA TAA Pearson relation -.142 .114 .032 -.090 -.052 -.204 .116 .119 -.042 .015 -.055 -.019 .073 .164 .106 .023 .064 .024 7 Appendix B – Required equipment and reagents for used procedures Amylose Equipment: - Glassware: Volumetric flask (25 mL); glass test tubes (16 x 120 mm, 15 mL); screw capped sample tubes (Kimax®) (10 mL). - Micro-pipettors, to dispense 50-1000 µL (e.g. Gilson Pipetman). - Positive displacement pipettor e.g. Eppendorf Multipette®. - Eppendorf® microfuge tubes (2.0 mL capacity). - Boiling water bath. - Bench centrifuge (capable of 2.000 g). - Vortex mixer (e.g. IKA® Yellowline Test Tube Shaker TTS2). - Spectrophotometer (set at 510 nm). - Stop clock. - Analytical balance. - Microfuge (capable of 14.000 g). - Thermostated water bath set at 40°C. Reagents: Besides Megazyme Kit (bottle 1 to 6), buffer and solvents: - Sodium Acetate Buffer (100 mM, pH 4.5) Add 5.9 mL of glacial acetic acid (1.05 g/mL) to 900 mL of distilled water. Adjust the pH to pH 4.5 by the addition of 1 M (4 g/100 mL) sodium hydroxide solution (approx. 30 mL is required). Add 0.2 g of sodium azide and adjust the volume to 1 L. Stable for > 2 years at room temperature. 8 - Concentrated Con A Solvent (600 mM, pH 6.4 sodium acetate buffer) Dissolve 49.2 g of anhydrous sodium acetate (Sigma cat. no. 71183), 175.5 g of sodium chloride (Sigma cat. no. S 7652), 0.5 g of CaCl2.2H2O (Sigma cat. no. C 5080), 0.7 g of MgCl2.6H2O (Sigma cat. no. M 2670) and 0.7 g of MnCl2.4H2O (Sigma cat. no. M 3634) in 900 mL of distilled water. Adjust the pH to 6.4 by dropwise addition of glacial acetic acid and then adjust the volume to 1 L with distilled water. - Con A Solvent (working concentration) Dilute 30 mL of Concentrated Con A Solvent to 100 mL with distilled water. - Dimethyl sulphoxide (DMSO) Analytical reagent grade (BDH Analar cat. no. 10323). Total protein Equipment: - Analytical balance with a resolution of 0.0001 g. - Tecator Kjeltec equipment. - Volumetric flasks. - Automatic Titrator "Titrando 808” - 300 ml erlenmeyer flasks - 5 mL pipette calibrated - 250 mL digestion tubes - Electric oven set at 102 º C ± 2 ° C Reagents: - Concentrated sulfuric acid - 95-98% (H 2 SO 4 , r20 = 1.84 g/cm 3 ). - Catalyst mixture: 9 Commercially available in the form of tablets: 3.5 g K2SO4 + 0.4 g CuSO45H - Boric acid, at 4 - 1L flask. Complete the volume. Measure and record the pH. - Solution of sodium hydroxid at 40 - Solution of 0.1 N HCl or H - Tryptophan (98.5%) (C11H12182.65 g/mol) - Ammonium sulfate (99.5%) (NH) - Solution of de (NH4)2SO4 1.2% (m/v). - pH 4.0 and 7.0 standard solutions Amino acids Material and equipment: - Ultra Performance Liquid Chromatography of ACQUITY™ UPLC® (Waters) system equipped with a photodiode array detector (DAD) with a pre-column derivatisation 6-Naminoquinolil hidroxisuccinimidilcarbamate - BEH C18 column (100 mm × 2.1 mm. Diameter, 1.7 mM particle) certified by Waters. - Microwave, model brand a Milestone Ethos. - Analytical balance with a resolution of 0.0001 g. - 5 and 10 mL volumetric flask - Small aliquots. - Calibrated micropipettes, fixed and variable volume and respective ends. - Filters - 10 mL flask - Glass tube and its lid. Reagents: