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Rice (2011) 4:66–74 DOI 10.1007/s12284-011-9073-z Identification of a Major Genetic Determinant of Glycaemic Index in Rice M. A. Fitzgerald & S. Rahman & A. P. Resurreccion & J. Concepcion & V. D. Daygon & S. S. Dipti & K. A. Kabir & B. Klingner & M. K. Morell & A. R. Bird Received: 3 November 2011 /Accepted: 29 November 2011 /Published online: 17 December 2011 Springer Science+Business Media, LLC 2011 Abstract Type II diabetes is a major chronic disease. In was found using a set of 235 varieties. The major gene that developing countries, the prevalence of type II diabetes is associated with GI in the 235 varieties was the Waxy gene. increasing enormously. Much research indicates that choice This paper reports the first large-scale phenotyping of this of carbohydrates, particularly those with low glycaemic trait, provides important information for nutritionists to index (GI) is able to assist in the management or prevention identify and quantify the impact of low GI rices on blood of type II diabetes. Most developing countries consume rice sugar status and offers a mechanism for breeding pro- as the staple. The objectives of this study were to determine grammes to select for GI based on amylose content. the variability in the GI of popular improved and traditional Furthermore, it allows rice consumers to select particular varieties of rice and to find the genetic basis of GI. A varieties of rice as their choice of carbohydrate. method to predict GI using an in vitro system was compared . . . to the in vivo system using a range of rice varieties differing Keywords Glycaemic index Rice Type II diabetes in GI. Large variability in GI, ranging from low to high GI, Amylose Electronic supplementary material The online version of this article Introduction (doi:10.1007/s12284-011-9073-z) contains supplementary material, which is available to authorized users. Type II diabetes is a major global health problem and its : : : M. A. Fitzgerald (*) A. P. Resurreccion J. Concepcion : prevalence is increasing dramatically throughout the world, V. D. Daygon S. S. Dipti Grain Quality Nutrition and Postharvest Centre, International Rice especially in Asia (Chan et al. 2009; Danaei et al. 2011). By Research Institute, 2030, almost 330 million people will be affected by diabetes DAPO 7777 Metro Manila, Philippines and the greatest burden of this disease will be borne primar- e-mail: firstname.lastname@example.org ily by the socioeconomically disadvantaged in low and S. Rahman M. K. Morell middle income societies (Misra et al. 2010; Walgate 2008). CSIRO Division of Plant Industry, In those communities, the populace has limited access to GPO Box 1600, Canberra ACT 2601, Australia basic health services and the presence of diabetes is often only discovered when serious complications arise, such as : : : S. Rahman B. Klingner M. K. Morell A. R. Bird CSIRO Food Futures National Research Flagship, cardiac and kidney failure and peripheral vascular damage PO Box 93, North Ryde NSW 1670, Australia leading to strokes, blindness and amputations of toes, feet and limbs (Walgate 2008). S. S. Dipti K. A. Kabir The escalating diabetes pandemic is largely a conse- Grain Quality and Nutrition Division, Bangladesh Rice Research Institute (BRRI), quence of the shift away from traditional lifestyles and Gazipur 1701, Bangladesh dietary patterns to increasingly sedentary behaviours cou- pled with excess intake of energy dense foods and rising B. Klingner A. R. Bird rates of obesity. A growing body of evidence from epide- CSIRO Food and Nutritional Sciences, PO Box 10041, Adelaide BC, SA, Australia miological and clinical studies points to the adverse health Rice (2011) 4:66–74 67 consequences of foods and diets rich in carbohydrates which especially those in poorer urban and rural communities are readily and extensively digested (Brand-Miller et al. (www.irri.org). However, prospective cohort studies in ge- 2009;Huetal. 2001; Sluijs et al. 2010). Mechanistic studies netically divergent populations show that white rice con- demonstrate that chronically elevated blood glucose levels sumption is associated with increased risk of developing induce deleterious structural changes in many tissues of the type II diabetes independent of ethnicity (Murakami et body, in particular the macro- and microvasculature al. 2006;Sun et al. 2010). In a study of middle-aged (Kaushik et al. 2009). Postprandial glycaemia is emerging Chinese women, type II diabetes risk was 78% greater as a clinically useful independent risk factor for cardiovas- in those consuming more than 300 g rice/day relative to cular disease in non-diabetics and those with established those eating <200 g/day (Villegas et al. 2007). Whereas diabetes (Sheu et al. 2011). Carbohydrate-based foods white rice has been shown to adversely affect metabolic which elicit a modest metabolic response, namely slowed health, brown rice may be protective. In a study of US or delayed postprandial intestinal glucose absorption and men and women, a moderate inverse association between consequent insulin secretion are likely to be of benefit for diabetes risk and brown rice consumption was observed reducing risk of chronic diseases, such as type II diabetes. (Sun et al. 2010); however, varietal differences were not taken There is also a growing body of data suggesting that certain into account. Furthermore, brown rice intakes were overall populations are inherently more susceptible to developing very low and the results may have been confounded, in that type II diabetes (Kooner et al. 2011); for such people, dietary certain populations of rice eaters often have healthier diets and options for managing blood glucose levels are important. lifestyles (Batres-Marquez and Jesen 2009; Fulgoni et al. The glycaemic index (GI) ranks foods (and diets) on the 2010). Further, two studies that tested the GI of brown and basis of their propensity to raise blood glucose, thereby white rice of the same variety, each using different varieties, providing a relative measure of dietary carbohydrate quality. reached opposing conclusions (Brand-Miller et al. 1992; A prospective cohort study showed that dietary GI and Panlasigui and Thompson 2006). glycaemic load (GL00.01GI × grams of carbohydrate con- Replacing white with brown rice or other whole grains sumed) were positively associated with diabetes risk has been recommended to mitigate the adverse metabolic (Barclay et al. 2008; Halton et al. 2008). Subsequent re- consequences associated with refined rice consumption search has confirmed those findings and generated strong (Dixit et al. 2011; Kumar et al. 2011; Sun et al. 2010). evidence from meta-analysis and meta-regression studies However, consumption of brown rice is very low relative demonstrating that low GI diets are linked to improved risk to white rice. Most Asians, for instance, consider it inferior markers for prevention of type II diabetes and its co- to white rice because of its shorter shelf-life, longer cooking morbidities (Barclay et al. 2008; Brand-Miller et al. 2003; time and unappealing taste and texture (Zhang et al. 2010). Halton et al. 2008; Livesey et al. 2008; Marsh and Brand- Accordingly, strategies to encourage brown rice consump- Miller 2008; Opperman et al. 2004; Wolever and Mehling tion over that of polished rice so as to improve consumer 2002). Lower GI foods and diets provoke only transient, health are unlikely to be successful at the population level, moderate postprandial glycaemia and improve insulin sen- whereas a more effective approach may be to reduce the sitivity along with other endpoints of cardio-metabolic glycaemic impact of polished rice through the development health in obese and overweight subjects as well as those and introduction of suitable low GI rice varieties. with type II diabetes (Brand-Miller et al. 2003; Dickinson Furthermore, most commonly consumed rices have a high and Brand-Miller 2005; Livesey et al. 2008; Marsh and GI irrespective of whether they are unpolished or refined Brand-Miller 2008; Opperman et al. 2004; Wolever and (Brand-Miller et al. 2003; Lin et al. 2010). Mehling 2002). Furthermore, low GI diets improve meta- While primary prevention of type II diabetes through bolic health indices independent of the amount of carbohy- more judicious food choices may be the frontline strategy, drate consumed (Psaltopoulou et al. 2010). Accordingly, behavioural change that is sustained and of meaningful lowering the GI of the diet could help in preventing the magnitude is difficult to achieve in practice, especially in development and slowing the progression of type II diabetes the short term. Lowering the GI of staple foods such as rice and thereby lead to an improvement in public health. It also is likely to be more effective in promoting public health, may offer a practical means for diabetes sufferers in low especially in communities in which rice accounts for a large income countries to better manage their condition without share of dietary glycaemic load and where there are expensive medication. entrenched cultural preferences for consumption of white For the majority of the world’s population, polished rice rice. Some Australian, Indonesian, Indian and Bangladeshi is a dietary staple and has been since its domestication many varieties have been reported to have lower GI than other thousands of years ago (Sweeney and McCouch 2007). It rices, but the genetic basis of GI has not been determined. In serves as the primary source of dietary energy and carbohy- barley, a mutation in starch synthase IIa (SSIIa) led to a drates for most Asians, and increasingly for Africans, significant lowering of GI (King et al. 2008). Four 68 Rice (2011) 4:66–74 haplotypes of SSIIa are known in rice, two of which are inactive (Cuevas et al. 2010b; Waters et al. 2006), and if the enzymes operate the same way in barley and rice, this could lead to greater understanding of differences in GI in rice. Understanding this could enable breeding programmes to target this trait, leading to new varieties with even lower GI values than are currently known for rice. The purpose of the present study was to establish the major genetic determinants of GI in rice for informing future varietal development. The GIs of a diverse set of Asian rices, both improved and traditional varieties, were pre- 60 dicted using a newly developed, high throughput instrument designed to simulate carbohydrate assimilation in the human gut. The relationship between the predictive method and in vivo measurements of GI was confirmed on a subset of lines. A secondary objective of the study was to offer an insight as to whether rice improvement programmes have 40 50 60 70 80 90 100 changed the glycaemic properties of rices commonly eaten GI (in vivo) in Asian countries. Fig. 1 Correlation (r 00.85) between in vitro and in vivo measures of GI in 12 varieties of rice. Diamonds are in vivo values from the Results literature (Williams et al. 2005) with in vitro values tested in this study, and circles represent varieties for which in vitro and in vivo values are from the present study. Method validation In vivo values of GI were determined for both the sample was determined by genotyping for the four haplo- International Rice Research Institute (IRRI) and Australian types (Cuevas et al. 2010a). No significant difference was sets of rice at the International Diabetes Institute and the found between SSlla haplotype and GI, nor was there any University of Sydney, respectively. The available carbohy- interaction or modifying effect of SSlla haplotype on the drate for both sets was calculated by the direct method, and association between amylose alleles and GI (data not GI was predicted for both sets. Figure 1 shows that the in shown). vivo values of GI associate well with the in vitro values High amylose rices, those carrying the Wx allele, differ (Fig. 1). in the texture of the cooked rice in that some are soft and some are firm. Using progeny from a mapping population Association between GI and grain properties derived from parents both with the Wx allele and segregat- ing for cooked rice texture, the predicted GI was 60±6 for Using a diverse set of rices from different countries and the soft textured progeny and 59±4 for the firm-textured germplasm classes, the predicted GI values range from 48 progeny. to 92 (Fig. 2), spanning low, intermediate and high GI Figure 4 shows that traditional varieties, selected by ancient farmers, are not of significantly different GI than categories, with an average reading of 64. Predicted GI also associates with amylose content (Fig. 3a) for the 235 vari- improved varieties, with the average GI of improved varie- ties being 64.9 and of traditional, 64.0. However, traditional eties, with increasing amylose content leading to decreased values of GI. In Fig. 3a, clusters can be seen for high, varieties do not show so many high GI samples as improved intermediate, low and waxy rices. Table 1 shows that for varieties, so the weighted average GI of these is 63, whereas most alleles of the Wx gene, the average GI values are it is 68 for the improved varieties. significantly different, with the wx allele showing the high- est GI and the Wx allele showing the lowest values of GI. Figure 3b shows that one waxy, IRIS 6-59997, one low, Discussion IRIS 298-52752 and four high amylose, IRIS 266-4060, IRIS 249-1353606, IRIS 249-1353606 and IRIS 109–8916 The prevalence of lifestyle-related chronic diseases and (Table S1) varieties lie beyond the lower boundary of the conditions, such as obesity, cardiovascular disease, certain interquartile range, and four high amylose varieties lie cancers and type II diabetes is continuing to grow at an above the upper boundary. The activity of SSlla in each alarming pace throughout the world, the Asian region Predicted GI (in vitro) Rice (2011) 4:66–74 69 Fig. 2 Range in predicted GI values of 235 varieties of cooked, polished rice. 48 52 56 60 64 68 72 76 80 84 88 92 Predicted GI especially (Shaw et al. 2010). Diet is implicated in the onset playing the same role in African diets. Improving the car- and progression of these health problems and carbohydrate bohydrate quality of this popular commodity offers potential quality is a strong predictor of disease risk. Choosing to eat as a dietary strategy for preventing and managing type II foods with predominately slowly digestible carbohydrates diabetes and its co-morbidities, thereby promoting popula- has been shown to be linked to favourable health outcomes tion health and alleviating the public health burden of including reduced risk of type II diabetes and related con- chronic diseases. In countries with very high incidences of ditions (Barclay et al. 2008; Halton et al. 2008; Livesey et type II diabetes, such as Sri Lanka, Bangladesh, Indonesia, al. 2008; Marsh and Brand-Miller 2008). Malaysia and India, there is a belief that specific varieties of Rice is a traditional staple food and primary dietary rice can elicit lower glycaemic responses and these are sold source of carbohydrates for most Asians and is increasingly and marketed to type II patients. 010 20 30 40 Waxy V_low Low Intermed High Amylose content (%) Amylose content Fig. 3 a Correlation (r 00.73) between amylose content and predicted content, but for those with high amylose, a number of outliers extend in GI using 235 diverse samples and b box and whiskers plot of GI vs. both directions beyond the interquartile range. amylose content showing that most samples associate with amylose Predicted GI Proportion of varieties (%) Predicted GI 50 60 70 80 90 70 Rice (2011) 4:66–74 Table 1 Average GI is signifi- Vries 2007; Muller and Bird submitted). Consequently, pre- Mutation Predicted GI cantly different between each vious studies have measured GI on only a small subset of known allele of the Waxy gene wx 89.70 using the Welch’s T test and rice varieties and so variability in the diversity of rice is not op b pairwise comparisons (p<0.05). Wx 76.50 captured and definitive conclusions about possible relation- Different letters indicate signficant b b Wx 72.04 ships between GI and other grain traits cannot be drawn. differences in GI values in c Wx 64.33 GI is a numerical measure of the extent to which carbo- a d Wx 60.53 hydrates in foods affect postprandial blood glucose levels. GI glycaemic index Conventional GI determination therefore involves testing in humans. For most applications, this is impractical for the GI provides a measure of the glycaemic potency of foods reasons stated earlier. Indeed, stringent testing conditions and is widely used as a guide for choosing healthier foods are essential to achieve satisfactory levels of precision (De (Chiu et al. 2011; Mitchell 2008). Low GI diets are effective Vries 2007; Muller and Bird submitted; Pi-Sunyer 2002; in the prevention and treatment of type II diabetes (Barclay Venn and Green 2007). In the present study, we demonstrate et al. 2008; Gnagnarella et al. 2008; Jenkins et al. 2002). that the use of an automated laboratory-based assay for pre- However, rice improvement programmes have not been able dicting GI overcomes the methodological and ethical con- to focus on the development of varieties with potential for straints of in vivo testing and provides a practical solution to reducing the incidence and severity of type II diabetes screening large volumes of samples. The validity of the assay because variability for GI in rice is unknown, the genetics was established by testing a diverse set of rice varieties and of GI are unknown and phenotyping tools for nutritional comparing the results against those obtained using standar- traits, such as GI, are not yet available. dised in vivo procedures performed by two highly experi- Although a number of studies have attempted to draw enced testing agencies. Correlation analysis of the resultant associations between components of the grain and the GI of data demonstrated a strong relationship between predicted and the rice (Babu et al. 2007; Brand-Miller et al. 1992;Freiet actual GI values confirming that the in vitro method has al. 2003; Hettiarachchi et al. 2001; Hu et al. 2004; Matsuo et high predictive power, thereby justifying its use in the al. 1999; Panlasigui et al. 1991), establishing relationships current study to explore, for the first time, the range in between composition and genotypes of rices and GI has GI values across a large and diverse collection of im- been hampered by the low throughput, poor precision and proved and traditional rice varieties. The information we considerable expense of in vivo determination of GI (De have generated on the relative glycaemic properties of Fig. 4 Frequency histogram showing that the distribution in GI of improved varieties of rice (black bars) contains more high GI rices than the distribution of the traditional varieties (grey bars). 48 52 5 60 64 68 72 76 80 84 88 92 96 10 Predicted Glycaemic Index Proportion of samples (%) Rice (2011) 4:66–74 71 different types of rice has a wide scope of applicability. more important than the structure of the amylose in deter- In vivo GI values for a given food are essentially the mining GI. same regardless of ethnicity or physiological status of Intermediate amylose rices are preferred in many the volunteers on which the data are based (Chiu et al. countries in which over 5% of the population have type II 2011). Furthermore, the relationship between GI and diabetes. There is also a strong positive association between adverse health impacts is just as pertinent to Asians as amylose content and texture of the rice (Bhattacharya 2009; it is to Caucasians and other racial and ethnic groups Juliano 1979). The high amylose class contains both soft- (Murakami et al. 2006; Villegas et al. 2007). and firm-textured rice, and given that there is no effect of the The varieties measured included both landraces (143) and single-nucleotide polymorphism (SNP) on exon 10 of the improved (92) varieties developed by leading rice breeding Wx gene on GI within the high amylose class, it should be programmes in many different countries. The collection possible for breeding programmes concerned with the GI of included indica and tropical and temperate japonica rices. rice to develop soft-textured high amylose rices to replace GI ranged from 48–98 in the set of rices, with no association the intermediate amylose rices, especially for countries and between germplasm class. A similar range in the GI of rices, regions with high incidences of type II diabetes, such as the including low GI varieties as determined by acceptable in Philippines, South Asia and the Middle East. vivo methods, has been reported previously (Brand-Miller et While this study has identified a major determinant of GI al. 1992; Larsen et al. 1996). While there are in vitro GI data in rice, the data do not preclude the possibility that other on different rice lines (Frei et al. 2003), caution should be genes have a modifying effect on GI. Additional studies in exercised in interpreting these findings because their phys- genetic populations will be required to identify such genes iological relevance has not been satisfactorily substantiated. and quantify their contribution to determining GI. Our data demonstrate that improved varieties have on aver- The identification of low GI rice varieties offers the possi- age a slightly higher GI than traditional ones (Fig. 4), sug- bility of conducting well-designed, randomised controlled gesting that breeding programmes have produced a slow, trials and epidemiological studies (long-term prospective passive drift towards higher GI rices. Until recently, the investigations that take into account the various confounding nutritional potential of rice has not been a target of rice factors operating across different populations, regional loca- improvement programmes, and while various countries tions, culinary customs and ethnic groups) to examine the would like to develop low GI rices, the limitation lies in relationship between sustained consumption of low GI rice, selecting for the trait. metabolic control and health outcomes. Such information will Strong correlations between amylose content, the Waxy be useful for informing the development of long-term public locus and GI were observed across all samples (Fig. 3a, health strategies and clinical management plans for people Table 1), indicating that amylose is the major grain constit- with metabolic diseases. uent that affects GI. However, the size of the interquartile ranges and the presence of outliers in Fig. 3b suggest that (a) within each class of amylose content, and for each allele of Materials and methods the Waxy gene, variability can be found for GI and (b) there must be other loci that interact with the Waxy gene to Method validation produce variability within each class. The absence of starch synthase IIa (SSlla) activity lowers GI in barley (King et al. In order to predict the GI of a large and diverse set of rice 2008) but no association was found between varieties with varieties with an in vitro method, it is necessary to determine active and inactive haplotypes of SSlla in this study. This the association between the in vivo method of measuring GI suggests that SSlla plays different roles in starch synthesis in and the in vitro method. A set of six varieties of rice, Oryza barley and rice. sativa L., that have been widely researched in previous In the high amylose classification of rice, the texture of studies were selected to validate the method. These were freshly cooked rice can be either soft or firm (Cagampang et IR65, IR24, IR64, IR8, BD192 (from Bangladesh) and al. 1973). This difference is due to a single-nucleotide Samba Mahsuri (from India). All varieties, other than polymorphism in the Waxy gene that leads to different BD192, were grown in the dry season of 2008 at the structures of amylose within the grain and different retro- International Rice Research Institute in the Philippines. gradation rates (Tran et al. 2011). Intuitively, it might be Grain was harvested at maturity, stored for 6 weeks to assumed that amylose structure would affect the GI and that equilibrate for moisture content, then 150 g was dehulled the firm-textured varieties might have a lower GI. However, (THU35A Test Husker, Satake) and polished (Grainman 60- the difference in GI between progeny of a mapping popula- 230-60-2AT, Grain Machinery Mfg. Corp.). BD192 was tion with soft and firm texture after cooking was not signif- obtained from the Genetic Resources Centre of the icantly different, suggesting that the amount of amylose is Bangladesh Rice Research Institute (BRRI) and grown in 72 Rice (2011) 4:66–74 both the Aman and Boro seasons at BRRI. Grain was Quantities of raw test rices equating to 5 g of glycaemic harvested at maturity, dehulled (THU35A Test Husker, (available) carbohydrate were added to an excess of boiling Satake) and polished using a home-made polisher. water (approximately 60 mL) and cooked for 16 min. The Polished grain from each variety was cooked in excess rices were then drained using a domestic sieve and allowed water. Once the water reached a light boil, the rice was to cool for 5 min at room temperature before intact rice added, and after 17 min, the rice was drained and allowed grains were assayed immediately for their predicted GI to cool for 5 min. Total starch of the cooked rice was using an in vitro system which models the buccal, gastric determined as described using the Megazyme total starch and pancreatic phases of food digestion as it occurs in the kit (Megazyme, Wicklow, Ireland) (AACC Standard 76 human upper gastrointestinal tract (Bird, Usher, Klingner, 13.01). Topping and Morrell, unpublished data). Briefly, cooked rices were added to a conical flask and mixed with artificial saliva (250 U/mL of α-amylase) at pH 7.0. In vivo testing for GI After approximately 20 s, acidified (0.02 M HCl) pepsin (1 mg/mL) was added and the flask incubated at 37°C GI of the six rices was tested according to the Australian for 30 min in a shaking water bath. The digest was Standard AS 4694-2007: Glycaemic Index of Foods. The adjusted to pH 6.0 (0.2 M acetate buffer pH 6.0) fol- tests were performed by the International Diabetes Institute lowed by the addition of pancreatin (2 mg/mL) and testing facility, Caulfield, Victoria, Australia. Blood glucose amyloglucosidase (28 U/mL) and the digest incubated was determined in 10 to 12 volunteers who had fasted for for a further 5 h. Aliquots of supernatant were sampled 10 h prior to the test. The volunteers then consumed the test at preset intervals and the glucose concentration deter- (glucose drink) or reference food (rice) over 12 min, and mined using an automated electrochemical technique then, changes in circulating levels of blood glucose were (YSI 2700 Select Bioanalyser) (Yellow Springs, OH). measured over the following 2 h. The test rices contained The predicted GIs of the rices were calculated as a 50 g of glycaemic (available) carbohydrate, based on total percentage of available CHO converted to glucose over starch of the cooked rice, and the reference food (glucose the duration of the incubation. drink) had been tested in each volunteer on three previous occasions. The incremental area under the blood glucose curve (IAUC) was calculated and indexed to that of the Range in predicted GI using diverse varieties of rice mean IAUC for the reference food and then GI of each of the six rices was calculated according to the trapezoid rule. A set of 111 varieties was randomly selected from the The area beneath the fasting concentration is ignored in the Genetic Resources Centre of (BRRI). Of these, 72 were calculation of GI. Glucose is used as the reference food and traditional varieties and 39 were improved. A second set by definition has a GI of 100. was selected at IRRI to represent the popular and traditional A second set of values of in vivo GI was previously varieties of many other Asian countries. All samples (235) obtained for another six Australian varieties of rice were shipped to CSIRO as polished grain for the prediction (Williams et al. 2005). These were Amaroo, Doongara, of GI by the in vitro method described above. Opus, Langi, Kyeema and Basmati. Samples of each were supplied by Sunrice Cooperative Ltd to the University of Association between grain properties and GI Sydney and to IRRI as polished rice. Each sample was analysed for proximate analysis and amylose content to A set of 40 samples from a population (F ) of recombinant determine available carbohydrate, and GI values were inbred lines derived from a cross between two high amylose obtained by the University of Sydney (Williams et al. 2005). varieties, IR5 and IR8, were selected to determine whether predicted GI associates with the texture of the grain after In vitro testing for GI cooking. Twenty soft-textured and 20 firm-textured progeny were selected for GI testing. Cooked rice texture of the 40 Both sets of samples that were tested for in vivo GI at the samples was measured by the gel consistency test and International Diabetes Institute and the University of confirmed by texture profiling using a TaXt-plus as Sydney were sent to Commonwealth Scientific and described previously (Tran et al. 2011). Amylose con- Industrial Research Organisation (CSIRO) Food Nutrition tent was measured on the 235 varieties of rice, includ- for determining predicted GI. Samples of the test rices IR65, ing those used to validate the method, by the standard IR24, IR64, IR8, BD192 and Samba Mahsuri were cooked method (AACC-6647), except that an additional standard was using a scaled-down version of the rapid boil procedure that included in the standard curve, IR65, which is a waxy variety was used in the in vivo GI studies described previously. and contains no amylose. Rice (2011) 4:66–74 73 Babu, Uma S., and Paddy L. Wiesenfeld. 2007. Rice, global food Three SNPs at the Waxy locus, on the splice site of exon source and rice controversy related to obesity and glycemic index. 1, exons 4 and 6, define the haplotypes that associate with In interactions of rice components and obesity-lipid biomarkers amylose class. DNA was extracted from each sample and immune function, 11–18. 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Rice – Springer Journals
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