Premium and second best varieties were obtained from nine countries. The two varieties in each pair were very similar based on the current suite of quality evaluation tools. Table 1 shows the variety, the country of origin, gelatinization temperature, amylose content, and protein content. Only the pair from Pakistan differed in gelatinization temperature, which was unexpected since the standard for Basmati quality defines intermediate gelatinization temperature. Perhaps, some environmental condition during grain-filling led to the low value obtained for Basmati 385. For most pairs, there were small differences in amylose content, but in most cases, these differences did not cross the current classifications of amylose (Fitzgerald et al. 2009). Protein content ranged from 5.9% to 11.2% across the set, but in most cases, the protein content was similar for the pairs although statistical analysis of technical replicates indicates significant differences between many pairs
Table 1 Premium (rank 1) and second best (rank 2) variety pairs with country of origin Color
One of the most important attributes of raw and cooked rice is degree of whiteness (Goodwin et al. 1992, Suwansri et al. 2002). The whiteness (L*) of the raw premium rice compared to its second best counterpart was not an indicator of the relative whiteness of the cooked rice (Tables 2 and 3). However, when cooked, the only premium rice varieties that were not of the same or greater whiteness than their second best counterparts were IR64 and BR IRGA 417 (2009).
Table 2 Rice samples prepared using rice cooker and excess water methods Table 3 Tristimulus L*, a*, and b* values for color measured using a HunterLab MiniScan XE Plus Diffuse LAV M072096 colorimeter Green–red color (a*) varied markedly across countries and between premium–second best variety pairs (Table 3). Cooking decreased the green color of all the varieties and resulted in a* values that differed by no more than 0.1 unit.
In the raw rice, yellow color (b*) was significantly lower in the premium varieties IR64, KDML-105, BR IRGA-417 (2008 and 2009), and Super Basmati when compared to their second best counterparts. The converse relationship was observed for the Pelde–Langi, Sambha Mahsuri–Swarna, and Hashemi–Khazar pairs. No significant differences in b* were observed for the pairs from Japan (Koshihikari–Koshiibuki) or China (Zhongzheyou 1–Guodao 6). Upon cooking, varieties became less yellow (b* = 2.4–7.0 versus 10.0–15.3) and the significant differences in b* observed for the raw varieties were still seen for most variety pairs. No parameter of color provided a consistent explanation of differences in quality.
Comparison of flavor of premium and second best varieties
No significant (P < 0.1) flavor (aromatics, taste, mouthfeel) differences were observed between the premium and second best variety pairs from Japan, India, and one set from Brazil. The other second best variety from Brazil, BRS Jaçanã, only differed from BR IRGA-417 (also harvested in 2008) by having a lower level of sour/silage (Table 4). Sour/silage is an off-flavor note that increases with increase in harvest moisture content of paddy and length of storage prior to drying (Champagne et al. 2004a) and, thus, was not inherently higher in BR IRGA-417.
Table 4 Flavor attributes that differed significantly (P < 0.1) in intensity between premium and second best variety pairs The flavor of the other premium–second best variety pairs differed in intensity for only a few attributes, as shown in Table 4. The premium varieties from China and the Philippines were distinguished from their second best counterparts by having significantly higher levels of sweet taste (desirable attribute) and lower level of water-like metallic (undesirable attribute). A lower level of water-like metallic also distinguished the premium Super Basmati from Pakistan from its second best counterpart Basmati 385. Water-like metallic has been shown to decrease with storage time of rough rice (Meullenet et al. 2000), so the difference in intensities between the Super Basmati and the longer-stored Basmati-385 can be attributed to differences between varieties and not storage duration. The intensity of water-like metallic was also numerically but not significantly lower in the premium varieties KDML105, Pelde, IRGA-417 (2008), and Sambha Mahsuri compared to their second best counterparts. A comparison of the combined premium varieties with the combined second best varieties showed water-like metallic to be significantly lower (P = 0.02) in the premium varieties. No other flavor attribute was significantly different between combined premium and second best varieties.
The compound 2-acetyl-1-pyrroline (2-AP) imparts a popcorn flavor to fragrant rice varieties (Buttery et al. 1983). Premium KDML105 was significantly higher in popcorn aroma/flavor than second best PTT1 (1.5 and 1.1, respectively; P = 0.08). Quantification of 2-AP by GC-MS showed about twice as much 2-AP in KDML-105 (1,358 ppb) than in PTT-1 (637 ppb). Super Basmati, Basmati-385, and Hashemi are also aromatic. The panel found that premium Super Basmati and second best Basmati-385 had the same popcorn intensity as non-aromatic varieties (mean = 0.7). GC-MS analysis, however, found 553 ppb of 2-AP in the Super Basmati and none in the Basmati-385. The Basmati-385 was stored as rough rice for about a year prior to milling; whereas, the Super Basmati had not been stored. The 2-AP content of rough rice decreases during storage (Wongpornchai et al. 2004). Although the Super Basmati had approximately the same 2-AP content as PTT1, the panelists perceived the popcorn aroma/flavor to be lower in the Super Basmati, consistent with differences in aroma/flavor between jasmine styles and basmati styles and suggesting that compounds other than 2-AP contribute to their aromatic character, perhaps masking the 2-AP flavor. The popcorn aroma/flavor of Hashemi was not significantly higher than that of the non-aromatic variety Khazar (1.2 and 0.8, respectively). The 2-AP content of Hashemi was 1,045 ppb, but none was detected in Khazar, further suggesting a role for volatile compounds other than 2-AP in determining popcorn aroma/flavor.
Ward’s cluster analysis, using selected aromatic (Table 5) and taste/mouthfeel (Table 6) attributes, was used to determine whether the premium and second best varieties grouped into the same or different clusters. The varieties are listed in the Tables in the order they appear in the cluster analysis tree charts. The varieties did not cluster based on premium–second best classification (Tables 5 and 6). Apart from China, India, and the Philippines, varieties from each country fell in the same cluster, suggesting that flavor is specific to the country of origin. Premium Zhongzheyou1 clustered with varieties high in popcorn, corn, hay-like musty, grain/starchy, and sweet aromatic (Table 5). Its counterpart Guodao 6 clustered with ones lower in these attributes. Premium IR64 clustered with varieties high in sweet taste and low in water-like metallic, while its counterpart IRRI-132 grouped with those high in sewer animal, water-like metallic, astringent, and sour/silage and low in sweet taste (Tables 5 and 6). IRRI-132 yields very well in upland and water-scarce areas, but it has not been widely accepted by consumers, even though current tools for measuring grain quality show that it is similar in quality to the highly popular IR64. If its flavor profile explains its non-adoption, quality evaluation programs need to add flavor evaluations to their repertoire. A high score for sewer animal differentiated second best Swarna from premium Sambha Mahsuri in the cluster analysis (Table 5). Analysis of variance (ANOVA), however, showed no significant differences (P = 0.16) in sewer animal between the two varieties. Sambha Mahsuri and Swarna clustered for the other aromatic and mouthfeel/taste attributes, and as noted above, in a comparison of the two varieties, none of these attributes were significantly different. Thus, flavor differences do not appear to explain why Sambha Mahsuri commands much higher prices in the market than Swarna.
Table 5 Ward’s cluster analysis using select aroma/flavor attributes to categorize varieties Table 6 Ward’s cluster analysis using taste and mouthfeel attributes to categorize varieties Comparison of texture of premium and second best varieties
Roughness was a distinguishing trait between most pairs (Table 7). The premium variety from Southeast Asia and Northern Asian countries was always less rough than the second best, but for South and Central Asia, the cooked surface of the premium variety was rougher. The cuisine of South and Central Asia is predominantly thick curries and consumers like the curry sauce to stick to the rice. A sauce is more likely to stick to a rough surface than a smooth one, which could explain the preference for surface roughness in the varieties of that region.
Table 7 Texture attributes that differed significantly (P < 0.1) in intensity between premium and second best variety pairs An association between roughness and protein content (r2 = 0.58) was observed and concurs with earlier observations (Champagne et al. 2004b, 2009). However, the present paper indicates that other factors also contribute to roughness. The 0.2% difference in protein content between Zhongzheyou 1 and Guodao 6 would be too low to result in a detectable difference in roughness by the trained panel (Champagne et al. 2009). Moreover, IRRI-132 had the highest roughness score (6.6) of all the varieties with a protein content of 8.7%, and with identical protein content, IRGA-417 (2008) scored a significantly lower value for roughness, further indicating the contribution of other factors. Given that roughness was a distinguishing feature in almost all pairs, and appears to be market-specific, it is important to understand further the biology and structures that lead to a rough surface when the grain is cooked.
Slickness was a distinguishing textural feature for five of the pairs, and in all but one case, slickness was higher in the premium variety (Table 7). In this study, slickness was negatively correlated with both protein (r2 = 0.60) and apparent amylose (r2 = 0.39) contents. These parameters could indicate differences in slickness when large differences in protein and/or amylose are present. However, in the present paper, the small differences in protein and amylose contents between the premium and second best of each country are not likely to be a sufficient predictor of differences in slickness (Champagne et al. 2009).
For the varietal pairs from South and Central Asia, a number of textural attributes distinguished the premium from the second best, but common to all was springiness, which was higher in the premium variety. Springiness was not a distinguishing feature of the pairs from North and Southeast Asia, Australia, and Brazil. A weak negative correlation (r2 = 0.31) was found between springiness and amylose content, but there was no significant difference between the amylose content of each variety in each pair from South and Central Asia, suggesting that amylose is not the primary basis of springiness.
Ward’s cluster analysis was used to categorize the rice based on texture characteristics described in Table 10. Analysis using phase I texture attributes resulted in two clusters with the varieties from Iran, India, Brazil, and IRRI-132 from the Philippines comprising cluster A and cluster B composed of varieties from Japan, China, Thailand, Australia, and IR64 from the Philippines (Table 8). Cluster A contained varieties with high roughness scores. Interestingly, all varieties in cluster A, with the exception of IRRI-132, were boiled in a pan (Table 2). Excess cooking water was used for all but the Brazilian samples. This suggests that the cooking method could contribute to roughness. Cluster B was characterized by varieties that scored high for slickness, stickiness to lips, initial starchy coating, and stickiness between grains. Koshihikari and Koshiibuki had the highest scores for initial starchy coating, slickness, stickiness to lips, and stickiness between grains. All varieties in cluster B were cooked by the absorption method in rice cookers, and there is a relatively good association between the order of varieties within cluster B (Table 8) and the length of soaking time before cooking (Table 2), strengthening the need to understand the effect of cooking method on sensory properties.
Table 8 Ward’s cluster analysis using phase 1 texture attributes to categorize varieties