Breeding Novel Short Grain Rice for Tropical Region to Combine Important Agronomical Traits, Biotic Stress Resistance and Cooking Quality in Koshihikari Background

Uthomphon Saichompoo, Possawat Narumol, Pawat Nakwilai, Peeranut Thongyos, Aekchupong Nanta, Patompong Tippunya, Siriphat Ruengphayak, Teerarat Itthisoponkul, Niranee Bueraheng, Sulaiman Cheabu, Chanate Malumpong

Research Paper

Breeding Novel Short Grain Rice for Tropical Region to Combine Important Agronomical Traits, Biotic Stress Resistance and Cooking Quality in Koshihikari Background

Uthomphon Saichompoo1, Possawat Narumol1, Pawat Nakwilai1, Peeranut Thongyos1, Aekchupong Nanta2, Patompong Tippunya2, Siriphat Ruengphayak3, Teerarat Itthisoponkul4, Niranee Bueraheng5, Sulaiman Cheabu6, Chanate Malumpong1

(Department of Agronomy, Faculty of Agriculture at Kamphaeng Saen, Kasetsart University, Nakhon Pathom 73140, Thailand; Tana Group International Co., Ltd., Phan, Chiang Rai 57120, Thailand; Rice Science Center & Rice Gene Discovery Unit, Kasetsart University, Kamphaeng Sean Campus, Nakhon Pathom 73140, Thailand; Faculty of Agricultural Product Innovation and Technology, Srinakharinwirot University, Bangkok 10110, Thailand; Faculty of Science Technology and Agriculture, Yala Rajabhat University, Mueang, Yala 95000, Thailand; Faculty of Agriculture, Princess of Naradhiwas University, Narathiwat 96000, Thailand)

Breeding program strategies to develop novel short grain white rice varieties such as(short grain) that introgress biotic stress resistance and high grain quality have been developed usingrice (Pin Kaset+4 and Riceberry) for applications inrice (Koshihikari) improvement. Four breeding lines showing promising agronomic performance with short grain and low amylose content (< 20%) were obtained. In addition, sensory testing of these breeding lines showed high scores that similar to Koshihikari. Two promising lines, KP48-1-5 and KP48-1-9, which possessed a combination of four genes resistance to different biotic stresses (+++) and four genes for grain quality (++wx+), were developed using marker-assisted selection (MAS) with the pedigree method. The current study clearly illustrated the successful use of MAS in combining resistance to multiple biotic stresses while maintaining a high yield potential and preferred grain quality. Moreover, the results indicated that this breeding program, which includes crossingwith,can create novel short grain rice varieties adapted to a tropical environment, like thetype.

marker-assisted breeding; short grain rice; grain quality; biotic resistance

The popularity of Japanese food and the increase in the Japanese population in Thailand have recently increased the demand forrice. In fact, restaurant chains from Japan have increasingly invested in Thailand to open Japanese restaurants at a growth rate of 10%?15% per year. As a result, Thailand ranks the fifth in the world in terms of its number of Japanese restaurants (Miyamoto, 2017). However, the production ofrice in tropical region such as Thailand is very limited, resulting in a high price for this commodity (Kang, 2010). Therefore, therice used for cultivation under tropical conditions should be improved.

Chiang Rai, the northernmost province in Thailand, has become a major production base forrice because of its climate, and locally developed accessions ofvarieties have qualities similar to those of accessions grown in Japan (Warinrak, 2013). In 1995, there were two knownrice varieties [DOA1 from Sasanishiki (SN) and DOA2 from Akitakomachi(AK)] that are suitable for planting in the northern parts of Thailand because their resistance to hot weather is higher than otherrice varieties (Seemanon et al, 2015). However, DOA1 and DOA2 off-type plants were found in the fields, and the genetic background of the two varieties was changed compared with the original SN and AK from Japan (Nakwilai et al, 2020). Therefore, after 25 years, DOA1 and DOA2 were incompletely integrated into the genetic backgrounds of SN and AK, respectively. Thus, arice breeding program should be started in Thailand to breed new varieties for alternative choices inrice production.

In Japan, the bestcultivar is ‘Koshihikari’ (KH), which was grown on 36.2% of the total rice area in 2016, and since then, it has continuously maintained its top position in Japan because of its high eating quality and appeal to Japanese consumers (Kobayashi et al, 2018). Thus, it has been used as a genetic resource to improve eating quality in rice breeding throughout Japan (Wada et al, 2013). However, KH is less resistant to lodging and more susceptible to diseases such as blast than other varieties. In addition, it is slight resistance to bacterial leaf blight (Ishizaka et al, 1989).

The new Thaivariety ‘Pin Kaset+4’ (PinK4) was improved by the pseudobackcrossing method for pyramiding multiple traits. PinK4 is introgressed with six target genes and three QTLs, including those for resistance to bacterial leaf blight (BLB;and), leaf-neck blast (BL;), brown planthopper (BPH;,,and) and flash flooding (Sub;and). In addition, it is characterizedas high yield and aromatic qualities () and exhibits improved starch profiles (soluble starch synthase IIa;) (Ruengphayak et al, 2015). Another Thaivariety ‘Riceberry’ (RB), a new black rice variety, was developed using conventional breeding between Hom Nin, a local non-glutinous purple rice, and Khoa Dawk Mali 105, a premium fragrant rice, and then selected by the pedigree method. RB becomes soft, fluffy and fragrant when cooked (Poosri et al, 2019). Thus, these Thaivarieties were used as parents in this research.

Therefore, breeding program strategies that are successful in developing novel short grain white rice varieties such as(short grain) have been developed to support the Japanese food industry by employingrice (PinK4 and RB) for application inrice (KH) improvement. Pedigree and backcross methods with marker-assisted selection (MAS) were used to select rice varieties for short grain, high yield, good cooking quality and resistance to biotic stress.

RESULTS

Weather data during breeding program

The weather data during the five years of the breeding program is shown in Fig. S1. The mean daytime and nighttime temperatures for the five years were 26.7 oC and 23.0 oC, and the mean maximum and minimum temperatures for the five years were 31.2 oC and 20.2 oC, respectively. In addition, the mean relative humidities during the daytime and nighttime over the five years were 72.1% and 88.2%, respectively, and the average rainfall over the five years was 4.1 mm.

Breeding program during early generations

The results of the breeding program are shown in Fig. 1. In the first cross, the paddy grain shapes of the two parents KH (width/length 3.80/6.90 mm) and RB (width/length 2.60/11.20 mm) were identified as the shortest and longest grain phenotypes, respectively, whereas the paddy grain shapes of their progenies in BC1F1ranged from2.50?3.70 mm in grain width and 7.00?11.00 mm in grain length (data not shown). The paddy grain shapes of the F2progenies ranged from 2.60?3.90 mm in grain width and 6.60?11.00 mm in grain length (Fig. 2-A and -B). Thus, 52short grain plants of BC1F1and 45 plants of F2were selected and continued to BC1F3and F4generations, respectively.

In the second cross, KH × PinK4, the paddy grain shapes of the F2progenies ranged from 2.61?3.80 mm in width and 6.60?10.00 mm in length. For the parental lines, KH displayed a short grain (width/ length 3.39/7.30 mm), while PinK4 had a long grain (width/length 2.85/10.70 mm) (Fig. 2-C and -D). Thus, 27 F2plants were selected and continued to F4generation.

Advancement of generations

Phylogenetic relationships of selected lines

For BC1F4and F5from KH × RB, five and one lines were selected, respectively. Notably, seven lines were selected from KH × PinK4. Thus, a total of 13 selectedlines from both crosses were analyzed for their genetic backgrounds together with their parents and control varieties (DOA1, DOA2, AK and PTT1).

Fig. 1. Scheme of breeding programs for short grain rice derived from Koshihikari × Riceberry and Koshihikari × Pin Kaset+4 from WS15 to WS19 in Phan district, Chiang Rai Province, Thailand.

WS, Wet season; DS, Dry season; MAS, Marker-assisted selection; GBS, Genotype by sequencing.

The phylogenetic tree was divided into two groups (Fig. 3). Group I contained 12 selected lines together with KH, AK, DOA1 and DOA2. This group was clearly identified as atype. When considering the selected lines, KP48-1-5 and KP48-2-4 had close relationships to KH and DOA2, whereas BC1F4(95-2-14) was close to AK and DOA1. Group II containedparental lines (RB and PinK4) and the controlrice, PTT1. However, the selected line namely Ped (2-12-17) was classified into thegroup. Thus, this line was discarded and the remaining 12 selected lines were evaluated during a preliminary yield trial.

Preliminary yield trial

The preliminary yields of 12 selected lines were evaluated in wet season in 2018 (WS18) at Tana Grain Polish, Ltd., Phan district, Chiang Rai Province, Thailand. The grain yield (GY) and agronomic traits were significantly different among the lines/varieties (< 0.05) (Table 1). The days to 100% flowering (DF) of the 12 lines were not significantly different compared to DOA1 and DOA2, but were significantly longer than those of AK and KH. The 1000-grain weights of the lines were significantly lower than those of DOA1 and DOA2 except for KP48-1-5 and KP48-1-3. However, the GYs of the other 10 lines excepted BC69-3-1 and BC90-2-4 were significantly higher than those of AK and KH, and showed similar to those of DOA1 and DOA2.

Fig. 2. F2segregations of paddy grain length and width from Koshihikari (KH) × Riceberry (RB) (A and B) and KH × Pin Kaset+4 (PinK4) (C and D).

When considering the grain quality, the grain length to width ratios were significantly different among lines/varieties (< 0.05) (Table 2), and the length to width ratios of milled grains were below 2.0 for all the 12 lines. This indicated that all the lines can be identified as short grain rice. The amylose contents (AC) of KP65-1-2 (23.49%) and KP48-2-4 (24.42%) were the highest when compared with other lines/varieties identified as hard rice. The AC of the other 10 lines was less than 20%, and AK (15.79%) and KH (15.23%) had the lowest AC (Table 2). KP65-1-2, KP48-2-4 and KP65-2-4 were identified as having intermediate-high gelatinization temperatures, while the other lines had high gelatinization temperatures, similar to those of AK, KH, DOA1 and DOA2 (Table 2).

Fig. 3. Phylogenetic tree of breeding lines and control varieties based on genotyping by sequencing.

The phylogenetic tree revealed two groups. Group I comprises thetype, while group II is made up of thetype. The numbers at the node indicate the percentage obtained with 1000 bootstraps.

Overall sensory scores were combined from the evaluation of nine characteristics (Fig. 4-A). The overall scores were significantly different among lines/ varieties. KP48-1-5 (32.91) and BC95-2-14 (30.27) had the highest overall scores, while the overall scores of the control varieties (DOA2 and KH) were 28.73 and 29.16, respectively.

Considering all traits, including GY, agronomic traits, grain quality and sensory score, and by MAS, five lines KP48-1-5, KP48-1-9, BC95-2-14, BC95-2-12 and BC95-2-7 were selected for continued yield trials in dry season in 2019 (DS19) and wet season in 2019 (WS19). Finally, the sensory test in WS19 revealed that the highest overall scores were found in BC95-2-12 and KP48-1-9, and the second highest overall scores were found in KP48-1-5 and BC95-2-14 (Fig. 4-B).

Validation of promising lines

Evaluation of BPH, BLB and blast resistance

In 2019, the yield trial experiment was conducted in dry season (DS19) (F6and BC1F5) and wet season (WS19) (F7and BC1F6). MAS was used to detect the target genes/QTLs and indicated that KP48-1-5 and KP-1-9 were successfully fixed in terms of the homozygosity of the eight target genes (,wx,,,,,and), while BC95-2-12, BC95-2-14 and BC95-2-7 had homozygosityin the four target genes (,wx,and) (Table 3).

Fig. 4. Sensory test in BC1F5derived from Koshihikari × Riceberry and F6derived from Koshihikari × Pin Kaset+4 in wet season in 2018 (A) and candidate lines in BC1F6and F7in wet season in 2019 (B).

Different lowercase letters follow the numbers above the column indicate significant differences among the lines at the 0.05 level using the LSD method.

In WS19, the five candidate lines were screened for their reactions to BPH resistance. Surprisingly, the phenotyping of KP48-1-5 and KP48-1-9, which haveandgenes, showed moderate resistance in all three biotypes, while PinK4, which contains the same genes, was scored as resistant (Fig. 5-A). This might be because PinK4 possesses another gene,, which was not screened during the MAS procedure.

The screening of BLB found that all the five candidate lines and KH, which contain thegene, were classified as moderately resistant to SK1-2 and XON2-1 strains, and susceptible to NP3-5, XORE1-1 and CR2-4 strains. In addition, KP48-1-5 and KP48-1-9were classified as moderately resistant to CN1-3 strain, while BC95-2-12, BC95-2-14, BC95-2-7 and KH were classified as moderately susceptible (Fig. 5-B).

gene resistance to blast disease was detected in every candidate line because their parents (RB, PinK4 and KH) have already possessed this gene. The blast disease screening of seven mixed groups indicated that all the candidate lines and a resistant check (Jao Hom Nin, JHN) were moderately resistant to resistant against blast. However, the parent varieties were resistant to most of the seven mixed groups, except PinK4, which was susceptible to mixed group 1 and moderately resistant to mixed group 5, while RB was moderately resistant to mixed group 5 (Fig. 5-C).

Table 3. SNP/InDel marker information on breeding lines identified in wet seasons of 2018 (WS18) and 2019 (WS19).

‘+’, Desirable allele; ‘-’, Uundesirable allele; ‘+/+’ or ‘-/-’, Homozygous; ‘+/-’, Heterozygous. Blue color marks homozygosity in the target genes.

Fig. 5. Evaluation of candidate lines for brown planthopper (BPH), bacterial leaf blight (BLB) and blast resistance during wet season in 2019.

A, Resistance of candidate lines, parents and control varieties against three biotypes of BPH. KPP, TPY and SBR refer to BPH populations of Kamphaeng Phet, Ta Phaya and Sing Buri, respectively.

B, Resistance of candidate lines, parents and control varieties against six strains of BLB.

C, Resistance of candidate lines, parents and control varieties against seven mixed strain groups of the blast.

SES, Standard evaluation system. Data are Mean ± SD (= 30).

Evaluation of agronomic traits and grain yield

The five candidate lines of the advanced progeny (in DS19 and WS19) exhibited non-significant GYs, but the agronomic traits among lines/varieties were significant (< 0.05), as shown in Table 1. In addition, the five candidate lines in the two yield trials were also compared with those in the preliminary yield trial in WS18. DFs in WS18 and WS19 were earlier than those in DS19 in all the lines/varieties. However, the GYs in WS18 and WS19 were higher than those in DS19. In addition, the other agronomic traits varied among the lines and seasons.

GYs of the five candidate lines in DS19 and WS19 were not significant from those of DOA1 and DOA2, but were significant from those of AK and KH in WS19 (Table 1). In addition, the genotype and genotype- by-environment (GGE) biplot of GY stability was analyzed (Fig. 6-A).

The relationship between the mean GY and PC1 indicated that KP48-1-5 had the highest stability, followed by BC95-2-14 with the highest GY. The second highest average GY was observed for KP48-1-9, but it had low stability. Notably, the control varieties AK and KH had good stability relative to DOA1 and DOA2. In addition, the stability of these varieties was lower than that for KP48-1-5 and BC95-2-14. The biplot graph between PC1 and PC2 of GY in Fig. 6-B showed that KP48-1-5 was also highly stable, followed by BC95-2-14, KP48-1-9 and BC95-2-7 during all the three seasons.

Evaluation of cooking quality and sensory test

In WS19, physicochemical and cooking quality traits of the candidate lines and control varieties were analyzed (Table 4). The rice flour from RB and KP48-1-5 had the highest protein contents compared to the other lines/varieties. The cooking times (CT) of different lines and control varieties ranged from 10.5?23.0 min. RB and BC95-2-14 had the highest CT. The pasting properties of the candidate lines and control varieties displayed no systematic trend. The textural properties in terms of hardness and stickiness, which were measured using the texture profile analysisof cooked rice displayed significant differences among rice varieties.

Fig. 6. Biplot graphs of grain yield and grain quality of five candidate lines and their control varieties.

A, Biplot graph of the PC1 score versus the mean grain yield of five candidate lines and the control varieties in WS18, DS19 and WS19.

B, Biplot graph of the PC1 score versus the PC2 score for the grain yields of five candidate lines and the control varieties in WS18, DS19 and WS19.

C, Biplot graph of the PC1 score versus the PC2 score for the grain quality of five candidate lines and the control varieties. AC, Amylose content; SB, Setback; CPV, Cold paste viscosity; HPV, Hot paste viscosity; PV, Peak viscosity; BD, Breakdown; PC, Protein content.

WS18, DS19 and WS19 refer to wet season in 2018, dry season in 2019 and wet season in 2019, respectively.

The hardness is negatively correlated with the stickiness of cooked rice (Tao et al, 2020). In this study, both BC95-2-7 and KP48-1-5 presented the highest hardness values, while KP48-1-5 had lower stickiness than BC95-2-7.

The correlation coefficients () of the factors for all the rice samples are presented in Table 5. The results showed that the parameters including peak viscosity (PV), breakdown (BD), hot paste viscosity (HPV), cold paste viscosity (CPV), setback (SB) and AC played important roles and had positive relationships with one another. AC is considered the most important determinant of cooked rice texture, and positive correlations between AC and HPV, CPV and SB were found. The hardness had a negative correlation with AC (= -0.182), therefore, AC may not suitable to be used as a parameter to predict the texture of cooked rice as suggested in other previous studies.

Table 4.Physicochemical and cooking qualities of candidate lines compared with their parents and commercial varieties in wet season in 2019.

Different lowercase letters in the same column indicate significant difference at the 0.05 level using the LSD method.

Table 5.Correlation coefficients (r) of factors for all rice samples.

* and ** represent significance at the 5% and 1% levels, respectively.

The two principal components explained a total of 69.48% of the variation (Fig. 6-C). The first principal component (PC1) accounted for 47.06% of the variation and seemed to differentiate rice samples according to their PV, HPV, CPV, SB and protein content values. The second principal component (PC2) accounted for 22.42% of the variation and primarily explained the textural attributes of cooked rice, and AC was negatively correlated with BD. Positive correlations were observed between PV and HPV, BD, CPV and SB. In addition, to classify the candidate lines with control varieties using all the factors, four distinct groups of rice were identified. The first was PinK4, which had a high AC, SB and PV. Second, KP48-1-5, KP48-1-9 and BC95-2-7 were found to have similar protein content, stickiness and hardness values. Third, BC95-2-12, BC95-2-14, KH and DOA2 were higher in BD than the other varieties, and had other chemical and cooking properties that were notably more similar to each other. Finally, RB had the lowest values for the pasting properties (SB, CPV, HPV, PV and BD), and these unique characteristics made this rice variety distinct from the other lines/ varieties.

DISCUSSION

Agronomic and environmental factors

Geographically,is cultivated in temperate regions. Thus, the grain yields ofrice grown in tropical regions are usually 1–3 t/hm2, while the yields ofrice grown in temperate areas are 4–6 t/hm2(Kobayashi et al, 2018). Mostrice plants show insufficient vegetative growth, premature flowering and spikelet sterility under high temperatures, which are the primary reasons for their poor growth and low grain yields in tropical regions (Yoshida, 1983; Lee et al, 2018). In this study, the short grain lines and control varieties showed clear differences in DF between the wet season (75 d in WS18 and 68 d in WS19) and dry season (91 d in DS19). This result can be explained by the average temperature during the wet season was higher than that during the dry season by approximately 3 oC in both the day and night. In addition, the candidate lines did not flower earlier thanvarieties (AK and KH). Thus, the adaptability of the candidate lines to a tropical climate was improved relative to theirparents.

The GYs of the four candidate lines during the three seasons were higher than those of KH and AK, but were not significant for DOA1 and DOA2. Hosoi (1979) recommended that KH can be cultivated at latitudes ranging from 31o N to 40o N, and it is sensitive to high temperatures. Therefore, KH had a lower GY in the Phan district of Thailand than at the latitude of 19o N. Thus, in this breeding program, methodological factors, including the air temperature, relative humidity and amount of rainfall between the wet and dry seasons were different, which then affectedthe agronomic traits and GY. However, it was confirmed that the four candidate short grain lines had good agronomic traits and produced GY that were similar to those of the former varieties in a tropical climate.

Genetic background

Surprisingly, the genetic background of KP48-1-5, which derived from the pedigree selection, was the closest to that of KH, rather than the lines (BC95-2-12 and BC95-2-14) that came from the backcross method. According to the theory of backcross breeding, 75% of the genetic background in BC1is close to the recurrent parent, while 50% of the genetic background in F2during pedigree selection is close to the parent (Allard, 1960). In this breeding program, backcrossing to the recurrent parent (KH) occurred until BC1because KH is very sensitive to adaptation to tropical regions. Thus, if the backcross process followed the theory (until BC8), the genetic background of KH will be increased in backcross progenies and then adaptability and agronomic performance may be decreased. However, the genetic background of BC95-2-14 derived from the backcross was closer to that of AK, which is derived from KH × Ouu292 (Kobayashi et al, 2018). In addition, most of the selected breeding lines from BC1F4and F5were identified in thegroup.

Biotic stress resistance

KH is very susceptible to leaf blast, moderately susceptible to panicle blast and slightly resistance to BLB in most paddy fields in Japan (Ishizaka et al, 1989; Hori et al, 2017). By contrast, DOA1 and DOA2 are susceptible to leaf blast, BLB and BPH (Warinrak, 2013). Therefore, this breeding strategy used both molecular and conventional approaches to combine resistance to multiple biotic stresses, including blast (), BLB () and BPH resistance (and) genes/QTLs in candidate lines, especially in KP48-1-5 and KP48-1-9.

For BPH resistance,andgenes were detected in the selected lines. The candidate lines did not show higher levels of resistance than Ratuhinati (resistant check) because other resistance genes such as,,andfor BPH were not introgress during this breeding program. KP48-1-5 and KP48-1-9, in whichandwere already identified, were more resistant to BPH than the DOA1 and DOA2 varieties.

When considering BLB, Yugander et al (2017) reported that single resistance gene for BLB cannot provide durable resistance against the prevalent pathotypes. Thus, using a combination of three or four genes is broadly effective. However, among the various available BLB resistance genes,is reported to confer broad-spectrum resistance againstraces (Das and Rao, 2015). In this study, PinK4 hadand, while KH had only. However, all the candidate lines only had. This finding suggested that the priority trait in this study is grain shape, while thegene was not identified in the short grain phenotype from earlier generations. However, the levels of resistance to BLB in the candidate lines were better than those of KH and the current varieties DOA1 and DOA2.

Thegene commonly used in rice breeding around the world originated fromcultivars and was introgressed intocultivars to control rice blast disease in the 1950s (Rybka et al, 1997). In this study, PinK4 (Ruengphayak et al, 2015), RB (unpublished) and KH (Kobayashi et al, 2018) carried thegene. Thus, all the candidate lines contained this gene and showed resistant to moderately resistant reactions against blast disease in every mixed strain group.

Grain and cooking qualities

Generally,rice shows decreased cooking quality and a tendency towards decreased palatability when grown at daytime/nighttime temperatures exceeding 28 oC / 20 oC (Chun et al, 2015; Zhao et al, 2017). In general, the AC of KH is relatively low (17.5%) (Ise et al, 2001). In this study, the AC of KH grown in WS18 and WS19 were 17.82% and 15.49%, respectively, while the AC of the candidate lines ranged between 19.34% to 20.16% and 17.27% to 18.86% in WS18 and WS19, respectively. Therefore, the candidate lines were sufficient to produce good grain quality. In addition, the milled grain length to width ratio of the candidate lines was less than 2.0 for candidates identified as short grain types (Juliano and Villareal, 1993). This indicated that the breeding program derived from long grain () × short grain () was successful in obtaining short grain rice by phenotyping with MAS ().

The cooking quality of rice primarily depends on AC, which determines the texture of cooked rice and the gelatinization temperature (Saleh and Meullenet, 2015). PinK4, therice variety, had the highest AC, which resulted in a high gelatinization temperature and high paste viscosity, but had less hardness than the others. This result may explain how the structural characteristics of other chemical components such as protein influence cooked rice quality (Hamaker and Griffin, 1993). Interestingly, different observations regarding the correlations of AC, protein content and texture of cooked rice were not found in the candidate lines. This may be due to the thickness of rice kernels. For example, PinK4 is white rice while RB is colored rice. Moreover, Li et al (2016) reported that the difference in cooking properties between rice varieties may be due to their genetic make-up and differences in their granular structure, such as the amylopectin chain length.

The PCA results revealed that four distinct groups of rice were identified based on physicochemical and eating quality. There were clear distinctions between the samevarieties, PinK4 and RB, because one is white rice and the other is purple rice. For the candidate lines, two groups were separated from each other, but members of each group were clustered together without differences among accessions from theandgroups. Three candidate lines, KP48-1-5, KP48-1-9 and BC95-2-7, had higher scores for overall sensory quality and were in the same cluster that tended to have similar protein content (6%?8%) and hardness properties (31?45 N). However, KP48-1-9, which had lower protein content and moderate hardness, had the highest overall sensory score. The results were consistent with the findings of Xu et al (2018), who suggested that the overall sensory quality is negatively correlated with protein content and positively correlated with hardness. Therefore, protein content and hardness can provide good estimates for the eating quality of cooked rice. Similar characteristics between BC95-2-12 and KP48-1-9, including low protein content and moderate hardness were found, but the dissimilar factors were the pasting characteristics, in which BC95-2-12 showed higher viscosity than KP48-1-9. Previous studies reported that eating quality has significantly positive correlations with minimum viscosity, final viscosity and setback (Nakamura et al, 2004; Tong et al, 2014). Therefore, candidate lines with high eating quality tended towards low hardness and viscosity. The overall results indicated that genetic factors as well as physicochemical properties are involved in creating different variations in eating quality traits in the crossbred lines amongandrice.

An ideal rice variety should exhibit a high yield, stable performance over a wide range of environments and good cooking quality. Therefore, four promising short grain breeding lines, KP48-1-5, KP48-1-9, BC95-2-12 and BC95-2-14, exhibited good agronomic performance (Fig. S2) and maintained grain yields that were not lower than those of the DOA1 and DOA2. Moreover, MAS can introgress multiple genes for biotic stress resistance and grain quality into promising lines. In addition, the four promising lines had high sensory test values and cooked taste scores that were close to those of KH and DOA2. In the future, the four promising lines will be subject to yield trials on a farmer’s fields to confirm the potential and to evaluate farmer satisfaction. Subsequently, the best line will be released as a commercial variety in the northern part of Thailand.

METHODS

Growth conditions

The study was conducted from 2015 to 2019 at Tana Grain Polish, Ltd., Phan district, Chiang Rai Province, Thailand (19o35′ N, 99o44′ E, 413 m above sea level). The rice plants were seeded in a field nursery. After 30 d, the rice seedlings were transplanted into breeding plots. The soil in the Phan district consisted of 1.56% organic matter, 0.07% total N, 26.70 mg/kg available P, 75.54 mg/kg exchangeable K, 629.0 mg/kg exchangeable Ca and 76.50 mg/kg exchangeable Mg, and had a pH of 5.40. Additionally, basal fertilizer was applied at 15 d after planting at a rate of 33.7 kg/hm2of N (diammonium phosphate) and 41.3 kg /hm2of P2O5. The second split of fertilizer was applied at the booting stage (65 d after planting) at a rate of 57.5 kg /hm2of N. Other management practices were performed in accordance with conventional high yielding cultivation approaches. The weather data, including air temperature, relative humidity and amount of rainfall in the field, were measured every 3 h each year (2015?2019) with a data logger (WatchDog 2000 Series Micro Stations, Spectrum Technologies, Inc., USA).

Screening SNP/InDel markers by Kompettitive Allele Specific PCR (KASPTM) genotyping technology

The SNP/InDel markers included starch (wx), gelatinization temperature (), short grain (), aroma (), blast resistance (), BLB (and), BPH (and) and submergence tolerance () genes were conducted in F2, F5and F7(Table S1). All KASP genotyping was performed using the LGC SNP line system following the standard KASP protocols (LGC Group, 2016). The thermal cyclers of PCR is shown in Table S2. Finally, the PCR products were analyzed for their genotypes using PHERAstarPlus SNP (LGC, Serial No. 470-0319, Middlesex, UK).

Breeding schemes

The breeding program for short grain rice involved the pairwise crossing is shown in Fig. 1. First, KH was crossed with RB to obtain F1seeds that were then divided two ways. The resulting F1plants were backcrossed to KH to produce BC1F1and selfed to produce F2seeds. After that, the pedigree selection was used for selection in both methods until BC1F6and F7, respectively. The second crossing, KH was crossed with PinK4 to obtain F1seeds and then selfed to produce F2seeds. After that the pedigree selection was used for selection until F7. The standardgrain shape (Juliano and Villareal, 1993) was used as a criterion for phenotypic selection.

The selected lines in the BC1F4and F5resulting from pairwise crossing were grown for a preliminary yield trial with the parents and control varieties (RB, PinK4, KH, AK, DOA1 and DOA2) during WS18 (June–September, 2018). The experiment was conducted as a randomized complete block design (RCBD), with three replications. The plot size for each treatment was 2.5 m × 2.5 m with a spacing of 25 cm × 25 cm.

The yield trial experiments on the BC1F5and F6were conducted during DS19 (January?April, 2019), and then the BC1F6and F7were validated with the parents and control varieties during WS19 (June?September, 2019). The RCBD with three replications was applied during both seasons. The plot size for each treatment was 2.5 m × 3.5 m with a spacing of 20 cm × 20 cm.

Agronomic trait determination during yield trials

The agronomic traits examined included DF, plant height, number of tillers per plant, number of panicles per plant, 1000-grain weight and GY. These traits were determined for rice plants grown during field trails in 2018 and 2019. DF was recorded when 100% of the individual plants in each plot flowered. Plant height, number of tillers per plant and number of panicles per plant were measured at maturity. GY in each plot was determined by finding the per harvested area of 6.25 or 8.75 m2. The grain moisture was adjusted to 14% and then extrapolated to units of kg/hm2. Following threshing, the grains were weighed to obtain the 1000-grain weight.

Evaluation of grain quality

The dried grains were stored at room temperature for one month prior to the grain quality evaluation. Paddy grains (300 g) were sampled from each replicate. The paddy grains were dehulled and polished using a mini-polisher. Three physical grain qualities, namely, grain length, grain width and grain length to width ratio of both paddy rice and milled rice, were measured by using a two-decimal-point digital Vernier caliper. Three chemical grain qualities, gelatinization temperature (GT), AC and protein content, were evaluated according to Juliano (1985).

Evaluation of cooking quality

Cooking characteristics including cooking time and the texture of cooked rice were studied on polished rice samples. Cooking time of the rice samples was determined according to Juliano (1985). A textural analysis of cooked rice samples was conducted with a texture analyzer equipped with a 35 mm cylindrical probe attachment (TA.XT Plus, Stable Micro System Corp., UK) according to Li et al (2016) with modifications. The pasting properties of the rice flours were evaluated according to the AACC method (AACC, 2000). The viscosity changes were measured using a Rapid Visco Analyzer (RVA, Model 4-D, Newport Scientific, Australia).

Evaluation of sensory quality of cooked rice

The rice cooking procedure by Xu et al (2018) was applied. The rice was cooked using the preset cooking setting of a rice cooker (Sharp model KS-ZT18, Thailand). Seven panelists who had been well-trained in the principles and concepts of descriptive sensory analysis participated in the sensory quality evaluation. The sensory items included smell (scores 1?5), appearance (scores 1?5), stickiness (scores 1?5), softness (scores 1?5) and taste (scores 1?5). A comprehensive assessment was made based on the above factors. Using a relative scale, the panelists gave a score for each attribute compared with the reference sample attributes, and the overall quality was the sum of the scores for all the attributes.

Phylogenetic analysis based on GBS

To determine the genetic background of the breeding lines (BC1F4and F5) compared with their parents, a phylogenetic analysis was performed. DNA from the rice leaves was isolated according to the DNeasy Plant Mini Kit (Qiagen, Germany) protocol, and then sequenced on an Illumina HiSeq X by Novogene AIT, Singapore. The Bowtie 2 program was subsequently used to align the nucleotides (Langmead and Salzberg, 2012), and the GATK program was used to analyze the single-nucleotide polymorphisms (SNPs) in each sample (McKenna et al, 2010). Finally, the nucleotide sequences from the breeding lines and control varieties were used to construct a phylogenetic tree using the MEGA X program.

Evaluation of biotic stress resistance

BPH resistance screening

Three BPH populations Kamphaeng Phet, Sing Buri and Ta Phaya were used to screen BPH resistance in the candidate lines and their parents with susceptible (TN1) and resistant (Ratuhinati) check varieties. Standard seed box screening was conducted at the seedling stage under greenhouse conditions according to Heinrichs et al (1985). Damage scores were recorded by using a standard system for evaluating damage (IRRI, 2013).

BLB resistance screening

CN1-3, NP3-5, XORE1-1, CR2-4, SK1-2 and XON2-1 isolates (Wonglom et al, 2015) were used to screen BLB resistance in the candidate lines and their parents with susceptible (KDML105) and resistant (PYBB-36) check varieties. Each isolate was grown following the methods described by Win et al (2012). The inoculation method was followed Theerayout et al (2009). The resistance reaction was classified as resistant, moderately resistant, moderately susceptible and susceptible described by Yang et al (2003).

Leaf blast resistance screening

Seven mixed groups of Thai(Table S3) were used to screen blast resistance in candidate lines and their parents with Sariceltik (resistant) and JHN (susceptible) varieties. The screening protocol was followed Marchetti et al (1987) and the disease scoring was recorded on a standard system for evaluating damage (IRRI, 2013).

Statistical analysis

All the data were analyzed using R program version 3.6.1 to test the significance of the agronomic trait and cooking quality results. The means were separated using the Duncan’s test at alpha levels of 0.05. If there was significant difference among the experiments for a given parameter, then the values from all of the experiments for that parameter were used to obtain the means and standard error. PCA was employed to reduce the complexity of the data. In addition, the AMMI model was used to analyze the G × E interactions (Gauch, 1988).

ACKNOWLEDGEMENT

This study was supported by the Tana Group International Co. Ltd., Thailand (2015?2019).

SUPPLEMENTAL DATA

The following materials are available in the online version of this article at http://www.sciencedirect.com/journal/rice-science; http://www.ricescience.org.

Fig. S1. Weather data from WS15?WS19 in Phan district, Chiang Rai Province, Thailand.

Fig. S2.Phenotypes of four promising lines and their parents in wet season in 2019.

Table S1. Gene-based/linked markers used for foreground selection of biotic resistance, abiotic tolerance and cooking quality for their validation in the breeding lines.

Table S2. Thermal cycling conditions for polymerase chain reaction amplification used by HydrocyclerTM.

Table S3. Seven mixed strain groups of blast diseases in Thailand as classified by amplified fragment length polymorphism.

AACC. 2000. Approved Methods of the American Association of Cereal Chemists. 10th edn. St. Paul, MN, USA: America Association of Cereal Chemists, John Wiley & Sons Inc.

Allard R W. 1960. Principles of Plant Breeding. New York, USA: John Wiley & Sons Inc.

Chun A, Lee H J, Hamaker B R, Janaswamy S. 2015. Effects of ripening temperature on starch structure and gelatinization, pasting, and cooking properties in rice ()., 63: 3085–3093.

Das G, Rao G J. 2015. Molecular marker assisted gene stacking for biotic and abiotic stress resistance genes in an elite rice cultivar., 6: 698.

Gauch H G. 1988. Model selection and validation for yield trials with interaction., 44: 705–715.

Hamaker B R, Griffin V K. 1993. Effect of disulfide bond-containing protein on rice starch gelatinization and pasting., 70: 377–380.

Heinrichs E A, Medrano F G, Rapusas H R. 1985. Genetic Evaluation for Insect Resistance in Rice. Los Banos, the Philippines: International Rice Research Institute.

Hori K, Yamamoto T, Yano M. 2017. Genetic dissection of agronomically important traits in closely related temperaterice cultivars., 67: 427–434.

Hosoi N. 1979. Studies on meteorological fluctuation in the growth of rice plants: III. Relation between the heading response of rice varieties to temperature under natural daylength and the thermos- sensitivity, photosensitivity, basic vegetative growth under controlled environments., 29: 294–304. (in Japanese with English abstract)

International Rice Research Institute (IRRI). 2013. Standard Evaluation System (SES) for Rice. 5th edn. Los Banos, Manila, the Philippines: International Rice Research Institute: 46.

Ise K, Akama Y, Horisue N, Nakane A, Yokoo M, Ando I, Hata T, Sito M, Numaguchi K, Nemoto H. 2001. ‘Milky queen’, a new high-quality rice cultivar with low amylose content in endosperm., 2: 39–61. (in Japanese with English abstract)

Ishizaka S, Uehara Y, Fujita Y, Okuno K, Horiuchi H, Miura K, Nakagahra M, Yamada T, Uchiyamada H, Samoto S. 1989. Breeding process and characteristic of new released variety Kinuhikari., 24: 25–27. (in Japanese)

Juliano B O. 1985. Criteria and test for rice grain quality.: Rice Chemistry and Technology. Saint Paul, USA: American Association of Cereal Chemists (AACC): 443–513.

Juliano B O, Villareal C P. 1993. Grain Quality Evaluation of World Rice. Manila, the Philippines: International Rice Research Institute.

Kang K H. 2010. Made for the TROPICS., 9: 34–35.

Kobayashi A, Hori K, Yamamoto T, Yano M. 2018. Koshihikari: A premium short-grain rice cultivar: Its expansion and breeding in Japan., 11: 15.

Langmead B, Salzberg S. 2012. Fast gapped-read alignment with Bowtie 2., 9: 357–359.

Lee J S, Torollo G, Ndayiragije A, Bizimana J B, Choi I R, Gulles A, Yeo U S, Jeong O Y, Venkatanagappa S, Kim B K. 2018. Genetic relationship of tropical region-bred temperaterice () plants and their grain yield variations in three different tropical environments., 137: 857–864.

LGC Group. 2016. SNPline genotyping automation. https://www. lgcgroup.com/products/genotyping-instruments/snpline/#.XFCv91xKhaQ. (Accessed 5 January 2020)

Li H, Prakash S, Nicholson T M, Fitzgerald M A, Gilbert R G. 2016. The importance of amylose and amylopectin fine structure for textural properties of cooked rice grains., 196: 702–711.

Marchetti M A, Lai X, Bollich C N. 1987. Inheritance of resistance toin rice cultivar grown in the United States., 77: 799–804.

McKenna A, Hanna M, Banks E, Sivachenko A, Cibulskis K, Kernytsky A, Garimella K, Altshuler D, Gabriel S, Daly M, DePristo M A. 2010. The genome analysis toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data., 20: 1297–1303.

Miyamoto M. 2017. Influence of changing Thai society on the Japanese restaurant industry in Thailand., 20: 13–32.

Nakamura S, Okadome H, Yoza K, Haraguchi K, Okunishi T, Suzuki K, Sato H, Ohtsubo K. 2004. Differentiation and search for palatability-factors of world-wide rice grains by PCR method., 78: 764–779. (in Japanese with English abstract)

Nakwilai P, Cheabu S, Narumon P, Saensuk C, Arikita S, Malumpong C. 2020. Evaluation ofrice (L.) varieties and their improvement in terms of stability, yield and cooking quality by pure-line selection in Thailand., 46: 157–168.

Poosri S, Thilavech T, Pasukamonset P, Suparpprom C, Adisakwattana S. 2019. Studies on Riceberry rice (L.) extract on the key steps related to carbohydrate and lipid digestion and absorption: A new source of natural bioactive substances., 17: 17–23.

Ruengphayak S, Chaichumpoo E, Phromphan S, Kamolsukyunyong W, Sukhaket W, Phuvanartnarubal E, Korinsak S, Korinsak S, Vanavichit A. 2015. Pseudo-backcrossing design for rapidly pyramiding multiple traits into a preferential rice variety., 8: 7.

Rybka K, Miyamoto M, Ando I, Saito A, Kawasaki S. 1997. High resolution mapping of the-derived rice blast resistance genes: II.andand a consideration of their origin.,10:517–524.

Seemanon K, Yamao M, Hosono K. 2015. Production of Japanese rice through contract farming system in Wiang Pa Pao district, Chiang Rai Province, Thailand., 3(2): 41–51.

Saleh M, Meullenet J F. 2015. Cooked rice texture and rice flour pasting properties; impacted by rice temperature during milling., 52: 1602–1609.

Tao K, Yu W, Prakash S, Gibert R G. 2020. Investigating cooked rice textural properties by instrumental measurements., 9(2): 130–135.

Theerayout T. 2009. Identification of microsatellite markers (SSR) linked to a new bacterial blight resistance gene(t) in rice cultivar ‘Ba7’., 3: 235–247.

Tong C, Chen Y L, Tang F F, Xu F F, Huang Y, Chen H, Bao J S. 2014. Genetic diversity of amylose content and RVA pasting parameters in 20 rice accessions grown in Hainan, China., 161: 239–245.

Wada T, Yasui H, Inoue T, Tsubone M, Ogata T, Doi K, Yoshimura A, Matsue Y. 2013. Validation of QTLs for eating quality ofrice ‘Koshihikari’ using backcross inbred lines., 16(2): 131–140.

Warinrak B. 2013. Japonica Rice Production Technology in Thailand. Rice Department, Thailand: CRC. (in Thai)

Win K M, Korinsak S, Jantaboon J, Siangliw M, Lanceras- Siangliw J, Sirithunya P, Vanavichit A, Pantuwan G, Jongdee B, Sishiwong N, Toojinda T. 2012. Breeding the Thai jasmine rice variety KDML105 for non-age-related broad-spectrum resistance to bacterial blight disease based on combined marker-assisted and phenotypic selection., 137: 186–194.

Wonglom P, Watcharachaiyakup J, Patarapuwadol S, Kositratana W. 2015. Assessment of diversity among pathotype ofpv.prevalent in Thailand., 46(2): 165–175. (in Thai with English abstract)

Xu Y J, Ying Y N, Ouyang S H, Duan X L, Sun H, Jiang S K, Sun S C, Bao J S. 2018. Factors affecting sensory quality of cookedrice., 25(6): 330–339.

Yang Z, Sun X, Wang S, Zhang Q. 2003. Genetic and physical mapping of a new gene for bacterial blight resistance in rice., 106: 1467–1472.

Yoshida S. 1983. Rice.: Smith W H, Banta S J. Potential Productivity of Field Crops under Different Environments. Los Ba?os, the Philippines: International Rice Research Institute: 103–127.

Yugander A, Sundaram R M, Ladhalakshmi D, Hajira S K, Prakasam V, Prasad M S, Madhav M S, Babu V R, Laha G S. 2017. Virulence profiling ofpv.isolates, causing bacterial blight of rice in India., 149: 171–191.

Zhao C J, Xie J Q, Li L, Cao C J. 2017. Comparative transcriptomic analysis in the paddy rice under storage and identification of differentially regulated genes in response to high temperatureand humidity., 65: 8145–8153.

10 August 2020;

26 October 2020

Chanate Malumpong (agrcnm@ku.ac.th)

Copyright ? 2021, China National Rice Research Institute. Hosting by Elsevier B V

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Peer review under responsibility of China National Rice Research Institute

http://dx.doi.org/10.1016/j.rsci.2021.07.008

(Managing Editor: Wu Yawen)