AS SESS MENT OF VARI ABIL ITY AND AS SO CI A TION ANAL Y SIS AMONG QUAL ITY
PARAMETERS OF RICE (
Oryza sativa
L.)
Priyanka Biswas, B. Sharma and M. Parikh
De part ment of Ge net ics and Plant Breed ing, Indira Gan dhi Krishi Vishwavidyalaya, Raipur 492 012 Chhattisgarh, In dia. Email: [email protected]
ABSTRACT
Forty-seven rice (Oryza sativa L.) genotypes were evaluated during kharif 2015 to estimate the genetic variability and to know the association among fifteen physicochemical and cooking quality traits. Among the traits, L/B ratio after cooking showed the maximum coefficients of variation (32.15 %) followed by Kernel L/B ratio (27.29 %), Gel consistency (26.30 %) and Alkali spreading value (24.15 %), indicating that there should be existence of variability for these traits. The significant and positive correlation was noticed for hulling per cent with milling percent (r = 0.607) and hulling per cent head rice recovery (r = 0.301), indicated that these are the primary traits for improvement of rice grain quality.
Key words : Vari abil ity, cor re la tion, qual ity, rice.
More than 90% of the world’s rice is grown and consumed in Asia, where 60% of the calories are consumed by 3 billion Asians (1). Rice is one of the major food grain crops in the world particularly in Asian countries. Rice crop is interwoven in the cultural, social and economic lives of millions of Indians and it holds the key for food and nutritional security of the country. India has the largest area and got second rank in rice production among the rice growing countries. However, its share for export in international market is less than five percent due to lacking in grain quality characteristics. Rice quality includes head rice recovery, kernel size, kernel shape, kernel length after cooking, elongation ratio, elongation index, and Gel consistency. Traditionally, rice plant breeders concentrated on breeding for high yield. In recent decades as living conditions are being steadily improved, human demand for high quality rice is continuously on increase, which entailed in incorporation of preferred grain quality features as the most important objective next to enhancement in yield. Also quality characteristics increase the total economic value of rice. Hence, improving rice grain quality has been a major concern in rice breeding programs to meet the consumer preference and market demand.
A wide range of genetic variability has been reported for quality traits in the past , but still their exist untapped genetic variability in germlasm which is of paramount importance in selecting the potential parent so as to get maximum heterosis and superior recombinants with respect to quality parameters (2). The correlation among grain quality and its components provide the information about their performance and association with one another. With the above background information, the present investigation was undertaken to estimate variability for quality characteristics and unravel the
correlation of different grain quality parameters among a set of 47 rice genotypes.
MATERIALS AND METHODS
Forty seven accessions of rice (Oryza sativa L.) which includes varieties, red rice and land races (Table-1) were grown at Research cum Instructional Farm, IGKV, Raipur during Kharif 2015. Seed harvested from these lines were used for quality analysis. Mature seeds from each genotype were harvested individually. The seeds were oven dried. The seed was dehusked in a Satake laboratory huller and polished in a Satake Rice Polisher. The polished seed obtained was then utilized for the analysis of fifteen seed quality traits namely hulling per cent, milling per cent, head rice recovery percentage, grain length (mm), grain breadth (mm), kernel length (mm), kernel breadth (mm), length/breadth ratio (L/B), kernel length after cooking (KLAC) (mm), kernel breadth after cooking (KBAC) (mm), length/breadth ratio (L/B) after cooking, kernel elongation ratio (ER), Elongation index (EI), alkali spreading value and gel consistency (mm), at Crop Quality Laboratory, Department of Genetics and Plant Breeding, College of Agriculture, IGKV, Raipur (C.G.).
Estimation of quality parameters : Milling percentage was calculated by dividing the weight of milled rice by weight of paddy. The HRR percentage and broken rice were calculated using the standard formula of (weight of milled rice/weight of grain) x 100] (3). Twenty grains at random from each sample were dehusked by hand and the length and breadth in millimeters was recorded. The L/B ratio was calculated by dividing the average length by the average breadth of rice kernel. Based on the L/B ratio, grains were classified into long slender (LS), short slender (SS), medium slender (MS), long bold (LB) and short bold (SB). Kernel elongation ratio (ER) was calculated by dividing the average length of cooked kernel by the
average length of the raw rice (4). KLAC was measured by the method of (5). ASV was estimated by the method advocated by (6). The simplified procedure suggested by (7) was used for estimating gel consistency.
Data analysis and inter-relationship : Frequency distribution was computed to categorize the genotypes into different classes. Simple statistics (Mean, Ranges, Standard deviation and Coefficient of variation) was calculated to have an idea of existing variability. Correlation coefficients between two variables were estimated by using the formula proposed by (8).
RESULTS AND DISCUSSION
Quality characters are important for plant description and mainly influenced by the consumers preference, socio-economic scenario and natural selection (9). Frequency distribution for fifteen quality traits is presented in Table-2. The variable expressions of all the quality traits were recorded for different accessions.
Basic statistics for all the quality traits is presented in Table 3. The wider range was observed for the Gel consistency (30.00-100.00 mm) followed by Head Rice recovery % (30.98 - 61.96 %) and Milling % (51.40 - 78.26 %). The coefficient of variation is useful tool for obtaining comparisons of variability in different characters. A
Table-1 : List of rice genotypes under study.
S. No. Genotypes S. No. Genotypes
1 Bashabhog 25 Dubraj
2 Ganga-Godavari 26 Amajhopa
3 Rau 3061 27 Khaju Jhopa
4 Pratiksha 28 Dulhabhog
5 IC 459643 29 Gangachur
6 Deshi safari 30 Malagkit sung song
7 Baikoni 31 Soth
8 IC 459207 32 IC 459644
9 Maasuri 33 Thaland/CBC
10 Bhokala 34 Parewadhan
11 Sarsariya 35 Gumdi
12 Hathi Panjari 36 Anjan
13 IGSR 2-1-6 37 Jalaka
14 Ganjeikalli 38 Barikumja
15 Thakur Bhog 39 IET 15835
16 Bhainsa Mundariya 40 Dudhkhasa
17 Shreeram 41 IR64
18 Dashehra matiya 42 Jaldubi
19 Tulasiful 43 Indira barani dhan 1
20 Katina 44 Pusa1121
21 Bohita 45 Safri17
22 Anjagdhan 46 Indira aerobic1
23 IC 252242 47 Dubraj selection 1
24 Chhatri
Table-2 : Frequency distribution for fifteen quality traits.
S. No.
Characters Category/
Class Interval
No. of genotypes
Percentage (%)
1. Grain length
(mm)
< 6 6.1 - 8.5 8.6 – 10.5 10.6 – 12.5
6 29 10 2
12.77 61.70 21.28 4.26
2. Grain
breadth (mm)
< 2 2.1 – 2.5 2.6 – 3.0
9 25 13
19.15 53.19 27.66
3. Hulling (% ) 65.5 – 70.5
70.6 – 75.5 75.6 – 80.5
> 90
8 23 15 1
17.02 48.94 31.91 2.13
4. Milling ( % ) 51.0 – 55.5
55.6 – 60.5 60.6 – 65.5 65.6 – 70.5
>70.5
4 8 20 14 1
8.51 17.02 42.55 29.79 2.13
5. Head rice
recovery (%)
30.0 – 40.5 40.6 – 50.5 50.6 – 60.5
> 60.5
11 21 12 3
23.40 44.68 25.53 6.38
6. Kernel
length (mm)
4.0 – 5.0 5.1 – 6.0 6.1 – 7.0 7.1 – 8.0 > 8.0
8 22 12 4 1
17.02 46.81 25.53 8.51 2.13
7. Kernel
breadth (mm)
1.0 – 1.5 1.6 – 2.0 2.1 – 2.5 > 2.5
3 27 16 1
6.38 57.45 34.04 2.13
8. Kernel L/B
ratio
1.0 – 2.0 2.1 – 3.0 3.1 – 4.0 4.1 – 5.0 > 5.1
4 22 18 2 1
8.51 46.81 38.30 4.26 > 5.1
9. Kernel
length after cooking (mm)
6.0 – 8.0 8.1 – 10.0 10.1 – 12.0
> 12.1
10 29 7 1
21.28 61.70 14.89 2.13
10. Kernel
breadth after cooking (mm)
< 3.0 3.1 – 3.5 3.6 – 4.0 4.1 – 4.5 > 4.5
6 21 17 2 1
12.77 44.68 36.17 4.26 2.13
11. Length
breadth ratio after cooking
1.0 – 2.0 2.1 – 3.0 3.1 – 4.0 > 4.1
4 36
6 1
8.51 76.60 12.77 2.13
12. Kernel
elongation ratio
1.0 – 1.5 1.6 – 2.0 2.1 – 2.5
25 18 4
53.19 38.30 8.51
13. Elongation
index
0.55 – 0.75 0.76 – 1.0 1.1 – 1.25
8 30
9
17.02 63.83 19.15
14. Alkali
spreading value
1.0 - 2.0 3 4.0 – 5.0 6.0 – 7.0
2 3 14 28
4.26 6.38 29.79 59.57
15. Gel
consistency
< 35 36 – 40 41 – 60 61 – 80 81 - 100
2 1 6 10 28
322 Vari abil ity and as so ci a tion anal y sis of rice
Table-3 : Descriptive statistics of 15 quality traits of 47 rice genotypes.
Characters Mean Range Range Min. Max. S.D. CV %
GL (mm) 7.89 6.40 5.60 12.00 16.95
GB (mm) 2.32 1.40 16.0 3.00 0.30 12.76
H (%) 74.50 23.35 67.54 90.89 3.83 5.14
M (%) 63.06 26.86 51.40 78.26 4.97 7.88
HRR (%) 46.34 30.98 30.98 61.96 8.18 17.64
KL (mm) 5.90 5.00 4.00 9.00 1.06 18.01
KB (mm) 1.99 1.20 1.40 2.60 0.30 14.80
KLBR 3.05 4.68 1.75 6.43 0.83 27.29
KLAC (mm) 9.15 12.00 6.00 18.00 1.82 19.86
KBAC (mm) 3.50 2.60 2.40 5.00 0.44 12.60
LBRAC 2.68 5.92 1.58 7.50 0.86 32.15
KER 1.57 1.00 1.11 2.11 0.25 15.84
EI 0.89 0.63 0.56 1.19 0.16 18.29
ASV 5.45 5.00 2.00 7.00 1.32 24.15
GC (mm) 78.66 70.00 30.00 100.00 20.69 26.30
Note : SD = Standard deviation, CV = Coefficient of variance, GL = Grain length,
GB = Grain breadth, H% = Hulling per cent, M% = Milling per cent,
HRR% = Head rice recovery percentage, KL = Kernel length, KB = Kernel breadth,
KLBR = Kernel length breadth ratio, KLAC = Kernel length after cooking, KBAC = Kernel breadth after cooking,
LBRAC = Length breadth ratio after cooking, KER = Kernel elongation ratio, EI = Elongation index,
ASV = Alkali spreading value, GC = Gel consistency.
Table-4 : List of top 5 entries for each quality trait.
S.
No. Characters
Top ranking genotypes
Genotype I Genotype II Genotype III Genotype IV Genotype V
1. GL (mm) Pusa1121
(12.00 mm)
IET 15835 (11.00mm)
Thaland/CBC (10.00mm)
Hathi panjari (10.00mm)
Indira barani dhan 1 (9.80mm)
2. GB (mm) Shreeram
(1.6mm)
Anjagdhan (1.6mm)
Pusa1121 (1.8mm)
Bashabhog (2mm)
Bohita (2mm)
3. HP % Indira barani dhan 1
(90.89%)
Anjan (80.26%)
Baikoni (79.94%)
Shreeram (79.36%)
IC 459643 (78.34%)
4. MP % Indira barani dhan 1
(78.26%)
IC 459643 (70.39%)
Sarsariya (68.65%)
Amajhopa (68.49)
Dulhabhog (68.03%)
5. HRR % Indira barani dhan 1
(61.96%)
IC 459643 (60.97%)
Sarsariya (60.58%)
IGSR-2-1-6 (58.63%)
Deshi safari (56.24)
6. KL (mm) Pusa 1121
(9.00mm)
IET 15835 (8.00mm)
Dashehra matiya (7.80mm)
Hathi panjari (7.80mm)
Thaland/CBC (7.20mm)
7. KB (mm) Shreeram
(1.4mm)
Anjagdhan (1.4mm)
Pusa1121 (1.4mm)
IC 459207 (1.6mm)
Dubraj (1.6mm)
8. KLBR Pusa 1121
(6.43)
IET 15835 (5.00)
Thaland/CBC (4.50)
Anjagdhan (4.00)
IR 64 (3.89)
9. KLAC(mm) Pusa 1121
(18.00mm)
IET 15835 (12.00mm)
IC 459207 (11.80mm)
Dubraj (11.60mm)
Bhainsa mundariya (11.20)
10. KBAC(mm) Pusa 1121
(2.40mm)
Indirabarani dhan 1 (2.60mm)
Pratiksha (3.00mm)
Dubraj (3.00mm)
Khaju jhopa (3.00mm)
11. LBRAC Pusa 1121
(7.50)
IET 15835 (4.00)
Dubraj (3.87)
IC 459207 (3.47)
Indirabarani dhan 1 (3.31)
12. KER IC 459207
(2.11)
Bhainsa mundariya (2.07)
Dubraj (2.07)
Jalaka (2.05)
Pusa 1121 (2.00)
13. EI Anjan
(1.19)
Pusa 1121 (1.17)
Thakur bhog (1.15)
Bhainsa mundariya (1.14)
Tulasiful (1.13)
14. ASV Bhainsa mundariya
(4.00)
Katina (4.00)
Gangachur (4.00)
Dudhkhasa (4.00)
Baikoni (5.00)
15. GC (mm) Indira aerobic 1
(44mm)
Bhainsa mundariya (45mm)
Katina (45mm)
Gangachur (46mm)
reasonable amount of genetic variation was displayed for the traits evaluated. Hulling % and Milling % were the only two characters with coefficient of variation (CV) values less than 10%. However, most traits have CV values above 10 % and as high as 32.15% for the Length Breadth ratio after cooking indicating that selection based on these characters is expected to be effective (10).
The number of genotypes showed better performance for different quality traits are depicted in Table 4. From this table, it was seen that Indira barani dhan 1, IC459643, Sarsariya, IGSR-2-1-6 and Deshi safari are top five entries for HRR %. Pusa 1121, IET 15835, Thaland/CBC, Anjagdhan and IR 64 for L/B ratio. IC459207, Bhainsa mundariya, Dubraj, Jalaka and Pusa 1121 for elongation ratio. The intermediate ASV found in the current experiment indicated medium disintegration of rice which is highly desirable for quality grain (11). Gel consistency measures the tendency of the cooked rice to harden on cooling. Rice grains with low gel consistency tend to be less sticky on cooking and are associated with harder cooked rices. Grains with intermediate gel consistency is one of the most preferred characteristics among the grain quality parameters. The genotypes Bhainsa mundariya, Katina and Gangachur possess moderate Alkali spreading value and Gel consistency.
Genotype Pusa 1121 shows maximum mean value for grain length (12.00 mm), kernel length (9.00 mm), kernel length after cooking (18.00 mm), kernel length breadth ratio (6.43) and kernel length breadth ratio after cooking (7.50). The genotype Indira barani dhan1 recorded maximum mean value for Hulling (90.89 %), Milling (78.26 %) and Head rice recovery (61.96 %). Maximum Kernel elongation ratio (2.11) and Elongation index (1.19) was shown by genotype IC459207 and Anjan respectively.
Correlation is a measure of the degree to which variables vary together or a measure of intensity of association. Correlation coefficient estimates showed the possibility of improvement of a character through selection for other character. In the present investigation, the correlation analysis indicated that the HRR % was highly significant and positively associated with milling percent (r = 0.600), whereas it showed significant and positively correlation with hulling percent (r = 0.301) (Table-5). Similar results were reported by several researchers (12). Head rice recovery showed negative but non-significant correlations with kernel dimensions like kernel length (r = -0.132) and L/B ratio (r = -0.193). These findings were in agreement with the findings reported earlier by (13). Genotypes with long slender grains are more prone to breakage than those possessing short bold grain.
Kernel length after cooking is one of the important cooking quality attributes. Lengthwise expansion after cooking is considered a high desirable trait in high quality rice such as basmati rice of India. It fetches maximum premium because of its linear elongation. Grain shape and visual appearance of rice before and after cooking are important to determine acceptance of a rice variety. Prime rice eating nations have the inclination towards varieties that elongate considerably after cooking. In this study, kernel length after cooking and kernel elongation ratio are interdependent as evidenced by the positive highly significant association between them (r = 0.435). Selection of either of the trait will ultimately enhance the mean performance of the interdependent trait. The positive highly significant association also observed between kernel length after cooking and L/B ratio after cooking (r = 0.900). The kernel breadth showed highly significant but negative correlation with L/B ratio. Similar association was reported by (14).
Physical quality trait namely L/B ratio was positively and highly significantly associated (r = 0.704) with cooking quality trait namely kernel length after cooking. L/B ratio is a good indicator of kernel length after cooking. Thus higher the L/B ratio, more the kernel length after cooking. Selection for these significantly and positively correlated traits will improve the overall quality trait.
CONCLUSIONS
From this study, we conclude that the genotypes possessed adequate variability for the quality traits under study. Considering all the grain quality traits, the genotype PUSA 1121 showed maximum mean value for grain length, kernel length, kernel length after cooking, kernel length breadth ratio and kernel length breadth ratio after cooking. Likewise, Indira barani dhan1 posses high Hulling %, Milling % and Head rice recovery %. Maximum Kernel elongation ratio and Elongation index was shown by genotype IC459207 and Anjan respectively. Bhainsa mundariya, Katina and Gangachur for moderate Alkali spreading value and Gel consistency. The above superior genotypes identified for traits of interest, can be used as donor in the crop improvement programme. Hulling %, milling % and HRR are important quality attributes for rice that enhances commercial success of a variety. Simultaneous improvement of these three quality traits can be made with the selection of a single trait is either hulling percent or milling percent or head rice recovery.
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