MATERIALS AND METHODS

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1 MATERIALS AND METHODS Time and Place Field studies were conducted from July 009 to May 010 at two locations, farmer s field in Bogor (elevation 00 m above sea level, ASL) and Pusakanagara experimental farm (8 m ASL), in the 009 dry season (DS) and 009 wet season (WS). Grain quality was evaluated in the grain quality laboratory at Muara Experimental Farm, Bogor. Randomized Complete Block Design (RCBD), in three replications was used. Materials tested were 35 promising aromatic lines and check varieties were Ciherang and Sintanur. The total treatments amounted to 37 lines (Table 1). The 1-day-old seedlings were planted one seedling per hole with spacing of 0 cm x 0 cm, in a plot size of m x 5 m per genotype; there were 50 plants per plot. The rice plants were fertilized with urea, SP36, KCl at the rates of 50 kg ha -1, 100 kg ha -1, 100 kg ha -1, respectively. Pests and diseases were controlled optimally. Parameters Observed Plants were observed at the generative phase. Yield components, plant height, and growth stage were observed from five plants of each line; procedures used by IRRI were followed. 1. Days to 50% flowering was number of days from sowing to time of flowering stage reaching 50% of the population.. Days to maturity; was number of days from seeding to grain ripening (90% of grains on panicle are mature). 3. Plant height (cm) was measured from soil surface to tip of the tallest panicle (awns excluded). 4. The number of productive tillers was the average number of tiller that could produce panicles per hill. 5. The amount of grains or filled spikelets per panicle. 14

2 Table 1. Genetic materials for research on developing NPT lines No. LINES COMBINATIONS 1 IPB 113-F-1 Pare Bau* x Fatmawati IPB 113-F- Pare Bau x Fatmawati 3 IPB 115-F-3- Fatmawati x Lambau* 4 IPB 115-F-11 Fatmawati x Lambau 5 IPB 116-F-3-1 Pinjan* x Fatmawati 6 IPB 116-F-44-1 Pinjan x Fatmawati 7 IPB 116-F-46-1 Pinjan x Fatmawati 8 IPB 117-F-1-3 Fatmawati x Pulu Mandoti* 9 IPB 117-F-4-1 Fatmawati x Pulu Mandoti 10 IPB 117-F-6-1 Fatmawati x Pulu Mandoti 11 IPB 117-F-14- Fatmawati x Pulu Mandoti 1 IPB 117-F-15- Fatmawati x Pulu Mandoti 13 IPB 117-F-17-4 Fatmawati x Pulu Mandoti 14 IPB 117-F-17-5 Fatmawati x Pulu Mandoti 15 IPB 117-F-18-3 Fatmawati x Pulu Mandoti 16 IPB 117-F-45- Fatmawati x Pulu Mandoti 17 IPB 140-F-1-1 Sintanur* x (Fatmawati x IPB6-d-14j-1-1-) 18 IPB 140-F--1 Sintanur x (Fatmawati x IPB6-d-14j-1-1-) 19 IPB 140-F-3 Sintanur x (Fatmawati x IPB6-d-14j-1-1-) 0 IPB 140-F-4 Sintanur x (Fatmawati x IPB6-d-14j-1-1-) 1 IPB 140-F-5 Sintanur x (Fatmawati x IPB6-d-14j-1-1-) IPB 140-F-6 Sintanur x (Fatmawati x IPB6-d-14j-1-1-) 3 IPB 140-F-7 Sintanur x (Fatmawati x IPB6-d-14j-1-1-) 4 IPB 149-F-1 Lambau* x Fatmawati 5 IPB 149-F- Lambau x Fatmawati 6 IPB 149-F-3 Lambau x Fatmawati 7 IPB 149-F-4 Lambau x Fatmawati 8 IPB 149-F-5 Lambau x Fatmawati 9 IPB 149-F-7 Lambau x Fatmawati 30 IPB 149-F-8 Lambau x Fatmawati 31 B1149-9C-PN MR-1 B10589F-KN//Memberamo/IR64 3 B11738-MR-1--Si-1- Gilirang*/BP34F-MR-1-3//Gilirang* 33 B1174-RS*-3-MR BP360E-MR-79-PN-/IR7118/BP360E 34 B1183-MR BP140F-MR-1-KN-1/Code/BP140F-MR-1 35 B11955-MR B11738-MR--5/B11738-MR-6B 36 CIHERANG IR / 3* IR // 4* IR64 37 SINTANUR Lusi/B7136C-MR--1-5 (Bengawan Solo) * Parent source of aroma 6. The amount of grain total per panicle. 7. Percentage of filled grain. 8. Grain yield was calculated by the weight of dry grain (14% moisture) from all plants in the plot that were harvested; border rows of plot were excluded. 15

3 9. Yield potential was calculated from yield components of the line. The formula used as follow (Yoshida 1981): Yield (t.ha -1 ) = number of panicle/m x number of total grain/panicle x % filled grain x 1000 grain weight (g) x 10 = number of grain/m x % filled grain x 1000 grain weight (g) x Grain Quality Testing Grain quality of brown rice, milled rice, head rice, length, shape, and chalkiness of grain, gelatinization temperature were evaluated, followed IRRI procedure (IRRI 00). About 500 g grains per line were milled with ST50 Yanmar Rice Huller to have brown rice (BR). Formula: BR (%) = Milled rice (MR) Brown rice was milled in Yakatama Miller machine to obtain white milled rice and bran; milled rice was weighted. Formula: MR (%) = Head rice (HR) A total of 100 g of milled rice was sifted and differentiated/separated between the head (HR) and broken rice. Formula: HR (%) = 16

4 Length, shape, and chalkiness Length and width of ten grains of head rice was measured manually using dial caliper. Scales of the rice length were long ( mm), medium ( mm), and short (< 5.5 mm). Rice shape was the ratio of length to width. Rice performance quality was determined by using indicators these were the appearance and clearness of the endosperm. Chalkiness was noted in the middle of rice (white center), front (white belly), or none at all (none). The scales of kernel area were small (< 10%), medium (11 0%), and large (> 0%). Amylose content analysis Amylose content was analyzed using calorimetric iodide. A total of 100 mg of white rice flour from each line was put in the 100 ml measuring flask, and then mixed with 1 ml of alcohol 95% and 9 ml of NaOH 1 N. Solution was kept and undisturbed at room temperature for 3 hours, then added with distillate water until line of measuring tera, then shaken. Five ml of solution was taken and then placed in a 100 ml measuring flask per sample; 85 ml water was added, then distillated with acetate 1 ml 1 N and ml % KI; the solution was then diluted to the tera. The value of light absorption of this solution was measured with a spectrophotometer. Amylose classification levels were: high (> 5%), medium (0.1-5%), low ( %), very low ( %) and waxy (0-5.0%). Gelatinization temperature Six head rice grains were soaked in 10 ml 1.7% KOH solution for 3 hours at 30 o C. Rice appearance and separation were visually seen and classified using IRRI scoring method (IRRI 00). Rice having low-gelatinization temperature would be completely separating or disappear. Rice having medium gelatinization temperature was only partially cracked or separated. Grain was affected by alkaline solution indicated high-temperature gelatinization. Temperature gelatinization was classified into 3 criteria, namely high (75-79ºC), moderate (70-74ºC), and low (55-69ºC). 17

5 Aroma Sensory Aroma was evaluated using three methods. The first method was made using the leaf samples according technique developed by Berner dan Hoff (1986) that was further modified by Dong et al. (001). The second, used a modified method of Sha and Linscombe (004) in the test tube, and the third followed Allidawati and Kustianto (1989) for cooked rice aroma. Leaf aroma tested with KOH Aroma of leaves was tested at maximum tillering until panicle initiation. Three to 5 leaves of the rice plants were taken. Leaf samples were cut at approximately 5 mm, and were placed in plastic sealed and stored in a temperature of -0 o C until frozen. The frozen leaf was weighed at about 0.8 g and placed in a test tube, filled previously with 5 ml of 1.7% KOH solution, and then were covered with aluminum foil and put into a 50 o C oven for 10 minutes. The tube was opened one by one and evaluated by 4 panelists to be scored at 0-3. Score 0 was no aroma, 1 was faint aroma, indicated aroma, and 3 represent strong aroma. Test scores of each lines were averaged and differentiated into 3 groups, namely aromatic (score > 1.0), slightly aroma (score ), and not aroma (score 0.5). Rice aroma tested in the test tube Aroma test after harvest used rice in test tubes. A total of 1 gram of rice grains was placed in test tube of 15 x 150 mm size which were filled with 10 ml of dh O, and covered with aluminum foil, and then cooked in boiling water for 15 minutes. After the samples were cool, aluminum was opened, and aroma was smelled one by one by the panelist and were scored using the same method as the previous method of testing; the test scores were averaged, and grouped into: aromatic (score > 1.0), slightly aroma (score of ), and not aroma (score < 0.5). 18

6 Test of cooked rice A total of 00 g of rice of each line was cooked with 300 ml of water, and then steamed for 30 minutes. Aroma and rice texture tested by 10 panelists to determine the aroma level (using score), and rice texture was grouped into tender to hard texture. Data Analysis Homogenity of error range from several growing environments was tested using Bartlett test that compares the chi-square value calculated by chi-square table (Gomez and Gomez 1995). The formula of calculating chi-squares is shown below: χ (chi-square) = where: k = number of varieties tested f = degree of freedom range tested S i = value of diversity at the i th environment S p = the value of the combined estimators of the entire range of environmental research If counted χ > χ table then the hypothesis was rejected or an error range of homogeneity was not homogeneous, and the tests were performed separately. But if counted χ < χ table then a combined analysis of the range of error was made. If the two environments in two seasons had a homogenous error range, stability test of results could be proceeded. Linear regression analysis introduced by Finlay and Wilkinson in 1963, then improved by Eberhart and Russell (1966) was used to analyze yield stability of the genotype. This method was used by Bahar et al. (1994), Carlos et al. (008), and Jusuf et al. (008). The model is shown in the following: Yij = μ + bi Ij + dij where: 19

7 Y ij = average yield of genotype i th at location j th μ = average yield of the i th genotype in all locations b I j d i ij = regression coefficient of the i th genotype = environmental Index at the of j th location = deviation of regression of genotype i th at location j th Adaptability and stability of a plant was measured by the regression coefficient between the average yields of a genotype with average yield of all genotypes in a particular environment. Thus the stability was classified into three possibilities: 1. If the regression coefficient (bi) is close or equal to one then the stability is in the average level (average stability). If the stability is in the average level and the average yield is higher than the average yield of all genotypes in all environments the genotypes have a good general adaptability. Conversely, if the average yield is lower than the overall average yield, then the adaptability is poor (poorly adapted) in all environments.. If the regression coefficient (bi) is more than one, then the stability is below average stability. Such genotype is sensitive to the environmental changes, and is adapted to specific a environment that is favorable. 3. If the regression coefficient (bi) is smaller than one then the stability is above average (above average stability). This genotype is adapted to marginal environments Yield stability was also analyzed by AMMI model using SAS 9.0 program. Proc GLM was used for analysis of variance. Proc IML was used to extract the interaction effects was a major component axes (PCA) based on principal component analysis method. Proc GPLOT was used to generate biplot from scores of genotype and score of the environment generated by principal components analysis. Appearance of plants depends on genotype and the environment in which plants grow, and the interaction between genotype and the environment. Environmental factors could not be controlled, such as sunlight, rainfall, soil, and altitude, and could not be changed during planting season at many locations. In field studies, assessment of the influence of environmental factors cannot be 0

8 Table. Combine analysis of variance Source of Variance degree of freedom Mean Square Environment (L) (l-1) - - Replication/env. (m-1) - - Expected MS Genotype (G) (g-1) M3 σ e + r σ gl + r l σ G x L Error (g-1) (l-1) M σ e + r σ (g-1) (r-1) l M1 σ e gl g controlled, and therefore responses of plants are analyzed by conducting experiments at several locations, or several seasons, and both are analyzed by using combined analysis (Table ). The purpose of combined analysis is to evaluate the interaction between treatments, season and locations to determine whether technology recommendations are separated or combined (Gomez and Gomez 1995). Linear model of RCBD with combined pattern (Singh and Chaudary 1979) as follow: Y ijr = µ + Gi + Ej + (GE)ij + εijr Where: Y ijr = observation result of i th genotype, j th environment, r th replication µ = general average G i = the effect of the i th genotype th Ej = the effect of the j environment (GE) ij = interaction effect of i th genotype, j th environment ε = the effect of research error ijr Data of this experiment were analyzed by Tukey (Honesty Significant Different, HSD) at α level of 5%; if the range of analysis using the F test showed significantly different values, means there were interaction between the genotype and genotype x environment. The variability was calculated by analysis of variance (Singh and Chaudary 1979). Calculations are: Variance of genotype (σ g) = Variance of G x E interaction (σ gl ) = Variance of the environments (σ e) = M 1 1

9 Variance of phenotypes (σ p) = + + Heritability broad sense (H bs) = x 100% Coefficient of genetic variance (CGV) = x 100% Coefficient of phenotypic variance (CPV) = x 100% Genetic advance (GA) = k x x GAP (%) = x 100%, is the value of genetic improvement in the percent of the average value of the population. where: k = selection differential in standard deviation units, k =.06 at 5% selection intensity X = general mean For characters that are influenced by the environment, heritability values and combination of growing environment were also calculated from each environment using analysis of variance (Table 3). Table 3. Analysis of variance random models in each environment Source of degree of Mean Square Expected MS Variance freedom Replication r-1 N1 σ e + g σ r Genotype g-1 N σ e + r σ Error (r-1)(g-1) N3 σ e g From the ANOVA, each variance of phenotype and genotype can be inferred by the following formula. σ p = σ g =

10 The correlation between covariance was analyzed according to the formula of Singh and Chaudary (1979): r (x 1 x ) = where: r (x 1 x ) = correlation between x 1 and x cov x1 x = covariance x 1 x σ (x 1 ) = variance of x 1 σ (x ) = variance of x Correlation of significant different test between characters was calculated by t test, t = where: r (x 1 x ) = correlation between x 1 and x r (x 1 x ) = square of correlation between x 1 and x df = degree of freedom (n-) All data were analyzed by using SAS 9.0 program. In plant breeding, the environment is usually described as location and year or season, so the experiments have to be carried out at least at two locations and two years or four seasons, so there are four environmental conditions. This is to overcome the effects of large bias in varietal testing conducted at one location or season because of the influence of large interaction between genotype and environment. 3

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