Journal of Plant Physiology & Pathology ISSN: 2329-955X

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Research Article, J Plant Physiol Pathol Vol: 6 Issue: 2

Combining Ability of Agronomic and Yield Traits in Rice Genotypes

Sheila Rono1*, Felister Nzuve1, James Muthomi1 and John Kimani2

1Department of Plant Science and Crop Protection, University of Nairobi, Kenya

2Kenya Agricultural and Livestock Research Organization (KALRO), Industrial Crops Research Centre, Mwea, Kerugoya, Kenya

*Corresponding Author : Sheila Rono
Department of Plant Science and Crop Protection, University of Nairobi, Kenya, Nairobi, Kenya
Tel: +254719746015
E-mail: [email protected]

Received: March 19, 2018 Accepted: April 11, 2018 Published: April 18, 2018

Citation: Rono S, Nzuve F, Muthomi J, Kimani J (2018) Combining Ability of Agronomic and Yield Traits in Rice Genotypes. J Plant Physiol Pathol 6:2. doi: 10.4172/2329-955X.1000180

Abstract

Combining Ability of Agronomic and Yield Traits in Rice Genotypes

The demand for rice production in Kenya is high while production has remained far below consumption demand for quite a number of years. Growing of poorly adapted rice varieties with undesirable traits is one of the major factors limiting production. The objectives of this study were to determine the performance and combining ability of rice cultivars for both agronomic and yield related traits. Seven genotypes were crossed in a North Carolina II mating design to generate the F1 hybrids. The 12 F2 seeds, 7 parents and 1 check variety were planted at KALRO-Mwea following a randomized complete block design replicated three times. Analysis of combining ability was done using SAS (Version 9.3) software. Rice genotypes were significantly different for all the agronomic and yield traits except chlorophyll content, filled grains and thousand grain weight. The mean square GCA (m) were significantly different for all traits except chlorophyll content while for GCA (f) except productive tillers, panicles per plant and thousand grain weight. Specific Combining Ability showed significant differences for all traits measured. The heritability results indicated that these traits were governed by nonadditive genes. The parents, Komboka, Mwur 4 and Nerica 4 were good general combiners for grain yield, filled grains and had shorter duration to flowering. These parents could be used in a hybridization program to introgress yield traits into adapted low yielding lines. The best specific combiners were hybrids generated from a cross between Mwur 4 and Nerica 4 and Komboka and Nerica 4. These hybrids could be exploited for heterosis breeding.

Keywords: Combining ability; Heritability; Hybridization; Oryza sativa; Yield

Introduction

Rice is an important cereal crop and nearly 2.7 billion people in the world depend on it [1]. Within Kenya, its demand has increased, particularly in urban areas where consumption has increased rapidly compared to other cereal crops [2]. Currently, local production is 130,000 metric tons while consumption is 540,000 metric tons year-1. This huge gap has to be met through importation valued at Ksh 7 billion [3]. The low production of rice is attributed to abiotic and biotic stresses, poor grain quality and lack of new improved and adapted varieties [4].

Growing of poorly adapted varieties with undesirable traits is one of the major factors limiting production. Rice farmers in western Kenya have been producing Duorado while lowland varieties have been grown mainly in coastal region whereby some have been lost. Irrigated rice mainly Basmati 370, Basmati 217, ITA 310, IR 2793-80- 1 and BW 196 is grown in central province, which is a major producer [5,6]. These varieties are susceptible to diseases, have undesirable traits for consumer acceptability and are poorly adapted to the prevailing low soil fertility settings [7]. The demand for high productive upland varieties has led to development of NERICA varieties which are high yielding. However, the NERICA varieties lack the local germplasm genes and have not been widely accepted by farmers [7].

A successful rice breeding program for developing new improved rice varieties requires an appropriate selection of parents and breeding methods [8]. This could be achieved through making crosses using an appropriate mating design which could then be tested against major production constraints such as low yields, disease and pest tolerance, drought tolerance and general adaptability. This is followed by determining the gene action involved in their resistance and their combining ability of agronomic traits and yield components [9]. Mating designs like Diallel and North Carolina design II gives GCA and SCA and also heritability which can be broad or narrow sense heritability [10]. Various researchers have reported the predominance of additive and non-additive gene action for various traits [11,12]. Hence to establish rice varieties with desirable traits and adapted to local condition, combining ability analysis gives useful information for selection of good parents and promising recombinants for the breeding program. Therefore, this study aimed at determining the performance and combining ability of agronomic and yield traits among selected rice varieties.

Materials and Methods

Description of experimental site

The genotypes were evaluated at Industrial Crop Research Center (ICRC) of the Kenya Agricultural and Livestock Research Organization (KALRO), Mwea Sub-County, Kirinyaga County in Kenya. The site lies on Latitude 00°37’S and Longitude 37°20’ E at an elevation of 1159 m above sea level (MASL). The average rainfall is about 850 mm with average temperatures ranging from 15.6°C to 28.6°C and nitosol soils [13].

Rice genotypes used in this study

The rice genotypes used for the study were obtained from KALROM-wea and were 7 parents, 12 hybrids and 1 check variety (Table 1).

Code Genotype Origin Characteristics
1 Basmati 370 Kenya Aroma, very good cooking quality, susceptible to blast
2 Kuchum Kenya Very good cooking quality, susceptible to blast
3 Mwur 4 Kenya High yield, taller , resistant to blast
4 Komboka Tanzania Aroma, high yielding, susceptible to blast
5 Nerica 4 Africa Rice centre High yield, taller , resistant to blast
6 Duorodo Kenya Good grain quality, resistant to blast
7 Nerica 1 Africa Rice centre High yield, taller , resistant to blast, moderate aroma

Table 1: Origin and characteristics of different rice genotypes used for evaluation.

Generation of crosses

Seven parents were planted in pots in three sets staggered at 14 and 21 days interval to synchronize flowering. The late flowering parents were planted early while the early flowering parents were planted late. At early flowering, female parents were emasculated in preparation for crossing using suction emasculator machine. Flowers were then covered to protect them from natural cross pollination until they open and are ready for pollination. The rice panicles were pollinated in the afternoon following North Carolina II mating design. At maturity, the seeds were harvested as F1 seed then planted next season and allowed to self to produce F2 seeds.

Evaluation of F2 and F3 segregating population: The 12 F2 seeds and 8 parents made a total of 20 entries which were planted at KALRO-Mwea on 27th September, 2016 and 7th July, 2017. A local variety, Basmati 370 was used as a check. Each genotype was planted in a plot size of 3 × 3 m, at inter-row spacing of 20 cm and intra spacing of 15 cm in a randomized complete block design replicated three times. A path of one meter was left between the plots to allow for easy movement during data taking. Three seeds per hill were sown and later thinned to one plant per hill. DAP fertilizers was applied at planting and top dressed with CAN at 14 days after seeding. Normal cultural practices such as weeding were carried out manually. Data was collected on plant height, productive tillers, chlorophyll content, days to anthesis, days to heading, days to maturity, filled grains, 1000 grain weight, panicle length, grain length and grain yield.

Assessment of agronomic and yield traits: Days to heading and anthesis were measured by counting days from planting to when 50% of plants in a plot and 50% of tillers per plant had panicle exerted 2/3 way and flowered and shed pollen respectively. Total chlorophyll content of ten randomly selected plants was recorded at heading stage using SPAD chlorophyll meter. Days to maturity was measured by counting the number of days from planting to when 80% of grains in the plot were mature. Plant height of ten random plants per replicate was measured in centimeters from the base of the main tiller to the tip of the panicle at maturity. Productive tillers of ten randomly plants per replicate were counted at maturity. A total of seven yield and yield contributing characters, designated as growth characters was recorded. Grains per panicle of ten randomly plants per replicate were counted at harvest. The 1000 well-developed whole grains of each genotype were measured in grams at harvest. They were dried to 13% moisture content and then weighed on a precision balance. Total number of panicles in a plant was counted for ten randomly selected hills at time of maturity. Total number of filled grains per panicle was counted from ten randomly selected panicles at maturity. The grain length of each ten sampled grain per plot was measured at harvest using a micrometer. Grain yield was harvested and weighed on plot basis [14].

Analysis of variance

Data was subjected to analysis of variance using Restricted Maximum Likelihood (REML) in GENSTAT 15th edition. Separation of genotype means was done by using the Fishers protected Least Significant Difference (LSD) at 5% level. The collected data were analyzed by SAS (Version 9.3) program.

Determination of General combining ability (GCA) and specific combining ability (SCA) effects:

These were estimated by the following formula [15]. The relative importance of GCA and SCA were estimated using the general predicted ratio for the traits observed [16]. Ratios close to one indicate additive effects and are important in the inheritance of the trait while ratios close to zero indicate dominance and epistasis effects which are important in the inheritance of the corresponding traits [17].

Estimation for the narrow sense heritability: Estimation for the narrow sense heritability was done by use of the Plant Breeding Tools (PBTools) Version: 1.3. [18].

image

Where, Vg = genotypic variance,

Vp = phenotypic variance and

Ve = environmental variance components

Results

Performance of rice cultivars for agronomic and yield traits

Rice genotypes were significantly different at P<0.05 for all agronomic and yield traits except chlorophyll content (SPAD values), filled grains and thousand grain weight. Seasonal variations were significant for plant height and filled grains. Significant genotypes x season interactions were revealed only among the filled grains (Table 2).

Source of variation Agronomic traits Yield traits
DF PH PTL SD DH DA DM FG PP TW PL GL GY
Replication 2 108.8 23.8 209.1 107.5 119.0 11.1 16.4 1.9 18.4 5.1 0.4 5.2
Genotypes 19 1092.9* 74.5* 105.0 1537.3* 1537.5* 1278.7* 175.9 53.9* 14.2 20.5* 4.2* 26.7*
Season 1 4165.4* 3.4 5.7 156.6 180.3 177.6 2766.7* 24.7 29.1 12.9 2.8 12.6
Genotypes x season 19 118.8 7.7 39.3 166.3 170.7 0.5 2270.3* 9.1 9.8 4.9 0.6 0.7
Residual 78 125.0 8.1 46.3 65.6 67.5 61.3 173.2 6.7 5.2 2.5 0.6 2.7

Table 2: Analysis of variance for agronomic and yield traits for different rice genotypes during long and short rainy season in KALRO-ICRC Mwea.

Rice genotypes were significantly different for all agronomic and yield traits. Variations among parents for plant height were found. The highest plant height was recorded in Duorodo and lowest in BW 196. Similarly, BW 196 and Komboka produced significantly higher number of productive tillers. The parents, Nerica 4, Nerica 1 and Mwur 4 showed significantly shorter duration to flowering while BW 196 and BS 370 had significantly longer periods to flowering. Parents, Nerica 1, Mwur 4 and BS 370 showed a significantly higher potential of producing panicles/plant but Kuchum produced significantly lower number of panicles/plant. Mwur 4, Nerica 4 and Nerica 1 recorded significantly higher grain yield compared to other parents. On the other hand, Duorado recorded significantly longer grain length while kuchum and Bs 370 produced significantly longer panicle length. The hybrids generated from a cross between Nerica 4 and mwur 4, nerica 1 and kuchum and nerica 1 and komboka showed significantly shorter duration to flowering while the hybrids generated from a cross between duorodo and mwur 4 and Nerica 4 and BS 370 had significantly longer periods to flowering. Significant higher plant height was recorded in a cross between Nerica 4 and Mwur 4 and the lowest in a cross between Nerica 4 and Kuchum. The cross between Nerica 1 and Kuchum produced significantly higher number of productive tillers. On the other hand, the hybrids generated from a cross between Duorodo and Komboka produced significantly longest panicle length while a cross between Nerica 1 and BS 370 and Nerica 1 and Kuchum produced significantly longest grain length. The significant higher grain yield of a cross between Nerica 4 and Komboka was due to high number of panicles/plant compared to other hybrids (Tables 3 and 4).

Genotypes Agronomic traits Yield traits
PH SD PTL DH DA DM FG 1000SW PL GL PP GY
BS 370 96.3 31.3 15.9 107.3 108.3 141.3 55.3 20.1 19.5 7.7 15.1 1.3
BW196 (check) 49.0 48.0 25.0 140.3 141.3 169.3 15.0 19.9 14.7 5.8 11.9 2.0
DUORODO 115.0 40.3 12.7 87.5 88.5 115.3 18.7 21.1 18.4 8.1 11.2 5.3
KOMBOKA 68.6 26.8 19.7 104.6 105.6 134.0 12.5 17.9 17.9 7.1 11.8 1.6
KUCHUM 105.6 38.1 10.4 87.0 87.9 120.3 18.9 15.0 20.8 7.4 9.8 3.4
MWUR 4 102.7 44.5 12.1 80.6 81.6 116.0 18.4 21.5 17.4 6.2 25.6 6.9
NERICA 1 96.0 43.8 10.0 77.5 78.5 116.7 23.6 20.1 18.0 6.5 16.7 6.0
NERICA 4 89.7 46.4 9.8 75.2 76.2 119.7 16.0 22.7 18.8 5.9 11.3 6.0
DUO × BS 370 83.2 34.2 8.6 95.5 99.9 137.3 45.9 19.4 16.2 5.1 12.1 1.8
DUO × KOMB 77.1 33.5 11.7 99.8 100.8 138.0 45.7 19.0 20.5 5.8 12.8 1.4
DUO × KUCHM 76.5 38.0 12.6 97.2 98.2 122.0 21.7 18.6 19.1 5.9 13.4 3.4
DUO × MWU 4 85.1 33.1 10.9 97.7 98.7 156.0 16.9 17.5 20.3 7.2 9.5 2.2
NER 1 × BS 370 82.9 41.2 12.9 88.7 89.7 128.0 59.5 19.8 15.4 7.9 10.6 3.5
NER 1 × KOMB 109.6 38.5 10.4 82.6 87.1 121.7 18.1 18.9 19.7 7.6 12.5 4.1
NER1 × KUCHM 93.3 34.0 13.9 74.9 75.9 119.3 39.2 21.7 15.8 8.3 12.6 1.0
NER 1 × MWU 4 76.2 33.2 6.7 97.8 98.8 120.7 49.9 19.6 10.9 5.2 11.9 2.5
NER 4 × BS 370 95.5 30.5 12.9 104.2 105.2 139.7 49.3 18.7 18.9 7.5 10.9 1.8
NER 4 × KOMB 97.1 46.5 13.2 86.1 83.6 121.3 16.9 19.2 16.5 7.4 15.8 7.8
NER 4 × KUCHM 63.2 34.2 11.5 89.8 90.8 136.7 39.2 20.8 18.3 6.0 10.9 2.4
NER 4 × MWU 4 111.1 39.0 12.7 74.7 75.7 114.7 21.2 18.7 19.7 7.5 12.4 6.2
Grand Mean 88.7 37.8 12.7 92.5 93.6 129.4 30.1 19.5 17.8 6.8 12.9 3.4
LSD 20.1 12.3 5.5 14.2 14.5 13.0 14.1 4.5 2.2 1.1 4.0 2.7
% CV 7.0 9.7 6.8 3.1 3.2 0.4 9.4 6.4 1.5 1.4 1.1 8.8

Table 3: Mean values for agronomic and yield traits for different rice genotypes during 2016 short rainy season in KALRO-ICRC Mwea.

Genotypes Agronomic parameters Yield parameters
PH SD PTL DH DA DM FG TSW PL GL PP GY
BS 370 81.4 34.5 17.3 90.6 91.6 144.3 9.5 13.2 18.5 7.7 13.3 1.5
BW196 (check) 48.7 32.3 23.1 158.3 159.3 171.7 47.1 16.6 14.6 5.8 10.7 2.9
DUORODO 94.9 43.4 8.5 88.9 89.9 119.3 42.3 21.4 17.4 8.2 10.4 3.9
KOMBOKA 61.0 35.3 16.3 81.7 82.7 117.7 56.7 16.5 17.2 7.1 11.3 2.0
KUCHUM 79.8 39.5 10.2 86.9 87.9 121.7 57.9 17.3 18.2 7.4 9.1 3.4
MWUR 4 84.6 41.4 10.3 75.3 76.3 136 51.1 21.4 16.3 8.1 11.9 7.7
NERICA 1 84.2 43.9 11.9 77.5 78.5 118.3 55.5 19.3 18.0 7.3 22.7 6.8
NERICA 4 87.5 44.6 10.6 74.0 75.0 123.3 72.9 19.2 16.4 6.9 11.7 5.8
DUO × BS 370 75.8 37.4 12.0 86.4 87.7 139.0 14.2 16.2 18.9 6.7 13.9 2.0
DUO × KOMB 70.5 34.9 9.3 89.8 91.1 140.7 11.1 17.8 20.4 5.7 10.3 1.8
DUO × KUCHM 74.4 37.5 11.3 98.5 99.5 123.7 46.8 20.4 17.8 6.7 13.1 4.0
DUO × MWU 4 69.3 35.6 11.8 103.8 105.2 158.3 69.1 20.8 20.1 7.2 8.0 2.7
NER 1 × BS 370 76.8 41.4 13.4 88.0 89.4 131.7 9.7 19.5 14.3 8.0 10.0 3.9
NER 1 × KOMB 88.7 40.4 12.1 79.8 81.1 124.0 51.9 17.2 16.4 7.3 12.9 7.6
NER1 × KUCHM 83.0 39.5 13.8 79.6 80.9 122.0 21.1 16.7 16.3 7.9 11.1 1.7
NER 1 × MWU 4 67.9 38.2 9.9 87.6 88.9 123.7 5.9 19.5 14.3 5.2 11.2 3.0
NER 4 × BS 370 82.7 33.0 13.9 95.2 96.2 142.3 8.2 16.8 17.6 7.3 12.1 2.1
NER 4 × KOMB 82.1 38.6 10.5 84.0 86.0 123.3 72.9 21.7 16.5 7.4 14.3 8.3
NER 4 × KUCHM 66.1 35.3 12.0 103.0 104.0 138.7 27.4 21.3 17.7 6.7 11.5 2.9
NER 4 × MWU 4 78.5 37.3 8.8 74.5 75.8 117.0 62.5 18.0 17.1 7.5 11.3 6.6
Grand Mean 76.9 38.2 12.4 90.2 91.2 131.8 39.7 18.5 17.2 7.1 12.0 4.0
LSD 13.1 9.9 3.6 12.5 12.5 13.2 26.9 2.6 3.0 1.4 4.5 2.8
%CV 4.4 2.5 8.6 1.1 1.1 0.4 8.5 2.4 2.7 2.1 4.5 13.1

Table 4: Mean values for agronomic and yield traits for different rice genotypes during 2017 long rainy season in KALRO ICRC Mwea.

General Combining Ability, Specific Combining Ability and heritability for various traits

The mean square GCA (m) were significantly different for all traits except chlorophyll content while for GCA (f) significant difference was recorded in all traits except productive tillers, panicles per plant and thousand grain weight. SCA showed significant differences for all traits measured. The Baker’s ratio ranged from 0.5 to 0.7 for agronomic traits and 0.5 to 0.8 for yield traits. Broad sense heritability (H2) was greater than Narrow sense heritability (h2) for both agronomic and yield traits. Non-additive gene action was more important than additive gene action (Tables 5A and 5B).

  Agronomic traits Yield traits
Source of variation Df PH PTL SD DM DH DA PP TGW PL GL GY FG
Replication 4 189.9 12.0 87.6 28.9 75.7 91.4 13.6 30.0 4.5 0.3 2.6 115.4
Season 1 2274.8* 268.0* 21.1 105.1* 44.3 51.2* 4.1 5.0* 2.0* 0.6* 8.5* 1168.1*
Genotype 11 626.1* 16.1* 58.7* 858.7* 459.5* 455.9* 8.9* 6.6* 28.1* 5.1* 27.2* 4858.2*
Season x genotype 11 128.6* 4.1 18.6 0.5 84.3* 92.9* 8.2* 8.4* 6.2* 0.4 1.2 200.6
GCA (m) 3 397.3* 25.8* 27.4 314.5* 111.9* 129.2* 13.2* 7.1* 5.4* 0.6* 28.3* 5831.2*
GCA (f) 2 535.1* 4.0 45.9* 1488.2* 735.5* 782.0* 2.7 2.9 84.8* 6.0* 32.9* 2882.0*
SC(m x f) 6 770.8* 15.3* 78.5* 920.9* 541.3* 510.5* 8.9* 7.5* 20.5* 7.1* 24.7* 5030.4*
Residuals 44 144.3 8.7 56.6 68.8 91.8 96.6 8.6 5.2 3.4 0.7 3.5 468.7

Table 5A: Analysis of variance for the combining ability of agronomic and yield traits for different rice genotypes during short and long rainy season in KALRO-Mwea.

Source of variation Agronomic traits Yield traits
PH PTL SD DM DH DA PP TGW PL GL GY FG
Male 397.3 25.8 27.4 314.5 111.9 129.2 13.2 7.1 5.4 0.6 28.3 5831.2
Female 535.1 4.0 45.9 1488.2 735.5 782.0 2.7 2.9 84.8 6.0 32.9 2882.0
Males x Females 770.8 15.3 78.5 920.9 541.3 510.5 8.9 7.5 20.5 7.1 24.7 5030.4
baker ratio 0.6 0.7 0.5 0.7 0.6 0.6 0.6 0.6 0.8 0.5 0.7 0.6

Table 5B: Proportional contribution to the total variance.

The parents, Nerica 1, Komboka, Nerica 4 and Mwur 4 were good combiners for days to flowering with negative GCA effects. Kuchum, Duorodo, Mwur 4 were good general combiners for plant height with negative GCA while for chlorophyll content, Komboka and Nerica 1 were good combiners with positive GCA. All parents were good general combiners for productive tillers except Komboka, mwur 4 and Duorodo. On the other hand, Komboka, Nerica 4 and Mwur 4 were good general combiners for grain yield but not a good combiner for panicles/plant. For thousand grain weight, Kuchum and Nerica 4 were found to be good general combiners with positive GCA effects while Komboka, Mwur 4, Nerica 4 and Duorodo were good general combiners for filled grains. No single parent contained all desirable traits. Overally, Mwur 4, Komboka and Nerica 4 were best parents for grain yield, filled grains and had shorter duration to flowering (Table 6).

Parents Agronomic traits Yield traits
PH TL SD DM DH DA PP TGW PL GL GY FG
BS 370 (P1) 0.9 0.9 -0.6 5.5* 3.0** 3.5* 0.6 -0.7 -0.6 0.2 -1.0 -24.6
Kuchum (P2) -5.9* 1.2 -0.4 -3.8 0.5 0.3 0.7 0.8 0.1 0.0 -1.0 -1.6
Mwur 4 (P3) -0.6 -0.9 -0.8 0.9 -0.6 -0.8 -1.2* -0.1 -0.2 -0.2* 0.3 10.0
Komboka (P4) 5.6 -1.2 1.8 -2.7 -3.0 -3.0 -0.1 -0.1 0.7* 0.0 1.6* 16.2*
Nerica 4 (P5) 2.6** 0.1 -0.1 -1.6* -1.5 -1.6 -0.1 0.3 0.5 0.3 1.2* 9.0
Duorodo (P6) -5.5* -0.5 -1.3 8.6* 6.1* 6.3* -0.2 -0.4 1.6 -0.6* -1.1 3.2
Nerica 1 (P7) 2.9 0.4 1.4 -7.0 -4.7 -4.7 0.4* 0.0 -2.1* 0.3 -0.1 -12.2*

Table 6: General combining ability of rice parents for agronomic and yield traits during short and long rainy season in KALRO-Mwea.

The hybrid generated from a cross between P5 and P3, P7 and P2, P6 and P1 and P5 and P4 were best specific combiners for minimum days to 50% flowering with negative SCA. The hybrids, generated from a cross between P5 and P2, P7 and P3 were the best specific combiners for plant height with negative GCA. On the other hand, hybrids generated from a cross between P6 and P3, P5 and P1, P7 and P1, P5 and P4 and P7 and P2 were best specific combiners for productive tillers with positive SCA. The best specific combiners for grain yield were hybrids generated from a cross between P6 and P2, P5 and P4 and P5 and P3 with positive SCA effects. The three hybrids had also positive GCA for filled grains. Hybrid generated from a cross between P5 and P3 was the best specific combiner for panicles/ plant while hybrid generated from a cross between P5 and P4 was the best for thousand grain weight. For panicle length hybrids generated from a cross between P7 and P3and P5 and P3 were the best specific combiners. Overall, hybrids generated from a cross between P5 and P3 and P5 and P4 were the best crosses for grain yield, filled grains and had minimum days to 50% days to flowering (Tables 7 and 8).

  Agronomic traits Yield traits
PH TL SD DM DH DA PP TGW PL GL GY FG
VA 0.0 0.4 0.0 0.0 0.0 0.0 0.0 0.0 3.3 0.0 1.1 0.0
VD 417.7 4.4 14.6 568.1 299.7 276.0 0.2 1.6 11.4 4.3 14.2 3041.1
Narrow sense (h2) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0 0.1 0.0
Broad sense (H2) 0.7 0.3 0.2 0.9 0.7 0.7 0.0 0.1 0.7 0.8 0.7 0.8

Table 7: Heritability and additive (A) and dominance (D) variance for agronomic and yield traits for different rice genotypes during short and long rainy season in KALRO-Mwea.

Code Crosses Agronomic traits Yield traits
PH TL SD DM DH D PP TGW PL GL FG GY
P5 x P1 Nerica 4 x Bs370 3.7 1.3 -4.5 6.3* 8.2 7.5 -0.9 -1.0 0.9 0.0 -14.4* -1.8
P6 x P1 Duorodo x s B370 2.1 -1.5 0.8 -6.7 -8.2 -7.2 0.8 -0.2 -1.0 -0.6* 3.4 0.5
P7 x P1 Nerica 1x Bs 370 -5.8 0.3 3.6 0.4 0.0 -0.4 0.1 1.2 0.0 0.6* 10.9 1.3
P5 x P2 Nerica 4 x Kuchum -14.1** -0.5 -1.6 12.2 7.4 7.6 0.2 0.8 0.1 -0.8 -11.4 -1.1
P6 x P2 DuorodoxKuchum 4.8 -0.8 2.7 -12.8* 1.2 0.9 0.9 -0.1 -0.7 0.0 20.4 2.2
P7 x P2 Nerica 1x Kuchum 9.2 1.2 -1.1 0.6 -8.6 -8.5 -1.1 -0.8 0.6 0.8** -9.0 -1.1
P5 x P3 Nerica 4x Mwur 4 10.8* -1.2 2.2 -14.3** -13.3** -13.2* 1.3 -1.0 1.2 0.6 7.2 1.3*
P6 x P3 Duorodo x Mwur 4 1.3 2.4 -0.4 16.9*** 5.3 5.0 -1.7 0.5 1.4 1.6 19.8* -0.3
P7 x P3 Nerica 1 x Mwur 4 -12.2 -1.3 -1.8 -2.6 8.0 8.2 0.5 0.5 -2.5* -1.7*** -27.0** -1.0
P5 x P4 Nerica4 x Komboka -0.5 0.4 3.9 -4.2 -2.3 -1.9 -0.6 1.2 -2.2 0.3 18.6** 1.7***
P6 x P4 Duorodo x Komboka -8.3 -0.1 -3.2 2.6 1.7 1.3 0.0 -0.2 0.2 -0.5* -43.7 -2.4
P7 x P4 Nerica1x Komboka 8.8** -0.3 -0.7 1.6 0.6 0.6 0.6 -0.9 1.9 0.3 25.1* 0.8*

Table 8: Specific combining ability of rice hybrids for agronomic and yield traits during short and long rainy season in KALRO-Mwea.

Discussion

Rice genotypes were significantly different for all agronomic and yield traits except filled grains, chlorophyll content and thousand grain weight. Similarly, Ismaila et al. [19], Kimani [7] and Malemba et al. [20] observed great variation in plant height, productive tillers and panicles/plant. However, the results are contradictory with the findings of Kavitha et al. [21] and Yang et al. [22]. These findings imply that there was an appreciable amount of genetic variability. Thus, these genotypes could be selected for genetic improvement of both agronomic traits and grain yield. Various authors have reported the importance of genetic variation in breeding of new improved rice varieties [19,23,24].

The maturity period varied greatly with Nerica 4, Nerica 1 and Mwur 4 maturing early while BW 196 and BS 370 were late. Similar findings have been reported by Bing et al. [25] and Blum [26] who evaluated rice genotypes for drought tolerance and identified early maturing genotypes. Such genotypes with early maturity could be used to breed early maturing varieties which escape terminal drought [27].

The parents Mwur 4 and Nerica 1 had significant higher grain yield. However, BS 370 which is preferred by consumers and Kenyan farmers had low yield. The findings were in agreement with previous work of Karim et al. [28] and Singh [29] that aromatic types have low yields and the trait seems to be strongly linked to low yield. Similarly, previous study by Rad et al. [30] and Muthuram et al. [31] identified genotypes with high grain yield based on their mean performance. These findings indicate that the genotypes with high yield would result in good performing progenies and could be used in a hybridization program to introgress yield traits into adapted low yielding lines with desirable traits [31].

The significance of GCA and SCA variance for most of the traits evaluated suggested the importance of both non-additive and additive gene actions in expression of these traits. Further analysis in this study using baker’s ratio of GCA/SCA [16] showed that agronomic and yield traits such as days to anthesis, number of tillers, days to heading, panicle length, thousand grain weights and grain yield were governed by non-additive genes. Similar results have been reported by Sharifi [32], Kumar et al. [33], Mehmood et al. [12] and Yogameenaki et al. [34]. However, these findings differed from Panwar [11] and Bansal et al. [35] who reported the predominance of additive gene action for these traits. Hybridization followed by selection in later generations may be recommended for improvement of these traits.

The present study revealed parents with good combining ability for grain yield and duration to flowering namely Komboka, Mwur 4 and Nerica 4. Previous researchers have identified good parents based on their mean performance for agronomic and yield traits and also GCA effects [36]. Generally, parents with positive GCA and high mean performance are preferred for positive traits of grain yields while parents with low estimates and negative GCA are suitable for negative traits of grain yield such as plant height and days to 50% flowering. High GCA effects show broad adaptation and ability of parents to generate hybrids with high acclimatization potential over a range of environments [30].

The hybrid combinations with high mean performance, best specific combiner for yield and involving at least one of the parents with high GCA were identified in this study. These were hybrids generated from a cross between mwur 4 and Nerica 4 and Komboka and Nerica 4. Similar findings have been reported by Alam et al. [37] who worked on genetic basis of heterosis and inbreeding depression in rice. This implies that these hybrids would likely enhance the concentration of favorable alleles and thus yield desirable progenies [38-40].

The study revealed best specific combiners for most traits evaluated. The hybrids generated from a cross between Mwur 4 and Nerica 4 and Komboka and Nerica 4 were best specific combiners for grain yield, filled grains and 50% days to flowering. Previous study by Li et al. [39] who worked on analysis of heterosis of main agronomic traits in indica-japonica lines of rice identified best specific combiners. The findings indicate that the hybrids would yield desirable progenies. SCA has a relationship with heterosis therefore these two specific combiners could be exploited for heterosis breeding.

In general, grain yield is a quantitative trait controlled by many genes; therefore its overall net effect is produced by various yield components interacting with one another [41]. Based on genetic variability and correlation analysis in this study, thousand grain weights, filled grains per panicle plant height and panicle per plant seems to be the primary yield contributing characters and could be relied upon for selection of genotypes to improve genetic yield potential of rice. Selection of plants on the basis of these traits would certainly lead to improvement in grain yield. Similar results had been reported by Priya et al. [42] and Anbanandan et al. [43].

Conclusion and Recommendation

Three parents namely Mwur 4, Komboka and Nerica 4 were good general combiners for grain yield and could be used in a hybridization program to introgress yield traits into adapted low yielding lines. The hybrids generated from a cross between Mwur 4 and Nerica 4 and between Komboka and Nerica 4 showed good SCA for grain yield, filled grains and 50% days to flowering. These hybrids could be advanced to the next generation and tested in different environment for yield stability and then be released as new varieties to be used by the farmers. None of the genotype showed combination of all traits hence to develop a high yielding genotype, a combination of desirable traits may be introgressed into adapted rice genotypes.

Acknowledgements

The authors express sincere appreciation to Industrial Crop Research Center (ICRC) of the Kenya Agricultural and Livestock Research Organization (KALRO), Mwea for provision of infrastructure for this study. My heartfelt gratitude also goes to my supervisors and other technicians for assisting me in setting up my experiments.

References

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