Results and Discussions

3. Results and Discussions

and OWODE-5 produced pod yield above average while The analysis of variance for pod yield per plant of 20

OWODE-2 was slightly lower than the average yield. selected accessions in an environment × accession

Mean squares from the stability analysis of variance interaction study is presented in Table 2 which shows

for number of fruits per plant, plant height, seeds per that only environment and environment (linear) were

fruit and 100 seed weight are presented in Table 4. highly significant. It implies that the three Only number of seeds per fruit was significant for environments used for the study differ from each other

accession × environment. The four agronomic and since the genotype × environment was not

characters considered were significant at P < 0.01 for significant; there was an indication that the genetic

environment and environment linear. Number of fruits differences among the 20 accessions were not detected.

per plant and number of seeds per fruit were also The joint regression analysis and deviation mean

significant for pooled deviation whereas plant height

Table 2 Mean pod yield per plant, regression coefficient, b, and deviation mean square for 20 okra accessions.

Code Genotype

Deviation mean square (S 2 di) A NGAE-96-012-1

Mean yield per plant (g)

Regression coefficient (b ± sd)

524.0111 B NGAE-96-012-3

721.7084 C OAA/96/175-5328

1,475.6714 D CEN 009

350.8209 E NGAE-96-062-1

391.1020 a F NGAE-96-062-2

93.85 1.1768 b ± 0.21

1,920.5657 G NGAE-96-0066

409.6537 H NGAE-96-0061

1,527.7704 I NGAE-96-0060

NGAE-96-0067

527.7057 L

NGAE-96-0064

NGAE-96-011

NGAE-96-0065

NGAE-96-0069

2,491.9927 R OWODE-2

AKURE-2-9

287.7374 a S

93.65 1.3000 b ± 0.18

597.5189 T OWODE-5

OWODE-3

369.7751 a Total

a Regression coefficient (b) significantly greater than or less than 1.0; b Deviation mean square (S 2 di), significantly greater than 0.

Stability Assessment of Some West African Okra (Abelmoschus caillei)

Genotypes in Nigerian Genebank

Table 3 Mean square from the stability analysis of variance of 20 accessions [6].

Source of variation

DF No. of

Plant height

No. of

100 seed

Days to

Pod yield

/plant (g) Environment (Env.)

fruits /plant (cm)

seeds /fruit

weight (g) 50% flowering

155,612.726** 37.001** 10.207** 20,540.418** 2,063.2476 Accession (Acc)

81.28 ns 107,856.5766** Acc × Env.

19 0.871 ns 1,411.097** 2.851** 0.595 ns

40.361 ns 2,711.8124 Env. + (Acc × Env.)

95 0.834 ns 724.253 ns 1.923** 0.284 ns

100 0.771 ns 8,468.677** 3.677** 0.780** 105.536** 7,969.0506 Env. (linear)

185.006** 51.038** 102,702.089** 539,282.8829** Acc × Env. (linear)

28.217 ns 2,501.2357 Pooled deviation

19 0.475 ns 910.367 ns 3.161** 0.327 ns

43.396 2,764.4566 Pooled error

677.725 ns 1.613** 0.273 ns

32.864 3,133.5889 ** Significant at P = 0.01; ns: not significant.

Table 4 Deviation mean square (S 2 di) of 5 characters of 20 selected accessions of A. caillei.

Accessions Days to 50% flower Seeds/fruit

100 seed wt. NGAE-96-012-1 9.895

Fruits/plant

Plant/height

57.982 b 0.062 NGAE-96-012-3 13.616

0.036 b 0.351 165.599 0.014 OAA/96/175-5328 10.522

3.097 b 0.155 233.565 0.044 CEN 009

0.063 NGAE-96-062-1 1.916 b 0.520 0.176 266.023 0.031 NGAE-96-062-2 16.741

0.032 NGAE-96-0066 16.183

99.355 0.084 NGAE-96-0060 7.702

NGAE-96-0061 3.817 b 0.177 0.088

32.288 b 0.226 b

NGAE-96-0067 6.981 b 0.468 0.226

14.909 b 0.174 b NGAE-96-0064 4.044 b 0.548 0.202 135.852 0.213 b

NGAE-96-011 7.963 0.347 0.033 655.07 0.090

49.767 b 0.006 NCRI-05 17.573 1.309

NGAE-96-0065 6.665 b 0.046 0.105

198.076 0.026 NGAE-96-0069 11.869

0.50 b OJAOBA-4 38.509

0.283 b AKURE-2-9 33.991

0.131 b OWODE-3 36.797

0.052 OWODE-5 7.446 b 0.516 0.215 428.588 0.057 b Deviation mean square (S 2 di), significantly greater than 0.

and 100-seed weight were not. It showed that all the Table 5. NGAE-96-062-1, NGAE-96-0061, accessions responded differently to the six NGAE-96-0067, NGAE-96-0064, NGAE-960065 and

environments and that plant height and seed production 2 OWODE-5 had deviation mean square (S di) were significantly different across the six environments.

significantly greater than 0 for days to 50% flowering. There was influence of genotypes × environment on the

This showed that flowering of these genotypes were number of seed produced at each environment.

inconsistent. None of the genotypes had significant

deviation mean square greater than 0 for fruits per plant selected 20 accessions of A. caillei is presented in

Deviation mean square (S 2 di) of 5 characters for

and seeds per fruit. NGAE-96-012-1, NGAE-96-0060,

Stability Assessment of Some West African Okra (Abelmoschus caillei)

Genotypes in Nigerian Genebank

NGAE-96-067 and NGAE-96-0065 had significant CEN 009 and NGAE-96-0069. This group had low deviation mean square (S 2 di) greater than 0 for plant

yield and low CV. On the top right we have accessions height at maturity. It showed that these four genotypes

NCRI-05, NGAE-96-0061, NGAE-96-0062-2, OAA were influenced for plant height at maturity by the

96/175-5328 and NGAE-96-0067 with high yield and environments. The deviation mean square for 100-seed

large CV. The genotypes in this group can only thrive weight was greater than 0 for NGAE-96-0060,

in a high input environment. The lower right NGAE-96-0067, NGAE-96-0064, NGAE-96-0069, quadrangle consisted of four accessions: OJAOBA-4, OJAOBA-4 and OWODE-2. It is an indication that

NGAE-96-012-3, AKURE-2-9 and OWODE-3, which seed size of these genotypes might have been affected

had low yield but large CV.

by different environments. Significant pooled deviation for number of fruits per Graphic plots of Coefficient of Variation (CV)

plant and number of seeds per pod indicated that some versus mean pod yield of each of the 20 accessions

genotypes had a non-linear response to environments. analyzed for stability studies are presented in Fig. 1.

The environmental effects were significant for all the The top left quadrangle, had accessions with high

characters considered indicating that environmental yields and low coefficients of variation. Seven

conditions varied. The variability among the locations accessions fall into this group and they were:

may be attributed to the differences in soil type, NGAE-96-011, NGAE-96-0065, NGAE-96-0064, temperature and rainfall during the seasons [10]. NGAE-96-0060, OWODE-2, OWODE-3 and

According to definition of stability, accessions that NGAE-96-062-1. The lower left quadrangle consisted

combined high pod yield with low coefficient of of four accessions; NGAE-96-012-1, NGAE-96-0066,

variation are most desirable and could be recommended

Table 5 Regression coefficient b, for five characters of 20 selected accessions of West African okra.

Accessions Days to flowering Seeds/fruit Fruits/plant Plant/height 100-seed wt. NGAE-96-012-1

1.05 ± 0.07 a 1.10 ± 0.27 NGAE-96-012-3

1.14 ± 0.13 OAA/96/175-5328

1.61 ± 0.27 NGAE-96-062-1

0.93 ± 0.19 NGAE-96-062-2

1.04 ± 0.19 NGAE-96-0066

1.52 ± 0.23 NGAE-96-0061

1.71 ± 0.31 NGAE-96-0060

1.07 ± 0.05 a 0.77 ± 0.52 NGAE-96-0067

1.16 ± 0.03 a 1.11 ± 0.45 NGAE-96-0064

1.06 ± 0.06 a 1.24 ± 0.39

0.86 ± 0.50 NGAE-96-011

0.75 ± 0.32 NGAE-96-0065

1.07 ± 0.06 a 1.39 ± 0.08 a NCRI-05

1.00 ± 0.06 a 1.41 ± 0.12

0.29 ± 0.17 NGAE-96-0069

0.56 ± 0.58 AKURE-2-9

0.67 ± 0.26 a Regression coefficient (b) significantly greater or less than 1.0.

0.96 ± 0.07 a 0.32 ± 0.41

Stability Assessment of Some West African Okra (Abelmoschus caillei)

Genotypes in Nigerian Genebank

Fig. 1 Mean pod yield of 20 accessions of okra plotted against CV.

to farmers or breeders [7]. Therefore NGAE-96-011, for high input environments. However, caution should NGAE-96-0065, NGAE-96-0064, NGAE-96-0060,

be taken, because yield of these genotypes would be OWODE-2, OWODE-3 and NGAE-96-062-1 were

prone to fluctuate from location to location because of recommended for cultivation. Although NCRI-05 was

the high CV, in low input environments [11]. the highest yielding genotype, it had high response to

Accessions NGAE-96-012-1, NGAE-96-0066, environments. This suggested that some okra CEN009 and NGAE-96-0069 with low yield and low accessions performed better in some environments than

CV had poor response to environment. These others. Breeders can therefore select for specific

accessions may be good for poor input location where locations. Other accessions in the categories of average

input resources are not readily available. AKURE 2-9, yield but high response to environment included

NGAE-96-012-3 and OWODE-5 were the worst NGAE-96-0061, OAA96/175-5328, NGAE-96-0062-2

accessions with low yield and high CV. This group and NGAE-96-0067. These accessions would be good

should be rejected in any breeding programme except

Stability Assessment of Some West African Okra (Abelmoschus caillei)

Genotypes in Nigerian Genebank

there are specific traits that could be transferred into phenotypic marker polymorphism, Biologia, Bratislava,

62 (1) (2007) 41-45.

other elite varieties in the future. OJAOBA-4 was close [2] A. Ghaderi, E.H. Everson, C.E. Cress, Classification of

to the average mean yield and CV; such an accession environments and genotypes in wheat, Crop Sci. 20 (1980) should be given a second trial in future evaluation

707-710.

before a decision is taken on it. [3] S. Ceccarelli, Positive interpretation of genotype by environment interaction in relation to sustainability and

4. Conclusions

biodiversity, in: M. Cooper, G.L. Hammer (Eds.), Plant Adaptation and Crop Improvement, CABI, Wallingford,

There were pod yield instability at Mokwa and

UK, 1996, pp. 467-486.

Abeokuta during the two years of testing; whereas pod [4] J. Crossa, Statistical analyses of multilocation trials, Adv.

Agron. 44 (1990) 55-85.

yield at Ibadan, though averagely low was stable. It can [5] IBPGR (International Board for Plant Genetic Resources),

therefore be concluded that environmental conditions Report on International Workshop on Okra Genetic in Ibadan were more consistent than other two

Resources Held at the National Bureau for Plant Genetic locations. Breeding for okra should necessarily be

Resources, New Delhi, India, October 8-12, 1990. [6] S.A. Eberhart, W.A. Russell, Stability prameters for

carried out in a more stable environment to achieve comparing varieties crop, Sc. 6 (1996) 36-40.

authentic improvement. Genotypes NGAE-96-011 and [7] T.R. Francis, L.W. Kannenberg, Yield stability studies in NGAE-96-0060 were the two most promising

short-season maize. I: A descriptive method of grouping genotypes from the twenty accessions of okra genotypes, Can. J. Plant Sc. 58 (1978) 1029-1034. [8] SAS, SAS Institute User’s Guide, Version 9, Cary, N.C.,

evaluated in terms of stability and productivity.

USA, 2003. [9] M, Ashraf, A.S. Qureshi, A. GhaFoor N.A. Khan,

Acknowledgments

Genotype-environment interaction in wheat, Online J. of This research was supported by the Federal Ministry Biol. Sc. 5 (2001) 356-357. [10] A. Rashid, G.R. Hazara, N. Javed, M.S. Nawazx, G.M. Ali,

of Science and Technology, Nigeria and research field Genotype × environment interaction and stability analysis at Mokwa, Nigeria was provided by National Cereals

in mustard, Asian J. of Plant Sc. 1 (5) (2002) 591-592. Research Institute, Badegi, Nigeria.

[11] H. Ojulong, P. Ntawuruhunga, A.G.O. Dixon, G. Ssemakula, Genotypic stability analysis and its application

References

to cassava regional trails, in: Proceeding of 6th Symposium of International Society for Tropical Root

[1] O. Gulsen, S. Karagul, K. Abak, Diversity and Crops – Africa Branch, ISTRC-AB, 1995, pp. 237-241. relationships among Turkish germplasm by SRAP and

Journal of Life Sciences 5 (2011) 913-920

In Vitro Picloram-Induced Somatic Embryogenesis from Leaflets of Cherry (Prunus incisa Thunb.)

1 2 1 2 Ben Mahmoud Kaouther 3 , Elloumi Nadhra , Chakroun Ahlem , Ahmed Jemmali and Philippe Druart 1. Institut National Agronomique de Tunisie, Cité El Mahrajène, Tunis 1082, Tunisie

2. Département Biotechnologie et Physiologie Végétale, Institut National de la Recherche Agronomique de Tunisie, Rue Hédi Karray, Ariana 2080, Tunisie

3. Unité “Génie Biologique”, Département Sciences du Vivant, Centre Wallon de Recherches Agronomiques, Chaussée de Charleroi, 234, Gembloux 5030, Belgique

Received: March 27, 2011 / Accepted: May 18, 2011 / Published: November 30, 2011.

Abstract: Cherry regeneration via somatic embryogenesis is a powerful tool to breeding. In this way, the embryogenic capacity of Prunus incisa specie has been tested from leaves under different interactions of picloram concentrations and darkness exposures. Induction culture was achieved on MS medium supplemented with picloram concentrations at 0.5, 1 and 1.5 mg·L -1 and submitted to 10,

20, 30 and 40 days of darkness. The best rate of embryogenic leaves was obtained with the interaction of 30 days darkness exposure*1 mg·L -1 picloram. According to their age, leaves were differently reacted to somatic embryogenesis; indeed, the 2nd expanded leaf from the apex was the most embryogenic one. Concerning the effect of additional auxin to picloram (1 mg·L -1 ), IAA at 0.1 mg·L -1 and IBA at

0.1 mg·L -1 gave significantly higher induction rates than all other concentrations, but regenerating somatic embryos showed some teratological abnormalities probably due to secondary embryogenesis. At the opposite, NAA at 0.5 mg·L -1 didn’t improve embryogenic rate but affected positively embryo development. Furthermore, embryogenesis preferentially took place on the basal part of leaf. Satisfactory rates of somatic embryogenesis are obtained but further improvement remains possible.

Key words: Auxin, picloram, somatic embryogenesis, leaf explants, Prunus incisa.

Abbreviations

on mechanism of cell totipotency.

It is well known that regeneration of somatic MS: Murashige and Skoog medium; embryos differs according to the species and to a BAP: 6-benzylaminopurine; number of endogenous and exogenous factors among IAA: indole-3-acetic acid; which hormonal balance has a primary role. In NAA: α-naphthaleneacetic acid; particular, the auxin-cytokinin ratio requires Picloram: 4-amino-3,5,6- trichloropicolinic acid. adaptations according to successive stages of