Correlation between the Growth Parameters under the Influence of Triacontanol in Peanut

Year : 2012, Volume : 1, Issue : 1
First page : ( 69) Last page : ( 73)
Print ISSN : 2319-118X. Online ISSN : 2319-1198. Published online : 2012 April 1.

Verma Aman^1,*, Malik CP², Sinsinwar YK³

¹Assistant Professor, School of Life Sciences, Jaipur National University, Jaipur, Rajasthan, India

²Academic Advisor, School of Life Sciences, Jaipur National University, Jaipur, Rajasthan, India

³Associate Professor, Department of Agronomy, Agricultural Research Station, Durgapura, Jaipur, Rajasthan, India

*Email id: nimmikd1@gmail.com

Abstract

By correlation analysis, the most relevant parameters for growth and development were identified among the following: shooting potential, chlorophyll content, antioxidant enzymes like catalase (CAT), peroxidase (POX), polyphenol oxidase (PPX), and ascorbate peroxidase (APX) activity, total soluble carbohydrate and protein content. In the present investigation, the biochemical parameters are found to be more correlated with each other in the presence of TRIA, in combination with BA in both the genotypes. Correlation studies will further help in determining the most effective procedures for selection of superior genotypes.

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Keywords

Groundnut, triacontinol, antioxidant enzymes, macromolecules, chlorophyll.

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Introduction

Peanut (Arachis hypogaea L.) or groundnut is grown in tropical and warm temperate regions throughout the world. The crop provides an excellent source of protein and other nutrients. Seeds contain about 50% oil (Cheng et al., 1992), 22%–30% proteins on a dry basis, a rich source of minerals (P, Ca, Mg and K) and vitamins (Savage and Keenan, 1994). The multiple uses of the peanut make it an excellent cash crop for domestic markets as well as foreign trade. Peanut production process, from planting to storage, is affected by different types of constraints. Poor yields of peanut is mainly due to the biotic and abiotic constraints like erratic rainfall, low residual moisture, lack of high yielding adapted cultivars, damage by pest and diseases, poor agronomic practices, and limited use of inputs (Nageshwara Rao and Nigam, 2001). Therefore, it would be pertinent to assess the potential of new genotypes of peanut in in vitro conditions and new combination of PGRs for regeneration of whole plants.

Triacontanol (TRIA), a long 30 carbon saturated primary alcohol, was discovered in 1933 as a natural component of epicuticulary waxes of Medicago sativa (Chibnall et al., 1933). The plant growth stimulating activities of TRIA (such as increase in dry weight, leaf area, and levels of reducing sugars, amino acids and soluble proteins) have been demonstrated by many researchers in many plants (Ries, 1985). Some authors have witnessed the role of TRIA in micropropagation of ornamental and other plants (Reddy et al., 2002; Tantos et al., 2001; Gururaj et al., 2007). However, very little information is available on the effect of this plant growth regulator in in vitro conditions in peanut. Its effect in modulating antioxidant defense and biochemical aspects was also a part of the investigation. Analysis of correlation was used to express the results.

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Materials and Methods

Two cultivars of groundnut (Arachis hypogaea L.), M-13 (Spreading) and PBS24030 (Semi-spreading) were procured from the Agricultural Research Station (ARS), Durgapura, Jaipur, Rajasthan, India. The seeds were washed with tap water for 10–15 min followed by immersion in a liquid detergent solution, labolene for 5 min. After washing with distilled water, the seeds were again immersed with 70% ethanol for 3–5 min and rinsed with distilled water 3–4 times. Then the seeds were brought to the inoculation chamber and were surface sterilised with 0.1% HgCl₂ for 8 min and rinsed with sterile distilled water 3–4 times. Four to six surface sterilised seeds were germinated aseptically in a 250 ml wide mouthed conical flask having sterilised wet cotton bed in the dark. Based on our previous findings, cotyledonary node (CN) was excised from a 10– 12 days old seedling and used as explants (Verma et al., 2009). Such explants were cultured on MS medium (Murashige and Skoog, 1962) containing 3% (w/v) sucrose and with varying concentrations (0.5, 1.0 and 2.0 ml L^–1) of Vipul (a commercial formulation of TRIA), procured from Godrej Agrovet Ltd., Sachin, India, alone and in combination with BA (3 mg L⁻¹). CN explant was inoculated and cultures were incubated at 24±2°C under 16 h exposures to white light of 80 µEm^–2s^–1 intensity provided by fluorescent tubes for 4–5 weeks for multiple shooting. Control set was devoid of any PGR. Shooting potential of this PGR was recorded after 40 DAI.

Biochemical and Enzymatic Estimations

Estimation of biochemical parameters and enzyme activity was carried in in vitro grown 25–30 days old leaves from lateral branches. Total chlorophyll content was estimated in leaves by the method given in Coombs et al. (1985). The levels of chlorophyll were converted to mg g^–1 FW. Hill Reaction Activity (HRA) was determined according to Cherry (1973). The HRA was expressed as µg g^–1 FW.

Catalase (CAT; EC 1.11.1.6) activity was calculated according to the modified method of Aebi (1984). One unit (U) of CAT activity was defined as the amount of enzyme catalysing the decomposition of 1 µmol H₂0₂ per min at 240 nm calculated from the extinction coefficient of absorbance for H₂0₂ at 240 nm of 0.036 cm² µmol⁻¹. The results were expressed as U g^–1 FW.

Ascorbate peroxidase (APX; EC 1.11.1.11) activity was determined according to the modified method of Zhu et al. (2004). One unit of APX activity was defined as the amount required to decompose 1µmol ascorbic acid oxidised min^–1 calculated from the extinction coefficient of 2.6 mM^–1 cm^–1. The results were expressed as U g^–1 FW.

Peroxidase (POX; 1.11.1.7) and Polyphenol oxidase (PPX; EC 1.14.18.1) activity was assayed adopting the method of Kar and Mishra (1976). One unit (U) of enzyme activity was defined as the amount of enzyme that caused an increase in absorbance at 420 nm of 0.01 per min. The enzyme activity was expressed in U g^–1 FW.

Malondialdehyde (MDA) content was estimated by following the method of Moshaty et al. (1993). The results were expressed in n moles of MDA g^–1 FW. Total soluble sugars and proteins were estimated following the method of Clegg (1956) and Lowry et al. (1951) respectively.

Each growth experiment was conducted thrice taking three replicates of each treatment, under in vitro conditions. The correlation analysis was carried out using SAS software for each biochemical characteristic on the two peanut genotypes only in the presence of PGRs and in combination with BA (3 mg L^–1).

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Result and Discussion

Analysis of correlation coefficient is important in plant breeding as it measures the degree of association, genetic and non-genetic linkage between the characters. Adebisi et al. (2004) reported that crop improvement depends upon the magnitude of genetic variability present in the population and once genetic variability has been ascertained in a crop, improvement is possible using an appropriate selection method. This involves the knowledge of correlation among the traits (Rasmusson and Cannell, 1970; Singh and Gupta, 1990; Lynch and Kozub, 1991)

Correlation between the Growth Parameters due to the Effect of TRIA, only, on M-13 Genotype

Table 1 shows the correlation coefficient of growth parameters of M-13 genotype in the presence of different concentrations of TRIA alone. Shooting potential revealed highly significant positive correlations with chlorophyll content, POX, PPX, APX activity, carbohydrate content and protein content (P<0.01). Total chlorophyll content gave highly significant positive correlations with POX, PPX, APX, carbohydrate content and protein content (P<0.01). HRA showed significant positive correlations with POX (P<0.05). CAT activity had highly significant positive correlations with shooting potential, chlorophyll content, POX and APX (P<0.01). POX activity was found to be positively correlated with all the parameters tested at P<0.01, except HRA (P<0.05). PPX activity was found to be non-significant with HRA. APX activity gave highly significant positive correlations with POX, PPX, MDA, carbohydrate content and protein content (P<0.01). MDA level gave highly significant positive correlations with the number of shoots, chlorophyll content, POX, PPX, APX activity, carbohydrate content and protein content (P<0.01). Total carbohydrate content was significantly positive, correlated with all the parameters tested (P<0.01) except HRA and CAT activity.

Correlation between the Growth Parameters due to the Effect of TRIA with BA (3 mg L⁻¹) on M-13 Genotype

Table 2 shows the correlation coefficient of growth parameters of M-13 genotype in the presence of different concentrations of TRIA in combination with BA (3 mg L⁻¹). HRA gave highly significant positive correlations with CAT activity (P<0.01) and PPX activity (P<0.05). APX activity showed positive correlations with carbohydrate and protein contents (P<0.01).

Correlation between the Growth Parameters due to the Effect of TRIA alone on PBS24030 Genotype

Table 3 shows the correlation coefficient of growth parameters of PBS24030 genotype in the presence of different concentrations of TRIA only. Shooting potential showed highly significant positive correlations with chlorophyll content, POX, PPX, APX activity and MDA content (P<0.01), whereas HRA and protein content were significantly correlated at P<0.05. Total chlorophyll content gave highly significant positive correlations with POX, PPX, APX and carbohydrate content (P<0.01).

HRA showed significant positive correlations with CAT, POX, PPX, APX, carbohydrate and protein content (P<0.01). CAT activity had highly significant positive correlations with shooting potential, chlorophyll content, HRA and APX (P<0.01) whereas POX and carbohydrate content were significantly correlated at P<0.05. POX activity was found to be positively correlated with all the parameters tested at P<0.01, except CAT. PPX activity was found to be significantly correlated with all the parameters (P<0.01). APX activity gave highly significant positive correlations with the number of shoots, chlorophyll content, POX, PPX, APX, MDA, carbohydrate and protein content (P<0.01). MDA levels showed positive correlation with every parameter. Total carbohydrate content was positively correlated with all the parameters tested (P<0.01) except CAT activity.

Correlation between the Growth Parameters due to the Effect of TRIA with BA (3 mg L^–1) on PBS24030 Genotype

Table 4 shows the correlation coefficient of growth parameters of PBS24030 genotype in the presence of different concentrations of TRIA in combination with BA (3 mg L^–1). Shooting potential showed highly significant positive correlations with the protein content (P<0.01). HRA was positively correlated at P<0.01 with MDA and protein content. CAT activity showed significant positive correlations with POX and APX activity (P<0.01).

POX activity was found to be positively correlated with PPX, APX, MDA and carbohydrate content (P<0.01). PPX activity was found to be positively correlated with CAT, POX and carbohydrate content (P<0.01). APX activity revealed positive correlations with HRA, POX, MDA, carbohydrate and protein content (P<0.01). MDA gave significant positive correlations with POX, PPX and APX (P<0.01). Carbohydrate content was found to be positively correlated with shooting potential, HRA, APX and protein content (P<0.01).

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Conclusion

The correlation matrix, as shown in Tables 1–4, helps determine pairs of characters that vary in the same or opposite directions. It is a useful tool especially for plant breeders who wish to associate a set of traits in their selection programme. In the present investigation, the biochemical parameters are found to be more correlated with each other in the presence of TRIA in combination with BA, in both the genotypes.

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Tables

Table 1::

Correlation matrix between growth parameters in M-13 cultivar of peanut at different concentrations of TRIA only (ml L^–1)

	Chl.	HRA	CAT	POX	PPX	APX	MDA	Carbo.	Proteins
Shoots	0.829^**	0.29459	0.50225	0.803^**	0.899^**	0.836^**	-0.84271	0.724^**	0.771^**
Chl.		0.34231	0.40255	0.780^**	0.931^**	0.915^**	-0.95295	0.887^**	0.750^**
HRA			0.17697	0.573^*	0.28225	0.49587	-0.37057	0.43142	0.40271
CAT				0.669^**	0.32758	0.611^**	-0.35225	0.05330	0.45446
POX					0.769^**	0.932^**	-0.824^**	0.692^**	0.793^**
PPX						0.897^**	-0.962^**	0.904^**	0.701^**
APX							-0.936^**	0.814^**	0.752^**
MDA								-0.94^**	-0.745^**
Carbo									0.668^**

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Table 2::

Correlation matrix between growth parameters of M-13 cultivar of peanut at different concentrations of TRIA (ml L⁻¹) with BA (3 mg L⁻¹)

	Chl.	HRA	CAT	POX	PPX	APX	MDA	Carbo.	Proteins
Shoots	0.44266	0.09793	-0.1126	-0.1854	0.25366	0.39309	-0.3755	0.17539	0.08915
Chl		-0.16281	-0.4789	-0.3413	0.21792	0.47064	-0.2463	-0.04771	0.34337
HRA			0.672^**	0.37974	0.608^*	-0.1853	-0.6293	-0.24404	0.09986
CAT				0.36873	-0.0707	-0.7103	0.04706	-0.44444	-0.53255
POX					0.24306	-0.6117	0.21375	-0.67852	-0.32333
PPX						0.30912	-0.7274	-0.02103	0.46829
APX							-0.6363	0.801^**	0.7295^**
MDA								-0.42783	-0.64911
Carbo									0.51797

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Table 3::

Correlation matrix between growth parameters of PBS24030 cultivar of peanut at different concentrations of TRIA only (ml L⁻¹)

	Chl.	HRA	CAT	POX	PPX	APX	MDA	Carbo.	Proteins
Shoots	0.748^**	0.553^*	0.42889	0.821^**	0.886^**	0.914^**	-0.912^**	0.7524^**	0.597^*
Chl.		0.635^*	0.40471	0.824^**	0.847^**	0.828^**	-0.840^**	0.794^**	0.670^*
HRA			0.889^**	0.858^**	0.713^**	0.805^**	-0.77602	0.886^**	0.681^**
CAT				0.665^*	0.54190	0.651^**	-0.56270	0.650^*	0.44720
POX					0.879^**	0.949^**	-0.946^**	0.924^**	0.841^**
PPX						0.937^**	-0.931^**	0.891^**	0.745^**
APX							-0.981^**	0.926^**	0.781^**
MDA								-0.913^**	-0.781^**
Carbo									0.832^**

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Table 4::

Correlation matrix between growth parameters of PBS24030 cultivar of peanut at different concentrations of TRIA (ml L⁻¹) with BA (3 mg L⁻¹)

	Chl.	HRA	CAT	POX	PPX	APX	MDA	Carbo.	Proteins
Shoots	0.073	0.319	-0.393	0.355	0.309	0.234	-0.228	0.528	0.616^**
Chl.		-0.155	-0.238	0.152	0.528	0.035	0.127	0.134	-0.080
HRA			-0.063	0.402	0.593^*	0.315	-0.75^**	0.578^*	0.730^**
CAT				-0.73^**	-0.549	-0.90^**	0.517	-0.775	-0.403
POX					0.741^**	0.787^**	-0.71^**	0.847^**	0.593^*
PPX						0.638^*	-0.677^*	0.784^**	0.658^*
APX							-0.73^**	0.814^**	0.497^**
MDA								-0.737	-0.696
Carbo									0.814^**

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