Genotype-season interaction and yield stability analysis of bush beans (Phaseolus vulgaris L.)

P.D.Abeytilakarathna¹, H.M.Jayamenike² and K.G.N.A.B.Wijethunga ³

¹ Agricultural Research & Development Center, Department of Agriculture, Bandarawela, Sri Lanka.  

² Agricultural Research Station, Department of Agriculture, Rahangala, Boralanda, Sri Lanka.

³ Fruit Crop Research & Development Center, Gannoruwa, Peradeniya, Sri Lanka

ABSTRACT

A yield stability of seven bush bean lines were evaluated with different cropping seasons in order to develop an efficient method for selecting  bush beans promising varieties that secure high stable yield with climate changes in bean varietal breeding programme. Seven bush beans lines were grown in randomised complete block design with three replicates at the open field of agricultural research station at Rahangala of department of agriculture during 2010 yala, 2011/12 maha and 2012 yala seasons.

Concurrently use of simple linear regression and additive main effect and multiplicative interaction (AMMI) models were proposed to analysis seasonal yield stability of bush beans. The mean yield of AMMI model was determined by adding  grand mean, genotype effect, seasonal effect, residual and the product of  Eigen value of single value interaction principle component axes (IPCAs) with genotype and seasonal IPCAs scores. Varieties that were showed  above grand mean yield and regression coefficients (ß_1i) which were less than +5 % or higher than -5 % of grand mean yield, coefficient of determination (r²) and IPCAs were close to zero were considered as stable, high yielding promising lines suitable for growing during both yala and maha seasons.

Bush bean variety “Wade” was showed the highest yield stability over different seasons but its yield was low. Bush bean line, BB 2904 was found the highest yield, but its yield was highly fluctuated with different seasons. Crossing bush beans line, BB 2904 with Wade might be beneficial to breed, high yielding and more yield stable promising variety to mitigate the future climate change.

Keywords: AMMI model, Bush beans, , IPCAs, Linear regression, Seasonal yield stability

INTRODUCTION

Bush bean (Phaseolus vulgaris L.) is an important leguminous crop in the up country intermediate zone of Sri Lanka that were grown both yala and maha seasons as short age crop which fit to the existing cropping pattern. Beans are growing mainly in Badulla, NuwaraEliya and Kandy districts with annual growing extent of 7700 ha and average production of 5.5 mt/ha (AgStat, 2011).

According to CGIAR (2013) globally, about 12 million metric tons of common beans are produced annually. In addition, it provides protein and complex carbohydrates for more than 300 million people in the tropics. In many areas, common bean is the second most important source of calories after maize. However, the seasonal climate changes; especially wet seasons were more wetter, dry seasons were more drier and unpredictability of drought could be effect to production of bush beans. Farmers throughout the country are experiencing changed seasons year on year for many the past four years have been worst in term of aberrant weather.  Paddy production in the yala season of 2012 was reduced by 4% due to drought. This also cause to declining the GDP (20% in 2000 and 13 % in 2010) and it will further reduced to 8% in 2020. 

Climate projections and crop model for 2030 were stated that  South Asia and southern Africa could suffer negative impacts on several important food security crops (Lobell et al., 2008). When compare with cowpea, mungbean like leguminous crops, beans are less adapted to extreme environments such as very low rainfall, high temperatures, low fertility acid soils. Nevertheless, gene pools and races within gene pools differ in adaptation ranges (Beebe et al., 2011). Climate change will alter the pest and disease incidence and intensity. Equatorial region will receive more rain as climate changing while extreme rainfall will receive due to La Nina phenomenon (Babee et al., 2011).

Common beans are grown well in area of mid-altitudes with moderate temperatures, organic soils, and seasonally abundant rainfall (Beebe et al. 2008).High yielding, promising varieties in plant breeding programmes should be evaluated under different condition similar real condition that they will experience when growing. New varieties should be high performance for yield and agronomic traits over a wide range of environment condition. Consequently, new lines are tested under multi-locations trials with different condition of climate, soil fertility and different seasons of the years. Locations and seasons are considered to be a single factor for environmental condition (Acciaresi and Chidichimo, 1999; Becker and Leon, 1998). For this reason, growing season can be consider as the environment factor in the primary yield trials with different seasons.

The additive main effect and multiplicative interaction (AMMI) model is widely used for analyzing genotype x environment interaction (GEI) . This model capture large portion of GEI sum of squares ( Tarakanovas and Ruzgas, 2006). Genotypes with above grand mean yield having the lowest mean deviation and single value of interaction principal component axes (IPCAs) scores which are close to zero were found to be more effective for selecting wide adaptability and stability of lines in diverse environment (Abeytilakarathna, 2010).

Understanding and measuring of the seasonal stability in varietal breeding programmes, multi-location varietal trials and varietal adaptability trials will be beneficial to produce promising bush bean varieties with seasonal stable yields. This could be possible by breeding varieties for yield and yield component stability ( Lal et al., 2010).

Consequently, there is great need for technological development to reach the rural farmers. One of the aspects is to breed new varieties of climate and pest resistant crop (Sunday Times, 2013).Therefore, this paper was aimed to developed efficient statistical method to evaluate the bean varieties for seasonal stability using AMMI model and IPCAs vs. mean yield bi-plot.

MATERIALS AND METHODS

Agronomic practices

Seven bush beans lines were planted in the open field of agricultural research station at Rahangala of department of agriculture in Boralanda. Beans lines were established on  1.5 x 2 m size plots in randomized complete block design with three replicates. Planting space was 40 x 10 cm. Compost were applied at the rate of 10 t/ha on 5 days before seed establishing. Urea, triple super phosphate (TSP), and muriate of potash (MOP) were applied at the rate of 85, 165 and 65 kg/ha respectively as a basal fertilizer dressing. After three weeks of planting, urea and MOP were used at the rate of 85 and 65 kg/ha correspondingly. Pest and disease control and other cultural practices were carried out according to the recommendation of department of agriculture of Sri Lanka. Net plot yield were recorded by removing boarders. A combined AMMI analysis and ANOVA were preceded using AssiStat version 7.6 beta (2012) software.

AMMI model for seasonal varietal yield stability testing

The following model was proposed to measure the seasonal stability of a variety by phenotypic performances of g^th genotype in the s^th season.

Yij=µ + œ_g + ß_s + Ø^_g ð_s + þ_gs

Where Yij is the mean yield of the g^th genotype in the s^th season; µ is the grand mean; œ_g  is the g^th genotype effect; ß_s is the s^th seasonal effect; Ø is the Eigen value of IPCAs; ^_g and ð_s are the g^th genotype, s^th seasonal IPCAs scores; þ_gs is the residual.

Linear regression model

The normal liner regression models have several disadvantage due to environment index is not independent of the response variable and biased estimators of regression coefficients as independent variable is measured with errors (Becker and Leon, 1998; Toller and Burrows, 1998; Storck and Vencovsky, 1994). Consequently we proposed the following simple linear regression model without using environment index for stability testing with AMMI model and IPCAs Scores.

Y_ij = ß_0i+ ß_1iX+œ_ij + ê_ij

Where  Y_ij is the yield of i^th genotype in j^th environment, ß_0i is intercept, ß_1i is slope, X is season, œ_ij is the deviation from regression and  ê_ij is error.

Varietal selection method for seasonal yield stability

There are several methods of measuring phenotypic stability of varieties by using different models of GEI. A non-parametric method that was based on analysis of variance component of each genotype over the environment was proposed by Shukala (1972). Univariate parametric methods such as unisegmented and bi-segmented linear regression are also used to explain the GEI interaction by regressing the genotypes performance over the environmental yields (Eberhart and Russell, 1966; Finlay and Wilkinson, 1963, Toller, 1990; Toller and Burrows, 1998). AMMI model use as a multivariate method to study phenotypic stability (Crossa, 1990; Gauch, 1985; Gauch and Zobel, 1988). Both multivariate and univariate techniques are useful to identify the stable and adopted genotype (Acciaresi and Chidichimo, 1999).

A high yielding promising, seasonal stable lines could be selected by simultaneously using AMMI model with IPCAs vs. mean yield bi-plot and simple linear regression especially in the primary yield trials. Selection criteria for selection of seasonal stable lines was suggested as follows; selection could be done if (1) IPCAs  was significant, IPCAs score was close to zero and regression coefficient (ß_1i) less than +5% or higher than -5% of grand mean yield with coefficient of determination (r²) close to one and yield was above grand mean, (2) IPCAs was not significant and yield was above grand mean, (3) varieties recommended only for a specific season using IPCAs vs. mean yield bi-plot, ß_1i and r² .

RESULTS AND DISCUSSION

The genetic and non genetic interaction (GEI) on phenotypic expression contributes to non realization of expected gain from selection (Comstock and Moll, 1963). Static variability of a variety is best due to it secure constant yield in different environments. Consequently, ideal varieties should have higher mean yields and low degree of fluctuations (Tarakanovas and Ruzgas, 2006). Adaptability is define as the ability of a crop variety to perform well over diverse environment ( Abeysiriwardena et al., 1991). Therefore, adoptability to cropping seasons can be express as a crop variety to perform well over different cropping season under different weather condition.

Cropping seasons and genotypes were found in highly significant (p=0.01). Genotype x season interaction was also highly significant. Consequently, the genotypes respond in different way with the different cropping seasons (Table 1 and 2).  The AMMI analysis is help to understanding the genotype environment interaction, improving the accuracy of yield estimate, imputing missing data, increase flexibility and efficiency of experimental designs ( Gauch, 1992; Gauch and Zobel, 1996). The bi-plot of IPCAs explained how they achieved the average yield (Abeytilakarathna, 2010).AMMI bi-plot ordinate with IPCAs Score capture 100% of GEI (Abeytilakarathna, 2010).Abeysiriwardena (2001) used a method to evaluate varieties for adaptability by estimating the average varietal superiority by calculating mean deviation from maximum plot yield and deviation across locations.

Table 1. Analysis of variance of yield of 7 bush bean lines grown at Rahangala during 2010-2012

Source	DF	SS	MS
Replication Cropping seasons (S) Genotypes (G) G x S	2 2 6 12	7816.67 1702939.95 1834454.94 959856.97	39108.34 ns 851469.98 ** 305742.49 ** 79988.08 **

** Significant at 0.01 probability level, ns= not significant at 0.05 probability level, DF= degree of freedom, SS= sum of squares, MS= mean sum of squares

Table 2. Additive main effect and multiplicative interactions analysis of variance for the yield of  7 bush bean lines grown at Rahangala during 2010-2012

Source	DF	SS	MS
Replication Cropping seasons (S) Genotypes (G) IPCAs Residual	6 2 6 12 0	118454 1702940 1834455 959857 0	19742 ns 851470 ** 305742 ** 79988 **                          0

** Significant at 0.01 probability level, ns= not significant at 0.05 probability level

Table 3. Mean yields of 7 bush beans lines grown at Rahangala during 2010-2012

Lines	Mean yield (g/m2)**	IPCAs**
BB 2904 BB 21-2-3 BB 22-1-2 BB 22-2-1 BB 22-2-3 Cherokee Wax Wade	1013.33 a 525.74 c 540.93 c 516.48 c 745.00 b 641.85 bc 516.11 c	8.55 -0.56 -10.16 -1.20 -6.19  9.92 -0.06
CV%	24.18

** Significant at 0.01 probability level

Means followed by same letters in superscript are not significantly different at 5% probability level of DMR test.

Table 4. Mean yields and planting dates of 7 bush beans lines grown at Rahangala during 2010-2012

Cropping Season	Date of planting	Seasonal mean yield (g/m2)**	IPCAs**
2012 yala 2011/12 maha 2010 yala	23.08.2013 09.01.2012 19.08.2010	875.16 a 519.84 b 533.33 b	-5.38 -9.04 14.42
CV%		24.18

** Significant at 0.01 probability level

Means followed by same letters in superscript are not significantly different at 5% probability level of DMR test.

Table 5. Regression coefficient (ß_1i), coefficient of determination (r²) and 5% level of grand mean yield 7 bush beans lines grown at Rahangala during 2010-2012

Lines	ß1i	r2	±5% level of grand mean yield
BB 2904 BB 21-2-3 BB 22-1-2 BB 22-2-1 BB 22-2-3 Cherokee Wax Wade	-24.44 -229.10 -337.50 -129.10 -196.90 -35.00 -263.00	0.019 0.590 0.998 0.910 0.793 0.019 0.837	32.36 32.36 32.36 32.36 32.36 32.36 32.36

When consider the seasonal mean yield, higher yield than the above grand mean was seen in 2012 yala season while lower yield that below the mean were found in 2011/12 maha and 2010 yala seasons (Table 4).The highest mean yield was seen in BB 2904 bush bean line (1013.33 gm^-2). Then BB 22-2-3 was showed higher yield than above grand mean (745 gm^-2).  Cherokee wax were also observed a significantly higher yield (641 gm^-2), but it was below the grand mean yield. Wade, BB 21-2-3, BB 22-1-2 and BB 22-2-1 were found significantly lower yield than below grand mean (516.11, 525.74, 540.93 and 516.48 gm^-2 respectively)  (Table 3).

Genotypes that IPCAs close to zero are more stable. By increasing the IPCAs score cause to increase the unstable state of genotypes (Abeytilakarathna, 2010). Even though the higher yield were observed in BB 2904 line, it was unstable with cropping seasons due to higher IPCAs score ( 8.55).  Then the above grand mean yield was seen in BB 22-2-3 line but it was also unstable with the cropping seasons (IPCAs=-6.49). Wade was the most stable line for the cropping seasons (IPCAs= -0.06), followed by BB 21-2-3 line (-0.56). But these two lines were found below grand mean yield (Table 3 and figure 1). AMMI model have limitation due to it do not reveal the GEI response pattern. To overcome this, regression model with AMMI model should used simultaneously to estimate phenotypic stability. BB 2904 was showed the lowest ß_1i (ß_1i=32.36), but association with seasons and yield was very poor (r²= 0.019). Genotype BB 22-1-2, BB 22-2-1 and Wade were observed strong association with yield and seasons (r²= 0.998). however, its yields were reduced drastically with the seasons (Table 5).

Crossing wade that was showed more stable and yield was below grand mean yield, with BB 2904 that was showed high yielding and unstable, might be beneficial to breed high yielding, more stable promising line in bush bean crop improvement programmmes. Seasonal stable lines will be evaluated in multi-location trials to select the most promising seasonal and location wise stable genotypes.  These selected genotypes might fluctuate little with the climatic changed situation.

 

Fig. 1. IPCAs scores for mean yield of 7 bush bean lines grown at Rahangala in 3 seasons

                                         

CONCLUSIONS

Even though, bush bean line, BB 2904 was showed the highest yield, its yield was highly fluctuated with different seasons. The line BB 22-2-3 was also observed a higher yield than above grand mean yield. But its yield was also unstable with seasons. Variety Wade was showed high stable yield but its lower yield was than grand mean yield like line BB 21-2-3. Lines BB 22-1-2, BB 22-2-3 and variety Cherokee wax and they were unstable with different seasons. Crossing between Wade that was exhibited  stable and lower yield than grand mean with high yielding unstable line BB 2904 might be effective to breed high yielding and seasonal yield stable promising line to secure economic yield irrespective with the changing climatic condition.

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EFFECT OF HIGH ENERGY PROTON AND CARBON ION BEAMS ON FENUGREEK (Trigonella foenum-graecum L.) SEED IRRADIATION

P.D.ABEYTILAKARATHNA¹ and K.TAKAGI²

¹  Regional Agricultural Research and Development Centre, Bandarawela, Sri Lanka

²  The Wakasa Wan Energy Research Center, 64-52-1, Nagatani, Tsuruga, Fukui, 914-0192, Japan

ABSTRACT

 An experiment was conducted to find out the effect of high energy proton and carbon ion beams on fenugreek seeds irradiation at the Wakasa Wan Energy Research Center in Japan. Fenugreek Seeds were exposed to six proton beam doses; 0, 50, 150, 200, 300 and 400 Gy and five carbon beam doses; 0, 25, 50, 150 and 200 Gy. Proton beam irradiated seeds were established on planting trays using randomized complete block design with 3 replicates in the green house under the control environment. Seven groups of seeds; non-irradiated seeds, 50 Gy, 150 Gy, and 200 Gy of proton-beams irradiated, and 50 Gy, 150 Gy, and 200 Gy of carbon-beams irradiated fenugreek seeds were grown on aseptic laminar medium. Radio sensitivity parameters were recorded and data were subjected to statistical analysis using R software.

The 400 Gy dose was the optimum dose of proton beams for the irradiation fenugreek seeds for induce mutations. Carbon beam doses of 50, 150, and 200 Gy and proton beam doses of 150, 200 Gy were caused to reduce the hypocotyls and total lengths of hypocotyls and roots. Proton beam dose of 50 Gy was increased the hypocotyls and total lengths of hypocotyls and roots.

KEYWORDS: Carbon beams, Fenugreek, Mutation breeding, Proton beams, Seeds Irradiation

INTRODUCTION

Fenugreek is more important crop due to it uses for medicinal purposes as well as spice for food in Sri Lankan from very long time. Fenugreek is an annual legume native to the Mediterranean region. From ancient days, it has been grown in India, Argentina, Egypt and Mediterranean countries like Southern France, Morocco and Lebanon (Gupta, 2014).The leaves and seeds of fenugreek are consumed specially for medicinal purposes such as lowering blood sugar and cholesterol level, anti-cancer, anti-microbial etc. (Sadeghzadeh-Ahari et al., 2009). In addition, it is very useful legume crop that have ability to fix the nitrogen and fit to short-term rotation (Sadeghzadeh-Ahari et al., 2009). According to the studies of Neelakantan et al. (2014), fenugreek seeds support to control the glycemic in persons with diabetes.

The aim of the crop breeding is to obtain a reasonable number of desired mutations for a trait of interest while inflicting the least unintended disruption to the genotypic integrity of the crop. This ensures to obtain desirable induced mutant without presence of unintended induced deleterious alleles which would require additional interventions such as backcrossing with elite starting genotype (Mba, 2013; Magori et al., 2010). In order to produce high yielding, pest and disease resistance or tolerance promising fenugreek varieties with desirable traits, it is important to use modern mutation technologies. A mutation is a sudden heritable change in the DNA in a living cell, not caused by genetic segregation or genetic recombination (Van Harten, 1998). Mutagenesis is more important in genetic studies as well as selective breeding. Successful mutant isolation largely relies on the use of efficient mutagens. The ion beam mutagenesis is the one of the good technology and the ion beam is a physical mutagen that has just recently come into use for plants. In this type of mutagenesis, positively charged ions are accelerated at a high speed (around 20–80%of the speed of light) and used to irradiate target cells (Magori et al., 2010).

Plant mutations are carried out with high-energy (220 MeV) ion beam in Japan (Kondo et al., 2009) while low-energy (30 keV) ion beams use in China (Feng et al., 2009). In Japan, ion beam irradiation facilities are available in the Wakasa Wan Energy Research Center, at Tsuruga using Multi-purpose Accelerator with Synchrotron and Tandem (W-MAST). Moreover, ion beam facilities for plant mutation are available at TIARA of the Japan Atomic Energy Agency (JAEA), the RIKEN Accelerator Research Facility (RARF), and the Heavy Ion Medical Accelerator in Chiba (HIMAC) of National Institute of Radiological Sciences (NIRS) (Tanaka, 2009). Linear electron transport (LET) which is the energy deposited to target materials when an ionizing particle passing through them is very important in ion beam irradiation due to the effectiveness of ion beams as a mutagen might not be determined by the species of ions, but mostly by the LET of ions and ion beams with LET of around 10–500 keV/u appear to be suitable. (Magori et al., 2010). The unit of LET is in kilo electron volts per micrometer (keV/mm), which represents the average amount of energy lost per unit distance. Ion beams have a relatively high LET (around 10–1000 keV/mm or higher), while X-rays, gamma rays and electrons have low LETs (around 0.2 keV/mm). Therefore, ion beams have ability to make more severe damage to living cells and high relative biological effectiveness than other forms radiation (Blakey, 1992; Lett, 1992; Magori et al., 2010). Ion beams induce predominantly single- or double-strand DNA breaks with damaged end groups that are unable to be repaired easily due to ion beams deposit high energy on a local target (Goodhead, 1995). In addition to ion beams, the space crop breeding using cosmic radiation is a one of the novel plant mutation breeding techniques (Guo et al., 2010; Hu et al., 2010; Ou et al., 2010).

MATERILS AND METHODS

The fenugreek seeds were irradiated using 220 MeV proton beam and 660 MeV carbon beam at the Wakasa Wan Energy Research Center (WERC) at Tsuruga, Japan on 2014. Seeds were exposed to six proton irradiation doses; 0, 50, 150, 200, 300 and 400 Gy and five carbon irradiation doses; 0, 25, 50, 150 and 200 Gy.

Irradiation Sensitivity Test

Irradiated fenugreek seeds were established in 30cm x 30cm size planting trays using the flat method (Asncion, 2004) which consists of 25 of square shape planting holes of 4.5 cm width and 5.5 cm of depth, at the green house of WERC under the control environment. The irradiated seeds were established in three replicates of RCBD using the first 3 replicates of irradiated seeds. The planting trays were filled with the sterilized media containing vermiculite and coir dust and seeds were established. Irradiation sensitivity parameters such as Seeds germination, plant height at 14 after emergence, leaf abnormality of shots/ primary leaves were recorded. The data were subjected to analysis using open source scripts of R version 3.1.2 software.

Seven groups of seeds were used, each of which was non-irradiated seeds, 50 Gy, 150 Gy, and 200 Gy of proton-beams irradiated, and 50 Gy, 150 Gy, and 200 Gy of carbon-beams irradiated fenugreek seeds to compare the effect of carbon beams and proton beams. Seeds in each group were sterilized by immersing 5 minutes in 70% ethanol and subsequently immersed for 10 minutes in 10 % antiformin (effective chlorine concentration: ca. 0.5%) with 0.1% Tween 20,  and washed with sterile distilled water. Then seeds in each group were sown on aseptic laminar medium, consisted of 1/2 MS with 2% sucrose and 0.3% gellungum, in a square dishes. Dishes were vertically kept to facilitate rooting downward on the surface of a medium. Digital photographs of dishes were taken. Root length and other root characters of the fenugreek seeds were measured after digital photos using ImageJ software.

  

RESULTS AND DISCUSSION

Effect of Proton beams on Fenugreek Seedling Height

According to Owoseni et al. (2007), radio sensitivity or determination of the optimum dose of radiation is a term describing a relative measure of the quantity of recognizable effects of a radiation exposure on the irradiated material. Tshilenge-Lukanda et al. (2012), described that the optimum mutation doses can be determined using seedling survival rate and seedling height. Determination of first generation mutant (M₁) injury level using seedling height and survival should be a routine procedure in mutation breeding, because it has been established that these characters are correlated with M₁ mutation frequency (Asncion, 2004). In this study, the difference between height of fenugreek seedling at 13 days after planting was highly significant (p<0.001) with proton irradiation dose. The highest seedling heights were observed in both non-irradiated and 50 Gy proton irradiated seedlings (7.7 cm and 7.4 cm respectively). The seedling heights were reduced in both 150 and 200 Gy levels of irradiation (5.5 cm and 4.7 cm respectively) than the non-irradiated seedling. The lowest seeding heights were observed in both 300 and 400 Gy proton irradiation levels (2.8 cm and 2.7 cm respectively) (Table 01 & Figure 01).  According to Mba, (2013), the universally adopted norm is to select a dosage that results in reductions of 30 to 50 or 40 to 60 percent in growth or survival rates respectively of the first generation mutant (M₁) seedlings compared to the seedlings of untreated seeds. Seedling of which seeds were irradiated using 300 and 400 Gy proton doses were fallen in the range of 30 to 50 percent of height reduction than the seedling of non- irradiated seeds (Figure 01). 

 Effect of Proton Beams on Seedling Survival Rate

Seedlings were not dead up to 200 Gy irradiation dose of proton beam. The plant survival rates as percentage to the untreated seedling were started to decline after 200 Gy irradiation (Figure 02). According to recent studies of Magori et al.( 2010), irradiation dose at the shoulder end of the survival curves (200 and 1000Gy for carbon ions and electrons, respectively) or less than these doses is more efficient for ion beams . Brown (2013) also stated that the negative effects of radiation overdoses such as deletions of DNA nucleotide sequences that may cause reading-frame shifts, inactive protein products, or faulty transcripts. This would subsequently lead into null mutations, in which a particular gene may be inactivated. According to Mba et al. (2010), the dose of mutagen that is regarded as the optimal is one that achieves the optimum mutation frequency. The lethal dosage (LD50) was also used to determine the optimum irradiation dose. (Meyer,1996; Owoseni et al., 2007; Magori et al., 2010). The seedlings of which seeds were irradiated using 400 Gy proton dose was in the range of 40 to 60 percent of survival rates (Figure 02).

Effect of Carbon Beams and Proton Beams on Roots and Hypocotyls Lengths

Root lengths of fenugreek seedling at 6 days after sowing of seeds which irradiated with 0 to 200 Gy of proton beams and carbon beams were not seen significant different statistically at p < 0.05. The highest hypocotyls length (25.2 mm) was observed in the seedling of seed irradiated using  50 Gy proton beams while the shortest hypocotyls  length was seen in the seedling of seed irradiated using  50 Gy carbon beams. However, hypocotyls lengths were not affected significantly at p<0.05, up to 150 Gy proton beams. Likewise, 50 to 200 Gy carbon beams were also not showed a significant different at p<0.05 (Table 02).

The dosage of 50 Gy proton beam was caused to increase the hypocotyls lengths by 10.5 percent than the seedling of non-irradiated seeds while same dose of carbon beam was caused to reduce the hypocotyls length by 30.7 percent at 6 days after seed sowing. At the 150 Gy dose of carbon beam was caused to reduce the hypocotyls lengths by 2.7 fold than the same dose of proton beams. But, 0.7 fold reduction of hypocotyls was observed at 200 Gy carbon beam dose than same dose of proton beams (Figure 03).

The proton beam doses of 50, 150, 200 Gy and carbon beam dose of 150 Gy were effected to increase the root lengths  of the seedling at 6 days after irradiated seed sowing by 6.1, 8.7, 5.2 and 12.2 percent respectively than untreated seedlings. But, 50 and 200 Gy doses of carbon beams were caused to reduce root lengths by 7.8 & 34.8 percent respectively than non-irradiated seedlings (Figure 04).

The total length of roots and hypocotyls were seen significantly different at p<0.05 at 6 days after sowing the seeds but it was not significantly different at 8 days after sowing. Carbon beam 50 to 200 Gy doses and Proton beam 200 Gy dose were reasoned to reduce the total length of root and hypocotyls. The highest total length of root and hypocotyls was observed in 50 Gy dose of proton beams (37.4 mm) while the lowest length was observed in 50 Gy of carbon beams dose (table 03).  

Total lengths of root and hypocotyls at 50 Gy of proton beam was facilitated to increase the length by 8.7 percent than the non- irradiated seedlings while same dose of carbon beam facilitated to reduce the length by 23.3 percent. Carbon beam doses of 150 and 200 Gy were also caused to reduce the total length by 3.7 and 1.5 fold respectively than the same dose of proton beams (Figure 05).

CONCLUSIONS

The optimum proton beam dose for the irradiation of the fenugreek seeds for induce mutations was 400 Gy according to the radio sensitivity parameters such as seedling height and seedling survival rate. Hypocotyls lengths of irradiated fenugreek seedslings were reduced by 30.7, 23.7, 18.4, 8.8, 26.8  percent after expose to 50, 150 , 200 Gy carbon beams and 150, 200 Gy proton beams respectively. Hypocotyls length of the seedlings was increased by 10.5 percent after irradiated with 50 Gy proton beam. Roots lengths of the seedlings were reduced by 6.1, 8.7, 5.2, 7.8, 34.8 after irradiated with 50, 150, 200 Gy proton beams and 50, 200 Gy carbon beams respectively as well. In addition, roots length was increased by 12.2 percent after treated with 150 Gy of carbon beams. Total lengths of roots and hypocotyls were reduced by 3.2, 16.3, 23.26, 11.92, 24.13 percent after exposed to 150, 200 Gy of proton beams  and 50, 150, 200 Gy of carbon beams respectively while total lengths of roots and hypocotyls were increased by 8.7 percent when treated with 50 Gy proton beam.

ACKNOWLEDGEMENTS

We wish to express our thank to Fukui International Human Resource Development Center (FIHRDC) and the Wakasa Wan Energy Research Center (WERC) in Japan for funding this study under “the atomic energy researchers and research students acceptance program, FY 2014”

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Table 01. Proton beam irradiation dose (Gy) and the fenugreek seedling (cm) height at 13 days after planting.

 

*** Significantly different at p=0.001

   

Means of the same letters in superscripts are not significantly different at Duncan’s p=0.01

  

Table 02. Root lengths and hypocotyls lengths of fenugreek seedling with different seed irradiation dose of proton and carbon beams at 6 days after sowing.

 

 ns=  not significant at p=0.05, ** significant at p=0.01

means with the same letters are not significantly different at Duncan p=0.05

Table 03. Total lengths of roots and hypocotyls of fenugreek seedling with different seed irradiation dose of proton and carbon beams at 6 & 8 days after sowing.

ns=  not significant at p=0.05, * significant at p=0.05, DAS= days after sowing

means with the same letters are not significantly different at Duncan p=0.05

 

Figure 01. Relationship between proton irradiation dose (Gy) and seedling height as a percentage of untreated seedlings at 13 days after emergence.

 

Figure 02. Survival response curve of fenugreek seedling with different proton irradiation dose at 3 weeks after emergence.

 

Figure 03. Different proton  and carbon beams doses and hypocotyls lengths of fenugreek seedlings at 6 days after sowing.

 

Figure 04. Different proton  and carbon beams doses and root lengths of fenugreek at 6 days after sowing.

 

Figure 05. Different proton  and carbon beams doses and total lengths of roots & hypocotyls of fenugreek seedlings at 6 days after sowing.

  

(a)

 (b) 

 

Figure 06. High energy carbon and proton beams transport system to irradiation room at the Wakasa Wan Energy Research Center in Japan (a), Irradiated fenugreek seeds grown in aseptic laminar medium (b). 


Fruit & Vegetable Production in Sinhalese