STABILITY OF SUGARCANE (SACCHARUM OFFICINARUM L.) GENOTYPES FOR SUGAR YIELD UNDER THREE SOIL TYPES

Journal of Agricultural Science and Research (JASR) Vol. 4, Issue 1, Jun 2017, 13-18 TJPRC Pvt. Ltd. STABILITY OF SUGARCANE (SACCHARUM OFFICINARUM L.) GENOTYPES FOR SUGAR YIELD UNDER THREE SOIL TYPES SHITAHUN ALEMU 1, HUSSEIN MOHAMMED 2 & FEYISSA TADESSE 3 1 Sugarcane Breeding, Ethiopian Sugar Corporation Research and Training Division, Wenji, Ethiopia 2 Associate Professor, Department of Plant Breeding, Hawassa University, Hawassa, Ethiopia 3 Sugarcane Breeding, Ethiopian Sugar Corporation Research and Training Division, Wenji, Ethiopia ABSTRACT This study was done with the objective of identifying broadly adapted sugarcane genotypes introduced from CIRAD in France for sugar yield under heavy, medium and light soil types of Metahara Sugar Estate. The trial was laid out in a randomized complete block design with three replications. Data were collected for number of millable stalk, plant height, stalk diameter, cane yield, sugar recovery percent and sugar yield. The differences among soil types, genotypes and genotype by soil type s interactions were significant (p 0.05) for all quantitative traits analyzed except stalks diameter which is significant only for genotype and genotype by soil types interactions. According to four uni-variate stability parameters with mean sugar yield computed, CP 04 1935 gave above average environmental sugar yield and found to be relatively more stable than the others. KEYWORDS: Sugarcane, Genotypes, Soil Types, Genotype by Soil Interaction and Stability Received: Dec 06, 2016; Accepted: Jan 03, 2017; Published: Jan 18, 2017; Paper Id.: JASRJUN20173 INTRODUCTION Original Article Sugarcane is grown in countries within latitudes of 37 0 N and 32 0 S of the equator. It is an important cash crop as it is widely adapted to a wide range of tropical and semi tropical climate, soils and cultural conditions and to a long, warm growing season. The ideal climate for sugarcane is spelled as long warm growing season free from tropical storms and having adequate rainfall (or with irrigation), fairly dry and cool but frost free ripening and harvesting season (Singh, 2002). It is grown on soils varying in texture from light sands to heavy clays provided that it is supplied with the required elements. It is also tolerant to wide variations in acidity and alkalinity (growing in soils with ph in the range of 5 to 8.5) (Blackburn, 1984). Cane productivity was declining in Ethiopian sugar estates (Nayamuth, 2010).This might be due to shortage of improved varieties for the diversified sugarcane production areas (particularly in heavy and light soils) and failure of varieties to give consistent yield over a long period of time. Because of the expansion of the crop in diverse soil types in the sugar estates it is very common to get different performances from the same cultivars across the soil types (Falconer and Mackay, 1996), which is termed as genotype by soil type interactions (G x S). G x S presents limitations on selection and recommendations of varieties for the target set of soil types, particularly when it is a cross over type of interactions (Yann et al., 2011). Therefore, it is very important to evaluate genotypes in the different soil types of Metahara to take advantage of specifically adapted and stable genotypes, because it is often not possible to identify genotypes that

14 Shitahun Alemu, Hussein Mohammed & Feyissa Tadesse are superior in yield and yield components across different soil types. Furthermore, the same genetic system may not control yield over a diverse set of soil types. Therefore, this study was initiated for identifying broadly and specifically adapted genotypes at Metahara Sugar Estate under three soil types. MATERIALS AND METHODS The experiment was conducted at Metahara sugar estate. Metahara sugar estate is located in the Upper Awash Plain (UAP) in the Oromia Regional State. It is located at about 206 km East of Addis Abeba, 8 N latitude and 39 52' E longitude with an elevation of 950 m asl. Metahara receives about 554 mm annual average rainfall with mean maximum and mean minimum temperature of 32.8 C and 17.5 C, respectively. Eleven newly introduced sugarcane genotypes from CIRAD were evaluated along with standard checks NCO 334, B 52-298 and Mex 54/245 on three major soils (heavy, medium and light) of Metahara Sugar Estate. The experiment was laid out in Randomized Complete Block Design with three replications. Data were collected for number of millable stalks, plant height, stalks diameter, cane yield, sugar recovery percentage and sugar yield. The linear regression coefficient (slope) (b i ) (Finlay and Wilkinson, 1963) of genotype mean on environmental index, the mean square deviation from regression (S 2 d) for each genotype (Eberhart and Russell, 1966), Shukla (1972) unbiased estimate of the variance of GEI plus an error term associated with genotype termed as 'stability variance' (σi 2 ) and Wricke s (1962) ecovalence (W i ) were used to assess the stability of each genotypes. Finally, Pearson and rank correlation coefficients were done to measure the relationship between the stability parameters. RESULTS AND DISCUSSIONS Genotype by Soil Type Interaction The differences among the soil types as well as between 14 sugarcane genotypes were very highly significant for cane and sugar yield traits indicating the availability of high genetic variability among the genotypes studied. The Genotype by Soil interaction was also significant for cane and sugar yield pointing to the differential response of genotypes under the three soil types and the possibility that some genotypes are specifically adapted to a specific soil type. The presence of significant G x S interaction showed the inconsistency of sugarcane genotypes performances across soil types. Even though, very highly significant yield differences between genotypes, soil types and interactions revealed the need to select well adapted to specific soil type and it is very important to identify broadly adapted genotypes. The highly significant soil type effect and its high variance component in cane yield and sugar yield could be attributed to the large differences among the test locations in water holding capacity, nutrient utilizing efficiency and etc. This result was consistent with Gauch and Zobel (1996) reported that in multi-environment trials, the environment (E) normally explains up to 80% of the variation. It is evident that selection and recommendation of new varieties would be difficult under significant conditions of G x S owing to the masking effects of variable soil types. Pham and Kang (1991) reported that G S interaction minimizes the utility of genotypes by confounding their yield performances. Thus, it is very important to study in depth the yield levels, adaptation patterns and stability of sugarcane genotypes in different soil types. Table 1: Sum Square Variances of Genotypes, Soil Types and G x S for Cane and Sugar Yield Sources of Variation Sum Squares Sum Square Variance (%) Cane Yield Soil 644442 89.8 Genotype 28211.9 3.9 Genotype x Soil type 43696.4 6.1 Sugar Yield

Stability of Sugarcane (Saccharum officinarum L.) 15 Genotypes for Sugar Yield Under Three Soil Types Table 1: Contd., Soil 4697.6 78.7 Genotype 657.8 11 Genotype x Soil type 563.5 9.4 A plot of the interaction means for sugar yield performances revealed high differences in each genotype exposed to the 3 soil types (Figure 1). As shown in figure 1 there were significant cross over and non cross over genotype by soil type s interactions for the character sugar yield across three soil types at Metahara Sugar Estate. When data for the 14 genotypes were plotted against the environmental means (Figure 1), generally there was a linear increase in yield with increase in environmental yield potential (highest under heavy soil and lowest under light soil type), but there was one genotype which produced lowest sugar yield on medium soil that was VMC 9661. Figure 1: Mean Sugar Yield Performances of 14 Sugarcane Genotypes Across Three Soil Types Stability Analysis The high significance of G x S interactions for sugar yield of 14 sugarcane genotypes tested across three soil types indicated that the studied genotypes exhibited both crossover and non-crossover types of G x S interaction (Figure 1). Complexity of sugar yield as a quantitative trait is a result of diverse processes that occur during plant development. The larger degrees of G x S interaction cause to the more dissimilar the genetic systems controlling the physiological processes conferring adaptation to different environments. The relative contributions of G x S interaction effects for sugar yield found in this study were similar to those found in other crop adaptation studies of lentil (Sabaghnia et al., 2008) and wheat (Karimizadeh et al., 2012). Therefore, G x S interaction that makes it difficult to select the best performing and most stable genotypes is an important consideration in plant breeding programs (Yau, 1995). In this study, the mean performances coupled with the stability parameters of each sugarcane genotype for sugar yield were showed in Table 2. Average sugar yield of the 14 sugarcane genotypes ranged from 16.00 to 7.53 tons/ha with a grand mean of 11.3 tons/ha (Table 2). Among the genotypes, CP 96 1252 (16.00), CPCL 02 926 (13.79), B 52 298 (13.65), FG 04 356 (13.38), CP 04 1935 (12.86) and NCO 334 (11.85) gave above average sugar yield (tons/ha). While in the other genotypes sugar yield below the grand mean was observed. Regression Coefficient and Mean Square Deviation The joint regression of the mean genotypic performances and that of the three environmental index showed that results from the two stability parameters regression coefficient and mean square deviation from regression were not

16 Shitahun Alemu, Hussein Mohammed & Feyissa Tadesse consistent in assessing the reaction of genotypes to the three major soil types of Metahara Sugar Estate. According to regression coefficient MPT 97 203, FG 06 622, NCO 334, CP 04 1935, CP 00 2180, CP 96 1252, VMC 96 61 and FG 04 356 were the most stable genotypes, respectively as they had relatively less differences from unity. Among these NCO 334, CP 04 1935, CP 96 1252 and FG 04 356 gave more than average sugar yield and therefore they were the most stable genotypes. Based on mean square deviation from regression FG 06 622, FG 04 356, MPT 97 203, VMC 96 89, VMC 96 120, CP 00 21800, MEX 54/245 and CP 04 1935 were the most stable genotypes, respectively as they had relatively less differences from zero; but, among these only FG 04 356 and CP 04 1935 gave higher than overall average sugar yield. Therefore according to regression coefficient and mean square deviation from regression the genotypes FG 04 356 and CP 04 1935 were the most stable genotypes. Thus, based regression coefficient and mean square deviation from regression, two genotypes FG 04 356 and CP 04 1935 with above average sugar yield, close to unity and zero respectively were found to be more stable than the other genotypes. Ten other genotypes, MPT 97 203, FG 06 622, NCO 334, CP 04 1935, CP 00 2180, CP 96 1252, VMC 96 61, VMC 96 89, VMC 96 120 and MEX 54/245 not only were found to be among the lowest mean sugar yield but also showed poor adaptation to the test soil types (Table 2). Stability Variance and Wricke s Ecovalence According to stability variance and Wricke s Ecovalence, some low mean sugar yielding genotypes, namely MPT 97 203, FG 06 622, CP 00 2180 and VMC 96 89 and high mean sugar yielding genotypes, CP 04 1935, NCO 334 and FG 04 356 received the lowest values of these parameters and hence were found to be the most stable with respect to sugar yield performances across soil types (Table 2). This indicated that these genotypes showed lower differential responses to the changes in the growing soil types and contributed minimally to the sum of square of the interaction effect regardless of their low yielding ability. This result suggests that selection for genotypes performances based on stability variance and Wricke s Ecovalence favors below average yielding over high yielding genotypes. Correlations among Stability Parameters Four models with mean yield for evaluating stability have been used. However, no single method adequately explains genotype performance across soil types. The stability statistics (variation) are not informative and useful in selection unless they are combined with performance (mean). Thus, stability must be used along with mean performance. Pearson correlations were computed between stability parameters including mean sugar yield. Therefore, Pearson correlations were computed between stability parameters including mean sugar yield. Rank correlations of W i was significant with b i, S 2 d and shuk was (r=0.74**, 0.59* and 1***). Highly significant positive correlation between Wi2 and σi2 was observed in studies on yield stability of barley (Hordeum vulgare L.) (Bahrami et al., 2008), common beans (Phaseolus vulgaris L.) (Mekbib, 2003), and winter rapeseed (Brassica napus L.) (Marjanovic-Jeromela et al., 2008). The pairs of rank correlations between W i, b i, S 2 d and Shuk were significant in ranking the genotypes except b i with S 2 d (r=0.1, p=0.74) (Table 3). Table 2: Stability for Sugar Yield of Genotypes across Three Soil Types at Metahara Genotypes Means R of R of b Mean i R of b i W i W i S 2 d R of S 2 d σi 2 2 R of σi CP 96 1252 16 1 1.28 6 24.79 12 16.17 14 13.86 12 NCO 334 11.85 6 0.94 3 8.14 5 7.74 12 4.14 5 MPT 97 203 10.67 7 0.99 1 0.07 1 0.06 3-0.56 1 VMC 96 61 7.53 14 0.71 7 20.45 11 10.88 13 11.32 11

Stability of Sugarcane (Saccharum officinarum L.) 17 Genotypes for Sugar Yield Under Three Soil Types Table 2: Contd., FG 04 356 13.38 4 1.30 8 10.01 6 0.03 2 5.26 6 MPT 96 273 10.45 9 1.33 12 14.48 10 2.26 10 7.85 10 CP 04 1935 12.86 5 0.90 4 2.30 3 1.26 8 0.74 3 CPCL 02 926 13.79 2 1.40 9 25.80 13 7.57 11 14.45 13 B 52-298 13.65 3 1.31 10 13.06 8 2.18 9 7.02 8 VMC 96-120 8.87 13 0.65 13 14.36 9 0.44 5 7.77 9 VMC 96-89 10.55 8 0.67 11 12.17 7 0.09 4 6.50 7 FG 06-622 10.33 10 0.98 2 0.09 2 0.02 1-0.55 2 CP 00-2180 8.93 12 1.13 5 2.59 4 0.84 6 0.91 4 MEX 54/245 9.30 11 0.42 14 39.51 14 1.20 7 22.45 14 Where, mean = mean sugar yield (tons/ha), bi= linear regression coefficient (slope), S2d= mean square deviation from regression, Wi = Wricke s ecovalence, σi2 = shukla stability variance, R= rank of genotypes where for σi2, Wi, CV, shuk and Pi from lowet to highest, means from highest to lowest and for bi and S2d lowest devation from 1 and 0 respectively. CONCLUSIONS Table 3: Pearson Correlations among Ranking of Genotypes by Stability Parameters Stability Parameters b i W i S 2 d σi 2 b i 1 W i 0.74** 1 s2d 0.10 0.59* 1 σi 2 0.74** 1*** 0.59* 1 The presence of significant G x S interaction showed the inconsistency of sugarcane genotypes performances across soil types revealed the need to select well adapted to specific soil type and exceptionally for broadly adapted genotypes. As the investigation conducted across soil types consisting of a number of genotypes identifying the stable genotype had gave information for recommending best suited genotypes for all soil types. There was a linear increase in yield with increase in environmental yield potential (highest under heavy soil and lowest under light soil type) for all genotypes except VMC 9661 which produced lowest sugar yield on medium soil. The genotypes that had above average sugar yield ranked CP 961252 (6 th, 12 th, 14 th and 12 th ), CP CL 02 926 (9 th, 13 th, 11 th and 13 th ), B 52 298 (10 th, 8 th, 9 th and 8 th ), FG 04356 (8 th, 6 th, 2 nd and 6 th ), CP 04 1935 (4 th, 3 rd, 8 th and 3 rd ) and NCO 334 (3 rd, 5 th, 12 th and 5 th ) for the stability parameters regression coefficient, Wricke s ecovalence, mean square deviation from regression and Shukla s stability variance respectively. According to Pearson rank correlation conducted for stability parameters, the use of mean yield, b i, S 2 d, Shuk and W i as a tool to select would favor simultaneous development of stable and high yielding genotypes. Thus CP 04 1935 was relatively the most stable genotype according to four stability parameters with mean performances computed. REFERENCES 1. Bahrami, S., M.R. Bhimata, M. Salari, M. Soluki, A. Ghanbari, A.A.V. Sadehi, and A. Kazemipour. 2008. Yield stability analysis in hulless barley (Hordeum vulgare L.). Asian J. of Plant Sci. 7 (6): 589-593. 2. Blackburn, F. 1984. Sugarcane. Longman Inc., New York. Pp 184. 3. Eberhart, S.A. and W. A. Russell. 1966. Stability parameters for comparing varieties. Crop Sci. 6: 36-40. 4. Falconer, D.S. and Mackay, F.C. 1996. Introduction to Quantitative Genetics. Longman, New York. 464p.

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