Bulb Yield Stability in Shallot: The Case of Eighteen Shallot Genotypes Evaluated under Southeastern Ethiopia Highlands

Study was carried out to identify stable shallot genotypes with better yield performance over range of environments during 2008-2009 cropping season at south eastern highlands of Ethiopia. Eighteen shallot genotypes were evaluated including standard check (Huruta) and Local check over six environments (2 years x 3 locations) using randomized complete block design with three replications. Data was analyzed using MSTATC and IRRSTAT statistical softwares for combined analysis of variance and stability study respectively. Additive Main Effect and Multiplicative Interaction (AMMI) model was employed to handle the interaction effects. Combined analysis of variance indicated that there was highly significant difference (p<0.01) between genotypes, environments and genotype x environment (G X E) interactions. AMMI analysis confirmed that genotypes S2-68-89, DZ-SHT-57, DZSHT82, DZSHT-119 and P-403-OP-S1 were the most stable genotypes. Their regression slopes were not significantly different from one (p<0.01) and scores near zero when observed across the first Interaction Principal Component Axis (IPCA1). However, genotypes Waliso, DZ-SHT-21, DZSHT-93 and Huruta were relatively unstable when observed on AMMI bi-plots and had regression slopes significantly different from one (p<0.01). Genotype DZ-SHT-21 was the best with 17300 kg/ha mean bulb yields. Environments Shallo 2008, Sinana 2009, Shallo 2009 and Lower Dinsh 2009 had large positive scores indicating that they interacted in positive direction with the genotypes whereas environments Sinana 2008 and Lower Dinsho 2008 had negative score indicating that they interacted in opposite direction with genotypes. These environments are described as unpredictable that makes cultivar recommendation difficult or complex. This study revealed that breeding shallot genotypes for local or specific adaptation is highly important.


INTRODUCTION
Shallot is widely produced in high-and mid-altitudes of Ethiopia and mainly used as condiment in Ethiopian traditional food (Getachew and Asfaw, 2000;Getachew et al., 2009).It is an important substitute for bulb onion in most highland parts of the country.According to BOARD (2002), shallot is among the major cash crops produced in different parts of the country.However, the number of varieties under production is very few with narrow genetic adaptation (MoARD APHRD, 2009).Maximizing crop productivity requires effective selection and targeting of cultivars for appropriate production area.Understanding the stability of genotype performance over different environments is important to effectively choose materials (James, 1992).Several methodologies and techniques have been developed to describe and interpret the response of genotypes to variation in environments.Each of these methods employs statistics to measure genotypic stability.Lin et al. (1986) classified stability into three types.Type 1 stability follows the biological concept and it is measured by the minimum variance across a range of environments.A genotype is considered type 2 stability if its environmental response is parallel to the mean response of all genotypes in the test.A genotype is considered to have type 3 stability if its mean square for deviation from regression is negligible.Though, so far there is a lot of work on stability analysis on cereals and other crops (Mosisa et al., 2001;Hristov et al., 2011 andHintsa et al., 2011), there is virtually no information on stability of vegetable crops particularly on shallot.This experiment was, therefore, conducted to determine the bulb yield stability of shallot genotypes over different environments.

MATERIALS AND METHODS
Eighteen shallot (Allium cepa L. Aggregatum group) genotypes that were at pipe line in regional variety trial program were used and planted at Sinana, Shallo and Lower Dinsho in the south eastern parts of Ethiopia in randomized complete block design using three replication for tow years (2008)(2009).The map of study area and description of the locations are given in Figure1 and Table 1 respectively.The plot size used was 3.2m 2 in fourrows, net harvested area was 0. 64m 2 from the two middle rows exclusive of border plant for the two respective rows and bulb yield (converted into qtha -1 ) from this area was used for analysis.The genotypes were planted at the spacing of 40cm between rows and 10cm between plants.DAP fertilizer was applied at the rate of 200 kg/ha at planting in all the three locations, planting was made in early April during the onset of main rain season in the study areas.Combined analysis of data over years and location, was done using SAS GLM procedure (SAS Institute, 2002) and Stability analysis was under taken using IRRSTAT statistical software (IRRISTAT, 2003).Additive Main Effects and Multiplicative Interaction (AMMI) model analysis was carried out to identify stable genotypes.
On the other hand genotypes Waliso, DZ-SHT-21, DZSHT-93 and Huruta are relatively unstable, their regression slopes were significantly different from one (p < 0.01) (Table 4).In the same way, on first Interaction Principal Component Axis (IPCA1) these genotypes were located away from the middle right side of AMMI biplots (interaction scores were significantly different from zero) (Fig. 2, 3, 6 and 7), showing the instability of the genotypes except for Huruta, which was only with one year dat.

DISCUSSION
Combined analysis of variance showed that there is highly significant difference (p < 0.01) between the genotypes, environment and G x E interaction (Table 3) indicating the inconsistent performance of genotypes across the environments.This result was in line with the findings of Mosisa et al. (2001) in maize and Hintsa et al. (2011) in Wheat.However, the genotypes DZ-SHT-21 recorded the highest mean bulb yield (173 qtha -1 ) over environments compared to the stable genotypes, which is difficult for regional or national variety recommendation.
Usually those genotypes with slopes of regression grater than one highly perform in favorable environments while those with regression slopes less than one perform under stress environments (Khan et al., 2007).Genotypes with regression slopes equal to one indicate no or little response to change in growing environments.

CONCLUSION
Stability of genotypes over different environments is highly essential to exploit the potential of genotypes over wide range of environments.To this effect the current study revealed that environments Shallo 2008, Sinana 2009, Shallo 2009and Lower Dibsho 2009 had large scores on the first Interaction Principal Component Axis (IPCA1) indicating that these environments interacted in positive direction with the genotypes, whereas environments Sinana 2008 and Lower Dinsho 2008 had opposite direction indicating that these environments interacted in a negative with the genotypes (Fig. 4, 5 and 7).These environments are described as unpredictable making cultivars recommendation difficult or complex.From the current investigation, it was observed that breeding shallot genotypes for local or specific adaptation is highly important.

Table 1 :
Description of the Experimental sites

Table 3 :
Combined Analysis of Variance of Eighteen Shallot Genotypes Tested in Six Environments

Table 4 :
Analysis of variance and stability regression of eighteen genotypes of shallot tested in six environments