From 1996 to 2006, 10 improved pure line varieties having a mean yield range of 15.4 to 25.5 and 9 to 21 q/ha on research and farmer managed field conditions, respectively were developed and released (Tesfaye et al., 2008). According to Minister of Agriculture (MoA, 2018), different high yielding, disease resistance, early bearing and high quality Arabica coffee varieties were identified and released for official production at major coffee growing areas of the country. But their performance varied with agro-climatic condition (Location) in addition to their genetic performance. Belete and Bayeta (2008) indicated that cultivar yield is affected by location, that is, those cultivars outperformed in one location performs differently in other location with different altitude and agro-climatic condition indicating the low stability of yield of coffee varieties across locations. Multi-location adaptation tests carried out in other countries also illustrated similar result that genotype-environment interaction is a common scenario in Arabica coffee genotypes like other crops (Agwanda et al., 1997).

The native home of coffee species is characterized by low-water-deficit conditions, which probably allowed evolution without the need to develop extensive mechanisms to cope with drought stress (Coste, 1992). Nevertheless, some coffee cultivars are known to differ in their responses to drought (Orozco and Jaramillo, 1978; Carr, 2001; DaMatta and Rena, 2001), suggesting that modern cultivars are not very close to their wild relatives in terms of drought tolerance. In fact, field observations have indicated that some cultivars may endure 6 to 7 months with no rain, even in sandy soils, but obviously at the expense of strong declines in crop yield (DaMatta and Ramalho, 2006).

The report by Chemura et al. (2014) indicated that Coffea arabica varieties react differently to low soil moisture stress which otherwise had no statistically significant difference. They reported that no coffee variety was significantly superior in biomass before soil moisture deficit stress exposure. For most of the varieties, there was a reduction in fresh biomass and a slow buildup of dry biomass during period of soil moisture deficit stress. Some of coffee varieties showed positive changes in root biomass after 21 and 28 days of soil moisture. DaMatta (2004) pointed out that drought prone coffee farms are associated with low input systems and as such varieties that have better survival and yield stability under drought stress are of much greater value than those with greater yield potential under optimal conditions.

Despite the role of coffee in the national economy and in spite the country of origin of Arabica coffee, average national productivity has not exceeded six quintals (600 kg/ha) (Jefuka et al., 2012; Eshetu et al., 2000; Workafes and Kassu, 1999). This is very low in contrast to yield levels reported usually in some Latin American countries. The factors attributed to such low productivity include lack of resistant varieties to various diseases and insect pests and poor agronomic practices (Eshetu et al.,  2000;  Workafes and Kassu, 1999).

Lack of suitable varieties that exhibit stable yield performances across wide ranges of environments is the major factor among several production constraints contributing to low productivity of Arabica coffee in Ethiopia (Beksisa et al., 2018; Belete and Bayetta, 2008). Thus testing the adaptability of coffee varieties at range of environments and specific location is paramount important. Hence, this paper deals with adaptability of coffee varieties under low moisture stressed area of Southern Region of Ethiopia and recommend the best performing variety for further wider production.

 

 

Location description

The trials were conducted at four different locations in southern region of Ethiopia: Dilla, Halaba and Loka Abaya. They represented wider range of altitude, 1500-1900 masl (Table 1).

 

 

 

 

Analysis of variance

The combined analysis of variances indicated that there was statistically significant difference among varieties for main stem diameter (MSTD in cm), plant height at harvesting stage (PLHT in cm), plant height up to the first branch (PLHTFB in cm), number of primary branches (NPB), number of secondary branches (NSB), number of tertiary branches (NTB), number of main stems (NMST), fruiting nodes per branch (FNPB), number of beans per cherry (NBPC), canopy diameter (CAND in cm), specific leaf area (ELA in cm²), leaf area (LA in m²), number of leaves per branch (NLPB), number of leaves per tree (NLPT), hundred bean weight (HBW in g), weight of fresh husk (WHF), weight of dried husk (WHD), weight of fresh husked bean (WHBF in g per plot) and weight of husked bean (WHBD in g/plot). But the other yield and yield components were found to be statistically non-significant. These included stand count at harvest (STCNT), leaf length (LL in cm), leaf width (LW in cm), bean thickness (BTH in cm), bean length (BL in cm), bean yield per tree (YPT in g), bean yield per plot (YPP in g), bean yield per hectare (YPHA in kg) and weight of husked clean coffee (WHCC in q/ha). Location specific significant variations were observed on some of the variables such as STCNT, LL and LW at Halaba; YPT, YPP, YPHA and WHAC at all the three locations despite their non-significant value while combined (Table 2). All the significant variables were considered for mean separation so as to come up with the recommendation with special focus to clean coffee yield per hectare. The significant difference detected among cultivars indicates the existence of genetic variability, and that allowed the selection of better cultivars in regard to coffee yield, so as to include them in the next  value  for  cultivation  and  use  (Teixeira  et  al., 2013).

 

 

Performance of coffee varieties across locations

Main stem diameter (cm), PLHT, PLHTFB varied with varieties as the largest value was recorded from variety Angafa. But the highest result on NPB and NSB was obtained from variety Catimor J-19 while variety Koti showed the highest performance on number of tertiary branches (NTB) and number of main stem per plant, while the value obtained from Odicha was statically non-significant with Koti in case of NMST. Varieties Catimor J-19(5.6), Koti (5.0), 74112 (4.7) and Odicha (5.4) showed statistically non-significant result on fruiting nodes per branch (FNPB). Catimor J-19 also showed higher value for ELA, LA, NLPB and NLPT. As Shown in Table 3, varieties Catimor J-19 and Angafa outperformed all other varieties (Table 3). The least value was recorded from local farmer variety. This indicated that performance of coffee varied with varieties. The result is in line with the work of Tirunesh et al. (2015). They reported that three coffee genotypes: 8213, 8143 and 75187B exhibited superior performance consistently at all locations. Similarly, Gebreselassie et al. (2017a) indicated the existence of statistically significant differences among coffee hybrids for stem girth/diameter, plant height, number of main stem nodes and yield with the highest stem girth (7.13 cm), plant height (323.3 cm), and number of main stem nodes (58.06), while the lowest stem girth (6.36 cm), plant height (281.63 cm) and number of main stem nodes (45.06). On the contrary, Belete and Bayetta (2008), Demissie et al. (2011) and Belete et al. (2014) also confirmed that varieties exhibiting better adaptation at one location did not perform well at other locations.

 

 

All improved varieties showed statistically different performance compared with the local (farmers’) variety for HBW, WHD, WPBF and WPBD. The highest value ofHBW was recorded by the variety Angafa despite the non-significant difference with the values obtained from Catimor J-19, Koti, Odicha, 74112, and Fayate (Table 4). The coffee variety Fayate showed the top performance with regard to WHD while variety Catimor J-19 outperformed all other varieties in case of WPBF and WPBD. However, the  result  obtained  from  Odicha  and  Angafa were statistically non-significant compared with Catimor J-19.

 

 

Location specific performance of coffee varieties

The performance of coffee varieties varied with locations. At Halaba, stand count at harvest (STCNT), average leaf length (LL) and average leaf width (LW) showed specific and significant differences. Accordingly, higher value of stand count was recorded from varieties Catimor J-19, 74112, Odicha, Fayate, Angafa and local variety. The lowest was recorded from the variety Koti but not statistically significant from varieties Catimor J-19, 74112, Odicha,  and   local   farmers’  variety.  In  the  same  way coffee variety Fayate showed statistically higher average leaf length and width compared with 74112 and local variety. But it showed statistically no significant difference compared with Catimor J-19, Koti, Odicha, and Angafa. They are statistically at par (Table 5). It can be seen that the vegetative performances of improved varieties outweighed the local one in all aspects. Similarly, Abdulfeta (2018) reported very higher results of leaf width(8.77 m) and leaf length (18.4 m) coffee varieties.

 

 

Some yield traits such as YPT, YPP, YPHA and WHAC showed specific performance across all location despite their combined effect which was statistically non-significant. Accordingly, the highest values were obtained from Catimor J-19 irrespective of location differences following Angafa (Figure 1). Their performances were still in comparison with their initial yield which was recorded during their first release. In the same way the variety Catimor J-19 showed higher clean coffee per hectare in quintal across all locations followed by Angafa  as  shown in Figure 2. Accordingly, the highest clean coffee yield 11.96, 12.8 and 11.1 q/ha at Dilla, Halaba and Lokabaya, respectively were obtained from Catimor J-19 followed by Angafa  (Figure   2).   Such  mean  yield  at  the  first  two bearing is very high as climax yield in Arabica coffee is attained starting from the fourth bearing stage (Wrigley, 1988). The overall performance of the varieties (Catimore (J-19) and Angafa was also higher at all environments. This is in line with the work of Agwanda et al. (1997) and Belete and Bayetta (2008) who reported the possibility of developing stable genotypes which can adapt across wide environments. The same result was obtained by Teixeira et al. (2013) as they reported that a significant difference was detected among coffee cultivars and the mean of the four harvests, green coffee yield was 14.7 q/ha with the range from 6.5 to 25.6 q/ha depending on cultivar. Gebreselassie et al. (2017b) also indicated that the existence of significant variation among coffee varieties for mean yield across locations with the highest five years mean yield 12.21 q/ha (2500 tree/ha)  recorded at Awada followed by 5.342 q/ha at Komato and the lowest 4.34 q/ha recorded at Wonago growing condition.

 

 

 

Characters association

Coffee bean yield and clean coffee yield were statistically significant and positively correlated with different growth parameters. Yield of clean coffee in quintals per hectare was found to be positively and significantly correlated with stand count at harvest, main stem diameter, number of secondary branches, number of fruiting nodes per branch, number of beans per cherry, canopy diameter, leaf length, leaf width, specific/single leaf area, leaf area per plant, number of leaves per branch, fresh bean yield per  tree,  bean  yield  per  plot,  bean  yield  per  hectare, weight of pulped bean per plot and weight of dried bean per plot (Table 6). This indicates that anything that contributed to improve the traits improves/bust clean coffee that could be harvested per hectare. The result is in line with the findings reported by Tirunesh et al. (2015). They reported that the growth characters such as canopy diameter with correlation coefficient of 0.57 and stem girth with the correlation coefficient of 0.59 exhibited strong positive correlation with yield indicating that these characters have strong tie to improve productivity per tree basis.

 

 

Yield stability of coffee varieties across locations

The ASV parameter is used to quantify and classify the genotypes according to their stability performance. In this model, genotypes with least AMMI stability value (ASV) or have smallest distance from the origin are considered as the most stable, whereas those which have the highest ASV are considered as  unstable  (Mehari  et  al., 2014). The additive main effects and multiplicative interaction (AMMI) stability analysis of seven varieties on three environments indicated that the variability of performance of coffee varieties under different environmental condition. The clones 74112 followed by Catimor J-19 and Fayate had possessed wider adaptability as they found nearer to the origin. On the contrary, farmer varieties Angafa and Koti were found to be adapted to specific environmental conditions, Loca Abaya and Halaba, respectively which are far away from the origin of the plot (Figure 3). Similar research findings were reported by Beksisa et al. (2018) as they indicated that lack of suitable varieties that exhibit stable yield performances across wide ranges of environments is the major factor among several production constraints contributing to low productivity of Arabica coffee in Ethiopia. Two high yielding genotypes, namely (L52/2001) and (L55/2001), on average showed stable performance across environments. On the other hand, the study also illustrated the presence of location specific high yielding coffee genotype such  as  L56/2001.  In  this regard it can be seen that coffee by its very nature has a property to show stable and higher yield under different agro-ecological locations. Similarly, Tirunesh et al. (2015) confirmed that three coffee genotypes exhibited superior performance consistently at all locations irrespective of the interaction.

 

 

Disease incidences

Coffee berry disease (CBD) is very sever and causes appreciable yield loss in areas and/or seasons where the weather is favorable. Temperature and rainfall (amount and duration), and relative humidity are decisively determining the occurrence, prevalence and severity of the diseases (Belachew and Demelash, 2015; Arega et al., 2008; Girma et al., 2008). Totally, more than 13 types of diseases were registered to affect coffee plant in Ethiopia. While major coffee diseases are coffee berry diseases (CBD) caused by Colletotrichum kahawae, coffee wilt disease (CWD) of Gibberella Xylariales and coffee leaf rust caused by Hemileia vastatrix, however, the rest diseases were considered to be minor (Eshetu et al., 2000; Belachew et al., 2015). Even if coffee is infected by different diseases, there was no severe disease attach on the tested varieties with  the  exception of coffee berry disease and coffee leaf spot. Varieties Catimor J-19, Koti, 74112, Odicha and Fayate showed resistant reaction to coffee berry disease compared with Ahgafa and the local farmers’ variety. Among the three locations, the disease pressure at Dilla was very low compared to other location as there was no any statistically significant difference among the varieties on disease score (Table 7). Similarly, coffee leaf spot was prominent on some of the varieties while others showed less infestation level. Varieties Koti, Catimor J-19, 74112 and Angafa showed statistically non-significant but lower infestation level of coffee leaf spot. Odicha, Fayate and local farmers’ varieties were highly infested by disease. The result obtained was in line with the findings of Arega et al. (2008), Bayetta (2001), Bayetta et al. (2000), and Mohammed and Jambo (2015). They indicated the existence of wider genetic variability among coffee cultivars for the reaction against coffee diseases.

 

 

 

 

 

 

 

 

 

 

 

 

 

Despite the role of coffee in the national economy and in spite the country of origin of Arabica coffee, average national productivity has not exceeded six quintals (600 kg/ha). This is very low in contrast to yield levels reported usually in some Latin American countries. The factors attributed to such low productivity include lack of resistant varieties to various diseases and insect pests, and poor agronomic practices.

Lack of suitable varieties that exhibit stable yield performances across wide ranges of environments is the major factor among several production constraints contributing to low productivity of Arabica coffee in Ethiopia which indicated that testing the adaptability of coffee varieties at range of environments and specific location is paramount important.

A number of coffee varieties developed through short term and long term programs. But their performance varies with agro-climatic condition (Location) in addition to their genetic potential. Coffee cultivars yields are affected by location, that is, those cultivars outperformed in one location might perform differently in other locations with different altitude and agro-climatic condition. Accordingly, variety Catimor J-19 performed best at all location with respect to fresh bean yield and dried clean coffee followed by Angafa indicating that the materials are well adapted to the edaphic and agro-climatic condition of Dilla, Halaba and Loka Abaya. In line with the great yield performance and stable yield across locations, coffee varieties tested were tolerant to common coffee diseases (CBD and CLR).

Thus, these coffee varieties can confidently widely be promoted for larger commercial production at tested locations and locations with similar agro-ecological conditions.

 

The authors have not declared any conflict of interests.