Global climatic changes like increase in frequency and intensity of drought affect agriculture and food security at large. Among the effects of climate change, drought is the most frequent factor (Athar and Ashraf, 2009). Drought’s effect hinders crop production with estimates indicating that drought independently contributes up to 17% yield loss of  the major crops when compared with other abiotic stresses  (Athar and Ashraf, 2009). The rates of yield reduction for major crops such as barley, rice, sorghum, maize and wheat will therefore increase by more  than   50%   in   2050  and  almost  90% in  2100  if sufficient adaptation measures are not implemented (Athar and Ashraf, 2009). A necessary and sustainable solution is to develop crop cultivars that can tolerate these climatic stresses to be able to feed the growing population (El-Sharkawy, 2007).

Cassava (Manihot esculenta) has a high potential to reduce hunger as compared to other crops especially in the developing countries. The crop is resilient to climatic changes and could therefore give options while other major food crops face the climatic challenges (El-Sharkawy,  2007). It is drought tolerant because it can be grown in low fertile soils (Burns et al., 2010) and can be easily propagated (Hillocks, 2002). Additionally, the tubers which are highly perishable can be left in the soil and fetched when needed for up to 3 to 4 years after maturity (Okogbenin et al., 2013). After rice and maize, cassava is the third most important source of calories in the tropics (El-Sharkawy and Cadavid, 2002). The crop’s leaves can be consumed as vegetables because they have proteins and vitamins contents (Westby, 2002). Cassava serves as a greater part of the diet for almost a billion people in approximately 105 countries and Africa is the largest producer with 118 million tons (FAO, 2018).

The ability of cassava to be tolerant to drought has been associated with several morphological traits that enable it to prevent the negative effect of drought stress. Some of the traits include fine and deep rooting to access water, reduced leaf canopy and production of small leaves among others (Bull et al., 2011). Morphological traits are useful when it comes to primary assessment for drought tolerance in cassava because it provides information on variation and correlation on these traits (Okogbenin et al., 2013). However, they are highly influenced by the environment. Therefore, identification and characterization of the morphological traits will be critical in selecting drought tolerant cultivars for the purpose of cassava improvement. Rather than a single trait, a combination of different traits of direct importance is always used as selection criteria (El-Sharkawy and Cadavid, 2002). Characterization of these morphological differences therefore, will establish an essential foundation for future development of drought associated markers for cassava.

This study therefore aimed at assessing the performance of selected cassava varieties under drought conditions using morphological traits and identified high-yielding drought-tolerant cassava varieties as a means of contributing to increased food security.

Description of the study area

The experiment was carried out in Kiboko research station in Makindu sub-County of Makueni County, Kenya. The site is classified under arid and semi-arid lands (ASAL) of Kenya. Soil type analysed during the experiment was sandy clay loam. Rainfall data during the experiment confirmed a bi-modial pattern with long rains received between March and May and short rains between October and December. There was a period of drought from June to September  before the onset of short rains. The maximum mean annual temperature ranged from 29 to 30°C, while minimum temperature varied from 13 to 18°C.

Experimental design

The experiment was laid out in a randomized complete block design (RCBD) and 79 cassava varieties were used. Approximately,  1.5 ha of land was ploughed and each split into four blocks of equal sizes and each block divided into 79  plots  consisting  of  four  rows spacing 1×1 m per plot. Each row consisted of four plants per variety. For plant establishment, irrigation was sustained through overhead irrigation. Thirty days after planting (DAP), the treatments were introduced whereby, two blocks watered after every week and the other two after every two weeks. There was no application of fertilizer or agro-chemicals. The crop was manually weeded after every two months and the treatments were applied untill harvesting. Harvesting was done at 12 months after planting.

Measurement of phenotypic parameters

Data on the plant parameters was taken using standard cassava descriptors of IITA and modified by Fukuda et al. (2010) to evaluate the 79 cassava genotypes. Different parameters were collected and recorded at 3, 6, 9 and 12 months after planting (MAP). Vertical height (cm) was measured from the ground to the top of the canopy and recorded as plant height. After harvesting, storage roots (NSR) were counted manually with length greater than 20 cm and above ground weight (AGW) was obtained from the stems, branches and leaves. The storage fresh roots weight (SRFW) was measured using a scale, per plant. The harvest index (HI) was measured using to the formula: HI = weight of the roots / weight of roots + weight of above ground biomass. Leaf retention (LR) was determined at six months after planting because this period normally coincides with drought stress in most cassava growing regions in eastern and southern Africa.

Statistical analysis

The data were subjected to a two-way analysis of variance (ANOVA) using GenStat 12.0 statistical package. Least significance difference (LSD) at 5% probability level was used to compare treatment means. The Pearson correlation coefficient (r) was used to analyze the inter-relationship between traits.

Performance of the genotypes

Most of the genotypes assessed varied significantly (P<0.001) within genotypes, treatments and interactions between genotypes and treatments.

Significant (p<0.05) variations was observed for SRFW, NSR, AGW, PH, HI and LR. Similar traits have been reported (El-Sharkawy, 2007; Turyagyenda et al., 2013). Under water stress treatment (Table 1) the highest SRFW was obtained from LML/2008/363 (26kg) with 110 (07/0621HS) (1.85 kg) giving the least. Genotype SANGOJA had the highest NSR of 13.75, while MM96/6966A the least with 3.38. The highest AGW (14.57 kg) was recorded from MM06/0143 with MM96/5280 having the least (2.10 kg). SANGOJA expressed the highest PH with 290.00 (cm) with 99 (07/1313HS) (79 cm) as the least. Genotype LML/2008/363 had the highest HI of 0.77 with MM06/0143 having the lowest 0.26. Genotype 94 (05/0741HS) produced the highest LR of 100% among others while 93 (07/0756HS) and MM06/0138 as the least with 50.00%. Under non-stressed treatment as described in Table 2, LML/2008/363 expressed the highest SRFW of 24.13 kg with MM96/1871 (2.63 kg) giving the  least.  Genotype  SANGOJA  had  the  highest NSR of 14.75 while COLICANANA the least with 3. EYOPE had the highest AGW (26.82 kg) with MM96/1871 having the least (2.31 kg). F10-30R2 expressed the highest PH with 302.50 cm with TME 14 as the least with 151.20 cm. Genotype MM97/1744 had the highest HI of 0.77 with 197 (01/1797HS) as the lowest 0.24. Genotype MM96/0686 produced the highest LR of 100% among others while 93 (07/0756HS) as the least with 53.13%. Best and least yielding varieties were obtained from the difference between the non-stressed and water stressed varieties in terms of SRFW. With the best being MM06/0013 (-2.88) and the least MM96/6966B (13.29) shown in Table 3.

Trait correlations

Correlation analysis performed revealed very high significant (P<0.001) differences among the traits. Root yield in terms of SRFW which is the ultimate aim of cassava breeding (Asogwa et al., 2006) was positively correlated with some traits under both water treatments. Under water stressed treatment (Table 4), positive correlation was expressed between SRFW and NSR (0.373**), AGW (0.301**) and HI (0.560**). The HI and AGW expressed negative significant correlations -0.398**. Under non-stressed treatment (Table 5), SRFW had a positive and significant with all the traits NSR (0.434**), AGW (0.377**), PH (0.102*), HI (0.437**) and LR (0.184**). There was negative significant correlations between HI and AGW (-0.482**).

These conclusions have also been observed from other previous studies (Mutegi, 2009). NSR has been  used  as a sink strength indicator of cassava and this means that high  root  number  will  lead  to  an  increase  in  yield  as concluded by Aina et al. (2007). LR has also been recorded to be a very important trait when it comes to the selection of good performing varieties under drought conditions (Aina et al., 2007). Other traits can also be used for indirect selection of high yielding cassava, for example HI which in other words is dry matter accumulation in economic parts of cassava (Alves, 2002) was found positively correlated with the yield. The HI and AGW showed significantly negative correlations and this was attributed to formulae used to compute HI as a ratio of storage root weight to the total weight (Fukuda et al., 2010). Therefore, an increase in AGW increases total plant weight and lowers HI and vice versa (Jennings and Iglesias, 2002). Association between traits provides ways of improving yield through indirect selection for drought prone environments (Fukuda et al., 2010).

Although cassava is a drought tolerant crop, low soil moisture content still affects its growth and productivity. SRFW which was used as the key trait for selection, expressed significant and positive correlation with other traits. Most of the drought tolerant varieties in the study showed higher NSR, HI and AGW as compared to drought susceptible varieties. This suggests that effective selection of drought tolerant cassava depends on a number of traits such as high strong storage sink that is, high root number per plant, high harvest index and good plant canopy.

The authors have not declared any conflict of interests.