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African Crop Science Journal
African Crop Science Society
ISSN: 1021-9730 EISSN: 2072-6589
Vol. 10, Num. 2, 2002, pp. 139-144

African Crop Science Journal, Vol. 10. No. 2, 2002,  pp. 139-144

Stability assessment of soybean varieties in Kenya

Dankit Nassiuma and Wafula Wasike1

Egerton University, P.O. Box 536, Njoro, Kenya 1NPBRC, P.O. Njoro, Kenya

(Received 23 January, 2001; accepted 5 August, 2001)

Code Number: cs02013

ABSTRACT

Soybean (Glycine Max (L.) Merr.) varieties grown in Kenya are imported from different countries and there is a renewed  interest in the cultivation and utilisation of the crop for both  home and  industrial use. The objective of this study was to screen soybean varieties for yield stability in different environments in Kenya and compare their performance under these environments. The overall aim was to identify appropriate and high yielding varieties of soybeans for production in diverse agro-ecological zones. These trials were conducted at four sites located at Busia and Homabay  in western Kenya and Gachoka and Thika in central Kenya, over a five year period. Ten varieties  were tested and the trials were set up in a randomised complete block design, with each variety replicated four times at each site. Cultivar yield stability at the environments, yielding ability, height at maturity as well as days to maturity formed the basis for assessing cultivar suitability for a given environment. There were  significant  cultivar x environment  interactions for all the response variables tested. Four cultivars, EAI3600, Gazelle, Nyala and Sable were identified to be stable in the different environments and were consistently observed to be high yielding and of appropriate height, maturity period and highly adaptable to the sites.

Key Words: Days to maturity, Glycine max

RÉSUMÉ

Les variétiés de soja (Glycine Max (L.) Merr) plantées au Kenya sont importées de différents pays. Il y a un renouvellement d'intérêt à la culture et à l'utilisation à la fois domestique et industrielle de la plante. L'objectif de cette étude était de tester les variétiés du soja pour un rendement stable dans les différents environnements du Kenya et comparer leurs performances dans ces derniers. Le principal visé était d'identifier les variétiés améliorées appropriées du soja et leur augmentation de rendement pour la production dans diverses zones agro-écologiques. Ces essais étaient conduit dans quatre sites différents dont Busia et Homabag dans l'ouest , Gashoka et Thika au centre, du Kenya pendant une période de plus de cinq ans. Dix variétiés étaient testées dans un block complètement pris au hazard avec chaque variété repétée quatre fois à chaque site. La stabilité de rendement d'une variété, l'abilité de rendement, la taille à maturation aussi bien que la date de maturation ont formé la base de l'étude de convenance d'une variété pour un environnement donné. Les intéractions variétés x environnements étaient significatives pour toutes les variables réponses testées. Quatre variétés EAI 3600, Gazelle, Nyala et Sable étaient identifiées stables dans les différents environnements, et   observées de manière consistante à rendement  élévé, de taille et période de maturate appropriées, et adaptable aux sites.

Mots Clés: Jours de maturité, Glycine max

INTRODUCTION

Soybean (Glycine max (L.) Merr.) is recognised as one of the oldest crop species cultivated by man. Currently, the largest producer of soybeans in the world is North America whose production stands at 70.5 million metric tonnes per year followed by South America (44.8 million metric tonnes per year).  Africa produces 0.6 million metric tonnes per year while the rest of the world produces 28.0 million metric tonnes. Most of the soybean produced in Africa comes from Kenya, Nigeria, Zimbabwe, Egypt, South Africa, Zambia, Malawi and Uganda (GTZ, 1998).  

The cultivation and utilisation of soybean  locally and at industrial level in Kenya has continued to grow and is probably motivated by the search for alternative sources of proteins and cooking oil. The main soybean producing areas in Kenya are Rift valley, Western, Eastern, Nyanza and Central provinces.  Since 1993, the total production in Kenya is estimated to have increased from 1000 metric tones (MT) to 5000MT per year (GTZ, 1998).

Soybean germplasm evaluation started in 1993 with 96  local and imported soybean varieties, which were tested for yields and management requirements, seed colour and height. The imported varieties were from regions that are similar to Kenya in latitude (day length), soil age but not necessarily in altitude such as Nigeria, Zimbabwe, Zambia and Ecuador on the basis of high yields. Ten of these varieties met the required criteria and were evaluated in this study.  Prior to this, there had been no work done in Kenya on the screening of soybean varieties for yield stability in different environments. With the increasing demand for soybeans, it was prudent to evaluate the available varieties rather than embark on a crossing programme.

Genotype by environment interactions caused by differential responses of genotypes in environmental changes is a factor that often complicates and confounds the selection of superior varieties. Cultivar crossover interactions, and genotypic rank change across environments are of importance in plant breeding and may slow down the selection process (Abdalla et al., 1997). The environment is defined as the sum total of the external conditions which influence growth and development of an organism (Allard, 1960). The different attributes of the environment include moisture supply, temperature and soil type among others (Yau et al., 1991).

Among the procedures that have been proposed for determining the stability of cultivars are various stability measurements and cluster analysis. Lin et al. (1986) reviewed nine stability statistics while Liu and Sun (1993) evaluated 17 statistics recommended for description of cultivar stability and recommended the use of Eberhart and Russell (1966) regression model in yield stability analysis of cultivars. Paroda and Hayes (1971) emphasised that the regression coefficient could be regarded as a measure of the response of particular cultivars whereas the deviation around the regression line is the most suitable measure of stability. Becker (1981) found the regression coefficient to be closely correlated with the environmental variance which implies that it is an appropriate tool for discriminating environmental effects.

Biological stability is analogous to the concept of homeostasis and refers to the production of constant yields by a genotype in all environments whereas a genotype is considered to have agronomic stability if its yields vary  in proportion to the productivity of the environments (Becker, 1981; Lin et al.,1986). The variance of the actual yields across sites, which is a measure of biological stability, can be converted into a simple agronomic measure of stability if the relative yield is used (Yau and Hamblin, 1994). The basis for cultivar selection in this study is the agronomic stability using the genotype x environment interactions (G x E) within and between the sites. This approach has been successfully applied in relation to fatty acid composition (Schnebly and Fehr, 1993), yields (Pfeiffer et al., 1995) and disease assessment (Anand et al., 1995).

The objective of this study was to select potentially high yielding soybean varieties that are also stable with regard to yields over a range of environments for production in some short season regions of Kenya. The adaptability of the varieties over similar environments (sites) was also evaluated.

MATERIALS AND METHODS

Ten cultivars were studied at two marginal rainfall sites, Gachoka, Thika and three low altitude sites, Gachoka, Homabay, and Busia over five years (1994-1998), except for Busia which had four years. This resulted in nineteen different environments for which the growth period is about three months. The sites were selected based on the results of analysis of climatological data and represent short season areas that are suitable for soybean production. The sites selected and their altitude, rainfall, temperatures, agro-ecological zones (AEZ) and soil characteristics are given in Table 1.

Three of the varieties, Bossier, EAI 3600 and Hill are local ones while Duicker, Gazelle, Nyala, Sable and SCS-1 were imported from Zimbabwe. The variety TGM 237-2 was imported from Nigeria while INIAP 303 was from Ecuador. The imported varieties were selected among the best yielding in the respective countries, while the choice of the local varieties was based on yielding ability and seed availability.

The trials were set up in a randomised complete block design with treatments (varieties) replicated four times. The spacing was 50 cm between rows and 10 cm within rows. The rows were 6 meters long and plot size was 18 m2. A seed rate of 75 kg ha-1  was used and 125 kg ha-1 of diammonium phosphate (DAP) was applied at planting. The soybeans were planted during the main rains that start in mid-March in Thika, Gachoka and Homabay as a main crop, while at Busia, the planting was during the second rains in mid-August as a second crop. Weather data simulations had been done to determine the start and end of the cropping seasons at each site.

The  response variables recorded in the trials were: yield from the net plot centre rows (YIELD), days to 50% flowering (DTF), days to physiological maturity (DTM), plant height at maturity (HTM) based on distance from the ground surface to the top of the main stem, pod clearance (HTFP) based on distance from the ground surface to the first pod, the number of pods per plant (PODS) obtained as the mean of pods per plant estimated from five plants, and the seed weight (SW) in grams of 100 randomly selected seeds from clean dried grain.

The analysis of variance was performed on the data to compare the various response characteristics between the varieties, environments and their interaction. The Least Significant Differences (LSD) were used in the separation of means while the environmental stability analysis for the yield was carried out using the regression model following Eberhart and Russell (1966). Variety site adaptability was based on the yielding consistency using the ranked performance at each of the sites.

RESULTS AND DISCUSSION

The overall performance of the varieties was evaluated based on the major criteria that the varieties have maturity periods that fit within 90 days, give high yields within this period and are also widely adaptable over the sites. Such varieties were selected over those that are location specific. The mean yields for the varieties tested were more than 1 t ha-1 except for Bossier. The environment mean yields ranged from 348 kg ha-1 to 4,010 kg ha-1 although most of the environments registered yields of between 348 kg ha-1 and 2,171 kg ha-1. Significant (P<1%) interactions between various cultivar characteristics and the environments were observed (Table 2) and these have the implication that on average, different varieties are suitable for different environments. Homabay had the highest mean yields for most of the varieties and this was followed by Thika, Gachoka and Busia which had the lowest yields. Environments with high yields of up to four tonnes per hectare were those at Homabay.

Cultivar INIAP 303 recorded significantly higher mean yields than the other cultivars,  was the tallest and had the longest period to maturity. This is bound to exposes it to the risk of lodging and attack from pests especially birds. Gazelle, the second highest yielding cultivar, was relatively short and took 87 days to mature. It was also consistently high yielding at the four sites. Cultivar SCS-1 was high yielding although it took 96 days to mature, while cultivars Nyala, EAI 3600, Hill and Sable matured at between 78-86 days on average and had yields which were not significantly different. Another cultivar TGM 237-2 had a mean yield of 1,044 kg ha-1 which was not significantly different from that of the cultivar Duicker. The overall ranking of the varieties at the four sites, which gives an indication of site adaptability is given in Table 3.

The significant cultivar x environment interaction led to an evaluation of cultivar stability parameters for soybean yield as given in Table 4. The stability parameters were not evaluated for Bossier since it was planted to only one environment, thus, stability tests were based on nine varieties. Deviations from regression show that they were significant (P=0.01) for the cultivars Duicker and Hill, while the regression coefficient was significantly different  (P=0.01) for the cultivars SCS-1 and TGM 237-2.

A stable cultivar is expected to have  a regression coefficient that is close to one and has small deviations from regression (Eberhart and Russel, 1966). In this study, the results show that , with the exception of SCS-1 and TGM 237-2, all  varieties led to regression coefficients not significantly different from one another. The coefficient of determination and the deviations from regression indicate the appropriateness of the regression model and facilitates the assessment of the predictability of the response of the cultivars to the environments. This is why the deviation from regression is regarded as an appropriate stability indicator for agronomic trials (Bilbro and Ray, 1976; Paroda and Hayes, 1971).  Results in Table 4 show that Duicker and Hill are the only varieties which have significant deviations (P=0.01) from regression, but all varieties have coefficients of determination that are significantly different (P=0.01) from zero.

Five varieties EAI 3600, Gazelle, INIAP 303, Nyala and Sable are, thus, stable in yields across the environments. Generally, INIAP 303 is the highest yielder followed by Gazelle, Nyala, EAI 3600 and Sable. Yielding ability as well as other  soybean variety characteristics are affected by their adaptability (Castillo and Montoya, 1994; Morrison et al., 1994). Lynch and Smith (1993) have further indicated that the environmental adaptability of a soybean variety affects its nitrogen fixation ability. Gazelle is the most adaptable variety to sites on the basis of high yielding consistency (Table 3) followed by Nyala, Sable, EAI 3600, and INIAP 303.

Varieties Duicker and SCS-1 seem suitable for environments in Homabay and Busia which have high rainfall amounts, are low in altitude and have high temperatures.

CONCLUSION

It is observed here that soybean varieties in short season regions of Kenya perform differently in different environments due to varying amounts and timing of rainfall during the cropping season. Variety recommendations should, thus, be based on the site although common denominators in the varieties can be obtained.  Five cultivars EAI 3600, Gazelle, INIAP 303, Nyala and Sable were found  to be yield stable over the 19 environments. However, the cultivar INIAP 303 took  too long to mature and was not adaptable to many sites although it was high yielding. Thus, four cultivars EAI 3600, Gazelle, Nyala and Sable which were  yield stable over the studied environments and had other appropriate characteristics are thus recommended for production.

REFERENCES

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©2002, African Crop Science Society


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