African Crop Science Journal African Crop Science Society ISSN: 1021-9730 EISSN: 2072-6589 Vol. 6, Num. 3, 1998, pp. 283-291

P. R. SPEIJER, F. SSANGO, C. KAJUMBA and C.S. GOLD

International Institute of Tropical Agriculture (IITA), Eastern and Southern Africa Regional Centre (ESARC), P.O. Box 7878, Kampala Uganda

The optimum sample size for assessment of nematode densities and related damage in East African highland banana was estimated at Kikoni parish in Ntungamo district, Uganda. Kikoni parish is at an elevation ranging from 1360 to 1480 meters above sea level and the East African highland banana (Musa AAA, Matoke and Mbidde groups) is the dominant crop. The parish is approximately 10 km² in size, with an estimated total of 500 farms. Out of these farms, 24 were randomly selected and a minimum of 15 plants per farm were sampled. Root samples were collected from recently flowered plants, assessed for root damage and nematodes were extracted from the scored root segments. Hierarchical classification analysis was performed on the values for density and damage to calculate the coefficient of variation and the method of maximum curvature was used to determine the optimum number of farms in the parish and number of banana plants within each farm for nematode density and damage assessment. Pratylenchus goodeyi was the dominant species with densities ranging from 500 to 25,000 per 100g fresh root weight, while the percentage dead roots ranged from 0.8% to 14.0% and the percentage root necrosis from 1.1% to 17.1%. The optimum numbers established, were three farms within the parish and five recently flowered banana plants in each farm.

Key Words: East African highland banana, Musa AAA, Pratylenchus goodeyi, root health assessment, sampling

La grandeur optimale de l'échantillon pour évaluer les densités des nématodes et les dégâts qui y sont liés sur les bananes en hautes terres de l'Afrique de l'Est a été estimée en Uganda dans la localité de Kikoni, Ntungamo district, située entre 1360 et 1480 m d'altitude. La culture la plus dominante dans cette localité est la banane comprenant les groupes de Musa AAA, Matoke et Mbidde. Kikoni a une grandeur de 10 km² avec un nombre total d'environs 500 fermes. De ceci, 24 fermes ont été sélectionnées au hasard et 15 plants échantillonés par ferme. Les échantillons des racines ont été collectionnés des plants en floraison, évalués pour les dégâts sur les racines; et les nématodes ont été extraits à partir des fragments des racines évalués. L'analyse hiérarchique de classification a été performée sur les valeurs pour la densité et les dégâts afin de calculer le coefficient de corrélation. La méthode de courbure maximale a été utilisée pour déterminer le nombre optimum de fermes dans la localité et les plants des bananiers dans chaque ferme pour l'evaluation de la densité des nématodes et les dégâts. Pratylenchus goodeyi était l'espèce dominante avec densités allant de 500 à 25000 par 100 g de poids frais des racines, pendant que le pourcentage des racines mortes variat de 0.8 à 14.0 % et le pourcentage des racines nécrosées de 1.1 à 17.1 %. Le nombre optimun établi était de 3 fermes dans la localité et 5 plants de bananiers en floraison dans chaque ferme.

Mots Clés: Banane de haute terre d'Afrique de l'Est, Musa AAA, Pratylenchus goodeyi, évaluation de la santé racinaire, échantillonage

Highland banana (Musa AAA, 'Matoke'group) is one of the most important staple food crops in the Great Lakes region of East Africa. Its production is in the highland areas and is mainly by small holders (INIBAP, 1986). One of the major constraints to banana production in Uganda are plant parasitic nematodes (Sebasigari and Stover, 1988; Gold et al., 1993). Yield reduction as high as 51% on highland banana due to nematode infestation in Uganda has been reported (Speijer and Gold, 1996). The nematode species distribution and the extent of damage is elevation and Musa genome group dependent (Speijer, 1996). In Uganda, Pratylenchus goodeyi (Cobb) Sher and Allen dominates from 1350 meters above sea level (masl) and higher, while Radopholus similis (Cobb) Thorne and Helicotylenchus multicinctus (Cobb) Golden are more common at areas below this elevation (Kashaija et al., 1994). The highland bananas appear to be more susceptible to nematodes than the more recently introduced cultivar Pisang Awak (Musa ABB) (Speijer and Bosch, 1996).

For the establishment of nematode pest status and for the impact assessment of control strategies, such as the introduction of a resistant cultivar or a biological control agent, it is essential to accurately and cost effectively assess the extent of nematode damage in highland banana. Damage estimation and nematode identification are time consuming and therefore costly. The variability of nematode counts and damage among and within farms constitutes a major component of error (Sarah, 1991). This random error needs to be minimized by using adequate sampling techniques. Several methods for the assessment of nematode damage have been proposed (Bridge and Gowen, 1993; Speijer and Gold, 1996). However, no guidelines have been established on the optimum number of farms in a given area and banana plants within those farms to be sampled. The number of farms and number of plants within a farm required for an accurate assessment, depends on the size of study site, the variability in farming systems, nematode density and /or species (Ferris and Ferris, 1974). Use of an optimum sample size will greatly improve on the efficiency of sampling.

Therefore, a case study was conducted to estimate the number of farms and number of plants within each farm required for a representative sampling of a parish in one of the intensively cultivated highland banana-growing regions of Uganda.

Study location and sampling procedure. The study was carried out in Kikoni parish, Ntungamo district, south-west Uganda and is representative of the intensively cultivated highland banana growing regions of Uganda. Ntungamo district has hilly topography and the area's altitude ranges from 1360 to 1520 masl. The soils are sandy loam and vary in levels of organic matter (Okech et al., 1996). It is a densely populated district with intensive land use, which is resulting in a degradation of soil fertility and an increased pest pressure from mainly banana weevils and plant-parasitic nematodes. Consequently, highland banana production in the district is declining (Okech et al., 1996). Kikoni parish (1360 masl to 1480 masl) occupies approximately 10 km² with an estimated total of 500 farms. The approximate number of banana stands per farm ranged from 100 to 200 (Okech et al., 1996). The homesteads are scattered over the parish and the farms form a more or less continuum of banana plants. Boundaries between villages are of an administrative nature.

In Kikoni parish 24 farms were selected, based on the farmer's interest in farmer participatory research of the on-going African Highlands Initiative Project (Okech et al., 1996 ). The 24 farms were distributed over eight villages. In each farmer's field, samples were collected from a minimum of 15 plants in recently flowering stage (14 days or less after flower emerge) on separate banana mats. All roots were removed from an excavation of 20 cm³ extending outward from the corm of the flowered plants and characterized as dead or functional (Speijer and De Waele, 1997). Five functional roots per sample were randomly selected, indexed for extent of necrotic root cortex and scored for presence or absence of root knot nematode galls. The extent of damage to the root system was expressed as percentage dead roots and as percentage root necrosis. Nematodes were extracted from a 5 g of root mixture subsample of the indexed roots using a modified Baermann funnel technique (Hooper, 1990). Nematodes were identified at species level and counted under a light microscope in 2 ml aliquots from 25 ml suspensions. Nematode densities per 100 g fresh weight were estimated.

Data analyses. The villages, farms within villages and plants within farms were selected randomly. The P. goodeyi and Meloidogyne spp. J2 counts were transformed to the natural log (x + 1) scale, percentage dead roots and percentage root necrosis to the arcsine square root scale prior to analyses (Gomez and Gomez, 1984), while incidence of root knot nematode galls was used untransformed. Components of variance were estimated, using the VARCOMP procedures in SAS (SAS, 1992).

Relationships between P. goodeyi counts, Meloidogyne spp. J2 counts, percentage dead roots, percentage root necrosis and root knot nematode incidence were evaluated for linear correlation, using the CORR procedure in SAS (SAS, 1992).

To determine the optimum sample size for farms in a parish and plants in a farm the data set consisting of P. goodeyi densities, percentage dead roots and percentage root necrosis of 365 plants in 24 farms were considered as one unit. To estimate the optimum number of farms to be sampled this unit was randomly divided into two blocks each with 12 farms (Fig. 1). The blocks were randomly divided into four plots of six farms each. Similarly the plots were randomly divided into eight subplots each with three farms and in turn the subplots were divided into 24 sub-subplots each with one farm (Fig. 1). Hierarchical classification analysis was performed and coefficient of variation values of the respective divisions in hierarchical order were computed according to Gomez and Gomez (1984). The number of farms were plotted on the x-axis and coefficient of variation on the y-axis. The optimum points were determined by the method of maximum curvature (Le Clerg, 1966). The optimum number was read as the point on the curve where the rate of change for variability index per increment of number of farms plants is greatest (Ortiz, 1995), which is known as the point of inflection.

To estimate the optimum number of plants to be sampled in a farm, five farms with no significant differences in densities of P. goodeyi and damage indices were put together giving a total number of 60 plants (Fig. 2). This data set was randomly divided into three blocks each with 20 plants. The blocks were divided in turn into six plots each with 10 plants. The plots were subdivided into 12 subplots each with five plants and in turn subplots were divided into 60 sub-subplots each with one plant. Hierarchical classification analysis was performed and coefficient of variation values of the respective divisions in hierarchical order were computed according to Gomez and Gomez (1984). The number of farms in a parish and the number of banana plants in a farm were plotted on the x-axis and coefficient of variation for P. goodeyi counts, percentage dead roots and percentage root necrosis on the y-axis. The optimum sample size was read at the point of inflection.

Sampling procedure. At twenty-one farms, 15 or more recently flowered plants could be sampled. However at one farm 14 and at two farms only 10 recently flowered plants were obtained. This was either caused by a poor crop condition resulting in few flowered plants or due to a relatively small banana plot size compared to the general plot size of 100 to 200 mats. Plantation age ranged from 1 to 63 years, with an average of 36 years, but age did not show any significant association with P. goodeyi counts, percentage dead roots or percentage root necrosis (r£0.198, P>0.05) and was therefore excluded from further analyses.

Nematode densities and damage. Pratylenchus goodeyi was the dominant species observed and its densities ranged from 533 to 29,200 per 100 g among the farms and with a standard error ranging from 251 to 6170 per 100 g among the plants within a farm (Table 1). Meloidogyne spp. juveniles (J2) were extracted from roots in 15 of the 24 farms and the observed maximum average farm density was 750 J2 per 100 g roots. Heticotylenchus multicinctus was found in four of the 24 farms, whereby its maximum average farm density was 50 per 100 g. Radopholus similis was not observed. The percentage dead roots averaged 5.4 % for the parish and ranged from 0.8 % to 14.0 % between the farms (Table 1). Root necrosis averaged 4.8 % for the parish and ranged from 1.1 % to 17.1% between the farms. Root-knot nematode galls were observed in 18 of the 24 farms, whereby the maximum incidence of plants within a farm with root knot galls was 33%.

TABLE 1. Nematode densities percentage dead roots and percentage root necrosis, assessed on recently flowered highland banana plants in Kikoni parish, Ntungamo district, Uganda

Pratylenchus goodeyi density was well correlated with extent root necrosis (r=0.50, P<0.01) (Table 2), however, none of the other density and damage parameters were well correlated.

TABLE 2. Linear correlations tor Pratylenchus goodeyi counts, Meloidogyne J2 counts, percentage dead roots. percentage root necrosis and root knot nematode incidence for highland bananas in 24 farms in Kikoni parish, Ntungamo district, Uganda

Percentage contribution to the variance. Estimation of the percentage contribution to the total variance revealed that village effect was less than 2 % for P. goodeyi, percentage dead roots or percentage root necrosis (Table 3). Therefore farms from the different villages could be pooled in the parish for the estimation of the optimum sample size of farms within a parish. Farms within village effect contributed 12.4 % to the variation in P. goodeyi counts, 9.7 % to the variation in percentage dead roots and 8.8 % to the variation in percentage root necrosis, while the plants within farm effect contributed 4.2 % to the variation in P. goodeyi counts, 1.2 % to the variation in percentage dead roots and 25.2 % to the variation in percentage root necrosis.

TABLE 3. Estimation of the percentage variance in Pratylenchus goodeyi counts, dead root percentage and root necrosis percentage, assessed for recently flowered plants of highland bananas in eight villages, 24 farms and 365 plants in Kikoni parish, Ntungamo district, Uganda

Optimum sample size for farms within a parish and plants within a farm. An inverse relationship was observed between coefficient of variation for P. goodeyi counts, percentage dead roots and root necrosis, when plotted against number of farms (Fig. 3). The average coefficient of variation for percentage dead roots was lower compared to P. goodeyi counts and percentage root necrosis, however, the points of inflection suggest for all parameters that three farms is the optimum sample size within a parish. Also an inverse relationship was observed between coefficient of variation for P. goodeyi counts, percentage dead roots and root necrosis, when plotted against number of recently flowered plants within a farm. (Fig. 4). The average coefficient of P. goodeyi counts was lower, compared to percentage dead roots and percentage root necrosis, however, the points of inflection suggest for all parameters that five recently flowered plants is the optimum sample size within a farm.

Pratylenchus goodeyi was the dominant species observed. This nematode was first reported in Uganda in Mbarara and Bushenyi districts in the early 1960 (Whitehead, 1961). It is commonly observed in the highlands of East Africa (Kashaija et al., 1994; Speijer and Bosch, 1996) and believed to be indigenous (Gowen and Quénéhervé, 1990). The 5.4 % dead roots and 4.8 % root necrosis observed on recently flowered plants of highland banana in Ntungamo districts are in the same range as earlier observations made in Mbarara district (Rukungiri at1430-1460 masl with a 8 % dead roots of 8 % and 4 % root necrosis) and Bushenyi district (Ryeru at 1320-1420 masl with 12 % dead roots and 7 % root necrosis (Speijer et al., 1994).

Pratylenchus goodeyi density appears to be the major factor influencing the extent of root necrosis, while the severity of dead roots may be more influenced by other factors as crop management. Speijer et al. (1998) observed the opposite for H. multicinctus and R. similis, which appeared to influence the extent of dead roots of highland banana, while crop management was a major factor influencing root necrosis.

The relatively low contribution of village effect to the total variance on P. goodeyi counts, percentage dead roots and percentage root necrosis could be expected, as the farms are more or less evenly scattered over the parish and form a more or less continous area under highland banana.

An inverse relationship was observed between coefficient of variation for P. goodeyi counts, percentage dead roots and root necrosis, when plotted against number of farms in a parish (Fig. 3) or when plotted against number of recently flowered plants in a farm (Fig. 4). Similar relationships were found for the estimation of bunch weight in banana trials in Nigeria (Ortiz, 1995) and yield potential of sweet potato cultivars in Peru (23). The coefficient of variation values for the number of farms in hierarchical order (Fig. 2), were higher than those of the number of plants per farm (Fig. 3). The coefficient of variation values for farms were lowest for percentage dead roots and for plants within farms lowest for P. goodeyi counts. Highest coefficient of variation values were observed for percentage root necrosis in both situations. The farms across the parish differed in management practices, soil type, topography and elevation, which may have influenced nematode densities and damage resulting into higher coefficient of variation values between farms compared to those for the number of flowered plants within a farm. under similar management. The results suggested that three farms and five mats within each farm were optimal numbers for the assessment of nematode population densities and their damage.

The authors wish to thank Dr. S.H.O. Okech, for the help he rendered in data collection and the Africa Highlands Initiative (AHI), for funding this research.

Bridge, J. and Gowen, S.R. 1993. Visual assessment of plant parasitic nematode and weevil damage on bananas and plantain. In: Proceedings of a research coordination meeting for biological and integrated control of Highland banana and plantain pests and diseases with emphasis on banana weevil, Cosmopolites sordidus, held at Cotonou, Benin, 12 to 14 November, 1991. Gold, C.S. and Gemmil, B. (Eds.), pp. 147-154. The Printer, Davis, California, USA.

Ferris, V.R. and Ferris, J.M. 1974. Inter-relationships between nematode and plant communities in agricultural ecosystems. Agro-Ecosystems 1:275-299.

Gold, C.S., Ogenga-Latigo, M.W., Tushe-mereirwe, W., Kashaija, I.N. and Nankiga, C. 1993. Farmer perception of banana pest constraint in Uganda. Results of a rapid rural appraisal. In: Proceedings of a research coordination meeting for biological and integrated control of Highland banana and plantain pests and diseases with emphasis on banana weevil, Cosmopolites sordidus, held at Cotonou, Benin, 12 to 14 November, 1991. Gold, C.S. and Gemmill, B. (Eds.), pp. 3-24. The Printer, Davis, California, USA.

Gomez, K.A. and Gomez, A.A. 1984. Statistical Procedures for Agricultural Research. John Wiley and Sons, New York. 680pp.

Gowen, S.R. and Quénéhervé, P. 1990. Nematode parasites of banana, plantains and abaca. In: Plant parasitic nematodes in subtropical and tropical Agriculture. Luc, M., Sikora, R.A. and Bridge, J. (Eds.), pp. 431-460. CAB International, Wallingsford, Oxon, UK.

Hooper, D.J. 1990. Extraction and processing of plant and soil nematodes. In: Plant parasitic nematodes in subtropical and tropical Agriculture. Luc, M., Sikora, R.A. and Bridge, J. (Eds.), pp. 45- 68. CAB International, Wallingsford, Oxon, UK.

INIBAP. 1986. Banana research in Eastern Africa. Proposal for a regional research and development network, INIBAP/86/3/001 rev. INIBAP, Montpellier Cedex-France.106pp.

Kashaija, I.N., Speijer, P.R., Gold,C.S. and Gowen, S.R. 1994. Occurrence, distribution and abundance of plant parasitic nematodes of bananas in Uganda. African Crop Science Journal 2:99-104.

Le Clerg, E.L. 1966. Significance of experimental design in plant breeding. In: Plant breeding. Frey, K.J (Ed.), pp. 243-311. Iowa Univ. Press, Ames, USA.

Okech, S.H.O., Gold, C.S., Speijer, P.R., Karamura, E., Ssali, H. and McIntyre, B. 1996. Relationships between soil fertility, banana weevil, nematodes and agronomic practices in South western Uganda. Musafrica 10:31.

Ortiz, R. 1995. Plot techniques for assessment of bunch weight in banana trials under two systems of crop management. Agronomy Journal 87:63-69.

SAS. 1992. SAS Guide for Personal Computers. 6th ed. SAS Institute, Inc, Cary, NC.

Sarah, J.L. 1991. Estimation of nematode infestation in banana. Productions fruitieres et horticoles des regions tropicales et mediterraneennes. Fruits 46:643-646.

Sebasigari, K. and Stover, R.H. 1988. Banana diseases and pests in East Africa. A report of a survey made in November. 1987. INIBAP88/02, INIBAP Montpellier France pp.15.

Speijer, P.R. 1996. Root and rhizome damage comparison on four Musa cultivars. Musafrica 9:8-9.

Speijer, P.R. and Bosch,Ch.H. 1996. Nematode susceptibility within Musa and cultivar shifts in Kagera Region, Tanzania. Productions fruitieres et horticoles des regions tropicales et mediterraneennes Fruits, 51:217-222.

Speijer, P.R. and De Waele, D. 1997. Screening of Musa germplasm for resistance and tolerance to nematodes, INIBAP Technical Guidelines 1, International Network for the Improvement of Banana and Plantain, INIBAP Montpellier, France, pp. 47.

Speijer, P.R and Gold, C.S. 1996. Musa root health assessment: a technique for the evaluation of Musa germplasm for nematode resistance. In: Proceedings of the workshop on new frontiers in resistance breeding for nematode, Fusarium and Sigatoka held at Kuala Lumpur, Malaysia 2-5 October 1995, Frison, E.A., J-P. Horry, and D. De Waele (Eds.). pp. 62-78. INIBAP Montpellier, France.

Speijer, P.R., Gold,C.S., Karamura, E.B. and Kashaija, I.N. 1994. Banana weevil and nematode distribution patterns in highland banana systems in Uganda: Preliminary results from a diagnostic survey. In: First International Crop Science Conference for Eastern and Southern Africa, held in Kampala, 14-18 June 199, Volume 1. Adipala, E., M.W. Ogenga-Latigo, M. Bekunda, J.O., Mugah and J.S. Tenywa (Eds.), pp. 285-289. African Crop Science Society, Makerere University, Kampala, Uganda.

Speijer, P.R, Mudiope, J., Ssango, F. and Adipala, E. 1998. Comparison of plant stages for the evaluation of nematode damage to East African Highland banana (Musa AAA-EA). African Plant Protection 4:1-7.

Whitehead, A.G. 1961. Plant nematology progress report. East Africa high commission, East Africa Agriculture Forestry Research Organization, Muguga, Kenya.

Copyright 1998, African Crop Science Society

The following images related to this document are available:

Line drawing images