Ecological Factors Influencing Incidence and Severity of Coffee Leaf Rust and Coffee Berry Disease in Major Arabica Coffee Growing Districts of Uganda

Uganda Journal of Agricultural Sciences, 2013, 14 (1): 87 - 100 ISSN 1026-0919 Printed in Uganda. All rights reserved © 2013, National Agricultural Research Organisation Ecological factors influencing incidence and severity of Coffee Leaf Rust and Coffee Berry Disease in major Arabica coffee growing districts of Uganda R.J. Matovu1, A. Kangire1, N.A. Phiri2, G.J. Hakiza1, G.H. Kagezi1 and P.C. Musoli1 1National Agricultural Research Organisation (NARO)/National Crops Research Institute (NaCRRI)/ Coffee Research Center (COREC), P.O. Box 185 Mukono,Uganda 2CABI Africa Regional Center, P.O. Box 633-00621, Village Market, Nairobi, Kenya Author for correspondence: [email protected] Abstract Coffee Leaf Rust and Coffee Berry Disease are the most devastating diseases of Arabica coffee in Africa. The importance of coffee in economies of many African countries like Uganda, presents urgent need for cost-effective disease control strategies. In this study, 192 coffee farms were surveyed and their corresponding incidence and severity recorded. Nebbi district had the highest CLR incidence (90.2%) and severity (2.2%) followed by Sironko (67.9% and 1.9%) and least in Kapchorwa (20.4% and 1.3%) respectively. CBD incidence was highest in Kapchorwa (6.0%) followed by Nebbi (1.7%).There was no CBD incidence observed in Sironko. There was a significant (pd”0.05) interaction between altitude and disease severity. Thin and medium shade intensity had highest CLR incidence followed by thick and no-shade levels. CLR was highest in farms under mono-shade followed by farms under mixed-shade and least in open-farms. CLR severity was found to be highest at very steep slopes and medium slopes and least on gentle slopes. In conclusion, CLR was present in all surveyed districts while CBDoccurred in Kapchorwa and Nebbi districts at intensity levels enough to trigger economic losses. Key words: Coffee Berry Disease, Coffee Leaf Rust, ecological factors, pathosystem, Uganda Introduction earnings either directly or indirectly along the value chain (Sayer, 2002). Uganda is the second biggest coffee Two major coffee diseases that have producer and exporter in Africa after ravaged Arabica coffee production in Ethiopia (ICO, 2009), contributing an Uganda are Coffee Leaf Rust (CLR) estimated 2.97% of its crop to the world caused by the biotrophic fungus Hemilea market (ICO, 2011). In the coffee year vastatrix (Berkeley and Broome) and 2010/2011, Uganda exported 3.15 million Coffee Berry Disease (CBD) caused by 60-kilo bags valued at $448.89 million, Colletotrichum kahawae (Bridge and constituting 78.87% Robusta and 21.13% waller) (UCDA,2011). Coffee Leaf Arabica coffee, (UCDA, 2011). Over 13 Rustis capable of infecting both million Ugandans derive a substantial commercial coffee species; Coffea proportion of their livelihood from coffee arabica and Coffea canephora, although 88 R.J. Matovu et al. the former is more susceptible. On the Host resistance remains the most other hand, CBD infects only C.arabica economically viable option especially for at elevations above 1500 meters above resource constrained farmers (Omondi et sea level (a.s.l) (Hakiza, 1997). al., 2001; Gichuruet al., 2008). This Coffee Leaf Rust causes about 10 to control strategy, however, is challenged by 50% yield loss in farms with susceptible resistance erosion presumably due to an coffee varieties especiallyif no control evolutionary response by pathogens to measures are undertaken (Van der host defense mechanisms through Vossen, 2001; Silva et al., 2006). In mutation and recombination (Hulbert et contrast, CBD may cause up to 70 to al., 2001; Vleeshouwers et al., 2001). 80% losses if no control measures are Agrios (2005) and Okori (2004) adopted, especially, in years when berry elucidate the significance of monitoring yield is high (Waller, 1985; Silva et al., populations of pathogens and host plants 2006). Coffee Leaf Rust manifests itself in an evolving environment. Most as yellow pustules on the lower surface importantly, such studies should give of leaves turning orange-yellow with special emphasis to biotic and abiotic powdery masses of uredeniospores in factors in the environment under going later stages. Defoliation of affected plants strong influence by human activity as a is a common symptom, which leads to loss result of disease management. Proper of yield and quality of coffee. Coffee understanding of the interaction of the Berry Disease infects all stages of the elements of disease triangle in the crop from flowers to ripe fruits and seldom pathosystem enables formulation of leaves. Major losses are observed efficient and cost-effective disease following infection of green immature management strategies before disease berries which then develop dark sunken progress reaches economic injury level. lesions with sporulation, causing The aim of this study was therefore to premature dropping and mummification determine incidence and severity of (Silva et al., 2006; Gichimu and Phiri, Coffee Leaf Rust and Coffee Berry 2010). Control of CLR by fungicide Diseases in major Arabica coffee growing application with Orius (Tebuconazole) districts of Uganda, and to study the following a bi-weekly spray regime has relationship between the observed disease proved very effective, although copper incidences and existing ecological factors. based fungicides such as Copper oxychloride and Nordox 75% have Materials and methods exhibited moderate potency (Matovu, unpublished data). Unfortunately, fungicide Study area use is fraught with resources constraints The study was conducted from August since most coffee farmers are small- to November 2009 in two major Arabica holders hence making it economically coffee growing regions of Uganda; Mt unfeasible. Cultural control measures such Elgon region (Kapchorwa and Sironko as pruning, stumping, de-suckering, districts) which borders with Kenya, and fertilizer application and coffee tree West-Nile region (Nebbi district) which spacing, have also shown promise although borders Democratic Republic of Congo they cannot stand alone if effective control (DRC). The study area in Mt. Elgon lies is to be achieved (Bigirimana et al., 2012). approximately between latitudes 1° 17’N Incidence and severity of Coffee Leaf Rust and Coffee Berry Disease 89 and 0° 51’N and longitude 34° 13’E and while for Coffee Berry Disease was the 34° 25’E at an altitude of 1288-2135M extensive brown to black sunken lesions above sea level (van Astenet al., 2011). on both green and red berries leading to In Nebbi district, the study area lies mummification of berries. The sampled between latitudes 2° 14’N and 2° 46’N trees were then physically counted and and longitudes 30° 76’E and 31° 52’E at tagged from 1-30 with the help of an altitude of 1450-1800M above sea conspicuous coloured labels. level. Mt Elgon region receives a mean Since both diseases cause observable annual rainfall of more than 1520 mm while and distinct symptoms to the coffee plant, West-Nile receives 1100 mm, following a a comprehensive and robust approach of bimodal pattern in both regions. quantifying disease was adopted. Disease Temperatures at both locations range incidence and severity were selected as between 15°C-30°C throughout the year. variables for data collection. In this case, All soils in Mt Elgon region are derived disease incidence accounted for the from volcanic ash and agglomerate. proportion of coffee trees diseased out of Specifically, Sironko areas generally have the 30 trees sampled, while disease dark-brown clays while Kapchorwa has severity (intensity) for the relative or red sandy clay loam soils. On the other absolute area of leaf/berry tissue affected hand, the soils in Nebbi are red clay loams by respective disease. Disease severity derived from amphibolites (Aniku, 2001). was visually estimated with the help of a A stratified random sampling procedure disease rating scale (1-4) to quantify the was adopted where in each district, four extent of infection per tree; 1= No coffee sub-counties were randomly selected. leaf rust or CBD, 2= <10% diseased From each of the sub-counties, four leaves or berries, 3= 10-30% diseased parishes were chosen and in each of these berries or leaves, 4= >30% diseased four villages were selected and leaves or berries (Phiri et al., 2001; subsequently in each village four coffee Bigirimana et al.,2012). In addition, data farms were surveyed. Coffee farmers in on current agronomic practices and each district were contacted and their environmental properties such as; soil type, farms surveyed with the help of district shade nature, farm topography and altitude, and sub-county agricultural extension were collected to determine their influence officials as guides. The importance of this on coffee disease occurrence. Data on team was to identify farmers, build trust shade types were collected at 3 levels and provide subsequent follow-ups to the where coffee farms shaded with more farmers. than 1 tree species were recorded as mixed tree species, while those with only Data collection procedures one tree species were recorded as mono At each farm, 30 randomly selected trees tree species and un-shaded farms in open on a diagonal transect across the farm sun were recorded as no-shade.The nature were assessed for incidence and severity of shade at each farm was assessed by of Coffee Leaf Rust and Coffee Berry visual estimates using a rating scale; No Disease. A diagnostic symptom of Coffee shade = 100% light penetration, thin shade Leaf Rust was the presence of yellow- = 99% to 70%, Medium shade = 69% to orange pustules on the underside of leaves 40% and Thick shade = 39% to 20%. Soil 90 R.J. Matovu et al. type was visually assessed by field Results analysis of soil texture using the ‘feeling method’.The nature of topography for Coffee Leaf Rust and Coffee Berry each farm was visually assessed based Disease incidence and severity on its degree of inclination; Gentle slope The survey results indicate a wide = below 5°, medium slope = 6° to 30°, distribution of CLR in all major Arabica steep slope = 31° to 50° and very steep coffee growing districts of Uganda (Table slope = 51° to 90°.

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