| Literature DB >> 25279278 |
Joshua Sikhu Okonya1, Robert Om Mwanga2, Katja Syndikus3, Jürgen Kroschel4.
Abstract
Insect pests are among the most important constraints limiting sweetpotato (Ipomoea batatas) production in Africa. However, there is inadequate information about farmers' knowledge, perceptions and practices in the management of key insect pests. This has hindered development of effective pest management approaches for smallholder farmers. A standard questionnaire was used to interview individual sweetpotato farmers (n = 192) about their perception and management practices regarding insect pests in six major sweetpotato producing districts of Uganda. The majority (93%) of farmers perceived insect pests to be a very serious problem. With the exception of Masindi and Wakiso districts where the sweetpotato butterfly (Acraea acerata) was the number one constraint, sweetpotato weevils (Cylas puncticollis and C. brunneus) were ranked as the most important insect pests. Insecticide use in sweetpotato fields was very low being highest (28-38% of households) in districts where A. acerata infestation is the biggest problem. On average, 65% and 87% of the farmers took no action to control A. acerata and Cylas spp., respectively. Farmers were more conversant with the presence of and damage by A. acerata than of Cylas spp. as they thought that Cylas spp. root damage was brought about by a prolonged dry season. Different levels of field resistance (ability of a variety to tolerate damage) of sweetpotato landraces to A. acerata (eight landraces) and Cylas spp. (six landraces) were reported by farmers in all the six districts. This perceived level of resistance to insect damage by landraces needs to be investigated. To improve farmers' capabilities for sweetpotato insect pest management, it is crucial to train them in the basic knowledge of insect pest biology and control.Entities:
Keywords: Acraea acerata; African sweetpotato weevils; Cylas brunneus; Cylas puncticollis; Integrated pest management; Ipomoea batatas; Production constraints; Sweetpotato butterfly
Year: 2014 PMID: 25279278 PMCID: PMC4169129 DOI: 10.1186/2193-1801-3-303
Source DB: PubMed Journal: Springerplus ISSN: 2193-1801
Figure 1Map of Uganda showing the six study districts with their corresponding agro-ecological zones; Gulu in the northern farming system, Masindi in the Lake Albert Crescent, Soroti in the Eastern Highlands, Wakiso in the Lake Victoria crescent, Kasese in the western range highlands and Kabale in the south western highlands.
Household characteristics of interviewed sweetpotato farmers in the six districts of Uganda and their sweetpotato production practices/techniques, August-October 2011
| Household characteristics | Gulu | Kabale | Kasese | Masindi | Soroti | Wakiso | p-value (N/A = not applicable) |
|---|---|---|---|---|---|---|---|
| Female respondents (%) | 53.1 | 62.5 | 59.4 | 75.0 | 37.5 | 78.1 | N/A |
| Female headed households (%) | 28.1 | 28.1 | 21.9 | 28.1 | 15.6 | 43.8 | N/A |
| No formal education (%) | 28.1 | 25.0 | 18.8 | 9.4 | 6.3 | 20.0 | N/A |
| ≤7 years of formal education (%) | 40.6 | 65.6 | 56.3 | 46.9 | 71.9 | 60.0 | N/A |
| >7 years of formal education (%) | 31.3 | 9.4 | 25.0 | 43.8 | 21.9 | 20.0 | N/A |
| Mean elevation (m a.s.l.) | 1091cd | 2090a | 1006e | 1124c | 1079d | 1191b | <0.0001 |
| Mean age of respondent (years) | 43.7 ± 2.6a | 40.0 ± 2.0a | 41.2 ± 2.4a | 44.9 ± 2.4a | 44.1 ± 2.0a | 45.8 ± 2.4a | 0.7024 |
| Mean household size (persons) | 10.2 ± 1.3a | 5.9 ± 0.5c | 6.6 ± 0.5bc | 6.5 ± 0.6c | 8.6 ± 0.7ab | 7.5 ± 0.8bc | 0.0002 |
| Mean rotation duration (months) | 20.4 ± 2.2ab | 11.0 ± 1.7c | 6.6 ± 0.8c | 17.2 ± 1.4b | 23.3 ± 2.1a | 9.1 ± 1.1c | <0.0001 |
| Mean years of growing sweetpotato | 25.1 ± 2.7ab | 19.6 ± 1.9abc | 16.8 ± 2.0c | 26.3 ± 2.3a | 23.8 ± 1.9ab | 19.7 ± 2.4bc | 0.0179 |
| Mean sweetpotato acreage in 2011 (ha) | 0.3 ± 0.1ab | 0.2 ± 0.0b | 0.2 ± 0.0b | 0.2 ± 0.0b | 0.3 ± 0.0ab | 0.4 ± 0.1a | 0.1393 |
| Arable land devoted to sweetpotato (%) | 12.3 ± 3.1b | 30.5 ± 5.0a | 17.9 ± 3.8b | 14.1 ± 2.0b | 20.0 ± 3.5b | 31.1 ± 5.1a | <0.0001 |
| Mean total land holding (ha) | 100.2 ± 82.3a | 2.9 ± 1.7a | 2.4 ± 0.5a | 6.6 ± 2.8a | 2.4 ± 0.3a | 1.3 ± 0.2a | 0.2625 |
| Total land cropped (%) | 59.5 ± 6.3c | 85.8 ± 5.6ab | 85.4 ± 3.9ab | 63.6 ± 5.9c | 77.8 ± 5.6b | 93.9 ± 3.0a | <0.0001 |
Means followed by the same letter in the same row are not significantly different (p ≥ 0.05, Fisher’s least significant difference). Values are means ± SE.
Top five most important constraints to sweetpotato production as ranked by farmers in the study districts of Uganda, August-October 2011
| Constraints to sweetpotato production | Rank for each constraint (% households)* | |||||
|---|---|---|---|---|---|---|
| 1st | 2nd | 3rd | 4th | 5th | Mean | |
| No constraint mentioned/experienced | 0.5 | 8.3 | 26.6 | 55.7 | 81.8 | 34.6 |
| Insect pests | 33.9 | 42.2 | 33.3 | 18.8 | 5.7 | 26.8 |
| Poor yields of local varieties/soils | 12.0 | 10.4 | 6.3 | 1.6 | 1.6 | 6.4 |
| Rats and rodents | 8.3 | 8.9 | 6.3 | 4.2 | 1.0 | 5.7 |
| Drought/prolonged dry seasons | 10.9 | 3.1 | 4.2 | 2.6 | 0.5 | 4.3 |
| High cost of labor/labor intensive/shortage of labor/weeds | 6.3 | 2.1 | 2.6 | 1.6 | 1.6 | 2.8 |
| Lack of market | 3.6 | 5.2 | 2.1 | 2.1 | 0.5 | 2.7 |
| Viral diseases | 2.6 | 3.1 | 3.1 | 2.6 | 1.0 | 2.5 |
| Shortage of planting material | 5.2 | 1.6 | 3.1 | 1.0 | 0.0 | 2.2 |
| Wild game (elephants, hippos, pigs) | 4.2 | 2.6 | 1.6 | 1.0 | 1.0 | 2.1 |
| Others | 1.5 | 2.6 | 2.1 | 3.1 | 1.0 | 2.1 |
| Millipedes | 1.6 | 1.6 | 3.6 | 0.5 | 2.6 | 2.0 |
| Land shortage | 2.1 | 2.1 | 2.6 | 0.5 | 0.5 | 1.6 |
| Floods/excess rainfall/storms | 1.0 | 1.6 | 1.0 | 1.0 | 0.5 | 1.0 |
| Lack of money to hire labor/plant large fields/build drying places | 2.1 | 1.6 | 0.0 | 0.5 | 0.0 | 0.8 |
| Domestic animals (cattle, goats) | 1.0 | 1.0 | 0.0 | 1.0 | 0.5 | 0.7 |
| Changed onset and cessation of rainfall in the seasons | 1.6 | 0.5 | 0.5 | 0.5 | 0.0 | 0.6 |
|
| 1.0 | 0.5 | 0.0 | 1.0 | 0.0 | 0.5 |
| Root rots | 0.0 | 1.0 | 1.0 | 0.5 | 0.0 | 0.5 |
*Some columns do not add up to 100% due to rounding off.
Major insect pests experienced by farmers in sweetpotato (% households) and rank
| Insect pest reported | % households* | ||||||
|---|---|---|---|---|---|---|---|
| Gulu | Kabale | Kasese | Masindi | Soroti | Wakiso | Overall mean | |
| Sweetpotato weevils ( | 97 (1) | 56 (1) | 84 (1) | 100 (2) | 94 (1) | 91 (1) | 87.0 |
| Sweetpotato butterfly ( | 28 (2) | 50 (2) | 88 (2) | 88 (1) | 13 (2) | 97 (2) | 60.7 |
| Sweetpotato hornworm ( | 33 | 0 | 0 | 0 | 25 | 0 | 9.7 |
| Armyworm ( | 0 | 0 | 0 | 0 | 34 | 0 | 5.7 |
| Others (ants, whiteflies) | 0 | 0 | 9 | 3 | 3 | 0 | 2.5 |
*percentage values add to more than 100 due to multiple responses. Rank (in parentheses) for the top two most important insect pests.
Control methods for the two ( . and spp.) most important insect pests of sweetpotato (% households)
| Control strategy for | % households | Overall mean | |||||
|---|---|---|---|---|---|---|---|
| Gulu | Kabale | Kasese | Masindi | Soroti | Wakiso | ||
|
| |||||||
| Chemical insecticides | 2 | 20 | 14 | 50 | 0 | 56 | 24 |
| Ash application | 0 | 0 | 7 | 8 | 0 | 0 | 3 |
| Hand-picking | 0 | 0 | 0 | 8 | 0 | 6 | 2 |
| Chemical insecticides and hand-picking | 0 | 0 | 0 | 8 | 0 | 0 | 1 |
| Chemical insecticides and ash application | 0 | 0 | 0 | 0 | 0 | 13 | 2 |
| Hand-picking and ash application | 0 | 0 | 0 | 8 | 0 | 0 | 1 |
| Chemical insecticides, hand-picking and ash application | 0 | 0 | 0 | 0 | 0 | 6 | 1 |
| None | 98 | 80 | 79 | 17 | 100 | 19 | 65 |
|
| |||||||
| Chemical insecticides | 0 | 0 | 0 | 6 | 0 | 8 | 2 |
| Chemical insecticides and re-hilling | 7 | 0 | 7 | 6 | 0 | 0 | 3 |
| Crop rotation | 7 | 8 | 0 | 0 | 0 | 0 | 3 |
| Early harvesting | 0 | 0 | 7 | 0 | 7 | 8 | 4 |
| Mulching and re-hilling | 0 | 0 | 0 | 0 | 0 | 8 | 1 |
| None | 87 | 92 | 87 | 88 | 93 | 77 | 87 |
Perceived field resistance of major local sweetpotato varieties or landraces to . and spp. in 2011
| District | Local name of Sweetpotato variety/landrace | % Households growing the variety | Resistence level to | Resistence level to | ||||
|---|---|---|---|---|---|---|---|---|
| Low | Moderate | High | Low | Moderate | High | |||
| GULU | Lalira | 22 | 0 | 15 | 9 | 0 | 13 | 11 |
| Alero | 12 | 0 | 6 | 3 | 0 | 7 | 4 | |
| Ochol/Ocuc | 12 | 0 | 6 | 3 | 1 | 7 | 1 | |
| Adoch | 11 | 0 | 6 | 15 | 0 | 2 | 9 | |
| Mukiga | 3 | 0 | 3 | 0 | 0 | 2 | 2 | |
| Others | 40 | 0 | 18 | 18 | 0 | 18 | 21 | |
| KABALE | Rwabafuluki, Kandazi/Mulungi | 22 | 0 | 4 | 25 | 0 | 7 | 17 |
| Mukazi | 17 | 0 | 0 | 11 | 0 | 17 | 14 | |
| Mukono | 8 | 4 | 0 | 11 | 0 | 7 | 3 | |
| Kidodo | 6 | 0 | 4 | 11 | 0 | 3 | 0 | |
| Kigabali/Magabali | 4 | 4 | 0 | 4 | 0 | 7 | 0 | |
| Others | 43 | 0 | 0 | 25 | 0 | 17 | 7 | |
| KASESE | Rwatoro | 13 | 0 | 2 | 9 | 2 | 2 | 6 |
| Red mamba | 10 | 2 | 4 | 4 | 0 | 4 | 0 | |
| Rosemary | 10 | 0 | 4 | 7 | 0 | 6 | 6 | |
| Kiryenamwami | 8 | 2 | 2 | 7 | 0 | 4 | 4 | |
| Muhamoud | 6 | 0 | 4 | 7 | 2 | 2 | 6 | |
| Bitambi | 6 | 0 | 2 | 2 | 0 | 2 | 2 | |
| Kyebandula | 6 | 0 | 2 | 2 | 0 | 4 | 2 | |
| Others | 41 | 11 | 0 | 26 | 4 | 21 | 17 | |
| MASINDI | Dimbuka | 22 | 1 | 7 | 18 | 1 | 16 | 10 |
| Nakato/Nyakato | 14 | 0 | 6 | 12 | 0 | 14 | 5 | |
| Kahogo/New Kawogo | 9 | 0 | 4 | 9 | 0 | 5 | 4 | |
| Kyebandula | 5 | 0 | 1 | 4 | 1 | 1 | 0 | |
| Suwedi | 3 | 0 | 3 | 1 | 0 | 3 | 3 | |
| Kabakumba | 3 | 0 | 0 | 3 | 0 | 0 | 3 | |
| Others | 44 | 0 | 4 | 25 | 0 | 18 | 16 | |
| SOROTI | Kampala | 18 | 0 | 0 | 11 | 0 | 6 | 12 |
| Araka | 18 | 0 | 5 | 16 | 0 | 8 | 12 | |
| Ateseke | 7 | 0 | 5 | 11 | 0 | 6 | 4 | |
| Opaku | 5 | 0 | 0 | 0 | 1 | 4 | 1 | |
| Letesi/Latesi | 4 | 0 | 0 | 0 | 0 | 3 | 1 | |
| Mwambi | 4 | 0 | 5 | 11 | 0 | 3 | 1 | |
| Boy | 4 | 5 | 0 | 0 | 0 | 0 | 4 | |
| Others | 40 | 0 | 16 | 16 | 1 | 16 | 17 | |
| WAKISO | Naspot 1 | 31 | 0 | 16 | 23 | 0 | 18 | 35 |
| Dimbuka | 23 | 2 | 5 | 16 | 3 | 3 | 15 | |
| Setyabule | 13 | 2 | 5 | 7 | 0 | 3 | 3 | |
| Mbale | 10 | 2 | 0 | 7 | 0 | 3 | 5 | |
| New Kawogo | 6 | 0 | 2 | 2 | 0 | 5 | 5 | |
| Others | 17 | 0 | 7 | 5 | 0 | 5 | 0 | |