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Plant disease and pest monitoring surveys in Africa RISING action areas in Tanzania
Africa RISING East and Southern Africa annual review and planning meeting, Lilongwe, Malawi, 3-5 September 2013
Lava Kumar (IITA) and Warren Arinaitwe (CIAT)
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Papias Binagwa and Edith KadegeSelian Agricultural Research Institute (SARI), Tanzania
Jean Claude Rubyogo, Mathew Abang and Warren Arinaitwe*International Center for Tropical Agriculture (CIAT)
Lava Kumar*, C Agboton, M Harun, E Mbiru, F Ngulu, E Swai, D Coyne, F Beed, M Tamo, M Bekunda and I Hoeschle-Zeledon A Owati, O Patricia, I David and M HemaInternational Institute of Tropical Agriculture (IITA)
*Presenting authors
Study Team and Authors
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Objective“To provide current information on the abundance and distribution of important pests and diseases of common bean, groundnut, maize, pigeonpea and soybean in the Africa RISING project action areas”
ApproachInterdisciplinary study teams from organizations working in the actions sites participated in the survey
Surveys were conducted in April
•Filed observation•Sample collection for laboratory analysis •Interview with farmers
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Geographic coverage
Sub-Humid District (1610 to 2178 mts)
NjoroSemi-Arid Districts
(1261- 1527 mts)Medium elevation
Low rainMoleti
Mlali-Lyegu
High rainSeletoLongLow rainSabelo
•Maize in all locations •Common bean survey in Babati
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Farmer fields and project sites were surveyed.
Structured questionnaires &
field observation methods used
to obtain data including, gender,
input usage, production trends
P&D Management,P&D incidence
&severity.
Data was analysed using SPSS
Survey MethodologyMaize
Common bean
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Variable Groups Frequency (%)Total land owned
0-4 acres 90.0
5-10 acres 10.011 and above 0.0
Land under maize
0-4 acres 100.05-10 acres 0.0
Cropping pattern
Monocropping 50.0Intercropping 40.0Both 10.0
Planting pattern
Row planting 100.0
Source of seed
Own saved seed 50.0Seed dealer 40.0Local market 10.0
Trend of maize production- 5 years:Decreasing: 30%Increasing: 10%Same: 60% Preferred varieties:Local: 40% reason drought tolerant, affordable/ easily accessibleImproved: 60% High yield Production constrainsWeather: DroughtPests and diseasesAccess to inputs: usually delayed, improved varieties are expensive Generally farmers perception on IPM option is low. They do not practice crop rotation.
Farmer responses (N=10)
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District Altitude (mts)
Locations Rainfall Total farms
Babati 1610 – 2178
Long High rain 5 Aphids (4/5)Stem borer (1/5)
Siloto High rain 5 Stem borer (3/5)Sabilo Low-rain 4 Aphids (1/4)
Kiteto 1520 – 1527
Njoro Low rain 2 Stem borer (2/2)
Kongwa 1132 - 1299
Mlali-Lyegu Low rain 3 Stem borer (2/3)
Moleti Low rain 2 Stem borer (2/2)Kwamasingisa Low rain 1 Stem borer
• Two maize varieties (Situka and Kilima) were more susceptible to the stem bores attacks (mainly Busseola fusca and Sesamia calamistis).
• There may exist other stem borer species to be identified.• Maize aphids also were encountered and its infestation rates were fluctuate• Some aphids parasitoids exist in the fields and other aphids were attacked by
Neozygites.
Summary of pests
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Larvae of Sesamia calamistis Larva of Busseola fusca Stem borer damages
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Aphid infestation on maize in Long (Babati district)
Neozygites sp
Neozygites sp
Aphids detected on 3 – 50% of the plants in Long (high altitude ca2100 mts)Biocontrol agents colonized aphid colonies
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D02_Rm2COI_826285
E02_Rm3COI_826286
G04_RmECR1_826304
G11_RmECR2_826360
H11_RmECR3_826361
A05_RmAIbo_826306
B01_F11TTa_840483
D03_Rm4COI_826293
C02_Rm1COI_826284
F02_Rm3bCO_826287
HQ112195India-R maidis
F01_F12Tan_840487
G01_F9Tanz_840488
A01_F10Tan_840482
C01_F11BTa_840484
TANZF13COF
D01_F2Tanz_840485
GU457795RhoKorea-R padi
GU140277Canada-P nigronervosa
100
100
99
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.00
0.07
0.02
0.03
0.04
0.01
0.01
Rhop
alos
iphu
m m
aidi
s
Rhop
alos
iphu
m p
adi
Molecular analysis (COI gene-based taxonomy) confirmed aphids found in all locations as R. padi. Only in one location (Long) R. maidis observed on cobs.Aphis craccivora detected on pigonpea in one location (Kiteto)
Identification of aphids
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Striga asciatica
Severe incidence of striga in Kongwa (Moleti)
Not observed in any other location
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Species Average per 100 g root sample from 78 samples
(frequency)
Host
Pratylenchus zeae 17804 (N = 51) Maize, groundnut, sorghum, sunflower, pigeonpea and common bean
Helicotylenchus multicinctus
335 (N=14) Maize, sorghum, bambara
Helicotylenchus dihystera 8000 (N=1) Common bean Meladogyne spp. 3297 (N=12) Maize, groundnut,
sorghum, sunflower, pigeonpea and common bean
Tylenchus semipenetrans 95 (N=6) Maize, common beanAphelenchus spp. 924 (N=25) Maize, common bean
Root nematodes
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SpeciesTotal detected (N=76)
Frequency
Pratylenchus zeae 1964 18Helicotylenchus multicinctus 620 17Helicotylenchus dihystera 87 5Tropholus spp 24 9Tylenchus semipenetrans 64 14Aphelenchus spp. 44 6Aphlencoid 2 1Hoploliamus spp. 40 8Paratrichodorus spp. 46 11Rhadinaphelenchus spp. 7 4Rhabditis (steinerma and Heterorhabdits spp.) 2542 76Rotylenchulus reniformis 2 2Xiphinema spp. 15 6Trichodorus spp. 0 0Longidorus spp. 0 0Meloidogyne spp 2324 23
Nematodes in soil samples
Molecular identification of nematode species is in progress
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Fungal and viral diseases
District Locations Bipolaris leaf blight% inc (sev)
Curvularia leaf spot
% inc (sev)
Turcicum leaf blight
% inc (sev)
MLND% inc (sev)
MSV% inc (sev)
Babati Long <10 (3) 10 – 20 (3) 10 - 40 (3) + <2 (3)Siloto 20 (3) 15 (3) 10 – 20 (2) 10 – 50 (4) <2 (3)Sabilo 35 (3) + 10 – 20 (3) - <2 (3)
Kiteto Njoro + + <10 (3) + <1 (2)Kongwa Mlali-Lyegu + + <10 (3) +
Moleti + + 30 (3) + 10-30 (3)Kwamasingisa + + + - -
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Babati
Bipolaris leaf blightCurvularia leaf spot Turcicum leaf blightVirus diseases (MLND) in Seleto
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Kiteto (Njoro)
Field trial of new maize lines in a farmer’s field
Brown spot
Termites
Rust ?
Drought and turcicum leaf blight
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Kongwa
Drought Curvularia leaf spot Turcicum leaf blight
Turcicum leaf blight Ergot / heat smut Curvularia leaf spot
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Maize lethal necrosis in Babati (Seloto)
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MCMoV + SCMV (MLND)
MCMV only
MCMV SCMV SCMV+MCMV MSV SScMVMaize stripe
Maize mosaic virus
51 (64%) 18 (22.5) 17 (21.5) 16 (20) 13 (16.2) 4 (5) 0
Viruses detected (N = 80 samples)
SCMV only
Incidence of MLN agents differ
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S FT W1 W2 W3 W4 E1 E2 E3 E4 E5 E6
MCMV CP1 induced with 1mM IPTG and purified through Ni-NTA column
S: Soluble fraction; FT: Flow throughW1-W4 : Washings; E1-E6 : Elutions
Expressed MCMoV CP
Cloning and expression of MCMoV Coat Protein in E. coli
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MCMoV Infected sample Healthy MSV Buffer1:2000 3.00 1.21 1.95 0.16 0.17 0.16
1:10,000 2.62 0.78 1.43 0.16 0.17 0.161:20,000 1.92 0.51 0.93 0.16 0.17 0.15
MCMoV antibodies in ELISA
0.00
0.50
1.00
1.50
2.00
2.50
OD
at 4
05 n
m
Inf Hel MSV Buf
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Production is male
dominated
63.3% of farmers
intercropped beans and
use of owned saved seed
is most common source
of planting seed
Key findings Variable Group Freq (%)
Sex Male 21 70.0
Female 9 30.0Land under beans
0-4 acres 24 80.0
5-10 acres 20.0
Cropping pattern
Monocrop 6 20.0
Intercrop 19 63.3
Both 5 16.7
Seed source Own-saved seed
12 40.0
Agro input deal
3 10.0
Local market
10 33.3
Others 5 16.7
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54% of farmers consider bean production to be decreasing
Pests and disease (36%); drought (40%) were cited as the major to decreasing trends.
Production trends in the last 5years
Decreasing Same Increasing Don’t know 0
2
4
6
8
10
12
14
16
18
Farmers perception
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More than 10 pests were observed but aphids and white flies were the most abundant.
AphidsWhiteflies
Foliage beetles Lady birds
Large black beetles
Village Variety Site In Se In Se In Se In Se In SeSeloto Local NP 70 2 90 3 30 1 70 0 0 0
Kunguru NP 60 2 100 3 60 2 0 0 0 0Selian 05 BS 50 2 90 3 40 1 0 0 0 0Selian06 MS 10 0 80 2 80 2 10 0 0 0Kunguru NP 70 2 90 3 40 1 100 0 0 0Selian97 NP 50 2 70 2 0 0 30 0 0 0
Mean 51.7 1.7 86.7 2.6 41.7 1.2 35.0 0.0 0.0 0.0Long Selian06 MS 90 2 40 1 0 0 60 0 50 3
Bwana-shamba NP 100 3 40 1 70 2 80 0 0 0Selian06 BS 0 0 80 2 0 0 0 0 70 3
Mean 63.3 1.7 53.3 1.3 23.3 0.7 46.7 0.0 40.0 2.0Sabilo Farm NP 80 3 80 2 0 0 30 0 0 0
Kunguru NP 60 2 70 2 50 1 20 0 0 0Bwana-shamba NP 40 1 80 2 0 0 30 0 0 0Lyamungo90 MS 60 3 60 2 40 1 60 0 0 0Farm NP 60 2 50 2 0 0 0 0 0 0
Mean 60.0 2.2 68.0 2.0 18.0 0.4 28.0 0.0 0.0 0.0
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5e 5f
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Disease varied significantly between sites with Common bacterial blight(CBB), Angular leaf spot(ALS) & viral diseases being the major.
CBB* Viral diseases Root rots Rust
Ascochytablight Anthracnose ALS*
Village Variety Site In Se In Se In Se In Se In Se In Se In SeSeloto Local NP 45 2 0 0 0 0 0 0 0 0 0 0 40 2
Kunguru NP 0 0 0 0 0 0 10 1 0 0 0 0 70 2Selian 05 BS 0 0 25 1 0 0 90 3 0 0 0 0 80 3Selian06 MS 40 2 20 1 0 0 0 0 0 0 0 0 50 2Kunguru NP 0 0 20 2 0 0 40 2 0 0 0 0 80 3Selian97 NP 0 0 0 0 10 2 0 0 0 0 0 0 30 2
Mean 14 1 11 1 2 0 23 1 0 0 0 0 58 2Long Selian06 MS 60 3 0 0 0 0 0 0 80 3 90 3 0 0
Bwana-shamba NP 80 3 0 0 0 0 0 0 0 0 0 0 0 0Selian06 BS 70 3 0 0 0 0 0 0 80 2 90 3 0 0
Mean 70 3 0 0 0 0 0 0 53 2 60 2 0 0Sabilo Farm NP 40 2 0 0 70 3 0 0 0 0 35 1 0 0
Kunguru NP 60 2 90 3 0 0 0 0 0 0 0 0 0 0Bwana-shamba NP 80 2 20 1 0 0 60 3 0 0 0 0 0 0Lyamungo90 MS 30 1 60 2 40 2 0 0 0 0 0 0 0 0Farm NP 60 3 0 0 0 0 0 0 0 0 25 1 0 0
Mean 54 2 34 1 22 1 12 1 0 0 12 0 0 0
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Pests: Beans: Observed in all fields. Aphids and whitefly infestations were
the highest Maize: Observed in all fields. Stem borers and aphids found to cause
significant damage, but incidence is less <40%. Work in progress to characterize insect specimens using DNA markers (CO1 gene)
Conclusions
Pathogens Beans: Multiple disease complex wide spread on beans. Individual
disease incidence and severity differ among sites. Characterization of pathogens pending.
Maize: Multiple diseases widespread in all locations. Turcicum leaf blight, bipolaris leaf blight, Curviularia leaf spot and MLND are significant.
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Agricultural extension packages promoting efficient IPDM options should be a priority in subsequent activities.
Widen the survey scope by increasing the sample size to at least 60 farmers/village. Also include non-project districts in Tanzania.
Identification of major pests and diseases using more robust methods (in progress)
Utilize the diversity knowledge to establish appropriate diagnostics and isolates for phenotyping germplasm for disease resistance
Promote improved disease resistant varieties to overcome common maize diseases.
Future directions
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Acknowledgments
Irene MwasagaLazaro Tango
Frank
Africa RISING
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Africa Research in Sustainable Intensification for the Next Generation
africa-rising.net