Occurrence, incidence, and severity of Alternaria leaf spot of cotton (Gossypium hirsutum L.) in major cotton-growing districts of the Lake Zone, Tanzania
EUSTACE, S. M. M.; Mwaipopo, B. V.; Madege, R. R.
Show abstract
Background: Alternaria leaf spot (ALS), caused by fungi in the genus Alternaria (family Pleosporaceae), is a significant fungal disease that affects cotton production in the Lake Zone of Tanzania, the country's main cotton-producing region. The disease reduces photosynthetic capacity, boll retention, and fiber quality, leading to substantial yield losses in affected fields. Despite its increasing prevalence, systematic baseline epidemiological data remain scarce. Objective: This study aimed to determine the occurrence, incidence, and severity of Alternaria leaf spot across the major cotton-growing districts of the Lake Zone, Tanzania. Methods: Field surveys were conducted during the 2024-2025 growing season in the districts of Bariadi, Bunda, Chato, and Magu; 20 representative cotton fields were systematically assessed using a diagonal sampling approach. Disease incidence, prevalence, and severity were recorded for 1,000 cotton plants. Fungal isolates recovered from symptomatic leaves were sent to the laboratory for isolation and morphological identification. Results: Field prevalence was 100%, and the overall mean incidence was 64.4%, with significant inter-district variation: Bariadi (77.6%), Bunda (68.8%), Chato (60.0%), and Magu (52.4%). Mean DSI ranged from 44.0% (Magu) to 70.1% (Bariadi), indicating moderate-to-severe infection. Disease incidence and Disease severity (DSI) were strongly correlated when uninfected plants were included (r = 0.942, P < 0.001). However, this relationship weakened substantially and became non-significant when restricted to infected plants only (r = 0.396, P = 0.084). This suggests that higher incidence reflected more plants becoming infected rather than greater severity among already infected plants. Morphological characterization identified all 40 isolates as belonging to the genus Alternaria. Conclusion: These findings provide the first systematic epidemiological baseline for Alternaria leaf spot across the major cotton-growing districts of Tanzania's Lake Zone. Disease incidence and severity varied significantly across districts, underscoring the need for tailored disease management strategies. This study recommends ongoing surveillance and integrated disease management to safeguard cotton productivity among smallholder farmers in the region.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Characterization of Metarhizium majus (Hypocreales: Clavicipitaceae) isolated from the Western Cape province, South Africa 94%
- Natural field diagnosis and molecular confirmation of fungal and bacterial watermelon pathogens in Bangladesh: A case study from Natore and Sylhet district 94%
- PCR-Based Detection and Phylogenetic Analysis of Candidatus Liberibacter asiaticus in Citrus Orchards Across Nepal 94%
Similar papers in this journal
- Uncovering Fusarium species diversity, distribution and pathogenicity associated with cotton-corn rotation fields in recently expanded cotton-growing areas of the Northern High Plains of Texas 95%
- Plasmodiophora brassicae in Mexico, from anecdote to fact 94%
- Diverse strains of aster yellows phytoplasma are associated with the potato leafhopper (Empoasca fabae) in Eastern Canada 93%
Similar papers in this journal
- Cassava planting material movement and grower behaviour in Zambia: implications for disease management 94%
- The Brazilian population of Fusarium oxysporum f. sp. cubense is not structured by VCG or by geographic origin 92%
- Modeling of yield Losses and risk analysis of fungicide profitability for managing Fusarium Head Blight in Brazilian spring wheat 92%
Similar papers in this journal
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.