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Weed infestation is considered as one of the major biotic stresses of dryland crop production. Weed species occurrence, abundance, and densities differ due to spatial soil fertility variability, and management practices by farmers. Weed surveys are therefore vital for tracking such changes and in turn developing appropriate weed management strategies for farmers. A weed survey was carried out in Wedza, eastern Zimbabwe to assess farmer knowledge and perceptions of major weeds in maize fields across catena landscape positions. A multistage sampling procedure was used, involving random sampling of six villages within a 20 km radius, divided according to the catena position and economic status of the farmer. Two hundred and forty-nine (249) households were interviewed using a structured questionnaire. The data were coded and processed using the CSPro software package, and then analysed using the SPSS program. Factors that predicted the spatial distribution of weeds were determined using a binary logistic model. From the survey, 52.8% and 42.3% of farms are on the upper catena and lower catena, respectively, and only 4.8% are on the middle catena. Thirty-one weed species belonging to 15 families were listed by respondents and identified by enumerators in the study area and were categorised into three main groups (broadleaf, grasses, and sedges). Acanthospermum hispidum and Striga asiatica were considered as problem weeds in maize fields on the upper and lower catena, respectively. Xanthium strumarium was perceived as a new invasive weed in low-lying arable fields. The binary logistic model predicted farm location on the landscape and fertiliser use as the main factors affecting weed types, distribution, and abundance. Moreover, farms on lower catena had more Striga infestations compared to upper catena. The results suggested an integrated weed management approach to control A. hispidum, Striga species, and the invasive fast-spreading X. strumarium in the area. |
