Date
Corporate author
Editor
Illustrator
Producer
Photographer
Contributor
Writer
Translator
Journal Title
Journal ISSN
Volume Title
Access Rights
Share
APA citation

Taa, A., Tanner, D. G., Temesgen, M., & Girma, K. (1997). On-farm evaluation of an animal-drawn implement developed in Ethiopia for row placement of wheat seed and basal fertiliser. African Crop Science Journal, 5(4). https://doi.org/10.4314/acsj.v5i4.27833

ISO citation
Abstract

Grass weeds are difficult to control by hand weeding in a broadcast wheat crop because several species are not easily distinguished from the crop at an early stage. Chemical weed control, on the other hand, can be highly effective, but is limited in Ethiopia by the unavailability and high cost of herbicides. Further, dependence on high efficacy herbicides to control grass weeds can result in weed species shifts and/or the development of resistant weed biotypes. Row sowing of wheat can facilitate hand and/or mechanical weeding by enabling farmers to identify grass weeds in the inter-row spaces. However, manual row seeding is extremely labour intensive and unacceptable to peasant farmers in Ethiopia. Row seeders developed elsewhere have not been accepted in Ethiopia because they were either too labour inefficient or ineffective in cloddy and rough fields. Therefore, a four-row seeder has been developed in Ethiopia with a new type of seed metering mechanism

Description
Keywords
Citation
Copyright
CIMMYT manages Intellectual Assets as International Public Goods. The user is free to download, print, store and share this work. In case you want to translate or create any other derivative work and share or distribute such translation/derivative work, please contact CIMMYT-Knowledge-Center@cgiar.org indicating the work you want to use and the kind of use you intend; CIMMYT will contact you with the suitable license for that purpose.
Journal
African Crop Science Journal
Journal volume
5
Journal issue
4
Article number
Place of Publication
Publisher
African Crop Science Society
Related Datasets