Cassava planting material movement and grower behaviour in Zambia: implications for disease management

Abstract

22Cassava is an important food crop for most small-holder growers across sub-Saharan Africa, where production is 23 largely limited by the presence of two viral diseases: cassava mosaic disease (CMD) and cassava brown streak 24 disease (CBSD), both propagated by a vector whitefly and via human-mediated movement of infected cassava 25 stems. Despite its importance, there is limited knowledge of growers' behaviour related to planting material 26 movement, as well as growers' perception and knowledge of cassava diseases, which have major implications for 27 disease spread and control. This study was conducted to address the knowledge gaps by surveying small-holder 28 growers in Zambia. A total of 96 subsistence cassava growers across five provinces were surveyed between 2015 29 and 2017. Most growers interviewed used planting materials from their own (94%) or nearby (<10 km) fields of 30 family and friends, although some large transactions with markets, middlemen, and NGOs occurred over longer 31 distances. Information related to cassava diseases and uninfected planting material, however, only reached 48% 32 of growers. Growers with access to information were more concerned about the disease, compared to uninformed 33 growers. These data provide a basis for future planning of cassava clean seed systems to control virus diseases, 34 emphasising the critical role of grower knowledge, and consequently education, in success of these systems. In 35 particular, we highlight the importance of extension workers in this education process, as well as farmer's groups 36 and the media.

How growers make decisions impacts plant disease control

“…p = 0) the disease spread across the landscape in a more “wavelike” pattern as expected from the thin-tailed dispersal kernel for the whitefly ( Shaw ( 1995 ), Appendix 2 Figure 6). However, when trade occurs via a market or central organisation the majority of transactions occur over a scale larger than our landscape (a square with sides 3.16 km), with around 70 % of transactions occur over a scale of 10-50 km ( Szyniszewska et al ( 2019 )). For more informal trade settings, with growers interacting with each other, a proximity-based kernel may be more appropriate ( McQuaid et al ( 2017b ), McQuaid et al ( 2017a ), though both of these were modelled over a larger landscape than ours).…”

“…- will play an important role in determining participation. Indeed, surveys of cassava growers in Sub-Saharan Africa have found that such qualitative traits have a greater role in determining a grower’s preference than economic traits such as yield ( Szyniszewska et al ( 2019 ), Houngue et al ( 2019 )). These private preferences or perceptions of risk are intangible and though they are somewhat encapsulated with our “cost of control” parameter will vary from grower to grower.…”

“… Bauch and Earn ( 2004 ); reviewed in Chang et al ( 2020 )) and animal (e.g. Delabouglise and Boni ( 2020 ), Mohr et al ( 2020 )) diseases, though there have been fewer studies for plant diseases ( Milne et al ( 2016 ), McQuaid et al ( 2017a ), Szyniszewska et al ( 2019 ), Milne et al ( 2020 ), Bate et al ( 2021 )). Where studies do consider individual growers’ decisions there is little justification of how decision-making is modelled, although it clearly will affect the outcomes of their decisions.…”

Modelling cassava production and pest management under biotic and abiotic constraints

“…As a result, stochasticity in the network or spatial structure highlights the importance of variability in the sourcing of cuttings. Here, modelling has shown that although re-use of supply from within a field, along with small-scale local exchanges, dominates in terms of seed and virus dispersal (Delaquis et al 2018 ; Szyniszewska et al 2019 ), the potential for larger-scale movement allows for rapid spread of virus across a landscape (McQuaid et al 2017b , 2017a ). Modelling of cassava viruses, transmitted both through a whitefly vector and infected cuttings, in this way requires the consideration not just of a network of interactions or a dispersal kernel, but of a spatially explicit network in combination with vector dispersal.…”

CassavaMap, a fine-resolution disaggregation of cassava production and harvested area in Africa in 2014

“…Mapping cassava on a continental scale based on satellite imagery remains a major challenge. Cassava in sub-Saharan Africa dominates in small-holder farming systems with field sizes most frequently less than 1000 m 2 , which are often intercropped 16,17 . Field rotation, flexible harvesting times and variable planting seasons means there is no strongly defined pattern of field maturation in many areas.…”