Tackling fall armyworm (Spodoptera frugiperda) outbreak in Africa: an analysis of farmers’ control actions

Abstract

Since its emergence in Africa in 2016, fall armyworm (FAW) has spread rapidly and poses a severe threat to the food security and livelihood of millions of smallholder farmers in the continent. Using survey data from Ghana and Zambia, we examined FAW prevention and control methods implemented by farm households and their impacts on maize output and household consumption of self-produced maize. The main control methods used included pesticide application and handpicking of larvae, while access to information on FAW was a key driver behind the implementation of the control methods. Results from an endogenous switching regression showed that the implementation of a FAW management strategy significantly enhanced maize yield and households' own maize consumption. When disentangling the impacts of the main control methods, we found that the combination of pesticide application and handpicking of larvae produced the highest yield gain of 125%. We concluded that the current interventions put in place by farmers to tackle FAW infestations are providing positive outcomes, but successful management of the pest will require more actions, including raising awareness to enhance the adoption of control interventions and exploring other control options.

The Efficacy of Alternative, Environmentally Friendly Plant Protection Measures for Control of Fall Armyworm, Spodoptera Frugiperda, in Maize

“…For the ash-and soil-based treatments, reports indicate that a number of farmers use these methods in Africa [6,7,31], as well as in the Americas [25]. In the present paper, however, even though larval numbers appeared to be lower, no evidence was found that plant damage can be mitigated or that the yield can be increased by any of the applied treatments.…”

“…The recent fall armyworm invasion in Africa and Asia is undoubtedly a major event in terms of pest management and food security in these continents. A number of publications have recently assessed the spread and impact of FAW, as well as farmer practices, in order to fight against the pest [7,28]. It is generally accepted that yield losses are massive, even though the few studies assessing yield losses from fields directly (e.g., Baudron et al [4]) have indicated less severe losses as compared to studies based on farmers' self-perception.…”

“…In the present paper, however, even though larval numbers appeared to be lower, no evidence was found that plant damage can be mitigated or that the yield can be increased by any of the applied treatments. A recent study showed that less than 1% of farmers in Ghana and about 5% of farmers in Zambia use ash for FAW control [7]. A recent paper that looked more closely into the decision making of farmers in five African countries found that between 2.5 and 17.7% of farmers apply ash or sand to the whorl, of which 48%-77% responded positively that they are efficacious, compared to 92%-97% responding positively for synthetic insecticides [30].…”

“…Farmers in the invaded area were not prepared for this devastating pest, resulting in heavy losses on one hand, but also a drastic increase of insecticide use on the other [6]. Farm households are reported to often use highly hazardous or banned products with generally no appropriate personal protective equipment [7]. Such over-reliance on insecticides is highly problematic due to potential environmental and health risks, as well as the strong capability of the fall armyworm to quickly develop resistance (e.g., Zhu et al [8]).…”

Have actions taken to control fall armyworm reduced the economic cost experienced in Ghana?

“…This figure was therefore used in the modelling as a standard expected yield loss due to FAW without control measures. The Lima et al (2010) is slightly lower than the farmer estimates of loss in 2017 in Ghana at 44% (Tambo et al 2018). However, as losses can be overestimated when reported by farmers, not measured, the Lima et al figure is considered to be a reasonable loss figure to use in this modelling.…”