Mobile community sensing with smallholder farmers in a developing nation; A scaled pilot for crop health monitoring

Assessing the contribution of the Adhoc crop health surveillance tool on the food security and livelihoods of smallholder farmers in Uganda

“…Furthermore, the team was also able to work with the experts and farmers to ensure that Adsurv met the needs of the farmers in terms of providing access to vital information to support crop production. The smallholder farmers recruited for the study received a series of training such as using smartphones, a demonstration, and a field test of how Adsurv works (Mutembesa et al, 2019). The experts and farmers contributed to the design and development of Adsurv and were not passive recipients aimed at testing a finished product (Mutembesa et al, 2019).…”

“…The smallholder farmers recruited for the study received a series of training such as using smartphones, a demonstration, and a field test of how Adsurv works (Mutembesa et al, 2019). The experts and farmers contributed to the design and development of Adsurv and were not passive recipients aimed at testing a finished product (Mutembesa et al, 2019). The preceding discussion shows how the study incorporated the fundamental principles of the SLF, making it a suitable choice of a theoretical framework for measuring the contribution of Adsurv to the farmer's livelihoods.…”

“…The team selected one Zonal Agricultural Research and Development Institute (ZARDI) per AEZ, at which the farmers assembled for the evaluation exercise. The team purposively selected 70 farmers out of the 175 who had participated in the project since its inception (Mutembesa et al, 2019). Table 3 130 submissions per month between May and October 2018), while 20 were less active; at least 30% of the participants per training center were female; and at least one farmer from every district within the AEZ's where the farmers on a previous project were initially selected.…”

“…Adsurv is a crop health surveillance and monitoring mobile application that facilitates the diagnosis and management of crop pests and diseases (See Figure 1). It consists of four channels: (1) a Data collection channel-which allows an agent to take an image; (2) a Diagnosis channel-that automatically detects the symptom of a disease on a leaf image using a customized crop disease diagnosis toolkit; (3) a News channel-that provides agriculture-related content, for example, best agronomic practices, and so forth; and (4) Question and Answer (Q&A)-that allows both farmers and experts to directly communicate among themselves and exchange knowledge on agriculture-focused topics (Mutembesa et al, 2019). Using Adsurv, farmers, extension workers, and agricultural experts can provide and classify surveillance data for monitoring crop health across Uganda.…”

“…The farmers who participated in the study were selected based on criteria jointly developed with agricultural experts from NaCRRI and UNFFE at the study's inception (Mutembesa et al, 2019). Typically, the farmer using Adsurv is registered with the farmer's group at the district level, ranges between 20 and 60 years, has at least attained primary school education, and can read and write.…”