Integration of indigenous knowledge systems and modern climate science: development of a mobile application to improve smallholder agricultural production.
Ubisi, Nomcebo Rhulani.
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In sub Saharan Africa, subsistence agriculture underpins rural livelihoods. However, climate change has negatively affected rural smallholder farming due to over-dependence on climate-sensitive rain-fed agriculture. The effects of climate change have become the most critical issue for rural smallholder farmers. Rural smallholder farmers are greatly impacted by climate change and variability, leading to reduced crop yields, crop failure, loss of assets and livelihood opportunities. However, despite such challenges, farming continued to sustain livelihoods in rural areas over the years. Traditionally, African rural smallholder farmers have relied on their indigenous knowledge (IK) to sustain themselves, maintain their cultural identity as well as understanding climate and weather patterns for their decision-making at a farm level. However, the increase in rainfall variability in the past few years associated with climate change has reduced the reliability of IK. To address such challenges, the study suggests the integration of indigenous knowledge with modern climate science at a local level, to enhance the resilience of smallholder farmers to climate change. The aim of the study was to establish commonly used indigenous knowledge indicators for climate and weather forecasts predictions and smallholder farmers’ perceptions on the integration of the two knowledge systems as well as the use of mobile app technology to improve agricultural production in Nkomazi Local Municipality, South Africa. The study information was collected through both qualitative and quantitative research methods. Data were collected from twelve villages, sampling 100 participants, 8 key informant interviews, transact walk conducted with a small group of farmers (maximum 5) and eight focus group discussions in Nkomazi Local Municipality. ArcMap 10.7.1 was used to map the distribution of indigenous indicators used by Nkomazi smallholder farmers and the Poynton model was used to predict the impact of the increasing temperature on smallholder farmers’ production using the plant and animal indigenous climate indicators in these villages, and SPSS 25 was used to analyse the quantitative data as well as Excel 2016. Qualitative data was analysed through thematic analysis. From the transect walks and focus group discussions, the study findings revealed that many of the Nkomazi smallholder farmers relied more on their indigenous knowledge (IK) than on scientific weather forecasts (SWFs) for farm level decision-making. The findings also revealed that elderly people passed down indigenous knowledge to them during field practices and through casual conversation as they were regarded as custodians of the indigenous knowledge systems. However, lack of IKS documentation is been the biggest challenge facing those farmers. Smallholder farmers' indigenous knowledge on weather foresting was compared with empirical evidence from Komati weather station from 1993-2018, and there were similarities on both knowledge systems. Further, it was revealed that there were different indigenous climate indicators utilised by Nkomazi smallholder farmers to predict weather forecasts. These indicators included certain patterns and behaviour of plants and animals, atmospheric, astronomic and human ailments. Animal indicators (31%) were the most commonly used followed by plant indicators (26%). The documentation of major climatic events recalled by the smallholder farmers over the study area agreed with what was collected from the rainfall and temperature data. Data from the South African Weather Services highlighted that Nkomazi rainfall has reduced greatly in the years 2000 and 2010 with 40 mm/year, with the highest temperature increase in 2003 (340). Poynton model predicted the indigenous indicators distribution with increasing temperature by 50C. The model predicted negative results with increasing temperature. Meaning that farmers would lose their indigenous indicators for weather predictions to make farm level decisions. Therefore, to address these challenges and help smallholder farmers adapt to the changing environment, the study suggests the need for reliable weather forecasts to guide the farmer's decision-making at a local level. To improve sustainability, efficient documentation of indigenous knowledge and the creation of a framework for integrating the two knowledge systems in weather forecasting is needed. Importantly, there is a great need to create an information dissemination network for weather forecasting within local municipalities. To achieve household food security, both knowledge systems should be integrated for farmers to make informed decisions. Therefore, mobile App development for rural smallholder farmers will bridge the gap and act as a key driver to reduce smallholder farmers' vulnerability to climate change and enhance resilience to improve productivity as it will focus on improving agricultural production. The mobile application for agricultural and rural development is a software that was designed for the collection and transmission of Indigenous knowledge information and modern climatic data through mobile (Web Application) technology for rural smallholder farmers. This mobile app is meant to provide practical indigenous knowledge system (IKS) used by smallholder farmers. The development of the mobile app will focus on improving agriculture production with functions such as providing climate and market information, increasing access to extension services, facilitating market links ability of sending chats/enquiries to App manager through sending chats and pics by farmers as well as IKS documentation. It will be accessible to smallholder farmers, extension officers and produce buyers. This mobile App will provide significant economic and social benefits among smallholder farmers by reducing product losses, improving agricultural production and providing the opportunity to make our developing country more globally competitive. It will include a non-redundant database (fast) that will include easy capturing of data. This system is user friendly and will be available as a light to load secure Web Application (Both Computer and Mobile). This App will contribute to the field through integrating IKS and modern science. It will assist in transforming, documenting and disseminating IKS information as well as improved accessibility of information through technology and contributing to diffusion of technology as we heading towards the 4th Industrial Revolution (4IR).