Opportunities and challenges for seasonal climate forecasts to more effectively assist smallholder farming decisions

Chisadza, Bright; Mushunje, Abbyssinia; Nhundu, Kenneth; Phiri, Ethel E.

doi:10.17159/sajs.2020/4649

Cited by 11 publications

(5 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The availability of data related to the primary factors is a prerequisite for modelling to be an effective solution. resolution input data to predict local variability in fungal growth and aflatoxin production (Chisadza et al, 2020).…”

Section: Current State Of Predictive Aflatoxin Risk Modelsmentioning

confidence: 99%

The potential for aflatoxin predictive risk modelling in sub-Saharan Africa: a review

Keller

Russo

Rembold

et al. 2022

WMJ

View full text Add to dashboard Cite

This review presents the current state of aflatoxin risk prediction models and their potential for value actors throughout the food chain in sub-Saharan Africa, with a specific focus on improving smallholder farmer management practices. Several empirical and mechanistic models have been developed either in academic research or by private sector aggregators and processors in high-income countries including Australia, the USA, and Southern Europe, but these models have been only minimally applied in sub-Saharan Africa, where there is significant potential and increasing need due to climate variability. Predictions can be made based on historic occurrence data using either a mechanistic microbiological framework for aflatoxin accumulation or an empirical model based on statistical correlations with climate conditions and local agronomic factors. Model results can then be distributed to smallholders through private, public, or mobile extension services, used by policymakers for strategy or policy, or utilised by private sector institutions for management decisions. Specific agricultural advice can be given during the three most critical points in the phenological cycle: preseason insight including sowing timing and crop varieties, preharvest advice about management and harvest timing, and postharvest optimal practices including storage, drying, and market information. Model development for sub-Saharan Africa is limited by a dearth of georeferenced aflatoxin occurrence data and real-time high resolution climate data; the wide diversity of farm typologies each with significant information and technology gaps; a prevalence of informal market structures and lack of economic incentives systems; and general lack of awareness around aflatoxins and best management practices to mitigate risk. Given advancements towards solving these challenges, predictive aflatoxin models can be integrated into decision support platforms to focus on optimisation of value for smallholders by minimising yield and nutritional losses, which can propagate value throughout the production and postharvest phases.

show abstract

Section: Current State Of Predictive Aflatoxin Risk Modelsmentioning

confidence: 99%

The potential for aflatoxin predictive risk modelling in sub-Saharan Africa: a review

Keller

Russo

Rembold

et al. 2022

WMJ

View full text Add to dashboard Cite

show abstract

“…difficult for communities to be resilient without it (Masekoameng and Molotja, 2019). Previous research has argued that IKS plays an important role in climate forecasting in Africa's smallholder farming communities, particularly in occasionally predicting local weather information and frost (Chisadza et al, 2018). According to Nhemachena (2015), this knowledge only qualifies to be IKS if it has significantly helped in the solving of problems that include problems related to climate change and variability among many other socio-environmental problems.…”

Section: Conceptualizing Indigenous Knowledge Systems In Climate Fore...mentioning

confidence: 99%

Incorporating indigenous knowledge systems-based climate services in anticipatory action in Zimbabwe: an ex-ante assessment

Dube,

Huhn,

Guimarães Nobre

et al. 2024

Front. Clim.

View full text Add to dashboard Cite

IntroductionThe success of anticipatory action (AA) in climate change related disaster risk reduction depends largely on the ability to accurately predict adverse weather events and to subsequently take appropriate and timely action. The current seasonal climate forecasts obtained through national and global forecasting centers such as the Zimbabwe Meteorological Services Department (MSD) and the European Center for Medium-Range Weather Forecasts (ECMWF) have been found to have several limitations including limited skill in intra-seasonal variability which is vital in most processes, lack of accessibility, difficult interpretability and applicability to local communities. As a result, calls for the integration of Indigenous Knowledge Systems (IKS)-based climate services in seasonal climate forecasting to bolster the efficacy and accuracy of forecasts are increasing.MethodologyThe study employed a mixed methods approach combining a survey of 200 household heads, document reviews and key informant interviews with IKS specialists, AA community of practice members and disaster risk reduction specialists.ResultsThis article presents the findings of a study carried out in four semi-arid districts of Zimbabwe (Mbire, Matobo, Binga, and Mudzi) to assess the feasibility of integrating IKS into the drought AA mechanism at national, district, and ward level. We find that 82% of the surveyed households used indigenous knowledge systems for seasonal climate forecasting and extreme weather forecasting combined with scientific forecasts. Respondents demonstrated preference for triangulated forecasting to increase reliability. Both the meteorological approaches to seasonal climate forecasting and the IKS based forecasting had different strengths and weaknesses.DiscussionBased on the found gaps in current seasonal forecasting techniques, local applicability, and limited quantitative analysis in IKS, this study provides a guideline on how scientific and IKS forecasting can be triangulated for leveraging forecasting information in Zimbabwe. The use of IKS may be of utmost relevance to agencies and entities seeking the achievement of drought risk reduction through AA programmes.

show abstract

“…Second, the benefits farmers derive from advice are, in part, based on the applicability of the advice relative to real-time changes in the local environment, such as weather and pest outbreaks. Studies suggest that weather forecasts affect farmer investment decisions (Pandey, 1998;Chisadza et al, 2020) and that accurate forecasts increase farm profitability (Rosenzweig & Udry, 2019). Third, both the appropriateness of agricultural content and optimal message design may vary by farmer characteristics, such as land size and access to storage, as well as gender, age, and other individual characteristics.…”

Section: Customizationmentioning

confidence: 99%

Digital Agricultural Extension for Development

Fabregas

Harigaya

Kremer

et al. 2022

Introduction to Development Engineering

View full text Add to dashboard Cite

Providing information at scale about improved agricultural practices to smallholder farmers remains a challenge in most developing countries. Traditional dissemination methods like in-person meetings or radio programming can be costly to scale or offer too generic information. Moreover, while most agronomic recommendations focus on maximizing crop yields, farmers weigh multiple other factors when making farming decisions, such as the profitability of investments and risks. The proliferation of mobile phones has shifted these trends. Mobile agriculture extension can cost-effectively provide tailored suggestions to farmers and improve their use of information. This case study describes the use of digital extension technologies to support farmers in a number of contexts. We draw insights from various studies and the experience of Precision Development on the importance of human-centered design, monitoring, and continuous experimentation. The chapter also discusses the ecosystem of stakeholders for digital agriculture, concerns relating to privacy and financing, and how mobile services can be used to facilitate social learning.

show abstract

Opportunities and challenges for seasonal climate forecasts to more effectively assist smallholder farming decisions

Cited by 11 publications

References 26 publications

The potential for aflatoxin predictive risk modelling in sub-Saharan Africa: a review

The potential for aflatoxin predictive risk modelling in sub-Saharan Africa: a review

Incorporating indigenous knowledge systems-based climate services in anticipatory action in Zimbabwe: an ex-ante assessment

Digital Agricultural Extension for Development

Contact Info

Product

Resources

About