CONTEXT

Big data applications in agriculture evolve fast, as more experience, applications, good practices and computational power become available. Actual solutions to real-life problems are scarce. What characterizes the adoption of big data problems to solutions and to what extent is there a match between them?

OBJECTIVE

We aim to assess the conditions of the adoption of big data technologies in agricultural applications, based on the investigation of twelve real-life practical use cases in the precision agriculture and livestock domain.

METHODS

Modern agriculture and food production systems are facingincreasing pressures from climate change, land and wateravailability, and, more recently, a pandemic. These factors arethreatening the environmental and economic sustainability ofcurrent and future food supply systems. Scientific andtechnological innovations are needed more than ever to secureenough food for a fast-growing global population. Scientificadvances have led to a better understanding of how variouscomponents of the agricultural system interact, from the cell tothe field level.

There is increasing demand for institutional reform in the agricultural sciences. This paper presents lessons from the content and directions in soil science research in India, to make a case for institutional reform in the agricultural sciences. It demonstrates how existing institutional and organizational contexts shape the research content of the soil sciences and its sub-disciplines. These contexts also shape the capacity of the soil sciences to understand and partner with other components of the wider natural resource management (NRM) innovation systems.

A fragmented digital agriculture ecosystem has been linked to the slow scale-out of digital platforms and other digital technology solutions for agriculture. This has undermined the prospects of digitalizing agriculture and increasing sectoral outcomes in sub-Saharan African countries. We conceptualized an aggregator platform for digital services in agriculture as a special form of digital platforms that can enhance the value and usage of digital technologies at the industry level. Little is known about how such a platform can create value as a new service ecology in agriculture.

Animal-source foods (ASF), such as fish, provide a critical source of nutrients for dietary quality and optimal growth of children. In sub-Saharan Africa, children often consume monotonous cereal-based diets, a key determinate of malnutrition such as stunting. Identifying existing sources of ASF for children’s diets will inform the development of nutritious food systems for vulnerable groups.

Fish is a key source of income, food, and nutrition in Zambia, although unlike in the past, capture fisheries no longer meet the national demand for fish. Supply shortfalls created an opportunity to develop the aquaculture sector in Zambia, which is now one of the largest producers of farmed fish (Tilapia spp.) on the continent. In its present form, the aquaculture sector exhibits a dichotomy.

This article investigates determinants and impacts of cooperative organization, using the example of smallholder banana farmers in Kenya. Farmer groups are inclusive of the poor, although wealthier households are more likely to join. Employing propensity score matching, we find positive income effects for active group members. Yet price advantages of collective marketing are small, and high-value market potentials have not yet been tapped. Beyond prices, farmer groups function as important catalysts for innovation adoption through promoting efficient information flows.

Many developing countries are experiencing a rapid expansion of supermarkets. New supermarket procurement systems could affect farming patterns and wider rural development. While previous studies have analyzed farm productivity and income effects, possible employment effects have received much less attention. Special supermarket requirements may entail intensified farm production and post-harvest handling, thus potentially increasing demand for hired labor. This could also have important gender implications, because female and male workers are often hired for distinct farm operations.

Plants are susceptive to various diseases in their growing phases. Early detection of diseases in plants is one of themost challenging problems in agriculture. If the diseases are not identified in the early stages, then they may ad-versely affect the total yield, resulting in a decrease in the farmers' profits. To overcome this problem, many re-searchers have presented different state-of-the-art systems based on Deep Learning and Machine Learningapproaches. However, most of these systems either use millions of training parameters or have low classificationaccuracies.

The recent proliferation of mobile phones in rural Africa has also led to increased interest in mobile financial services (MFS), such as mobile money and mobile banking. Such services are often portrayed as promising tools to improve agricultural finance, especially among smallholders who are typically underserved by traditional banks. However, empirical evidence on the actual use of MFS for agricultural activities is thin. Here, we use nationally representative data from Kenya to analyze the use of mobile payments, mobile savings, and mobile credit among the farming population.