CONTEXT: Adoption and diffusion of digital farming technologies are expected to help transform current agricultural systems towards sustainability. To enable and steer transformation we need to understand the mechanisms of adoption and diffusion holistically. Our current understanding is mainly informed by empirical farm-level adoption studies and by agent-based models simulating systemic diffusion mechanisms. These two approaches are weakly integrated.
Controlled Environment Agriculture (CEA) is the production of plants, fish, insects, or animals inside structures such as greenhouses, vertical farms, and growth chambers, in which environmental parameters such as humidity, light, temperature and CO2 can be controlled to create optimal growing conditions.
In creating a usable Information System (IS), the quality of information is crucial for making the right decisions. Although, many Information Quality (IQ) features have been identified in a broader context, only certain IQ features would become applicable for each domain from the usability perspective. This study focuses on a theoretical analysis to identify the IQ features which would be significant to produce a usable agricultural information system with respect to the developing countries.
The prevalence of “grass-fed” labeled food products on the market has increased in recent years, often commanding a premium price. To date, the majority of methods used for the authentication of grass-fed source products are driven by auditing and inspection of farm records. As such, the ability to verify grass-fed source claims to ensure consumer confidence will be important in the future. Mid-infrared (MIR) spectroscopy is widely used in the dairy industry as a rapid method for the routine monitoring of individual herd milk composition and quality.
Decision support systems (DSS) have long been used in research, service provision and extension. Despite the diversity of technological applications in which past agricultural DSS canvass, there has been relatively little information on either the functional aspects of DSS designed for economic decisions in irrigated cropping, or the human and social factors influencing the adoption of knowledge from such DSS.
The study assesses the farmers’ use of Global System for Mobile (GSM) for communication among farmers in agricultural extension programs in Taraba State, Nigeria. Specifically, the objectives include: identify key areas in which GSM are used for communication in agricultural extension programs activities, determine the frequency of usage of GSM for information exchange between farmers and extension personnel; and ascertain farmers’ satisfaction in the use of GSM in obtaining information in the various agricultural extension programs.
The evolution of mobile phone applications has opened up a platform for easy and real time dissemination and exchange of agricultural information among agricultural extension officers, farmers, agricultural institutions and non-governmental institutions. This study examined attitude, knowledge and constraint associated with the use of mobile phone apps by farmers in North West region of Nigeria. A descriptive survey design was adopted; data collection tool was pre-tested and administered as interview schedule to randomly sampled farmers.
Improvements in the sustainability of agricultural production depend essentially on advances in the efficient use of nitrogen. Precision farming promises solutions in this respect. Variable rate technologies allow the right quantities of fertilizer to be applied at the right place. This helps to both maintain yields and avoid nitrogen losses. However, these technologies are still not widely adopted, especially in small-scale farming systems. Recent developments in sensing technologies, like drones or satellites, open up new opportunities for variable rate technologies.
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
The problems of agricultural development for small and medium enterprises (SMEs) are considered. The features of modeling business processes in agriculture are analyzed. A financial decision support system is proposed to increase sustainability and reduce risks in the development of agricultural SMEs. The software modules are based on TEO-INVEST.