Based on GIS technologies, a decision support system (GIDSS) has been developed to remediate agricultural lands in the Bryansk region (Russia) contaminated by 137Cs after the accident at the Chernobyl nuclear power plant. GIDSS is a multilevel system consisting of basic, information and computational layers. GIDSS allows justifying a targeted approach for the remediation of agricultural lands belonging to agricultural enterprises for the production that meets the established radiological requirements for the content of radionuclides.
Undoubtedly, high demands for food from the world-wide growing population are impacting the environment and putting many pressures on agricultural productivity. Agriculture 4.0, as the fourth evolution in the farming technology, puts forward four essential requirements: increasing productivity, allocating resources reasonably, adapting to climate change, and avoiding food waste.
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.
International agricultural research is often motivated by the potential benefits it could bring to smallholder farmers in developing countries. A recent experimental literature has emerged on why innovations resulting from such research, which often focuses on yield enhancement, fail to be adopted due to either external or internal constraints. This article reviews this literature, focusing on the traits of the different technologies and their complexity and distinguishing between yield-enhancing, variance-reducing, and water- or labor-reducing technologies.
Monitoring animal performance is a challenge due to lack of systematic recording in the smallholder dairy sector in Malawi. A mobile recording system using short messaging service (SMS) was therefore trialled for data capturing and subsequent feedback provision to farmers following analyses and interpretation. This study aimed at drawing lessons regarding use of SMS recording system among dairy farmers. Of the 210 participants, 85% were farmers and 25% were other dairy value chain players.
This paper analyses a monitoring, evaluation and learning (MEL) system developed within an agricultural research for development institution. The system applies aspects of the Outcome Harvesting tool and focuses on learning for adaptation and improvement of innovation processes. Developmental evaluation principles are applied to discuss its application. The MEL system provides insight into the processes and interactions with next users that generate outcomes.
Dans un contexte de controverse sur la capacité des modèles agricoles à répondre conjointement aux enjeux alimentaires, environnementaux et de développement en Afrique, nous analysons les conditions de viabilité d’une agriculture à caractère biologique au Cameroun. La démarche mobilise une enquête par entretiens semi-directifs auprès des acteurs engagés dans les filières de production biologique et une mise en débat des connaissances générées lors d’ateliers participatifs multi-acteurs. Elle met en interaction les connaissances scientifiques, entrepreneuriales et techniques.
Internet of things (IoT) results in massive amount of streaming data, often referred to as “big data”, which brings new opportunities to monitor agricultural and food processes. Besides sensors, big data from social media is also becoming important for the food industry. In this review we present an overview of IoT, big data, and artificial intelligence (AI) and their disruptive role in shaping the future of agri-food systems.
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.
Xanthomonas Wilt of Banana (BXW) is a complex problem in the African Great Lakes Region that is affecting the livelihoods of millions of smallholder farmers. Since the first disease reports from Uganda and the Democratic Republic of Congo in 2001, BXW has been studied widely. The majority of these studies focus on the technological or biophysical dimensions, while aspects and influence of socio-cultural, economic and institutional dimensions only recently started to gain attention.