In recent years, the international status of agriculture in the BRICS countries—Brazil, Russia, India, China and South Africa—has been continuously improved. In 2018, the gross agricultural production of the BRICS countries accounted for more than 50% of the world’s total. Further strengthening the developing cooperation of the BRICS countries is of great significance for ensuring global food security.
The use of digital technologies has been recognized as one of the great challenges for businesses of the 21st century. This digitalization is characterized by the intensive use of information technologies in the different stages of the value chain of a sector. In this context, smart agriculture is transforming the agricultural sector in terms of economic, social, and environmental sustainability.
Boundary-spanning search for knowledge is an effective way for enterprises to acquire heterogeneous knowledge, and is also an important pre-stage to realize effective knowledge reconstruction. Based on the boundary-spanning search for knowledge theory, this paper studies the relationship between boundary-spanning search for knowledge and the sustainable innovation ability of agricultural enterprises considering the influence of organizational knowledge reconstruction, from a Chinese perspective.
The aim of the study was to provide the examples of eco-innovations in agriculture relating to the concept of sustainable development and the indication of their conditions. Quantitative and qualitative methods were applied to the research, namely: descriptive statistical and economic analysis of the Polish Farm Accountancy Data Network (FADN) data and Statistics Poland data, as well as case studies of organic food producers, covering the years 2005–2019.
Social farming (SF) has emerged as a social innovation practice shaping heterogeneous approaches and results. This study discusses the complexity of SF policy and practices, and it is led by the main hypothesis that the relationship between agricultural and social dimensions might be very heterogeneous, not only in different national contexts but also within the same national and local level. SF policy and practices are investigated testing the hypothesis of three main different modalities of interaction according to how the social and the agricultural perspectives interact.
The quest for innovation lies at the heart of European rural development policy and is integral to the Europe 2020 strategy. While social innovation has become a cornerstone of increased competitiveness and the rural situation legitimizes public intervention to encourage innovation, the challenges of its effective evaluation are compounded by the higher ‘failure’ rate implied by many traditional performance measures.
This paper provides a chronology and overview of events and policy initiatives aimed at addressing irrigation sustainability issues in the San Joaquin River Basin (SJRB) of California. Although the SJRB was selected in this case study, many of the same resource management issues are being played out in arid, agricultural regions around the world.
The application of ubiquitous computing has increased in recent years, especially due to the development of technologies such as mobile computing, more accurate sensors, and specific protocols for the Internet of Things (IoT). One of the trends in this area of research is the use of context awareness. In agriculture, the context involves the environment, for example, the conditions found inside a greenhouse.
Soil texture is a key soil property influencing many agronomic practices including fertilization and liming. Therefore, an accurate estimation of soil texture is essential for adopting sustainable soil management practices. In this study, we used different machine learning algorithms trained on vis–NIR spectra from existing soil spectral libraries (ICRAF and LUCAS) to predict soil textural fractions (sand–silt–clay %). In addition, we predicted the soil textural groups (G1: Fine, G2: Medium, and G3: Coarse) using routine chemical characteristics as auxiliary.
Visible and near-infrared diffuse reflectance spectroscopy (VIS-NIR) has shown levels of accuracy comparable to conventional laboratory methods for estimating soil properties. Soil chemical and physical properties have been predicted by reflectance spectroscopy successfully on subtropical and temperate soils, whereas soils from tropical agro-forest regions have received less attention, especially those from tropical rainforests. A spectral characterization provides a proficient pathway for soil characterization.