Smart Farming Technologies – Description, Taxonomy and Economic Impact

Abstract

Precision Agriculture is a cyclic optimization process where data have to be collected from the field, analysed and evaluated and finally used for decision making for site-specific management of the field. Smart farming technologies (SFT) cover all these aspects of precision agriculture and can be categorized in data acquisition, data analysis and evaluation and precision application technologies. Data acquisition technologies include GNSS technologies, mapping technologies, data acquisition of environmental properties and machines and their properties. Data analysis and evaluation technologies comprise the delineation of management zones, decision support systems and farm management information systems. Finally, preci-

What's Cooking: Digital Transformation of the Agrifood System

“…According to Biggar et al (2013), an 8 percent increase in wheat yields (for 10 percent less nitrogen) and 5 percent increase in corn yield (for 21 percent less nitrogen) was shown when GreenSeeker technology was used in Maryland, United States. In Virginia, United States, using again GreenSeeker technology in corn fields, there was nearly 27 kilograms per hectare less nitrogen application than the conventional method with a nearly equivalent yield (Balafoutis et al 2017).…”

“…On-farm, digital technologies can help farmers manage their soil and water more sustainably by reducing input use and waste, directly contributing to environmental sustainability. Precision technologies apply water, fertilizers, herbicides, and pesticides only when and where they are needed, limiting the harm to soil and water resources caused by excessive or inadequate applications (Balafoutis et al 2017;Berry et al 2003;Bongiovanni and Lowenbert-Deboer 2004). For example, with better targeted input applications, fertilizer runoff can be reduced and fewer pesticides reach surrounding resources such as water bodies.…”

“…Precision machinery reduces nitrous oxide soil emissions by reducing nitrogen fertilizer use, which accounts for about 1.2 percent of global GHG emissions (Wood and Cowie 2004). Machine guidance and controlled traffic farming reduces fuel consumption by reducing overlap in farm operations-self-guided machines reduce carbon dioxide emissions by using less fuel (Balafoutis et al 2017). At the same time, mechanical agricultural solutions typically produce carbon dioxide by burning fuel, an effect that can be reduced by using renewable energy sources.…”

Low-cost Technological Strategies for Smallholders Sustainability: A Review

“…Digital technologies allow automatic data collection of the environment, soil, fertilization, irrigation, and crop development (Balafoutis et al, 2017). With data, it is possible to use the natural resources of the agroecosystem intelligently, improve the adaptation to the variability of climatic conditions and increase the agricultural potential.…”

Technological aspects of smart dairy farm development

“…По аналогии с термином «умный» дом (smart house) термин «умная» ферма подразумевал высокоавтоматизированную сельскохозяйственную ферму, в которой благодаря интеллектуальной составляющей в проектировании и управлении машинами фермеры могут объединить данные, полученные с датчиков со знаниями специалистов. «Умная» ферма, по определению зарубежных специалистов [1,2,3,4], должна предоставить владельцам современных молочных ферминструмент поддержки принятия решений и технологий автоматизации, позволяющий органично объединить оборудование, услуги и интеллектуальную составляющую (знания) для повышения качества молока, управления стадом, повышения продуктивности и рентабельности.…”