Showing results for: Farm management tools
FCRN member Susanne Freidberg of Dartmouth College has written this paper about the difficulties that companies such as food manufacturers face in gathering data about their food supply chains and using that data to promote sustainability. The paper is based on over fifty semi-structured interviews with companies and analysis of their data collection tools.
This paper presents a newly developed open-source system for precision agriculture in lettuce production. The system, known as AirSurf, uses a lightweight manned aircraft to gather images of lettuce fields, then a deep learning algorithm assesses the state of the lettuce crops on a number of characteristics, including lettuce size and number per field.
This book synthesises the academic literature on sustainable food supply chains and offers quantitative models on topics such as shelf life, vehicle routing and waste management.
FCRN member Mark Measures has produced this report on the use of different soil analysis and management techniques for organic and agro-ecological farming. The report is the outcome of a Churchill Fellowship.
This feature in the New Food Economy explores how autonomous weed-picking robots could replace herbicides and tackle weeds that have become resistant to some herbicides. The robots use both GPS tracking and cameras to navigate fields and remove weeds.
This publication from the Food and Agriculture Organisation of the United Nations explains what blockchain technology is and explores how it could be used in agriculture, for example in insurance, land registration or tracking supply chains.
This report from the US National Academies of Sciences, Engineering, and Medicine identifies emerging scientific advances that could help to make the US food system more resilient to rapid changes and extreme conditions, as well as making agriculture more efficient and sustainable.
Research literature, policy indicators, and assessment tools use many different variables to assess sustainable agricultural land systems in Europe (for example soil loss, landscape diversity and food quality). Out of 239 of these variables identified in this paper, 32 have been covered by all three perspectives (i.e. research, policy and practice) while the remainder have only been considered by one or two perspectives.
The 2019 Green Alliance Annual Debate discusses the ways in which earth observation and data science can improve our understanding of and ability to address environmental issues - for example, monitoring deforestation or water levels in reservoirs in real time through satellite images.
This paper presents the Open Source Seed (OSS) Licence, a new legal instrument (inspired by open source software) designed to protect access to plant germplasm as a commons accessible to everyone. The legally enforceable licence is being trialled with varieties of tomato, wheat and maize.
Non-profit organisation Ceres has produced an overview of resources (standards, methodologies, tools, and calculators) for assessing greenhouse gas emissions from agricultural production and agriculturally-driven land use change.
Facial recognition could be used on pig farms in China to provide individualised feeding plans. The artificial intelligence system, created by a subsidiary of Chinese e-commerce company JD, can also track a pig’s growth, physical condition and vaccinations over its lifespan.
A new method for monitoring nutrient concentrations in pasture in real time - using a small near-infrared spectroscopy device - could allow farmers to improve productivity by adjusting livestock grazing patterns, according to this paper.
This paper compared soil moisture and biomass growth between pasture both with and without photovoltaic solar panel arrays. While average soil moisture was similar across the fields with and without solar panels, the field with the solar panels had more variable soil moisture: directly underneath the solar panels, persistent stores of soil water were available throughout the growing season. Without solar panels, the pasture experienced water stress in the middle of summer.
Israeli startup Taranis has raised $20 million in funding for its aerial imaging technology, which uses multispectral images from satellites, planes and drones to scan fields. Artificial intelligence then identifies threats such as insects, crop disease, weeds and nutrient deficiencies. The company claims its technology can increase crop yields by up to 7.5%.