Data-driven agriculture and sustainable farming: friends or foes?

Rozenstein, O., Cohen, Y., Alchanatis, V., Behrendt, K., Bonfil, D.J., Eshel, G., Harari, A., Harris, E., Klapp, I., Laor, Y., Linker, R., Paz-Kagan, T., Peets, S., Rutter, S.M., Salzer, Y. and Lowenberg-DeBoer, J.M. (2023) Data-driven agriculture and sustainable farming: friends or foes? Precision Agriculture. ISSN 1385-2256

[img]
Preview
Text
Karl Behrendt Data driven agriculture UPLOAD.OCR.3.pdf - Published Version
Available under License Creative Commons Attribution.

Download (858kB) | Preview

Abstract

Sustainability in our food and fiber agriculture systems is inherently knowledge intensive. It is more likely to be achieved by using all the knowledge, technology, and resources available, including data-driven agricultural technology and precision agriculture methods, than by relying entirely on human powers of observation, analysis, and memory following practical experience. Data collected by sensors and digested by artificial intelligence (AI) can help farmers learn about synergies between the domains of natural systems that are key to simultaneously achieve sustainability and food security. In the quest for agricultural sustainability, some high-payoff research areas are suggested to resolve critical legal and technical barriers as well as economic and social constraints. These include: the development of holistic decision-making systems, automated animal intake measurement, low-cost environmental sensors, robot obstacle avoidance, integrating remote sensing with crop and pasture models, extension methods for data-driven agriculture, methods for exploiting naturally occurring Genotype x Environment x Management experiments, innovation in business models for data sharing and data regulation reinforcing trust. Public funding for research is needed in several critical areas identified in this paper to enable sustainable agriculture and innovation.

Item Type: Article
Keywords: Regenerative agriculture, Data ownership, Privacy, Data integration, Decision support systems, Research needs, Research funding
Divisions: Agriculture and Environment (from 1.08.20)
Depositing User: Mrs Rachael Giles
Date Deposited: 24 Oct 2023 13:31
Last Modified: 24 Oct 2023 13:31
URI: https://hau.repository.guildhe.ac.uk/id/eprint/18009

Actions (login required)

Edit Item Edit Item