Big Data for weed control and crop protection

Abstract

SummaryFarmers have access to many data-intensive technologies to help them monitor and control weeds and pests. Data collection, data modelling and analysis, and data sharing have become core challenges in weed control and crop protection. We review the challenges and opportunities of Big Data in agriculture: the nature of data collected, Big Data analytics and tools to present the analyses that allow improved crop management decisions for weed control and crop protection. Big Data storage and querying incurs significant challenges, due to the need to distribute data across several machines, as well as due to constantly growing and evolving data from different sources. Semantic technologies are helpful when data from several sources are combined, which involves the challenge of detecting interactions of potential agronomic importance and establishing relationships between data items in terms of meanings and units. Data ownership is analysed using the ethical matrix method to identify the concerns of farmers, agribusiness owners, consumers and the environment. Big Data analytics models are outlined, together with numerical algorithms for training them. Advances and tools to present processed Big Data in the form of actionable information to farmers are reviewed, and a success story from the Netherlands is highlighted. Finally, it is argued that the potential utility of Big Data for weed control is large, especially for invasive, parasitic and herbicide-resistant weeds. This potential can only be realised when agricultural scientists collaborate with data scientists and when organisational, ethical and legal arrangements of data sharing are established.

Can Precision Agriculture Increase the Profitability and Sustainability of the Production of Potatoes and Olives?

“…For example, Akkerweb (www.akkerweb.nl), which evolved out of a decision support system for control of plant parasitic nematodes [9,10], has more than ten recommendation apps [11,12]. A recent review of data recording and processing for weed control and crop protection is available [13].…”

How should we turn data into decisions in AgriFood?

“…Thus, the opportunities, challenges and action points shown later are not simply the views of the authors, but an amalgamation of the views of over 70 professionals in this area, as interpreted and brought together by the authors with the context of the cloud of literature that is already available and known use‐cases. Many of the conclusions may be found in other sources . Although our method of collecting data was different from that used by other authors, the themes that emerged were not so different.…”

“…to manage resource efficiency, health and welfare of animals, and it could also be used to decrease bureaucracy for farmers . Examples of other international initiatives include those led by Wageningen University and Research (the Netherlands), INRA (France), Agroknow (Greece and Belgium), and AgGateway (USA) . International organisations and initiatives supporting the digitalisation of AgriFood sector include GODAN, CGIAR, and Food and Agriculture Organization of the United Nations (FAO) (with a dedicated Interest Group on Agricultural Data).…”

“…Many of the conclusions may be found in other sources. [1][2][3] Although our method of collecting data was different from that used by other authors, the themes that emerged were not so different.…”

“…A revolution in food production, processing and distribution is underway. [1][2][3] Various technologies are already transforming the flow of food from field to consumer: technologies such as artificial intelligence (AI), cloud computer processing, remote sensing and robotics. Can these changes benefit the AgriFood supply chain and consumers?…”