Prodata Weather Systems, suppliers of the Davis EnviroMonitor environmental data monitoring system, has announced a new offer to reduce data costs.
Business carries on here at Agri-TechE as we send our second newsletter whilst in social distancing. “Response to challenge” is our theme for this month.
The farming community is used to managing risk but extreme weather events appear to happening with greater frequency. In our free webinar a number of agri-tech entrepreneurs will explain how new AI-based tools can help mitigate the impact of weather and other ‘acts of God’.
“To provide more resilience against climate uncertainty everywhere as quickly as possible, we have started building a global inventory –with UK/Europe first – of land assets such as those just described and then mapping them at speed.” says Mark Hodgson, Chief Business Officer at Cervest. “We may be putting our livelihoods at risk unless we accurately and objectively understand how climate uncertainty effects the assets we rely on, and have a better way to manage them.”
How can you manage the risk created by weather? AI and data modelling are offering new ways to mitigate the impact: bespoke weather forecasting to optimise crop scheduling; a novel way to predict extreme events, and an insurance policy to protect against price volatility are to be discussed at an Agri-TechE event ‘Keeping a Sunny Outlook – De-risking Agriculture Through Weather-Tech’.
On 25 July 2019 Prodata Weather Systems recorded a high temperature of 39.5C near to Soham, Cambridgeshire.
Farming has always had to work alongside the elements, but just how far can technology go to help mitigate the risks of weather and make even better use of increasingly complex on-farm weather data?
The REAP technology exhibition showcase new innovations, technologies and equipment that will transform the industry. Here is an overview of some of our exhibitors this
Recent prolonged rainfall has caused delays for harvesting, reports ADAS in its latest Harvest Report for AHDB. Crop harvest has been considerably slower in the