1. Service/Fix Your Weather Station or Buy a New One for Correct Fruit Disease Model Predictions in 2022; 2. Learn How to Use RIMpro Apple Scab and Fire Blight Prediction Models
1. Now is the Time to Purchase New or Service Your Existing Weather Station(s) Connected to NEWA Plant Disease Models for 2022 Season!
Some RainWise (now KestrelMet) weather stations might not have operated properly in 2021 as they had faulty sensor for either leaf wetness, temperature or rain. It is critical for your weather stations to be serviced every five years and anytime when you doubt your data is correct or the multi-point malfunction occurs on the station. The news is that RainWise is now part of KestrelMet so if you have a RainWise station that hasn’t been serviced for last 5 years or is malfunctioning please contact KestrelMet technical support today at: (207) 801-4043 or via e-mail address bluscombe@rainwise.com (Brad Luscombe, Manager Support, Sales, and Service). You must have the temperature sensor, wetting sensor and rain gauge sensor fully functional. If your on-farm weather station is not functioning properly you will not get accurate tree fruit disease infection predictions due to false data feed into the prediction models. Only accurate weather data gives you the accurate scab, fire blight and Sooty Blotch and Flyspeck model predictions that will best time your spray applications. This in turn will allow you to save money by omitting the unnecessary spray(s) when scab infections do not occur early in the spring. If your station sensors break down in the middle of the apple scab season and are not providing accurate data reads, we recommend that you can use the nearest functional NEWA station to you, but only until you fix the one you have on farm. Finally, for more info on this weather station, use link KestrelMet. Please review the NEWA Maintenance Guide page for additional information before making your purchase.
The other option for purchasing a weather station is Onset Data Loggers and this and the above mentioned weather stations are the only two pre-configured for full compatibility with NEWA’s agricultural production tools. The NEWA network does not accept data from other brands or custom-built devices. To ask for purchasing a new Onset Data Loggers station contact Matt Sharp, Strategic Sales Representative in Environmental & Agricultural Monitoring at 508 473 3126 or via e-mail address matt_sharp@onsetcomp.com. Please review the NEWA Maintenance Guide page for additional information before making your purchase.
Weather station placement and activation
Once you get the station, follow manufacturer guidelines for placement of your weather station to ensure accurate and unobstructed data collection. Also, read the NEWA Placement Guide page for tips on siting your weather station. Connect the weather station to your vendor’s server and verify your machine is successfully reporting. KestrelMet uses KestrelNet (https://kestrelnet.net) and Onset Data Loggers uses HOBOlink (https://hobolink.com).
Connect with NEWA
Connect your weather station to the NEWA network after linking with your vendor’s online platform. Contact the NEWA Help Desk at support@newa.zendesk.com to start this final step. Help Desk staff will confirm your request and generate a work ticket to onboard your new machine. You will receive final confirmation when your weather station has been added to NEWA.
2. RIMpro Learning Partnership: Learn How to Use RIMpro Apple Scab and Fire Blight Prediction Models
We are assembling a group of growers in Virginia who are interested to learn how to use and interpret RIMpro prediction models for apple scab and fire blight infection(s). RIMpro is a cloud based (online) cluster of many tree fruit and grape disease prediction models developed over the last 30 years by the European scientists and a private company RIMpro B.V. from Netherlands. RIMpro is subscription based: https://www.rimpro.eu/ As you can see on their website, if you click on the button “Pricing and Create Account” under the box “Create new RIMpro account”, one i costs 220 Euros per year (~$250) for an account with one connected weather station (you can use a VISA or MasterCard to pay after you subscribe via PayPal or you will use an invoice that will be sent to you in a separate e-mail once you subscribe). An additional 165 Euros per year (~$187) is charged for every extra weather station you wish to additionally connect to your RIMpro account.
Once you subscribe, you must connect your own or any nearby NEWA weather station to the RIMpro by paying a NEWA Data License ($50 per location) via this link here: https://blogs.cornell.edu/newa/rimpro-data-feeds/ This allows RIMpro to use your NEWA station weather data in the RIMpro models and to add the local weather forecast of up to 10 days. This will enable you to see how the disease model prediction looks like for the future weather data i.e. forecast. No other people can or will have access to your data unless you choose to be a member of a RIMpro user group that Dr. Acimovic will lead for the e-mail list that is assembled for the purpose of learning RIMpro (the members of the group can see models from the other stations in the group). If you pay the subscription, the data from your station are your property and you cannot share that data publicly. However, you can get the interpretation of your model outputs via e-mail from your RIMpro group leader (plant pathologist Srdjan Acimovic).
Any interested growers who want to participate in this group should contact your local VTech plant pathologist Srdjan Acimovic on 540 232 6037 or 517 449 0905 to communicate that you wish to join this learning partnership. To join, you should use your own weather station, or select your neighbor’s weather station near you, to be connected to RIMpro cloud. If you have any questions on the above outlined steps to connect your station to RIMpro, please contact Srdjan Acimovic on 540 232 6037 or 517 449 0905.
To decide on joining this group, you can read more about the RIMpro models using the following links:
Introduction to RIMpro tree and grape disease prediction models
Two Years of Experience With Using RIMpro Article