I built these apps because I wanted these functions for myself easily accessible on my smart phone while I was out in the shack or the bush.
The temp app was my first one and it remains kind of stand alone in its function. The log collection and mapping and forecasting are more integrated. Together they have evolved into a crowdsourced data science project, using modern mobile technology for data collection combined with cloud based machine learning for analysis and data presentation.
If you use these apps let me know, send me a note on my feedback page. I would like to continue to make these more accurate and add features over time.
Click on the icons below to learn more.
This web app displays the temperature in both Fahrenheit and Celsius that maple sap becomes syrup. The calculation uses a real-time atmospheric pressure reading from the closest weather station based on your mobile devices location.
Myself I was tired of going to several sites to collect the same data to make calculations or re-calibrating my thermometer in a pot of water all the time. I also wanted it to be easy to use on my smart phone while I was out in the shack.
I didn't create the actual mathematical formulas involved here. The formulas are well known and published in scientific journals and books. And it is also true I didn't even have to write out the math involved in calculating the boiling point of water for given pressure. There are libraries that programmers can use to call functions to do common math routines like this for us.
For the boiling point of water I use a function of the coolprop library referenced below where sea level pressure is the variable that I'm getting from the closest weather station. I then fetch the device elevation from Google Maps api, add that into the formula. Then I am adding 7.5 degrees fahrenheit to the result.
I did a lot of research online to determine the number of degrees above boiling water. There is a ton of information on the web that would lead you to believe the number is 7 degrees above boiling water. I looked for resources that I could consider authoritative and decided to use the values provided by a publication from the University of New Hampshire which said 7.5 and agreed closely to a publication from the Ontario Ministry of Agriculture, Food and Rural Affairs which publicized a number in celsius that converts to between 7.38 and 7.56 degrees fahrenheit.
Used these references for the boiling point of sap to syrup:
Used a function of this library for boiling point of water by pressure
When ever I would look at the tapping updates threads at mapletrader.com I always think how cool it would be to see what people are saying about how their flow is on a map. So I wrote that. I tried to make it simple to use so that people will want to participate. The first time you log in just create a profile for your sugar bush, then in the future you just log how many gallons or liters you collected since the previous collection. Then I make some calculations about volume per tap and plot it on a map.
I used a couple of Google Maps to display the collected data. For one, I used Google's heat map technology which I think displays the data nicely. This type of mapping is used with scientific data to display things like population density or seismic activity. This is a good overview map for how the season is progressing. I also used a map with pins that can show more detail, green pins show where data has been collected, clicking on the green pin shows the actual logs from that user. Of course, I offer a privacy setting, so these pins can be randomly offset within a 5k/3m radius.
Besides just plotting on the map I’m also collecting the current weather data from from a weather service about the closest observations to the location of your sugar bush for the time frame of each log entry. I'm just now (2019) starting to do some analysis of this data and have started creating an "Analytics" section. We’ve got plenty of old school, hand me down knowledge about what makes the sap run and averages per tap per tree, not to mention plenty of university studies that are made available to the public. But I also thought it would be modern to crowd source some data collection and make my own analysis from collections provided by both commercial and hobby producers here too.
The Sap Flowcaster was a natural offshoot of collecting data in the Maple Logs app. The more data I collect about my sap flow in the past the more accurate I should be able to predict when my sugar bush will flow in the future given my local weather forecast.
Again with this app, don't shoot the messenger, I'm not the meteorologist here. I pull the weather forecast data from known services like; The National Weather Service (US), Environment and Climate Change (Canada) as well as a couple commercial sources, DarkSky and WeatherUnderground. These are the same sources most other apps you would use get their forecasts from. And as you know, weather forecasts are not always 100% accurate. My app can only be as accurate as the forecasts I pull from those other sources.
The first thing I did was try and display the weather forecast in a way that makes sense to a syrup producer. What we care about is the previous night low, followed by the daily high. Most weather forecast applications show that data exactly backwards. Of course we've all gotten used to reading it that way, but I think my display makes more sense for our usage. Next instead sun, clouds or rain icons I added a flowing (or lack of) bucket icon. I have built a weight based system that gives back a 0-5 weighted ranking which is indicated by the buckets.
Note that the bucket icons indicating flow are a work in progress. I'm using analytics garnered from the Maple Logs program to build a machine learning prediction model. Over time the values from the Maple logs will provide more training data for the algorithms and they will continue to be more accurate.