Check out this light/ yield calculator from YOR, Hella good info on lighting

http://www.angelfire.com/cantina/fourtwenty/yor/yieldcalcadvanced.htm

Sadly it says im getting 29 grams a foot square an my canopy has to be 4 ft ish for my 175w mh an 150hps duel light grow cab.

I love this sight an spent quite awhile reading it today

You got to check it out.

Cool thanks for sharing

to bad more then light acounts for yeild, like strain,temps,soil,nutes, all types of stuff can increase or decrease yield

lots of info in the yor...numerous calculators, info on lighting and tons more...yor is a subsection of
http://www.angelfire.com/cantina/fourtwenty/index.html
later

What has been discovered from the YOR database

In the final analysis, 53% of crop yield variations found in the YOR database can be uniquely explained with just four key influences every indoor cannabis garden has in common.

• Lumens (31%)
• HPS Spectrum (14%)
• Experience (5%)
• Hydroponic Medium (3%)

http://www.angelfire.com/cantina/fourtwenty/yor/yieldcalc.htm For there bad ass HPS yield/ light calc.

I got to go read this sight again!

Great link! While I agree that there are many other factors that can affect growth, this nifty calculator gives a descent, rough estimate of what one can expect given all the specific variables

thanks for the link, cool to play around with

This isn't really a trustworthy formula for determining yield. Seriously...grow out your plants and determine for yourself what they yield. Don't set yourself up for heartbreak (or possibly extreme excitement due to the lack of accuracy of the calculator) there are just too many variables.

It should just come up at 0.

"You have just used an online calculator to predict the future. Your prize... Zero, Zilch, Nada."

The statistical analyses on the following pages are an attempt to take us beyond the realm of any single grower's anecdotal experience or subjective perception, and to add some scientific rigor to the analysis of the significant influences on crop yield. There are many fields or variables contained in the YOR database, and we are applying powerful statistical analytic techniques to try to tease apart these possible influences on crop yield to determine what really matters and what doesn't.

"So in the early rounds of analysis, we do simple correlations between one predictor at a time and crop yield, to see if the predictor seems to have any influence on crop yield. We do a large number of these correlations, one for each predictor, and remove from future consideration any variable that appears to have only a very weak correlation with crop yield"

Man do these guys know there math.. I cant beleve how much work it must have been to make this.


Here we can see that there is a fairly good correspondence between predicted and actual weight, indicating that the model is a good one. As the footnote in the graph indicates, the overall correlation between predicted and actual weight is .737 (compared with a maximum theoretical coefficient of 1.00.) If we square this number and then do some adjustments for our sample size, we arrive at a value of about .53. This means that we are explaining about 53% of the database's variation in crop yield using just these four predictors. And while some people might think this isn't a very good model, it actually is. In fact, it is rarely possible to explain anywhere near all of the variation in data such as those we are working with here. There are undoubtedly many subtle influences not captured in the YOR database. In addition, there is probably some error in the reporting of the data by growers.