The math your land keeps asking for

Why Field & Farm Calc?

Most of these answers live buried in university extension PDFs, decades-old forum threads, and the back of a feed-store brochure. We turned the published formulas into clean, fast calculators that work on your phone — in the barn, in the woods, or on the water. Every tool shows its math and cites its sources, so you can trust the number and double-check it too.

What's here, and when you'd reach for it

Feeding the herd through winter. The hay calculator turns head count, body weight and days of feeding into bales, including the feeding waste that most back-of-the-envelope estimates leave out — and waste is not a rounding error, since the difference between a bale ring and rolling hay out on the ground can be a fifth of the crop. Once you know how many tons you need, hay prices shows what hay is actually trading for by state and quality grade, pulled from USDA Agricultural Marketing Service market reports with the report name and date on every row, so you can tell whether the load in the classified ad is priced fairly.

Managing pasture. Three tools cover one subject at three different time scales. Stocking rate is the season-long question: how many head the whole place carries between green-up and dormancy. Paddock calculator is the layout question: how many paddocks a given rest period needs, and how big each one should be. Grazing days is the everyday question: how long the herd can stay where they are before they should move. All three run on the same published forage figures from the University of Kentucky grazing stick tables and the same rotation identity from West Virginia University Extension, so their answers agree with each other.

Getting application rates right. Spreader calibration uses Penn State Extension's tarp method to tell you what your manure spreader is actually putting down per acre — which is almost never what the spec plate implies, because the plate is a volume figure and manure's weight per cubic foot swings with bedding and moisture. Drill calibration does the same for seed, using a catch test that is checked against Penn State's own worked example. Both exist because equipment drifts and rate charts were written for different seed, in a different condition, years ago.

Land and lease decisions. Cash rent reports USDA National Agricultural Statistics Service survey values for cropland and pasture by state, pulled from the QuickStats database rather than from someone's recollection. Hunting lease shows published state lease-rate surveys as ranges with the survey year attached, deliberately never averaged together, because a 2001–02 Kansas survey and a 2024 Missouri survey are two different facts rather than two samples of the same one.

Heat and firewood. Heat cost converts wood, propane, natural gas, heating oil and electricity into the one unit that lets them be compared — dollars per million Btu delivered into the room — using Utah State's species heat values and standard energy constants, with appliance efficiency applied exactly once. Firewood estimates how many cords a winter takes for your house and climate.

Ponds, fish and deer. Pond calculator handles volume, surface acres and the treatment math that depends on them. Fish weight estimates weight from length by species, so a fish can go back in the water without a scale. Food plots sizes seed and fertilizer for the acreage you actually have, including the pure-live-seed conversion that bag tags require. Rut timing maps peak breeding dates by state from wildlife agency studies, most of them based on fetal measurement, with the states that have no published study listed honestly as having none.

The six mistakes these tools were built around

Almost every calculator here exists because of a specific, repeatable arithmetic error — one that is easy to make, hard to notice, and expensive. They are not obscure. They turn up in feed-store advice, in spreadsheets passed between neighbors, and in most of the free calculators on the internet. Here they are with the sizes attached, because a mistake you can put a number on is a mistake you will remember.

1. Counting bales without counting waste. Twenty dry beef cows at 1,300 pounds, fed 120 days at 2.5 percent of body weight, need 78,000 pounds of hay into the animals. Delivered through a restrictive feeder at 10 percent loss that is about 124 round bales of 700 pounds. Rolled out on the ground at 35 percent loss it is about 171 — the same cows, the same winter, 48 more bales, a difference of 38 percent that is decided entirely by what the hay is sitting in. Even the ordinary gap between a well-managed ring and an unrestricted one, 15 against 25 percent, is about 17 bales. Waste is not a rounding factor in this arithmetic; on many places it is the largest single line in the winter feed bill. The hay calculator makes you choose it rather than hiding it in a default.

2. Buying a "cord" that is a third of a cord. A full cord is 128 cubic feet — a stack 4 feet high, 8 feet long, and 4 feet deep. What is usually delivered and photographed is a single row of 16-inch pieces, 4 feet by 8 feet, which is 42.7 cubic feet, or one third of a cord. Pay cord money for it and you have paid three times the price you thought. This is the most costly unit confusion in rural life and it is settled by a tape measure, so heat cost carries a checker that takes the three dimensions of the stack in front of you and returns the fraction of a cord it actually is.

3. Applying an efficiency twice. Some circulated firewood tables publish "available" Btu per cord with a stove efficiency already applied. Multiply one of those by your own stove's efficiency and you have discounted twice — and the error runs the way people least expect. A $250 cord of red oak in a 75-percent stove truly costs $13.55 per million Btu; run through a table already baked at 50 percent it reads $27.10, exactly twice the real figure, which is enough to talk somebody out of a woodstove that was in fact beating their propane by a wide margin. The same trap has a mirror image in pasture: enter forage that is already discounted to "usable" and then pick a utilization percentage on top of it, and the grazing answer drops to 47.5 percent of what it should be. Both heat cost and grazing days apply their discount exactly once and show it on the screen.

4. Trusting the spec plate. A manure spreader's rated capacity is a volume — how many cubic feet the box holds — and manure's weight per cubic foot moves with bedding, moisture and species. The same box that holds four tons of wet dairy slurry might hold two and a half tons of half-straw bedded pack, so a rate figured from the plate can be 60 percent off before the tractor moves. Spreader calibration uses Penn State's tarp method instead: catch what actually lands on a measured area and weigh it.

5. Reading the seed bag as if the bag were seed. A recommendation of 8 pounds per acre means 8 pounds of pure live seed — purity times germination, both printed on the tag. An 80 percent bag needs 10 pounds of product to deliver those 8. Sow 8 pounds of the bag and you have put down 6.4 pounds of live seed, 20 percent under the rate, and a thin plot in October is the sort of failure people blame on the weather. Food plots does the conversion from the tag numbers.

6. Averaging numbers that are not samples of the same thing. This one is ours as much as anybody's, and it is why several tables on this site look messier than they could. A Kansas hunting-lease survey from 2001–02 and a Missouri one from 2024 are two different facts about two different places twenty-odd years apart. Averaging them produces a tidy national figure that describes nowhere and no year. So the hunting lease and rut timing pages show each study separately with its state, its year and its method attached, and leave the states nobody has studied visibly blank rather than filling them with a regional guess. A blank is information. A made-up number is not.

Which guess costs you the most

Across the fourteen calculators on this site there are thirty dropdown menus and sixty-nine numeric boxes. They are not equally important, and the difference is not a matter of taste. Every dropdown that holds a multiplier has a top option and a bottom option, and the ratio between them is the most that one menu can move an answer while every other input on the page stays exactly where it is. Those options are printed in the pages themselves, so the ranking below is arithmetic rather than editorial judgment.

Sorting them that way separates the menus into two kinds, and the distinction is the useful part. Some ask you to report something you can go and measure: which species of wood, how much a bale weighs, how many acres. Get one of those wrong and you had the wrong fact. The others ask you to judge something nobody can hand you a figure for — how much forage the herd will actually get into itself, how much hay ends up trampled, how efficiently an appliance burns. Those are the ones worth slowing down on, because there is no tag to read and no scale to check them against. Here they are, biggest first:

The top of that list is worth staring at. The single most expensive guess on this entire site is how well a fire burns — not how cold the winter is, not how big the house is, not what species the wood is. An open fireplace against a modern stove is a factor of five, and it is the one figure in the whole firewood-and-heating question that most people never think to ask about. Winter severity, the thing everybody leads with, is a 2.29× swing. It is less than half as powerful as the appliance sitting in the room.

The pasture side tells the same story from the other direction. Stand density and utilization together span 10 times, and neither one is printed anywhere — both are eyeball estimates made while standing in the field. Every farm-planning spreadsheet that ships with a single hard-coded utilization percentage has quietly made the largest decision in the calculation on the user's behalf and then hidden it.

None of this means the low-ranking inputs do not matter. Insulation sits at the bottom of that table at 1.47×, and that is a statement about the three options this site offers, not about building science. The column measures how far these tools let a judgment move an answer. It is a guide to where your attention is worth spending, not a ranking of what is important in the world.

The three pasture tools are one calculation

Stocking rate, the paddock calculator and grazing days look like three separate tools and are described that way above — season-long carrying capacity, rotation layout, and how many days until the herd should move. Underneath they are the same two lines of arithmetic. Usable forage is area times yield times utilization. Demand is animal weight times intake as a share of body weight. Everything else is division.

That is a claim you can check rather than take on faith, so here it is checked. Start with 40 acres carrying 8 inches of grazable growth at 250 pounds of dry matter per acre-inch — 2,000 pounds an acre — on slow rotation at 47.5 percent utilization, with 30 head of thousand-pound cattle eating 3 percent of body weight a day.

The last row is the point. Feed the answer from one tool into the next and the chain closes exactly back onto the 40 acres it started from — not approximately, not to within a rounding error, but to the digit. 38,000 pounds of usable forage against 900 pounds a day of demand is 42.2 days however you ask the question. A tool that returns 30 head where another returns 42 days is not offering a second opinion; it is offering the same opinion in different clothes.

This is deliberate, and it is the reason all three pages draw their utilization options from the same list — 35 percent for continuous grazing, 47.5 for slow rotation, 62.5 for fast — and their intake options from the same list of 2, 2.5, 3 and 3.5 percent of body weight. If those lists ever drifted apart, the three tools would start quietly disagreeing about the same pasture, and the disagreement would look like a real finding to anyone who did not know where it came from. An automated test now reads the option values out of all three pages and fails the build if they stop matching.

There is a practical use for knowing this. If a grazing answer looks wrong, you do not have three things to check — you have two. Either the forage estimate is off or the demand estimate is off, and demand is the easy one, because head count and body weight are things you can go and count and weigh. Almost every surprising pasture answer traces back to the forage side, which is exactly where the two biggest guesses on the site live.

Where the same number has to appear twice

Two pages here handle combustion efficiency, and they express it in opposite directions. Heat cost asks for efficiency straight — 75 percent for a modern EPA stove, 65 for an older airtight, 50 for a basic stove, 15 for an open fireplace — because it is converting fuel prices into dollars per million Btu delivered into the room. The firewood calculator instead multiplies your cord requirement, since a worse appliance means more wood, and it uses 1.0, 1.27 and 4.7.

Those two sets are not independent, and they had better not be. A demand multiplier is just efficiency turned upside down and scaled to the modern stove. Divide 70 percent by 55 percent and you get 1.27 — the figure printed in the firewood dropdown. Divide 70 by the 4.7 multiplier and you get 14.9 percent, which is the 15 percent that heat cost uses for an open fireplace. The two pages are carrying one physical fact in two shapes, and the shapes agree to the last digit either page publishes.

The same is true of the seven species heat values — white oak at 29.1 million Btu per cord down to cottonwood at 15.8 — which appear both as a table on the firewood page and as a dropdown on heat cost, taken from a single Utah State University Extension source. And of the utilization and intake lists shared by the three pasture tools. In each case the number exists in more than one place because more than one question needs it, and in each case there is now a test that re-reads every copy out of the shipped pages and compares them to each other rather than to a value written down in the test.

That last distinction is the whole method. A test that checks a page against a number typed into the test only proves that somebody once typed the same thing twice. A test that re-reads the page's own constants and recomputes every published sentence from them will fail the moment the two drift apart — which is what you want, because the failure everybody actually ships is not a wrong formula. It is a correct formula and a paragraph describing what the formula used to do.

How these are built

Every formula on this site traces to a published extension-service, university or federal-agency source, named on the page where the number is used and dated. Every calculator has an automated test that re-implements its math independently, and where the source authority publishes a worked example, that example is the test — so the page is checked against the extension service's answer, not against itself. Nothing deploys unless the whole suite passes.

Everything runs in your browser. Nothing you type is sent anywhere, there is no account, and there is no app to install. These are planning estimates built from published averages and ranges, and rural averages have wide spread — for decisions where being wrong is expensive, your county extension office, veterinarian or state fisheries biologist can see your ground in a way a calculator cannot. More on the sourcing, the testing and the review schedule is on the about page.