Noelle Landauer II

Hey Mathew, thanks for the detailed reply. I agree 100% that actual observation, in different locations with different farming techniques, would be ideal for this kind of modeling. In my dreams we’d have a small army of folks — permaculturists, homesteaders, preppers, whoever wants to join — reporting real-world yields of staple crops. We can’t do small scale analysis of nutritional content (unfortunately), but everyone can break out a scale and weigh what they harvest, and break out a tape measure and estimate how much land it took to produce that harvest. I know there are people on this forum planting all kinds of interesting perennials. Looking through the archives as a newbie, I wonder how many of those plants really perform.

The Jeavons data is just a starting point, like all yield data, including mono-agriculture’s commodity yield per acre. The low numbers really are quite low, but I do think it requires some gardening experience — or perhaps call it judgement — to decide which crops to start with in a given climate. For example here in the PNW, no amount of soil fiddling will get sweet potatoes to yield as much as regular potatoes, or induce limas to perform like favas. People do need this background knowledge of their own area area going into it. Step one of any given model should be to strike out any plants that perform poorly your climate, unless you are willing to put some real breeding effort into it, a la Joseph Lofthouse.

I too am concerned about irrigation, it immediately emerges as an issue for anyone attempting to seriously grow their calories on the west coast. I’m fortunate to live in a rural area with my own land, but even then, I can only irrigate a small patch of that land, legally and physically. Even if my family was desperate for food, you can only push a well so far. I have an irrigation-free food forest started, but it’s still young. So from a calorie production perspective, there are two options: test out the dryland method, or restrict yourself to spring-sown crops that are already known to finish in the dry season without irrigation.

It’s been on my radar to actually test out Steve Solomon’s water-wise methods for a few years now, hopefully this year I can actually break a chunk of pasture and get some real-world yields. It has to compete with a true potato seed project, but maybe this is the impetus to get it going. I’m a little skeptical of Steve’s contention that increased per-plant yield will largely make up for decreased plant density, at least for anything planted in May or later. But hey, that’s what experiments are for! Break out the scale and tape measure, lol. I’ll have to read Steve’s books again for his exact methods and results. Even if the per area yield does end up lower, it may be worth it if inputs are lower. It’s an issue of competing resource usage, water vs. land area.

Another way to prioritize crops is to allocate high, medium and low density plants in the diet — for example, maybe shoot for 1000 calories per day of high density seeds, 600 calories of medium density root crops and fruit, 400 calories everything else. (Again, this isn’t a dictate on what exactly to eat on a daily basis, but just a model to get an idea of the minimum you need of each item to get an adequate diet over the whole year). This is the peasant diet of many cultures: a backbone of grains and legumes (the proverbial rice and beans), plus high yielding veggies and root crops, then flavor and diversity last on the priority list. In this model, squash and onions would roughly go in the medium density category and tomatoes in the low density. I love tomatoes, grow a ton of them and the world can pry them from my cold dead low-yielding hands, but it’s helpful to recognize that they are just not very calorie dense. Their main purpose is micronutrients and to flavor the corn or beans or whatever. So it doesn’t make sense to devote a whole acre to tomatoes, but it may make sense to allocate 200 square feet and some precious water. Folks who don’t want to deal with grains may have to reverse the proportions, eat a bunch more medium density foods and fewer seeds.

Since it sounds like you (Mathew) created this calculator with your own project in mind, do you care if I borrow the concept and expand on it? I’m thinking of a public spreadsheet that will include macronutrients for a wide variety of potential calorie crops, and yield data from variety of sources. It sounds like there is demand for a more comprehensive document beyond annual crops for the Pacific Northwest. At least I would find it fun to work on such a project.

Good luck with your food production this season, and report back how it goes. And maybe give quinoa a shot. It’s a heck of a lot of labor to produce one’s own food.

Hello,
I just stumbled upon this discussion and your excellent project. I’ve been thinking about the calorie issue for years now, so it's great to see someone put together calorie-based modeling tool. One resource that I highly recommend is John Jeavon’s “How to Grow More Vegetables.” The title makes it sound like an ordinary gardening book, but is actually the published results of an outfit in California called Ecology Action, which has been working on this exact same project for decades: trying to design subsistence calorie diets that can be grown by hand on the smallest amount of land possible. They have compiled several model diets (I’ve got One Circle: Mexico and One Circle: Kenya floating around my bookshelves somewhere), but most usefully they provide quantified yield data for a wide variety of foodstuffs, both per weight and per area. The per-weight data is taken from the USDA Standard Reference, but combined with per-area data allows you to calculate both the amount of food to grow and how much space it will take up. The area data is expressed in high-intensity 100 square foot beds, which I think makes it easier for the would-be mini farmer to calculate how much to grow, as opposed to factors like per-plant or per-acre yield.

They also provide three yield levels for each plant (low, medium and high). I’ve been measuring my own yields (weight/area) to compare, to see if their numbers are in the ballpark to my own garden. Generally the “low” yield has been accurate for a new-to-me crops, or results under crappy weather, or pushing a plant out of its ideal climate. The “medium” yields were accurate for crops I have experience with, know which varieties to grow and know will do well here. “High” yields were only obtained under exceptional circumstances. (For example, dry peas, the thing you all were discussing upthread, usually comes in at 8-12 lbs per 100 square feet, but my best ever variety was a whopping 21 lbs/100 sf. Jeavons lists the medium yield for dry peas at 10lbs/100sf, and high yield at 24lbs/100sf.) For your purposes, the low yields are probably sufficient, since it seems you want to establish a comfortable floor to plan from.

One nice thing about their yield charts is that they include a lot — grains, tree crops, fruit, oil crops, tropical and temperate crops. This makes it easier to plug in every major crop for in your climate, and spit out all the results for both calories/weight and calories/area. There’s no real reason that grains aren’t on this calculator, for instance. You may not want to get out there with a scythe whacking on hulless barley, but at 1583 calories/pound someone might, even knowing it only yields 5 lbs/100 square feet. Plugging everything in also generates potential crops that you may have dismissed without real data. For instance, all of the following have a higher caloric density (calories/pound) than winter squash (I’ll use 200 Kcal/lb as the cutoff, since USDA lists raw butternut as 204):

* Apples (242)
* Aronia berries (212)
* Blackberries (264)
* Blueberries (259)
* Sour pie cherries (242)
* Sweet corn (400)
* Garlic (676)
* Grapes (270)
* Figs (363)
* Kale (224)
* Leeks (227)
* Pears (252)
* Plums (272)

This isn't an argument that everyone must include sweet corn in their models, just to not dismiss crops out of hand solely because we have the impression that they're low density. In some respects we are really talking about two categories of foodstuffs: high density (mostly seeds) and medium density (mostly roots, fruits, and other starchy storage structures). It's okay to include both as caloric staples, so long as the total mass of food eaten per day doesn't get out of hand, more than six pounds-ish. Supposedly the modern gut can only take so much roughage.

Some other high density calorie crops to consider adding, that I don’t already see on the calculator: barley, buckwheat, chestnuts, chickpeas, flax, hazelnuts, hempseed, lentils, oats, quinoa, rapeseed, rye, safflower seed, walnuts, wheat. All of these grow well in the PNW and come in at over 1500 calories/lb, so there’s no good reason to exclude them. People can look at the calories/square foot and decide if it’s worth the effort for themselves. I would also include warmer weather crops such as almonds, avocado, cassava, millet, mung beans, olives, pecan, pistachios, rice, sesame, soybeans. We all may be living in a warmer world in the very near future, so it’s good to keep mind adaptable crops that we may have to turn to in that world.

Anyway, combining together all the data allows you to put together many different of models for potential diets. It’s a fun and informative exercise to think about different combinations, and how much to grow of each staple. One of my models had apples, favas, common beans, corn, garlic, hazelnut, kale, leeks, parsnips, peas, potatoes, quinoa, rutabaga, squash, and sunflower seeds as the caloric staples. Some of these were picked solely for the calorie density, others for the calorie density AND yield. For instance, you can cram more leeks into a small space than bulb onions, so the calories/sf for leeks is higher. Other models worked in enough wheat to grow a loaf of bread per week, or estimating how much space for grains and greens needs to be allocated to keep a few chickens for eggs. Other people will undoubtedly pick different sets. But its nice to have a model on hand, and then be able to go out there and plant and measure results from real gardens, to see how close to reality the model can get.