lathyrus_long

Tissue culture is also used without genetic engineering. Orchid flasking is the classic example, since the seedlings require an external source of energy. A symbiotic fungus provides that in nature, but it's easier to replace that with the usual agar medium.

Many other species can be propagated conventionally, but will grow faster in tissue culture. That's typically referred to as micropropagation, and widely used for aroids (like here), flytraps, cactus, etc. It's also common for aquarium plants, I think because that eliminates the risk of introducing pests.

It's not fundamentally incompatible, but non-proprietary hybrids are extremely rare. The effort to maintain the two parents and do the cross is much greater than that of saving seed from an open-pollinated variety, so very few growers will undertake that even given the chance. Even if multiple growers do, the smaller population of plants in each of the pure lines increases the chance of significant divergence between sites, at which point the multiple production sites implicitly become multiple different varieties.

Anyone interested here might also wish to read Carol Deppe's "Breed Your Own Vegetable Varieties". She's a Harvard-trained geneticist and amateur vegetable breeder, with special interest in open-pollinated varieties derived from proprietary F1 hybrids. Her book extensively discusses the underlying biology, the practical breeding process, and the legal situation of such work.

You could say that a log scale is useful only when the variable can be usefully regarded as the exponential of something, and I think you'd be tautologically right. That exponential structure just shows up very often, whether from human sensory perception, or from linear systems math, or from economics, or from many other causes.

I generally prefer log units to linear percentages for anything like a scale factor or a ratio. A lot of stuff comes out cleaner and more symmetric, for example because (1 + 0.10)*(1 - 0.10) isn't equal to one exactly, but exp(0.1)*exp(-0.1) is. The case for that in the university chart seems slightly pedantic but fine to me.

Log scales are also widely used for physical quantities that humans can't directly perceive, like radio-frequency electric fields. The logarithmic nature of human perception provides an additional benefit in some cases, but it's not the sole or primary benefit. For example, the amplitude response of any linear differential equation to a sinusoidally varying input is (roughly, at low Q, etc.) piecewise linear vs. frequency on a log-log Bode plot. It has no similarly useful structure on a linear plot. That structure is relevant to all manner of problems in electromagnetics, optics, acoustics, dynamics in mechanics, and other areas. Any introductory course in signals and systems will cover it.

That's not very relevant to this university chart, though. For a simpler example, stock price charts are sometimes logarithmic. On such a chart, if I buy a constant dollar amount and then sell it, I'll make the same dollar gain or loss for any buy and sell points the same vertical distance apart. I believe this chart's creator was thinking of an analogous property; the labels are placed in pairs geometrically equidistant from 0%, since (1 + 0.25)*(1 - 0.2) = (1 + 0.5)*(1 - 0.333...) = 1. I believe the rounding to 34% and not 33% is a mistake, but that the scale is otherwise fine.

That's a question of why Fourier transforms are important though, not just how they're defined and computed. The next-level answer is presumably that sinusoids (or complex exponentials in general) are the eigenfunctions of general linear time-invariant systems, i.e. that if the input to an LTI system is exp(j*w*t), then its output will be A*exp(j*w*t) for some complex constant A. Some other comments here already alluded to that, noting that sinusoids are good for solving linear differential equations (which are LTI systems), or that the sum of two sinusoids of the same frequency shifted in time (which is an LTI operation, since addition and time shift are both LTI) is another sinusoid of that same frequency.

LTI systems closely model many practical systems, including the tuning forks and flutes that give our intuition of what a "pure tone" means. I guess there's a level after that noting that conservation laws lead to LTI systems. I guess there's further levels too, but I'm not a physicist.

That eigenfunction property means we can describe the response of any LTI system to a sinusoid (again, complex exponential in general) at a given frequency by a single complex scalar, whose magnitude represents a gain and whose phase represents a phase shift. No other set of basis functions has this property, thus the special importance of a Fourier transform.

We could write a perfectly meaningful transform using any set of basis functions, not just sinusoids (and e.g. the graphics people often do, and call them wavelets). But if we place one of those non-sinusoidal basis functions at the input of an LTI system, then the output will in general be the sum of infinitely many different basis functions, not describable by any finite number of scalars. This makes those non-sinusoidal basis functions much less useful in modeling LTI systems.

As others note, it's exactly a change in basis. In particular, it's an orthonormal basis, meaning that the dot product (correlation) between a basis function and itself is one, and between any two different basis functions is zero. This gives some intuition for why the forward and inverse transforms look so similar, in the same way that the inverse of an orthonormal matrix (like a rotation matrix) is just its transpose.

This article doesn't say, but vertical farms almost always grow hydroponically, using sterilized inert media (like coir) or inherently sterile inert media (like rockwool). The water and fertilizer are delivered together by drip irrigation. Some farms may instead use no medium at all, like in NFT or DWC. With precise control over the plant nutrition, this can achieve higher yields per square foot than soil, making optimal use of the expensive indoor space. (I think grains are particularly unsuitable crops though, per my other comments here.)

In theory it's possible to run completely free of insects, with cleanroom-like precautions, and I think some facilities do. I think it's more common to live with some level of insect pests though, since it's so hard to avoid introductions and so destructive when they occur--with no natural predators, they can multiply far faster than in nature. That implies some level of pesticides, deliberately introduced predatory insects (which are particularly effective indoors, since they can't fly away), etc.

It's more complicated than that, since the wavelength distribution matters--we can effectively transform green photons that the plant would have reflected into red or blue photons that it will absorb. (The plant still benefits from some green light, but less than in sunlight.) We can also supply each plant with its exact optimal PPFD and DLI. For example, lettuce may be grown under shade cloth, deliberately wasting much of the incident sunlight, because the extra light won't make it grow faster and will make it taste bitter. In a vertical farm, we can just set the LED current and spacing wherever we want.

I've heard that 1 m^2 of modern solar panels will support >1 m^2 of a low-light crop (like lettuce, unlike grain) under modern LEDs. I haven't done the math myself, and this obviously varies with climate. I think vertical farms (growing entirely by artificial light) are still uneconomic vs. greenhouses almost everywhere, per my other comment here. Supplemental artificial light in a greenhouse is of course highly economic in many climates, and Dutch growers have been using it for decades.

The cost to heat or cool a vertical farm should be lower than for a greenhouse with equivalent growing area, since it's got lower surface-area-to-volume ratio and doesn't need to be transparent. That may be important for stuff like high-end strawberries, where tight control of the day-night temperature swing enables higher sugar content. I again wouldn't expect a useful benefit for grains, though.

What do you mean by "sludge"? Typical hydroponic solution just looks like water, thus the name. The fertilizers used are higher purity ("greenhouse grade", "ultra-soluble", etc.) than those applied to soil, since impurities risk clogging the fertigation equipment.

Surely this relationship is noteworthy only to the extent it's potentially a causality? The authors are careful not to make explicit claims, but most discussion here is about that possibility. The title of this HN submission is too ("could negate"), though the title of the paper itself is more cautious.

After more carefully reading the paper, I think the premise of my original comment was completely wrong though. The study apparently had no information on whether the participants were eating conventional or organic produce. Rather, they categorized by type of fruit or vegetable, converting the average results of tests for residues to a score from 0 (best) to 6 (worst) with a somewhat arbitrary heuristic. For example, grapefruit scored 0, and spinach scored 6.

That eliminates the spurious correlation I speculated about, though others may exist; it would be interesting to know which specific fruits and vegetables accounted for most of the effect. That heuristic also increases the risk of data dredging; I wonder how many versions they tried before they got their result. As to the residues, it seems they considered all pesticides equally, even though some are strongly suspected to be much more dangerous than others. It would be interesting to repeat the analysis considering only residues of those suspected to be most (or least) dangerous, to see if their effect gets bigger (or smaller).