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If your only exposure is analytical lab work (where by definition the work is difficult), you may not be familiar with the breadth of field utility of near-IR.

Some application examples: https://news.ycombinator.com/item?id=7699186

> And how the hell does it determine the ripeness of a avocado through the skin?

eg: http://ucanr.edu/datastoreFiles/234-347.pdf and http://www.aseanfood.info/Articles/13004404.pdf

[edit: removed LMGTFY link - sorry, that was rude. But please don't pull the expert card outside your area of expertise: NIR has been used to assess fruit ripeness for decades]



The optical and internal quality data were then merged and a PLS regression analysis was conducted using the NSAS software package (NSAS, 1990).

My comment wasn't that you couldn't test the ripeness of fruit using near-IR, it was that you could reliably doing it using a handheld consumer product.

There is a BIG difference between running a lab analysis using near-IR and making a consumer friendly product that can accurately produce the same data.


There are multiple manufacturers making NIR-based fruit quality sensors used quite far from laboratory conditions, as well as portable NIR sensors.

(See my other comments in this thread)


By "lab setting" I mean someone who can run controls, and do the statistical analysis to arrive a decent data, not just portable equipment.

I guess if they are willing to measure ripeness with a margin of error of +/-50%, that'll work.


+/- 50% wouldn't work in a consumer setting, but +/- 5% would work great. If you're in a lab, +/- 5% might be a disaster.




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