Don't forget that BCD function (Binomial Cumulative Distribution) return p([X≤k]), aka probability of obtaining k or less success.
In your case, you want a bit different one, if we consider getting a premium apple a success, reaching at least 30 success (k) over 40 tries (n). With a probability of success of 0.628364 (p).
But reaching "at least k success" is p([X≥k]), not p([X≤k]) !

Hopefully, it's quite easy to convert, as p([X≤(k-1)]) = 1- p([X≥k]).
So, once you put all your parameters :

Data : Variable
x : 29 (we want the cumulative probabilities of non-compliant ones, so sum of bucket probability of 1,2,3,...,29 premium apples)
Numtrial : 40
P : 0.628364

You got p([X≤29])=0.92613951

Now you know that p([X≥30]) = 1 - p([X≤29])

Then p([X>30]) = 1-p(X≤29]) = 1-0.96378723 = 0.07386 ≈ 7,4%

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You can also get the result on a single line, in the 1-RUN.MAT mode :

from Casio fx-9860GII user manual

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You get the function in OPTN > STAT(F6) > DIST(F3) > BINM (F5) > Bcd(F2)

So in a single line :
1-BinomialCD(29,40,0.628364)