Let $Y_i$ be a random variable taking the value $1$ if the seed is brown and $0$ otherwise. Moreover, I assume the all $Y_i 's$ are independent. As you already correctly stated, the expectation is
$E[X] = E[\sum_{i=1}^{80} Y_i] = \sum_{i=1}^{80} E[Y_i] = \sum_{i=1}^{80} 0.75 = 60$.
The standard deviation is defined as the square root of the variance of a random variable: $SD[X] = \sqrt{Var[X]}$. The Variance is defined as $Var[X] = E[X^2] - E[X]^2$. In your case,
$Var[X] = Var[\sum_{i=1}^{80} Y_i] = E[\sum_{i=1}^{80} Y_i^2] - E[\sum_{i=1}^{80} Y_i]^2$.
Now, since the all $Y_i$ are independent the variance of the sum is equal to the sum of variances. Moreover, you know already the expectation for one $Y_i$. It's $0.75$. In addition, $E[X^2] = E[X]$ because squaring 0 or 1 is again 0 or 1. Hence, you get
$Var[\sum_{i=1}^{80} Y_i] = \sum_{i=1}^{80} Var[ Y_i] \\
\qquad \qquad \qquad = \sum_{i=1}^{80}(E[Y_i^2] - E[Y_i]^2) \\
\qquad \qquad \qquad= \sum_{i=1}^{80} (E[Y_i] - 0.75^2) = 80(0.75 - 0.75^2) = 15 $.
So, your standard deviation is eventually $SD[X] = \sqrt{Var[Y_i]} = \sqrt{15}$
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