What is the null hypothesis, when there is no research hypothesis? (a) Apples grow to different sizes, from small to average and large. Farmers want large apples.

(b) There is this rare bug, the apple bark bug, which lives in the bark of apple trees. Due to its rarity, the apple bark bug is not well understood.

(c) Agronomists are divided about the effect the apple bark bug has on the size of apples. Some believe that apples from trees that have been infested with colonies of this bug are smaller than on trees without such an infestation; others believe that in fact they are larger.

The ministry for agriculture has commissioned a study on the effects of the apple bark bug on apple size. Based on the results of this study they want to either exterminate the apple bark bug, ignore it, or cultivate it. There is no scientific literature on the matter, there is no reliable data, and the research institute commissioned with this study now wonders:

What should be the null hypothesis?

As natural scientists they know they cannot present their limited observations as general fact, but only falsify a hypothesis. But what should it be?

The third semester student apprentice from the nearby university, who has just finished a course in the theory of measurement, suggests:

H0 : Applebug = Appleno bug

H1 : Applebug ≠ Appleno bug

His friend, who has heard the same lecture, rolls her eyes and suggests:

H0 : Applebug ≤ Appleno bug

H1 : Applebug > Appleno bug

The research group leader smiles and compliments them on their attentiveness.

What does he suggest?

This is, of course, an example, illustrating a question relating to psychological research: How do we define the null hypothesis, if we have no presupposition about the effects of an intervention?
So your independent variable is the bug, and your dependent variable is apple size.

The question asks whether you are testing a directional hypothesis. 
Given that researchers are divided about the direction of the effect of the IV on the DV, it makes more sense to treat it as a non-directional hypothesis:

i.e., H0 is that apple size is equal with and without bugs.
The alternative hypothesis is that they are not equal. Or in some senses, there are two alternative hypotheses, one suggesting an increase and another suggesting a decrease.

Of course, you ultimately want to conclude whether there is a difference and if so what is the direction of the effect. Thus, confidence intervals from a frequentist perspective or a posterior density from a bayesian perspective might be more useful in understanding the direction and degree of any effect.

You may also want to read about suggestions for testing the hypothesis of no group differences.