Building Image Dataset In a Studio
Disclaimer:

This is a question that is probably going to be flagged since it is too broad and answers will be mainly based on opinion.

Is this effort worth it?

That is subjective, what commercial/social use does this have? Is this kind of detection really relevant? What can you do with those detections and classifications? That is something only an entomologist could answer properly, you will get better answers for this one with them.

If you can find this kind of motivations for your work, you probably get a good dataset with good use. But if you don't even know what kind of applications you're aiming to you should start doing more research on motivation.

Would these pictures significantly increase the model's accuracy?

It is highly probable that it will, but you can't be sure until you try. Also, train your models with recently acquired images during the acquisition process to make sure that those images are having an impact on your models.

Is there any opportunity for publication?

Surely there is, if it will be cited multiple times or if the paper will be well received by Machine Learning community? Probably. If not, that probably would get you a top publication on entomology.

Is there any paper that uses studio photos as well as field photos for object detection?

Well, there are many. These controlled datasets are pretty easy to come up with and have been used extensively see BioID for example, until today many publications use it for benchmarking on Eye Pupil Detection and Facial Landmark Detection. In the wild datasets (usually collected from the web) are usually more challenging and also more fitted to real-world application, but it is not always possible to acquire them easily.

Last year CEFET-RJ and UFRJ published papers in IEEE with created datasets for Aedes Aegypti breeding sites detection. This dataset was created using drones and manually annotated by CEFET-RJ and UFRJ undergrad students.