There are several pro's and con's for using NAIP in land classification.
- High spatial resolution
- nIR band is useful for discriminating major vegetation classes (e.g.
a crop circle surrounded by arid land)
- Acquired usually during peak growing season
NAIP simply does not have the spectral resolution necessary to discriminate between most classes of vegetation. On the other hand, utilizing EVI or NDVI from NAIP in your classification is a great way to extract healthy green vegetation of any type from the image. Imagery such as Worldview-2 is much better suited for discriminating between types of vegetation--even types of crops!
Unless the tomato farms are growing in the desert surrounded by arid vegetation, you will likely need to do some sort of object oriented image analaysis (OBIA), such as image segmentation and classification. This method segments the image into image objects based on spectral characteristics. You can then classify those image objects by a variety of metrics such as shape, size, texture etc. This essentially adds flexibility to your analysis that you could not get from spectral bands alone. Common programs for image segmentation include: eCognition, SPRING, and some of the add-ons in QGIS.