Information technology is playing an increasingly important role in today’s agricultural production systems, regardless of operation size, commodity or management approach. Precision horticulture is an information-based management strategy that relies on collecting site-specific or plant-specific data. These data can be converted to useful information that helps growers make informed management decisions. Precision horticulture can benefit growers because of the high value of their products and the large amounts of crop inputs used in producing horticultural crops. Any improvement in reducing production costs can greatly increase profit for producers. Also, the optimal use of crop inputs in precision horticulture can potentially reduce the environmental impact of horticultural crop production. Implementation of precision horticulture relies heavily on sensors and systems that can collect weather, soil and plant-specific data cost-effectively. Plant data, in particular, allow a direct feedback for production and harvest management. Examples of data that need to be recorded by the plant sensors include biotic and abiotic stress detection at asymptomatic or early stages, canopy size and density, yield estimation and crop quality. For example, LiDAR-based or computer vision-based sensors are being used for measuring tree canopy size and density. The quantifying of variation in canopy size of orchards is needed for variable-rate crop inputs. With advances in sensing technology, various types of sensors have been developed commercially and are becoming available for precision horticulture. Optical sensors are most commonly used and several techniques have shown the potential for efficient, rapid, non-invasive field detection of plant diseases and yield estimation. This chapter reviews the current applications of sensor technologies being used in horticultural production systems.