Migrant farmworkers in the United States often perform physically-demanding work but are less likely to report poor working condition, which exposes them to the physical risks of workrelated musculoskeletal disorders including prolonged non-neutral postures, repetitive motions and forceful exertions. In industrialized countries, such technology as the harvest-assisted mobile orchard platform has been introduced to increase efficiency;​ however, research on potential musculoskeletal health effects associated with the introduction of the mobile platforms on the workers is lacking. The existing methods to assess ergonomic risk factors in laboratories or other industries are not suitable to agricultural work due to the variability of the work in the field-based settings. The goal of this study was to develop methods to characterize these musculoskeletal health risk exposures from data directly collected in the field. Kinematic measures included static non-neutral postures of upper arms and back and work repetition rates of upper arms derived from accelerometer data. Physiological measures included muscle fatigue and muscle activity of upper trapezius obtained from surface electromyography (EMG). Muscle fatigue was investigated in terms of the EMG median power frequency shift and changes in EMG amplitude over time. Muscle activity was characterized as EMG amplitudes normalized to reference activity and maximal dynamic activity. Moreover, subjective Borg RPE and Borg CR10 scales were used to assess perceived overall exertion and local body part fatigue, respectively. Then the exposure assessment methods were implemented to compare different apple harvesting methods in Washington State. Lastly, correlations between objective and subjective measures were calculated to study whether one measure can replace the other. The outcomes from this dissertation and its implications for future studies could potentially lead to the improvement in work environment for farmworkers and will ultimately improve their health and well-being.