Real-time yield monitoring is a critical but effective process for the assessment of the spatial variability of yield in fields, and profit information instantly. Since a few researches were conducted for upland crops yield monitoring, especially for Chinese cabbage, therefore the objective of this study was to conduct the basic tests for evaluating the potentials of mass and volume-based sensing approaches for Chinese cabbage yield monitoring for small-sized cabbage harvesters. Basic tests were conducted under laboratory conditions. Two types of sensors were used: load cells (for mass-based sensing), and CCD cameras (for volume-based sensing). For mass-based yield monitoring, an impact plate was fabricated using load cells, and installed in such a way that the cabbages reached to the collection section touching the impact plate. Mass was calculated from the load cell signals, and the effects of different dropping heights on the impact plate were also investigated. For volume-based yield monitoring, the top and side images of the cabbages were captured using CCD cameras, and volume was determined through image processing techniques. The weight of cabbage and the number of harvested cabbage were also determined. Linear calibrations with R2 of 0.97 and 0.94 were found for mass-based, and volume-based yield monitoring approaches, respectively. No significant differences were found for different cabbage falling heights. The average percentage of error for cabbage weighting and counting were 10.73% and 10%, respectively. The results showed the potentials of the candidate sensors for Chinese cabbage yield monitoring, however, further study would be necessary to minimize the effects of the factors affect the real-time yield monitoring and mapping during crop harvest.
Figures & Tables
Fig. 1. Major components of the considered Chinese cabbage harvester.