A flight sensing detector for apple maturity indexes in orchard

Abstract

Apples quality monitoring and maturity measurement are important for yield evaluation, profit estimation, determination of harvest time and postharvest storage conditions. This study explored the monitoring ability of the micro-Unmanned Aerial Vehicle (UAV) to the orchard, the force sensor and gyroscope are used to observe the force and posture changes of apples during the spectral collection process. The UAV carries 18 channels of visible/near-infrared multispectral sensor to collect the internal information of growing apples at close range. A total of 200 apples were collected in the orchard, and then soluble solid content (SSC), titratable acid (TA), firmness, and starch pattern index (SPI) were destructively tested. Multiple scatter correction (MSC) and Standard normal variate (SNV) pretreatment combined with partial least squares regression (PLSR) were used to establish the internal quality prediction model. Streif index is used to evaluate the maturity of apples. The results showed that the detection of apples on trees by UAV would not affect the growth of apples and could collect the internal quality information. The correlation coefficient of the prediction model for apple maturity is 0.8593 and root mean square error is 0.0102. It shows that this study has potential in detecting the changes of quality and maturity of growing apples and is helpful to the overall perception of orchards.