Project Number: 8080-21000-025-02-T
Project Type: Trust
Start Date: Oct 1, 2012
End Date: Mar 15, 2016
The objective of this project is to develop improved and more economical methods of harvesting blueberries that require less hand-picking labor and that will result in higher recovery of fresh market quality blueberries. This will be done by: 1) improving the blueberry impact recording device (BIRD) sensor and 2) using the BIRD sensor to evaluate over-the-row mechanical harvesters and the packing operation.
The BIRD was developed in a USDA-SCRI funded project and will be further refined by reducing its size and weight, and will be used to evaluate bruising during the harvesting of blueberries. The BIRD sensor records impacts in three directions and acceleration values in real time that is integrated to obtain velocity. In the proposed research, the impact and speed data obtained in our previous project will be regressed with fruit bruising data obtained for northern highbush genotypes. Studies will be conducted to collect multiple data points in field studies to analyze commercial over-the-row blueberry harvesters as well as to characterize field transportation systems and packinghouse operation. BIRD and other single-axis accelerometers, and digital strain and compression gauges with different sensing ranges will be mounted on blueberry plants, lugs, and pallets to determine mechanical forces that fruit is exposed to from the bush through the machine, and then into various transportation systems used by growers. These will include lugs riding pull-behind carts, then loaded on pallets and handled by a forklift onto trucks or directly on a forklift for transport to the packinghouse, where they will be unloaded and moved into a pre-cooling room. In this project, a series of machine runs will be performed to correlate the force measured by BIRD and other accelerometers mounted on the bush with a range of harvester settings. Packinghouse operation (machinery and handling evaluation) will be performed with the introduction of the BIRD sensor alone and with blueberry fruit on the packing line. The flow of the sensor through fruit handling (emptying of lug into the hopper, rolling on visual inspection belt), in-line sensors, electric sorting machines, and finally into a fruit collection bin and placement into small clamshells will be videotaped and time stamped. The sensor will be removed from clamshell, and data will be downloaded and analyzed with a software program (6) for impact force it has encountered during the packinghouse operation. Video image analysis will assist at the point where transit impact and compression forces (both the magnitude and numbers) were detected by the sensors. Also, studies will be conducted to provide the blueberry industry with engineering-based data on impact and compression forces. The BIRD sensor will be dropped onto the surfaces that the fruit samples were dropped to record the impact force that it encounters when dropped from 0.5 and 1.0 me heights onto hard and soft surfaces. In all studies, each treatment plot for machine harvesting will have at least 30 plants replicated four times, and the collected data will be subjected to appropriate statistical analysis. Data will be analyzed with General Linear Model analysis of variance (ANOVA). When differences are detected at P = 0.05, the data will be subjected to mean separation by differences of least square means using SAS Proc Mixed (SAS Institute, Cary, NC) and linear regression using the SigmaPlot V11.0 (Systat Software Inc., San Jose, CA).