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ARS Home » Midwest Area » East Lansing, Michigan » Sugarbeet and Bean Research » Research » Publications at this Location » Publication #357120

Research Project: Nondestructive Quality Assessment and Grading of Fruits and Vegetables

Location: Sugarbeet and Bean Research

Title: Improvements and evaluation of an in-field bin filler for apple bruising and distribution

Author
item ZHANG, ZHAO - US Department Of Agriculture (USDA)
item POTHULA, ANAND KUMAR - US Department Of Agriculture (USDA)
item Lu, Renfu

Submitted to: Transactions of the ASABE
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/1/2018
Publication Date: 3/1/2019
Citation: Zhang, Z., Pothula, A., Lu, R. 2019. Improvements and evaluation of an in-field bin filler for apple bruising and distribution. Transactions of the ASABE. 62(2):271-280.

Interpretive Summary: Harvest and postharvest handling are two major cost components in apple production. A new apple harvest and infield sorting machine prototype was recently developed by ARS researchers at East Lansing, Michigan, so as to improve harvest productivity and achieve postharvest cost savings for U.S. apple growers. The bin filler plays a critical function for the new apple harvest and sorting machine; it receives graded apples from the sorting system and then distribute them evenly in the bin without causing bruise damage. An innovative bin filler was developed for incorporation with the new apple harvest and sorting machine. Field tests of the first version bin filler in the 2016 harvest season showed relatively high bruise rates and uneven fruit distributions. Subsequently, major improvements were made in the construction of a new version bin filler. The improved bin filler was tested with the apple harvest and sorting machine in a commercial orchard in Michigan in 2017; 99% ‘Gala’ and 98% ‘Blondee’ apples were graded ‘Extra Fancy’, which were much better than the results for the first version bin filler tested under the laboratory test condition. Further laboratory tests of the improved bin filler, along with the first version bin filler, were conducted to evaluate their performance in distributing fruit in the bin. A three-dimensional depth imaging technique was used to collect the fruit distribution data when the bin fillers were operated under uniform and non-uniform feeding conditions. Quantitative analysis showed that the improved bin filler performed consistently better than the first version bin filler, in terms of fruit distributions in the bin, and feeding condition did not affect the performance of the bin fillers. The improved bin filler has met the requirements for apple harvest and infield sorting, and it can be potentially adapted for use with other harvest platforms.

Technical Abstract: Automatic bin filling is needed for apple harvest and infield sorting. A commercially viable bin filler for infield use should be simple, compact and low in cost, and be able to distribute apples evenly in the bin without causing bruising damage. An innovative bin filling technology was developed for incorporation with the new apple harvest and infield sorting machine recently developed by our group. Field tests of the first version bin filler in the 2016 harvest season showed relatively high bruising rates and uneven fruit distributions. Subsequently, a second version bin filler was developed with several major improvements, including the use of a new pair of foam rollers for better controlling apples exiting from the sorting system and avoiding fruit collisions during free falling, and installation of an improved pinwheel with nine longer soft pads, instead of four short ones with the original version, coupled with fruit moving guides, for avoiding apple collisions and reducing the rolling speed of fruit from the pads into the bin, with better fruit distributions. Field tests conducted in the 2017 harvest season showed that the improved bin filler achieved superior performance in reducing bruise damage, with 99% ‘Gala’ and 98% ‘Blondee’ apples being graded ‘Extra Fancy’. Furthermore, a depth imaging method, using Kinect-v2 camera, was proposed to quantitatively compare the performance of the two bin fillers for distribution of fruit in the bin under the uniform and non-uniform feeding conditions. Analysis of the fruit height data showed that the apple distributions were not significantly affected by feeding method for both bin fillers. Overall, the second version bin filler resulted in better distributions of apples in the bin, compared to the first version, and uneven distributions mainly occurred in the corner areas of the bin, which could not be reached by the bin filler’s pinwheel. The improved bin filler has met the requirements for apple harvest and infield sorting, and it also has potential for use with other harvest platforms.