Technology progress in mechanical harvest of fresh market apples

Highlights

• Reviewed fresh market apple harvest technologies of shake-and-catch, robotics, and platforms.

• High-throughput and bruising-free catching mechanism needed for shake-and-catch commercialization.

• Progress of sensing and automation technologies will help develop harvest robotics.

• Harvest platform, only technology adopted by growers, replaces ladder-and-bucket method.

• More functions incorporated and improved economics enhance harvest platform adoption.

Abstract

This article reviews the research and development progress of mechanical harvest technologies for fresh market apples over the past decades with a focus on the predominant technologies of shake-and-catch, robots, and harvest-assist platform methods. In addition, based on the review it points out the bottlenecks and future trends of these three technology categories. Major progress in the shake-and-catch method is related to theoretical studies on the effective removal of apples and catching mechanisms to minimize bruising. The unacceptable bruising conditions hinder the shake-and-catch method from commercial application. Two startups of apple harvesting robots are in the stage of commercializing their products based on vacuum and three-finger end-effectors, respectively. Economic benefits, as well as technology reliability and robustness of both robots, are pending for validation before they are on the market. In addition, a key obstacle faced by both robots before commercial use is to find a solution to pick apples grown in clusters. Harvest-assist platforms are gradually adopted by apple growers, but at a very low rate due to their doubts on economic benefits. Validation of harvest-assist platforms’ economic benefits and incorporation with more functions (e.g., sorting) would enhance their adoption. With the rapid development of sensing and automation technologies, such as novel sensors, embedded systems, and machine learning algorithms, and the progress in new tree canopy structures that are friendlier for fruit visibility and accessibility, it is believed the robots for fresh market apple harvest would be realized and commercialized in the near future. Currently, more efforts should be invested in analyzing and validating the economic benefits of harvest-assist platforms, as well as adding more functions to the harvest-assist platforms, to increase their application rate for the benefit of the apple industry.

Introduction

Apple is one of the most consumed fruit in both fresh eating and other forms (e.g., juice and sauce), and it provides a number of health benefits, such as reducing the incidence rates of cancers and cardiovascular diseases (Boyer and Liu, 2004, STATISTA, 2016, PBH., 2015). Fresh market apples are still manually harvested using the conventional ladder-and-bucket approach (Zhang, 2015, Freivalds et al., 2006). In manual harvesting of apples, seasonal workers stand on the ground for picking the low-level fruits and need to climb a ladder to get access to high-level fruits. During the whole harvest process, workers need to wear a bucket to temporarily hold apples, and after the bucket is full, they walk to a bin to unload the fruits. This harvest method is low in efficiency, since a lot of activities performed manually by workers (e.g., moving ladders, climbing up and down, and unloading apples from buckets to bins) are not directly related to apple picking. This conventional harvest approach demands high physical strength for the carrying out of the bucket (≈19 kg when full) continuously, not to mention workers have to climb/descend ladders with a heavy bucket (Freivalds et al., 2006). In addition, the conventional harvest approach is prone to causing occupational injuries, such as ladder falls, back strains, and musculoskeletal disorders (Zhang et al., 2019a, Zhang et al., 2019b, Fathallah, 2010). Mechanical apple harvest is an approach to alleviate the disadvantages of the conventional ladder-and-bucket apple harvest method.

Researchers during the past decades worked towards the realization of mechanical apple harvest using different methods that can be categorized into shake-and-catch method, robots, and harvest-assist platform (Zhang et al., 2016a). The shake-and-catch approach is to hold the trunk or limbs and then shake to detach apples (Allshouse and Morrow, 1972). Several harvest machines based on this concept have been developed, but they are not adopted commercially for fresh market apple harvest due to extensive impacts related to bruising damages on fruit (Berlage and Langmo, 1974, Tennes et al., 1976). Harvesting robots mainly include two components – a machine vision system and an end-effector. The machine vision system detects and localizes apples, and the end-effector detaches fruit from the tree. Though researchers have developed a variety of apple harvesting robot prototypes, none of them is commercialized, due to low throughput and efficiency, unreliable performance, and high cost (Slaughter and Harrell, 1987, Slaughter and Harrell, 1989, Zhao et al., 2016). Harvesting robots, however, can have the potential to entirely replace the laborers. To immediately benefit the apple industry, researchers shifted to the development of harvest-assist platforms to replace the use of ladders (Zhang et al., 2016a, 2017a). Instead of picking by standing on a ladder, picking fruit by standing on the harvest-assist platform would increase harvest efficiency, reduce physical strength requirements, improve overall safety, and alleviate occupational injuries (Schupp et al., 2011).

Numerous research projects have been conducted with results published in the past decades on the progress of mechanical fresh market apple harvest aforementioned concepts (Zhang and Karkee, 2016, He et al., 2017, Wheat, 2019, Zhang et al., 2019d). There were some reviews published in this domain, but they only focused on specific topics: Gongal et al. (2015) reviewed the progress on the machine vision for fruit detection; Bac et al., 2014, Zhao et al., 2016 summarized the progress in robots harvest and vision-based control for robots; and Zhang et al. (2016a) focused on the shake-and-catch method. However, no reviews were published about the mechanical harvest of fresh market apples in a holistic manner in the past decade. Thus, a proper synchronization of the literature in the mechanical fresh market apple harvest has been lacking, and this article aims to fill this need of reviewing the technology progress on the methods of shake-and-catch, robots, and harvest-assist platform.